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March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island

Assessment of Warty Sea Cucumber Abundance at Anacapa Island

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 1

Final Report to:

Resources Legacy Fund Foundation

Grant #13319

March, 2019

Andrew Lauermann, Heidi Lovig, Greta Goshorn

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 2

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

TABLE OF CONTENTS
LIST OF FIGURES………………………………………………………………………………………………………………………..2
LIST OF TABLES …………………………………………………………………………………………………………………………3
INTRODUCTION………………………………………………………………………………………………………………………….4
BACKGROUND ……………………………………………………………………………………………………………………………4
PURPOSE…………………………………………………………………………………………………………………………………….5
OBJECTIVES ……………………………………………………………………………………………………………………………….5
SURVEY METHODS ……………………………………………………………………………………………………………………..6
ROV EQUIPMENT AND SAMPLING OPERATIONS ………………………………………………………………………..7
SUBSTRATE AND HABITAT ANNOTATION……………………………………………………………………………………8
INVERTEBRATE ENUMERATION………………………………………………………………………………………………….9
ROV POSITIONAL DATA ……………………………………………………………………………………………………………….9
RESULTS……………………………………………………………………………………………………………………………………..10
SURVEY TOTALS………………………………………………………………………………………………………………………….10
SUBSTRATE AND HABITAT………………………………………………………………………………………………………….11
INVERTEBRATE TOTALS……………………………………………………………………………………………………………..12
WARTY SEA CUCUMBERS…………………………………………………………………………………………………………….13
DISCUSSION…………………………………………………………………………………………………………………………………15
PROJECT DELIVERABLES ……………………………………………………………………………………………………………15
REFERENCES ………………………………………………………………………………………………………………………………16

LIST OF FIGURES

Figure 1. Planned transect lines placed parallel to depth contours at Anacapa Island SMR
and East Fish Camp…………………………………………………………………………………………………………6

Figure 2. Basic ROV strip transect methodology used to collect video data along the sea floor,
showing overlapping base substrate layers produced during video processing and habitat
types (hard, mixed soft) derived from the overlapping substrates…………………………………….8

Figure 3. Density of WSCs per 100m2 in each habitat type for the spring and fall at Anacapa
Island SMR and East Fish Camp. Densities represent the total number of WCSs observed per
100m2 of each habitat type……………………………………………………………………………………………..13

Figure 4. The mean density of WSC (per m2) summarized from 10 meter transect segments
across all habitats by 5 meter depth bin for each season at Anacapa Island SMR and East
Fish Camp. Error bars represent one standard error…………………………………………………………………..14

LIST OF TABLES

Table 1. Survey totals for Anacapa Island SMR and East Fish Camp, including hours of video,
total distance surveyed (kilometers), swept area of transects (hectares), and average,
minimum and maximum depth (meters) by season…………………………………………………………10

Table 2. Percentages of substrates and habitats by season at Anacapa Island SMR and East
Fish Camp. …………………………………………………………………………………………………………………….11

Table 3. Common and taxonomic (species) names of quantified invertebrates for the spring
and fall combined………………………………………………………………………………………………………….12

Table 4. The average, minimum and maximum depth, and the number of warty sea
cucumbers observed at Anacapa SMR and East Fish Camp during the spring and fall. ………13

INTRODUCTION

BACKGROUND

Warty sea cucumbers (WSC), Apostichopus parvimensis, are an important component of the
subtidal zone, feeding on benthic waste and recycling nutrients. WSCs are found in and
adjacent to rocky outcroppings from the shallow intertidal to approximately 60 m deep from
Monterey, California to Bahia Tortugas, Mexico. Within their range in Southern California
and Mexico, dive fisheries catch WSCs for export to Asian markets. Similar to other sea
cucumber fisheries around the world, demand for WSCs seems to be consistently increasing,
while the resource is becoming less abundant. This trend is also evident in California, where
landings data gathered by the California Department of Fish and Wildlife (CDFW) show that
the fishery has declined in both overall catch and catch per unit of effort (CPUE) in recent
years (State of California Fish and Game Commission, 2017).

CDFW scientists have performed SCUBA surveys since 2013 in an effort to increase their
understanding of basic life history information of the species. Results from the surveys have
indicated that WSCs form spawning aggregations each year in the spring and summer. This
coincides with a peak in the number of cucumbers harvested in commercial dive landings,
with approximately 75% of landings occurring during spring and early summer periods.
Based on these findings, the Fish and Game Commission recently adopted a seasonal closure
to protect spawning aggregations of WSCs each year from March 1-June 14.

While seasonal abundance levels have been well documented at SCUBA depths (less than 30
meters), anecdotal reports from commercial fishery participants have suggested that WSCs
display a seasonal migration from deep to shallower water for spawning. However, to what
degree they utilize deeper waters when they are not found in shallow areas or what
proportion of the population moves to shallow areas during spawning remains unknown.
Because of this, CDFW biologists are interested in gathering more data on WSC distribution
and seasonality of abundance to determine the role that deeper, unstudied areas (greater
than 30 meters) play in supporting their populations. This data may be critical, as the
increasingly high demand for WSCs coupled with the lack of information about them makes
them vulnerable to overexploitation.

The Southern California WSC dive fishery occurs near Anacapa Island State Marine Reserve
(Anacapa Island SMR). A differential in WSC densities inside and outside of this Marine
Protected Area (MPA) has been documented by previous dive studies, where WSC were
shown to be much less abundant outside of the MPA than inside (Schroeter et al., 2001,
California Department of Fish and Game, 2007, State of California Fish and Game
Commission, 2017). To better understand seasonal abundance and depth distribution inside
and outside of MPAs and to examine seasonality of abundance deeper than SCUBA depths,
Marine Applied Research and Exploration (MARE) and CDFW conducted a 2-phase
assessment around Anacapa Island in 2018.Sampling was completed using MARE’s remotely
operated vehicle, ROV Beagle. Two study sites were selected, one inside the protection of
Anacapa Island SMR and one outside of the reserve that was subject to fishing. Both sites are
adjacent to CDFW and National Park Service monitoring stations. Each site was sampled
during the spring (phase 1), and fall (phase 2) to survey both WSC spawning and non-
spawning seasons.

PURPOSE

The purpose of this study was to provide CDFW with critical information that will be used to
inform the management of the WSC dive fishery and to further understand the performance
of an MPA in relation to the fishery. Specifically, we ask whether there is evidence of a
seasonal shift in abundance between shallow well studied areas and deeper areas out to the
observed maximum depth range of the species in the study area. In addition, these data will
inform future study design by providing information related to the extent of sampling
needed to accurately characterize WSC populations in both MPAs and fished areas.

OBJECTIVES

1) Estimate WSC density and relative abundance around two study locations off
Anacapa Island during spring and fall seasons.
2) Provide spatial data to CDFW to allow examination of the distribution and depth
range of WSC inside and outside of Anacapa Island SMR.
3) Provide an archive of high quality video transects capturing ecological conditions that
can be used to inform poorly understood aspects of WSC biology (i.e. growth, size
distribution, habitat associations and movement) that are important to future
management efforts.

The following report describes the data collection and post-processing methods used for this
study. Data summary statistics are presented to highlight preliminary survey results and
general trends. A complete dataset was provided to CDFW for further analysis.

SURVEY METHODS

Phase one surveys were performed in the spring, from May 10th – 12th, 2018 and the second
phase, in the fall, from November 18th – 20th, 2018. During each phase, two study sites were
surveyed, Anacapa Island SMR and East Fish Camp around Anacapa Island in the Channel
Islands (Figure 1). Survey sites and planned transect lines were provided to MARE by CDFW.
Transect lines were placed parallel to depth contours and evenly spaced across the target
range of 15 to 60 meters depth (Figure 1). Sites and transects were chosen to target rocky
habitat although the patchy nature of the Anacapa Island reefs ensured that sufficient soft
sediment and mixed habitats were surveyed.

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 3

Figure 1. Planned transect lines placed parallel to depth contours at Anacapa Island SMR
and East Fish Camp.

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 4ROV EQUIPMENT AND SAMPLING OPERATIONS
MARE’s ROV, the Beagle, was used
to collect data during the survey.
The ROV was operated off of NOAA’s
R/V Shearwater, a National Marine
Sanctuaries research vessel. The

ROV was flown along the pre-
planned transect lines between the

hours of 0800 and 1700. It was
flown off the vessel’s stern using a
“live boat” technique that employed
a 700 lb. depressor weight. Using
this method, the 50 meter tether
allowed the ROV pilot sufficient
maneuverability to maintain a
constant speed and a straight
course down the transect line. The ROV pilot and ship’s helm used real-time video displays
of the location of the ship and ROV to navigate.
For this survey, the Beagle was configured with a forward-facing high definition (HD) video
camera, downward-facing standard definition video camera, and forward facing HD still
camera that collected video and still imagery of WSCs and their surrounding habitats. Photos
were taken of WSCs by scientists when encountered and also automatically at approximately
30 second intervals to capture habitat and other species. The ROV’s on-screen display also
recorded time, depth, altitude, heading, temperature and range. In addition, positional
coordinates were recorded to track the position of the ROV relative to the ship in real time
and to provide the basis for determining length and area of transects for analysis.

POST-PROCESSING METHODS

All data collected by the ROV, along with subsequent observations extracted during post-
processing of the video, were linked in a Microsoft Access® database by time, which was

synced across all data streams at a one second interval. During video post-processing, a
customized computer keyboard was used to input the time of species observations and
habitat characteristics into a Microsoft Access® database.

SUBSTRATE AND HABITAT ANNOTATION

Video was reviewed for six different substrate types: rock, boulder, cobble, gravel, sand and
mud (Green et al. 1999). Each substrate was recorded as a discrete segment by entering the
beginning and ending time. Annotation was completed in a multi-viewing approach, in which
each substrate was recorded independently, capturing the often overlapping segments of
each substrate type (Figure 2). Percent by substrate represents the ratio of the transect lines
that have a given substrate compared to the total line, therefore overlapping substrates can
result in a sum greater than 100%.

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 5

Figure 2. Basic ROV strip transect methodology used to collect video data along the sea floor,
showing overlapping base substrate layers produced during video annotation and habitat
types (hard, mixed soft) derived from the overlapping substrates.

After the video review and annotation process, the substrate data were combined to create
three independent habitat categories: hard, soft, and mixed (Figure 2). Rock and boulder
were categorized as hard substrate types, while cobble, gravel, sand, and mud were
categorized as soft substrates. Hard habitat was defined as any combination of the hard
substrates, soft habitat as any combination of soft substrates, and mixed habitat as any
combination of hard and soft substrates. Habitat percentages sum to 100% and are derived
from substrate types as the proportion of the survey line that contained that specific habitat
type.

INVERTEBRATE ENUMERATION

Video was reviewed for observations of WSCs as well as the following invertebrates of
interest to CDFW scientists: other sea cucumber species, sea stars, sea urchins,
corals/gorgonians, spiny lobster, and keyhole limpets. During the review process, the
forward video camera files were reviewed, and the select macro-invertebrates were
recorded. Each invertebrate observation was entered into a Microsoft Access® database at
the one second time interval when it crossed the bottom of the viewing screen. This insured
that the positional coordinates of the observation were matched exactly with the estimated
position of the ROV.

ROV POSITIONAL DATA

Acoustic tracking systems generate numerous erroneous positional fixes due to acoustic
noise and other errors caused by vessel movement. For this reason, positional data were
post-processed to remove outliers and generate smoothed transects along each survey line
that best represent the true path of the ROV. Estimates of transect length derived from
survey lines processed using this technique have been found to have an accuracy of 1.7 ± 0.5
meters in total length when compared to known lengths between 0 and 100 meters (Karpov
et al. 2006).

ANALYSIS METHODOLOGIES

WARTY SEA CUCUMBER SUMMARIES

Data for WSCs was summarized by habitat type for each site and study season. The density
of WSCs per 100m2 in each habitat type (hard, mixed and soft) for the spring and fall at
Anacapa Island SMR and East Fish Camp were calculated using the following equation:
(Total number of WSCs per habitat type / Total m2 of each habitat type) * 100
Data for WSCs was also summarized by depth by breaking transects into 10 linear-meter
segments. Densities for each segment were calculated using the following equation:
(Total number of WSCs per 10 m segment / Total m2 of each 10 m segment)
Segments were then grouped into depth bins using the average depth per segment and
summarized for each study location and season.

RESULTS

SURVEY TOTALS

Survey effort was similar between sites and sampling periods (Table 1). A total of 15.7 hours
of video was reviewed, 8 hours for the spring survey, and 7.7 hours for the fall survey. Less
distance was surveyed during the spring (10.0 km) than in the fall (12.1 km), where effort
was added to fill in transects that were not surveyed at the East Fish Camp in spring due to
time restrictions (Figure 1). The range of depths surveyed during the spring and fall was
comparable at both sites (Table 1).

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 6

Table 1. Survey totals for Anacapa Island SMR and East Fish Camp, including hours of video,
total distance surveyed (kilometers), swept area of transects (hectares), and average,
minimum and maximum depth (meters) by season.

SUBSTRATE AND HABITAT

A summary of substrate and habitat composition for all survey sites and transects is given in
Table 2. Soft habitat was the dominant habitat observed overall, accounting for an average
of 59% of the habitat surveyed at Anacapa Island SMR, and 68% of the habitat observed at
East Fish Camp during both seasons (Table 2). Sand was the dominant substrate observed
within the soft category, accounting for an average of 83% at Anacapa Island SMR, and 86%
at East Fish Camp combined for both seasons. Hard and mixed habitats were less common
individually, however rocky substrate within those categories was relatively common
accounting for an average of 41% at Anacapa Island SMR and 31% at East Fish Camp for both
seasons combined (Table 2).

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 7

Table 2. Percentages of substrates and habitats by season at Anacapa Island SMR and East
Fish Camp.

INVERTEBRATE TOTALS

Total counts for all invertebrates observed at both Anacapa Island SMR and East Fish Camp
are given in Table for both survey sites and seasons combined. There were approximately
75% less WSCs enumerated during the fall than the spring survey (Table 4). Site specific
differences were not presented and data were not analyzed for non-WSC invertebrate
species observed in this study. These data were provided to CDFW scientists for further
analysis.

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 8

Table 3. Common and taxonomic (species) names of quantified invertebrates for the spring
and fall combined.

WARTY SEA CUCUMBERS

Overall, fewer WSCs were observed at East Fish Camp than at Anacapa Island SMR (Table 4).
And, while the largest proportion of habitat surveyed was soft habitat (Table 2), a greater
density of WSCs were found on hard and mixed habitat types (Figure 3). WSCs were also,
more abundant at both Anacapa Island SMR and East Fish Camp during the spring than the
fall (Table 4, Figure 3).

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 9

Table 4. The average, minimum, and maximum depth and the total number of warty sea
cucumbers observed at Anacapa Island SMR and East Fish Camp during the spring and fall.

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 10

Figure 3. Density of WSCs per 100m2 in each habitat type for the spring and fall at Anacapa
Island SMR and East Fish Camp. Densities represent the total number of WCSs observed
per 100m2 of each habitat type.

As expected, there was a lower mean density of WSCs at East Fish Camp (the fished site) in
all depth bins than at Anacapa Island SMR (the protected site) (Figure 4). Additionally,
there were higher mean densities of WSCs observed at both sites in the 15 to 20 meter
range than at any other depth (Figure 4).

March 2019- Assessment of Warty Sea Cucumber Abundance at Anacapa Island 11

Figure 4. The mean density of WSC (per m2) summarized from 10 meter transect segments
across all habitats by 5 meter depth bin for each season at Anacapa Island SMR and East
Fish Camp. Error bars represent one standard error.

DISCUSSION

The WSC dive fishery around Anacapa Island is not an exception to the pattern seen in other
sea cucumber fisheries, where market demand is increasing as the abundance of the
resource is decreasing (Chavez et al., 2011). The purpose of this study was to provide CDFW
with information to help inform management of the WSC dive fishery by further
understanding the performance of an MPA in relation to the fishery and by quantifying
seasonal WSC abundance to see if they undergo seasonal shifts from shallow to deep.
We looked at the role Anacapa Island SMR (a MPA) may play in providing refugee for this
species by documenting their densities within the SMR and in a nearby fished area. The
results clearly indicated a differential in WSC densities inside and outside the protection of
the MPA, with WSCs being more abundant (~75%) at the MPA site, than the fished site at all
depths and during both survey seasons. These results were consistent with previous results
reported by CDFW SCUBA surveys.
We also quantified WSCs to see if there was evidence of a seasonal shift in abundance
between shallow-water habitats (<30 m) and deep-water habitats (> 30 m). It was found that
anecdotal reports of WSCs exhibiting a seasonal depth migration were not supported by this
study. Although differences in abundance were observed between seasons, with densities
considerably lower in the fall than in the spring, there was no shift in the distribution of
abundance by depth.
In addition, there was no difference in WSC abundance by habitat type between seasons.
Density by habitat type remained proportional between seasons, with no shift from one
habitat type to another. Further study is required to explain the change in WSC abundance
in winter months, when densities in shallower waters decrease drastically.

PROJECT DELIVERABLES

MARE will provide CDFW lead scientist copies of the primary video (forward and downward
facing) and HD still photos for the entire survey on a portable hard drive. Each video and
photo file folder has an accompanying storyboard detailing the ROV name, date, dive
number, location, and transect number. All video recordings contain a timecode audio track
that can be used to automatically extract GPS time from the video.

A copy of the master Microsoft Access database, which contains all the raw and post-
processed data will also be provided to the CDFW lead scientist. These data will include ROV

position (raw and cleaned), ROV sensor readings (depth, temperature, salinity, dissolved
oxygen, forward and downward range, heading, pitch and roll), calculated transect width
and area, substrate and habitat, and invertebrate identifications. Included in the processed
position table are the computed transect identifications for invertebrate transects (see
methods).

REFERENCES

California Department of Fish and Game. 2007. Status of the Fisheries Report, 5. Sea
Cucumbers.

Chavez, E.A., Salgado-Rogel, A.L., Palleiro-Nayar, J. 2011. Stock Assessment of the Wary Sea
Cucumber Fishery (Parastichopus Parvimensis) of NW Baja California. CalCOFI Rep., Vol. 52.

Greene, H.G., M.M. Yoklavich, R.M. Starr, V.M. O’Connell, W.W. Wakefield, D.E. Sullivan, J.E.
McRea Jr., and G.M. Cailliet. 1999. A classification scheme for deep seafloor habitats:
Oceanologica Acta 22(6):663–678.

Gotshall, D.W. 2005. Guide to marine invertebrates – Alaska to Baja California, second
edition (revised). Sea Challengers, Monterey, California, USA.

Karpov, K., A. Lauermann, M. Bergen, and M. Prall. 2006. Accuracy and Precision of
Measurements of Transect Length and Width Made with a Remotely Operated Vehicle.
Marine Technical Science Journal 40(3):79–85.

Schroeter SC., Reed DS., Kushner DJ, Estes JA., Ono DS. 2001. The use of marine reserves in
evaluating the dive fishery for the warty sea cucumber (Apostichopus parvminesis) in
California, U.S.A. Canadian Journal of Fisheries and Aquatic Sciences. 58: 1173-1781.

State of California Fish and Game Commission. July 11, 2017. Initial Statement of Reasons
for Regulatory Action, Title 14 California Code of Regulations, Re: Commercial Taking of
Sea Cucumber.

Veisze, P. and K. Karpov. 2002. Geopositioning a Remotely Operated Vehicle for Marine
Species and Habitat Analysis. Pages 105–115 in Undersea with GIS. Dawn J.
Wright, Editor. ESRI Press.

2021-07-20T20:59:41-08:00March 1st, 2019|research|

August 2018 – A New Species of Gorgonian Octocoral from the Mesophotic Zone

PROCEEDINGS OF THE CALIFORNIA ACADEMY OF SCIENCES
A New Species of Gorgonian Octocoral from the Mesophotic Zone off the Central Coast of California, Eastern Pacific
with a Key to Related Regional Taxa(Anthozoa, Octocorallia, Alcyonacea)
Gary C. Williams 1, 4 and Odalisca Breedy 2, 3

1 Department of Invertebrate Zoology and Geology, California Academy of Sciences, Golden
Gate Park, 55 Music Concourse Drive, San Francisco, California 94118, USA.; 2 Centro de

Investigación en Estructuras Microscópicas, Centro de Investigación en Ciencias del Mar y Lim-
nología, Escuela de Biología, Universidad de Costa Rica. P.O. Box 11501-2060, San José, Costa

Rica; 3 Smithsonian Tropical Research Institute, P.O. Box 0843-03092, Republic of Panama;
4 Corresponding Author: Gary C. Williams (gwilliams@calacademy.org)

Recent offshore benthic surveys utilizing Remotely Operated Vehicles in the Nation- al Marine Sanctuaries along the California coastline under the auspices of the National Oceanic and Atmospheric Administration and the Ocean Exploration Trust, have yielded newly collected material and imagery of octocoral cnidarians from mesophotic and deep-sea habitats. As part of this effort, a new species of gorgonian coral is here described that was first observed at Cordell Bank, approximately 112 km WNW of San Francisco. The species is allocated to the gorgonian genus Chromoplexaura based on morphological considerations, and has since been collected or observed from four localities in central and southern California, 86–107 m in depth.

KEYWORDS: Corals, sea fans, gorgonian octocorals, Central California, Cordell Bank, mesophotic zone, taxonomic key to the genus and related taxa.
Chromoplexaura is currently regarded as a monotypic octocoral genus (Cordeiro et al. 2018c), represented by C. marki (Kükenthal, 1913), and is distributed from central Oregon to southern California on the west coast of North America. Bathymetric distribution of this species varies from nine to at least 90 m (Williams 2013). The new species described here represents a second species of the genus and is known from central to southern California with a depth range of 86 to 106 m. The two species currently share several morphological similarities. Herein we describe a new species that was first observed, but not collected in 2007 by ROV imagery at Cortes Bank in southern California, near the border between California and Mexico. In 2017, colonies were observed (also not collected) by ROV in the Cordell Bank National Marine Sanctuary in central California. In 2018, four specimens were collected by ROV and one was recorded by benthic ROV imagery on board the National Oceanic and Atmospheric Administration (NOAA) ship FSV Bell M. Shimada, at three locations in central and southern California: Cordell Bank NMS, Monterey Bay NMS, and Channel Islands NMS.

MATERIALS AND METHODS

The type material was collected during the benthic surveys of Cordell Bank and Greater Farallones National Marine Sanctuaries on board the NOAA ship FSV Bell M. Shimada (Fig. 1), between 28 July and 11 August 2018. The holotype and paratypes of the new species are deposit- ed in the marine invertebrate collections of the Department of Invertebrate Zoology and Geology at the California Academy of Sciences in San Francisco, California. Underwater video and still imagery were taken on board the ship by NOAA and MARE staff. Images of preserved material and scanning electron micrographs were taken by the first author at the California Academy of Sciences in 2018.
Abbreviations used in the text are as follows: FSV – Fisheries Survey Vessel, MARE – Marine
Applied Research and Education; CASIZ – California Academy of Sciences Invertebrate Zoology;
CBNMS – Cordell Bank National Marine Sanctuary; MBNMS – Monterey Bay National Marine Sanctuary; CINMS – Channel Islands National Marine Sanctuary; NMS – National Marine Sanc- tuary; NOAA – National Oceanic and Atmospheric Administration; ROV – Remotely Operated Vehicle.
Depths used in the text include: Shallow-water (0–40 m); Mesophotic (40–150 m); Deep-Sea (>150 m). Material used for comparative purposes: Chromoplexaura marki; CASIZ 190436; NOAA Sample S-17; Gulf of the Farallones National Marine Sanctuary, Rittenburg Bank (37.88°N 123.32°W); 89.4 m depth; 08 October 2012; ROV Beagle (MARE) from R/V Fulmar (NOAA); three terminal branches, wet-preserved in 95% ethanol. Euplexaura sp.; CASIZ 220608; Western Pacific Ocean, Caroline Islands, Palau (7.54°N 134.47°E); 7-31 m depth; 08 December 2016; cool G.C. Williams; one partial colony, wet-preserved in 95% ethanol. Swiftia torreyi; CASIZ 220958; Cordell Bank National Marine Sanctuary (37.98°N 123.49°W); 948.82 m depth; 10 August 2017;
ROV Hercules/Argus from E/V Nautilus; one whole colony, wet-preserved in 95% ethanol. 144

PROCEEDINGS OF THE CALIFORNIA ACADEMY OF SCIENCES
Series 4, Volume 65, No. 6

FIGURE 1. The National Oceanic and Atmospheric Administration (NOAA) Fisheries Survey Vessel, FSV Bell M. Shimada, conducts fisheries and oceanographic research throughout the Pacific coast of the United States. All type speci-mens of the new coral species described herein were collected by Remote Operational Vehicle (ROV) on board this ship in2018. Photo by Gary C. Williams.

SYSTEMATIC ACCOUNT
Subclass Octocorallia Haeckel, 1866
Order Alcyonacea Lamouroux, 1812
Family Plexauridae Gray, 1859
Chromoplexaura Williams, 2013

Euplexaura Kükenthal, 1913:266; 1924:93.
Chromoplexaura Williams, 2013:17.
GENERIC DIAGNOSIS.— Growth form planar and sparse, branching lateral. Retracted polyps form low rounded protuberances, mound-like to hemispherical in shape. Polyps are present on all sides of the branches, but can be arranged biserially on some narrow terminal branches. Coen-
cenchymal sclerites are primarily robust warty spindles, somewhat ovoid in shape or approaching girdled spindles. Other sclerite types that may be present include radiates, crosses, and spindles with a median waist that approach capstans. Anthocodial sclerites are rods that are straight or curved to sinuous. Colony color red or yellow due to conspicuous color of the sclerites.
TYPE SPECIES.— Euplexaura marki Kükenthal, 1913. Chromoplexaura cordellbankensis Williams and Breedy, sp. nov. Figures 2–10.
HOLOTYPE.— CASIZ 228195; NOAA Sample SH-18-09-017; Cordell Bank, Cordell Bank National Marine Sanctuary, CBNMS Transect-127; ca. 51 km W. of Point Reyes Peninsula (38°03′ 15.465′′N 123°28′48.072′′W); 100.5 m depth; 08 August 2018; ROV Beagle (MARE) from FSV
Bell M. Shimada (NOAA); one partial specimen (missing holdfast), wet–preserved in 95% ethanol.
PARATYPES.— CASIZ 228194. NOAA Sample SH-18-09-016; Cordell Bank, Cordell Bank

National Marine Sanctuary, CBNMS Transect-127; ca. 51 km W. of Point Reyes Peninsula, California, USA (38°03′15.915′′N 123°28′49.874′′W); 101.6 m depth; 08 August 2018; ROV Beagle

(MARE) from FSV Bell M. Shimada (NOAA); one partial specimen (14 mm long branch frag- ment), wet-preserved in 95% ethanol. CASIZ 207519; La Cruz Canyon, Monterey Bay National

Marine Sanctuary; California, USA (35.7694°N 121.4475°W); 106.8 m depth; 28 October 2018; coll. by ROV on board FSV Bell M. Shimada (NOAA); one whole specimen. CASIZ 207520; Anacapa Island, Channel Islands National Marine Sanctuary; California, USA (33.992°N
119.3722°W); 86 m depth; 31 October 2018; coll. by ROV on board FSV Bell M. Shimada (NOAA); one specimen in two pieces.

HABITAT AND DISTRIBUTION.— Found on rugose, rocky substrata often with conspicuous vertical relief, or on rounded boulders in boulder fields (Fig. 3). Distributed off the central and southern coasts of California, between 38.2° and 32.5°N latitude (Figs. 8–9); at mesophotic depths between 86 and 107 m. The type locality is Cordell Bank in the Cordell Bank National Marine Sanctuary, ca. 70 miles WNW of San Francisco, California, 100 m depth.
ETYMOLOGY.— The specific epithet is derived from Cordell Bank and the Latin suffix – ensis (belonging to); referring to the region of discovery of the new species and collection of the holotype – Cordell Bank National Marine Sanctuary.

DESCRIPTION OF THE HOLOTYPE

EXTERNAL MORPHOLOGY.— The holotype is part of a colony, 35 mm in length. The holdfast and basal portion of the colony are missing. Branching is sparse and lateral. The main stem gives rise to two lateral side branches, about 9 mm apart and 2–2.5 mm in diameter (including polyp mounds). The longest branch is 3.4 mm in length (Fig. 2). The retracted polyps form low-rounded to hemispherical polyp mounds, each < 1 mm in length. The polyps are largely distributed biserially on the thinner distal-most portions of branches (Fig. 2B), but occur all around the stouter and more basal parts of the lateral branches and main stem (Fig. 2E). There are approximately ten mounds per cm of branch length. Finger-shaped portions of the coenenchyme-covered internal axis
extend from the apical tips of some branches (Fig. 2B).
ANTHOCODIAE.— Most of the anthocodiae are preserved totally retracted into the polyp mounds, while a few are partially exserted. The walls of the anthocodiae and bases of the tentacles are relatively densely set with narrow rods that have conspicuous tuberculation (Fig. 7). Due the retracted condition of the polyps, an en chevron arrangement of sclerites was not observed or easily apparent. The sclerites of the anthocodiae are lighter in color than the coenenchymal sclerites, many appearing virtually colorless, thus resulting in a white coloration of the polyps.

The polyp mounds are represented by conspicuous rounded protuberances along the branches, usually expanded at the base while some are hemispherical in shape. Adjacent polyp mounds are generally separated by about 1.0–1.5 mm of bare rachis, and vary in width from 1.5–2.0 mm at the base, and are usually less than 1.0 mm in height (Fig. 2).

SCLERITES.— Coenenchymal sclerites vary from 0.06 to 0.22 mm in length (Figs. 4–6, 10A). They are predominantly wide, warty spindles with heavily warted tubercles, while some are narrower with less ornamentation (Figs. 4–5, 10A). Radiates and various immature forms are also present (Fig. 6). Polyp sclerites are elongate rods (Fig. 7), often slightly curved or sinuous with variable tuber- culation, while some are weakly club-shaped (Fig. 7, left). Small, flat rods (Fig. 7, center) are also present and could possibly be from the tentacles. Polyps sclerites vary in length from 0.08–0.24 mm in length.

COLOR.— Coenenchyme color is uniform lemon yellow throughout (Figs. 2–3), due to the conspicuous yellow coloration of the sclerites (Fig. 2F). The anthocodiae are colorless (Fig. 2E).

REMARKS

VARIATION: Although the holotype specimen exhibits only three branches including the main stem, the paratypes as well as additional colonies observed in underwater still images taken by ROV, all exhibit relatively sparse branching, but may possess as many as ten branches including the main stem. One of the paratype colonies (CASIZ 207519), branches up to four times and produces seven lateral branchlets.

DISCUSSION AND CONCLUSION

Key to species of Chromoplexaura and related taxa in California 1a. Colonies planar and sparsely branched. Coenenchymal sclerites are broad to ovoid spindles
with densely set tubercles, capstans, girdled spindles, elongated radiates, and/or tuberculated crosses . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2
1b. Colonies unbranched to copiously branched or bushy. Coenenchymal sclerites may include elongate to needlelike spindles, compact radiates, double discs, and/or disc spindles. . . . . . 3
2a. Colonies red. Coenenchymal sclerites include ovoid spindles and girdled spindles . . . . . . . . .. . . . . . . . .  . . . . . . . . . . . Chromoplexaura marki (Kükenthal, 1913)
2b. Colonies yellow. Coenenchymal sclerites include capstans, elongated radiates, and crosses . .. . . . . . . . . . . . . . . . . . . Chromoplexaura cordellbankensis sp. nov.
3a. Colonies unbranched or Y-shaped. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4
3b. Colonies branched – copiously branched or bushy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5
4a. Colonies white; polyp mounds low-rounded. . Swiftia farallonesica Williams & Breedy, 2016
4b. Colonies coral red to dark red. Polyp mounds prominent – conical to low cylindrical. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Swiftia simplex (Nutting, 1909)
5a. Branching bushy, polyp mounds prominent – conical to cylindrical . . . . . . . . . . . . . . . . . . . . 6
5b. Branching sparse, polyp mounds low-rounded. Colonies coral red with white polyps. . . . . . . . . . . . Swiftia spauldingi (Nutting, 1909)
6a. Polyp mounds truncated conical; sclerites are radiates and elongate spindles with rounded tubercles . . . . . . . . . . . . . . . . . . . . . . Swiftia torreyi (Nutting, 1909)
6b. Polyp mounds stout, conical to cylindrical; sclerites are primarily elongate spiny spindles, often needle-like and curve . . . . . . . Swiftia kofoidi (Nutting, 1909)

TAXONOMIC ASSESSMENT

The genus Chromoplexaura is superficially similar to several Pacific coast Swiftia species. The latter is currently regarded as a gorgonian genus of twenty species (Cordeiro et al. 2018b). The type species of Swiftia is Swiftia exserta (Ellis and Solander, 1786) from the western Atlantic Ocean. Several species from the Pacific coast of the Americas have been allocated to the genus Swiftia, and it is not clear at present whether the Atlantic vs. Pacific species represent the same genus or
separate genera (Williams 2013:17). In addition, there appears to be two distinguishable groups of eastern Pacific species of Swiftia based on morphological characteristics. Preliminary molecular analyses (Everett and Park 2018; Everett, personal communication) have shown that the two
groups (Chromoplexaura and Swiftia) have not exhibited a conspicuous differentiation, but from the morphological point of view are different (Fig. 10A, B, D). An overall detailed molecular analysis and morphological comparison are necessary to provide a cogent taxonomic assessment of the relevant taxa.
Chromoplexaura cordellbankensis sp. nov. shares superficial morphological similarities with some species of Eastern Pacific Swiftia regarding external morphology – such as branching pattern, low-rounded to hemispherical polyp mounds, and elongate-tubercated anthocodial sclerites. However, the coenenchymal sclerites differ markedly from those of Swiftia, while most closely resembling the sclerite complement of Chromoplexaura marki (Williams, 2013:20–21) – i.e. the presence of robust to ovoid, highly warty spindles in the coenenchyme, which are not found in species of
Swiftia (Fig. 10A, B, D).

Chromoplexaura marki was originally placed in the Indo-Pacific genus Euplexaura by Kukenthal, 1913. However, the coenenchymal sclerites of Euplexaura species differ markedly from the two California species of Chromoplexaura, by the possession of tuberculate spheroids, subspheroids, double heads, and plump ovoid to irregular spindles (Fig. 10C; Fabricius and Alderslade 2001:190; Williams 2013:21, 24).

ACKNOWLEDGMENTS

We express our thanks to the staff scientists of NOAA (National Oceanic and Atmospheric Administration), for their support, in particular — Dan Howard and Danielle Lipski (Cordell Bank National Marine Sanctuary), Jan Roletto (Greater Farallones National Marine Sanctuary), Enrique WILLIAMS & BREEDY: NEW SPECIES OF GORGONIAN OCTOCORAL  Salgado (NCCOS, National Centers for Coastal Ocean Science), and Meredith Everett (Northwest
Fisheries Science Center). We are grateful to Guy Cochrane (USGS, United States Geological Survey), Kirsten Lindquist (Gulf of the Farallones Association), the technical staff of MARE (Marine Applied Research and Exploration) — Dirk Rosen, Andy Lauermann, Heidi Lovig, Rick Botman, and Steve Holz, as well as the Marine Operations staff and crew of the NOAA ship FSV Bell M. Shimada.

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2021-07-21T18:43:09-08:00August 19th, 2018|research|

March 2017 – Survey and Research Priorities for Coastal and Marine Systems of the Northern Channel Islands, CA

Western North American Naturalist HORIZON SCANNING:

SURVEY AND RESEARCH PRIORITIES FOR COASTAL AND MARINE SYSTEMS

OF THE NORTHERN CHANNEL ISLANDS, CALIFORNIA

March 2017 - Survey and Research Priorities for Coastal and Marine Systems of the Northern Channel Islands, CA 12

Manuscript Number: WNAN-D-17-00067R1 

Full Title: HORIZON SCANNING: SURVEY AND RESEARCH PRIORITIES FOR COASTAL 

AND MARINE SYSTEMS OF THE NORTHERN CHANNEL ISLANDS, CALIFORNIA 

Article Type: California Islands Symposium Article 

Corresponding Author: Mary Gleason, Ph.D. Nature Conservancy Monterey, California UNITED STATES 

Corresponding Author Secondary Information: 

Corresponding Author’s Institution: Nature Conservancy 

Corresponding Author’s Secondary Institution: 

First Author: Mary G. Gleason 

First Author Secondary Information: 

Order of Authors: Mary G. Gleason 

Jennifer E. Caselle 

Chris Caldow 

Russell Galipeau 

Walter Heady 

Corinne Laverty 

Annie Little 

David Mazurkiewicz 

Eamon O’Byrne 

Dirk Rosen 

Stephen Whitaker 

March 2017 - Survey and Research Priorities for Coastal and Marine Systems of the Northern Channel Islands, CA 13

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

Order of Authors Secondary Information: 

Abstract: Historical marine ecology provides information on past ocean conditions and 

community structure that can inform current conservation and management. In an era of rapid global ocean changes, it is critical that managers and scientists ensure sufficient documentation of past and present conditions of resources they manage or study. Documenting, archiving, and preserving historic and contemporary data will provide their colleagues in the future with more information to make robust science- based management decisions. Using a workshop approach, we identified research and archiving priorities to enhance documentation of the past and present conditions of coastal and marine ecosystems of the northern Channel Islands in California. We identified a variety of types of historical data (e.g., archeological data, oral histories, environmental records, imagery) that should be preserved and analyzed to better understand past coastal and marine ecosystems around the northern Channel Islands. Continuing with long-term monitoring programs is also important for establishing baselines to inform contemporary management decisions and compare with future conditions. We underscore the role that individual scientists and managers working in the northern Channel Islands must play in documenting their work, archiving data, and preserving specimens in museums and institutions. Our case study for the northern Channel Islands provides a guide for how scientists should be documenting past and present conditions for marine resources around the world. Robust documentation of such conditions will give future scientists, managers, and other stakeholders the information needed to navigate what are sure to be increasingly complex management challenges. 

HORIZON SCANNING: SURVEY AND RESEARCH PRIORITIES FOR COASTAL AND MARINE SYSTEMS OF THE NORTHERN CHANNEL ISLANDS, CALIFORNIA

Gleason, M.G. 1*, J. E. Caselle2, C. Caldow3, R. Galipeau4, W. Heady1, C. Laverty5, A. Little6, D. Mazurkiewicz4, E. O’Byrne1, D. Rosen7, and S. Whitaker

1The Nature Conservancy, 201 Mission St., San Francisco, CA, USA 2 Marine Science Institute, University of California, Santa Barbara, CA, 93106 3 Channel Islands National Marine Sanctuary, University of California Santa Barbara Ocean Science Education Building 514, MC 6155, Santa Barbara, CA 93106-6155 4 Channel Islands National Park, 1901 Spinnaker Dr., Ventura, CA 93001 5 Natural History Museum of Los Angeles County, 900 Exposition Blvd., Los Angeles, CA 90007 6 U.S. Fish and Wildlife Service, 1901 Spinnaker Dr., Ventura, CA 93001 7 Marine Applied Research and Exploration, 1230 Brickyard Cove Rd. #101, Richmond, CA 94801 

*Corresponding author: mgleason@tnc.org 

Running Head: Coastal and marine information for the century ahead 

ABSTRACT
Historical marine ecology provides information on past ocean conditions and community
structure that can inform current conservation and management. In an era of rapid global ocean
changes, it is critical that managers and scientists ensure sufficient documentation of past and
present conditions of resources they manage or study. Documenting, archiving, and preserving
historic and contemporary data will provide their colleagues in the future with more information
to make robust science-based management decisions. Using a workshop approach, we identified
research and archiving priorities to enhance documentation of the past and present conditions of
coastal and marine ecosystems of the northern Channel Islands in California. We identified a
variety of types of historical data (e.g., archeological data, oral histories, environmental records,
imagery) that should be preserved and analyzed to better understand past coastal and marine
ecosystems around the northern Channel Islands. Continuing with long-term monitoring
programs is also important for establishing baselines to inform contemporary management
decisions and compare with future conditions. We underscore the role that individual scientists
and managers working in the northern Channel Islands must play in documenting their work,
archiving data, and preserving specimens in museums and institutions. Our case study for the
northern Channel Islands provides a guide for how scientists should be documenting past and
present conditions for marine resources around the world. Robust documentation of such
conditions will give future scientists, managers, and other stakeholders the information needed to
navigate what are sure to be increasingly complex management challenges.

INTRODUCTION

Coastal and marine ecosystems are being subjected to increasing impacts due to human activities
such as resource extraction, pollution, and anthropogenic climate changes that pose significant
threats to ecological processes, biodiversity, ecosystem health and food security (Worm et al.
2009; Hoegh-Guldburg and Bruno 2010; Cózara et al. 2014; Greene 2016). Understanding and
responding to these impacts represents a significant challenge to the scientific and conservation
communities, in part because of unique attributes of the marine environment. The pace of some
indicators of climate change (e.g., species shifts) may be faster in marine ecosystems, especially
mid-latitude upwelling ecosystems, relative to many other systems (Burrows et al. 2011; Doney
et al. 2012). Additionally, the scale of chemical and material transport in the ocean is generally
quite large (i.e., many kilometers). Due to the fluid nature of marine ecological processes, spatial
boundaries are dynamic across time and over many different parameters. The “openness” of
marine systems, with species distributions defined by dynamic water bodies and broad dispersal

and movement patterns, affects connectivity of populations, genetics, trophic interactions, and
the ability to protect and restore those populations (Kinlan and Gaines 2003; Carr et al. 2003).
Ownership and access issues are also markedly different in the marine environment than on land.
Additionally, we know relatively little about marine ecosystems, especially deeper zones,
compared to terrestrial ecosystems. This is because ocean ecosystems are difficult to access,
require the development of new tools, and, as a result, are expensive to study. Coastal
ecosystems, occupying a relatively narrow zone at the intersection of land and sea, have their
own unique conservation challenges and are subject to stressors from both land and sea, as well
as looming threats from sea level rise (Scavia et al. 2002; Sloan et al. 2007; Heberger et al.
2011).

Overcoming the special challenges of research in coastal and marine ecosystems and collecting
baseline data and information for informed management are essential. We need information on
the current status of resources and the processes affecting them, as well the natural variability
and responses of systems to specific environmental or anthropogenic-based changes. To better
equip and inform natural resource decision-making today and into the future, Morrison et al. (in
press) highlight the accountability that scientists and managers have to ensure data pertaining to
past and present conditions of the resources in their charge are collected and archived. Historical
marine ecology provides information on past ocean conditions and community structure that
informs our current understanding of conservation status, recovery targets, and management
needs (Jackson et al. 2001; Lotze et al. 2006; McClenachan et al. 2012). As memories fade,
records are lost, conditions change, and baselines shift it is important to do what we can now to
document and secure information from the past and present. Global change will bring added

complexity and challenges to stewardship of the coastal and marine environment, but we suggest
that a strong and easily accessible record and documentation of past and current conditions will
give stakeholders and decision-makers in the future the kind of valuable information they will
need. What future managers will ultimately do with this information from the past is hard to
predict and will be context-specific. However, there is a growing understanding that making
resource management decisions, such as how to maintain populations or communities in their
current state or whether to bring an ecosystem back to an earlier state, will benefit from an
understanding of baseline conditions, trajectories of historic change, and the impacts of humans
on observed changes (McClenachen 2012; Thurstan et al. 2015).

As a first stage in this process, we undertook an inquiry to examine the current state of
documentation of past and present conditions of the coastal and marine ecosystems of the
northern Channel Islands of California (USA), an area of high conservation value and of
management and scientific interest. Our inquiry focused on three questions: How can we better
document past conditions? How can we better document present conditions? And, how can we
build support for data collection and archiving that can be used to make more informed
management decisions today and into the future? Our inquiry was conducted as part of a broader
effort to assess research and archiving needs and opportunities for the California Islands
(Morrison et al., in revision). Our assessment presents a case study of, and a template for, how
this type of inquiry can be applied to marine resources elsewhere.

MANAGEMENT AREA AND RESOURCES OF INTEREST

The Santa Barbara Channel region is highly variable, sitting at the confluence of warm- and
cold-water ocean currents, which results in an important biogeographic transition zone for many
marine organisms (Hickey 1998; Hamilton et al. 2010). The ocean waters around the northern
Channel Islands are some of the most protected in the world, lying within the federal Channel
Islands National Marine Sanctuary (henceforth, the “Sanctuary”) and the Channel Islands
National Park. In addition to the federal designations, the State of California established a
network of 13 marine protected areas (MPAs) in 2003, 11 of which are no-take reserves
(Figure1; Airame et al. 2003; Gleason et al. 2013).

While much of the marine environment around the islands is protected from extractive activities,
large areas still support extractive activities, such as recreational and commercial fishing, that are
likely to grow in importance as human population increases. In addition, this region experiences
impacts from other sources including shipping (e.g., noise, whale strikes, pollution), land-based
pollutants carried offshore, offshore oil and gas development, tourism, and climate impacts (e.g.,
warming water temperatures, ocean acidification, sea level rise).

Santa Barbara Island, while geographically grouped with the southern Channel Island
archipelago, is included in this overview due to this shared management boundary and research
history. We assumed that as we identified questions and information needs related to this
jurisdictional unit, the geographic area of interest may scale outward depending on the specific
resource or question of interest. For example, connectivity issues in the marine environment, as
described above, may lead to conservation strategies that transcend political boundaries.
Similarly, conservation of particularly threatened species or habitats might dictate research
priorities at spatial scales larger than this study area boundary.
Coastal and marine resources

The coastal and marine ecosystems and resources in the northern Channel Islands are important
for their biodiversity values and relevance to the people who have lived, worked, and recreated
around the islands and their waters both currently and historically. As an ecoregional transition
zone, marine biodiversity is quite high, containing species with both northern (cold water) and
southern (warm water) affinities. The coastal bluffs and shorelines around the northern Channel
Islands include habitats such as coastal scrub, small wetlands, pocket beaches, intertidal rocky
habitats, and offshore rocks and islets. Each island supports unique vegetative communities on
the coastal margins (such as coastal bluff scrub, coastal sage scrub, and chaparral) and rare
endemic plant species; much of the coastal vegetation has been altered by human activities and is
in some stage of recovery. Coastal areas provide grounds for colonies of seabirds such as Ashy
Storm-Petrel (Oceanodroma homochroa), California Brown Pelican (Pelecanus occidentalis),
Brandt’s Cormorant (Phalacrocorax pencillatus), Pigeon Guillemot (Cepphus columba),
Cassin’s Auklet (Ptychoramphus aleuticus), Scripps’s Murrelet (Synthliboramphus scrippsi), and
others. These areas are also important for marine mammal rookeries and haul-outs for species

Study area boundary

We defined our study area as the waters around the northern Channel Islands, and used the
federal Sanctuary boundary as the demarcation (Figure 1). This is akin to using the management
unit of an individual island or protected area as a focal area for determining research and
documentation priorities for terrestrial resources. The Sanctuary encompasses 1,110 square
nautical miles (1,470 square miles or 3,807 km2) of water from mean high tide to six nautical
miles offshore of Santa Barbara, Anacapa, Santa Cruz, Santa Rosa, and San Miguel Islands.

such as California sea lion (Zalophus californianus), northern fur seal (Callorhinus ursinus),
northern elephant seal (Mirounga angustirostris), and others (NCCOS 2005).

Offshore, the marine environment can be characterized by different depth zones (e.g., inner shelf

0-30m, middle shelf 30-100m, outer shelf 100-200m, meso-benthal slope 200-500m, and bathy-
benthal slope >500m), different substrate types (e.g., silt, sand, cobble, bedrock), the presence of

submerged aquatic vegetation (e.g., eelgrass and surfgrass) or macroalgae (e.g., kelp forests).
The waters in the Sanctuary around the northern Channel Islands range from intertidal to
approximately 1,600 meters in depth, with bathymetric complexity in the form of submarine
canyons and pinnacles, and important deep sea coral and sponge communities. Similarly, there
are different pelagic zones (e.g., bathypelagic, mesopelagic, and epipelagic) characterized by
their depth, physical oceanographic parameters, and frontal boundaries. These marine
ecosystems support a diverse array of algal, invertebrate, fish, seabird, and marine mammal
populations. Important fishery species include spiny lobster (Panulirus interruptus), market
squid (Loligo opalescens), sea cucumbers, urchins, many species of rockfish (Sebastes spp.),
lingcod (Ophiodon elongatus), sanddabs (Citharichthys spp.), sheephead (Semicossyphus
pulcher), yellowtail (Seriola dorsalis), and many others. Marine mammals around the islands
include the pinnipeds listed above and many cetacean species such as blue whales (Balaenoptera
musculus), gray whales (Eschrichtius robustus), humpback whales (Megaptera novaeangliae),
bottlenose dolphin (Tursiops truncates), long-beaked and short-beaked common dolphins
(Delphinus capensis and D. delphis), and many others (NCCOS 2005).

We recognize that many of the resources that are the focus of our inquiry here are linked in
complex ways to the natural and cultural resources found in the terrestrial realm of the islands.
Similar inquiries as ours were directed to terrestrial flora and fauna and cultural resources of
Santa Cruz Island (Boser et al. in review; Morrison et al. in revision; Randall et al. in review;
Rick et al. in review.) We encourage readers to review those assessments for a multidisciplinary
overview of the study area, as there were many overlapping interests and complementary sets of
recommendations.

DOCUMENTATION OF THE PAST

Historical ecology approaches have been used to understand long-term change in marine systems
(Jackson et al. 2001; Pandolfi et al. 2003; McClenachan 2009) with goals of informing
restoration, conservation and management (Pesch and Garber 2001; VanDyke and Wasson
2005). For example, in California, museum seabird specimens have played a key role in
documenting historic population size, changes in diet, community structure, ocean conditions, or
pollutants over time (Beissinger and Peery 2007; Osterback et al. 2015). While some of the
methods and data sources for historical ecology are similar between terrestrial and coastal or
marine systems, there are important differences. For example, often specialized tools are
required for accessing underwater environments, so research in marine systems has lagged far
behind terrestrial systems. Relatively recent advances in SCUBA, remotely operated vehicles
(ROV), autonomous underwater vehicles (AUV) and submarines have made more habitats
accessible and some monitoring now occurs in most marine ecosystems. However,
reconstructions of the past in marine systems tend not to be as ‘deep in time’ as terrestrial
examples.

Examples of use of historical ecology from the Channel Islands

The Channel Islands and broader Santa Barbara Channel have a long history of environmental
change and human occupation and exploitation of resources, including 13,000 years of maritime
Chumash presence and hundreds of years of Spanish, Asian, and Euro American presence. The
archeological record reflects that history and documents significant changes in flora and fauna in
the region that can inform modern day management (Rick et al. 2008). In the Channel Islands,
two case studies using very different types of data provide examples of how historical
information could be used in modern-day management and conservation. Bellquist and Semmens
(2016) used fishing records compiled from a regional fishing newspaper (Western Outdoor
News) to reconstruct changes in size structure of recreationally-fished species throughout coastal
California, but with an emphasis on the northern Channel Islands. The work followed from
previous studies from Florida that utilized old photographs from fishing piers (McClenachan et
al. 2009) and a long-time series of fishing records from the International Game Fishing
Association (Roberts et al. 2001; Bohnsack 2011) to document temporal declines in fish size and
changes in fish community structure, and to assess benefits of MPAs to recreational fishing,
respectively. Bellquist and Semmens (2016) showed that since 1966, 12 out of 16 species
analyzed showed declines in trophy size (size of the largest individuals in a population). Of those
12 species, nine showed very recent stabilization or increases in trophy size. Importantly, the

creation of this database from an untraditional source overcame current limitations in temporal-
and spatial-resolution with traditional fisheries-dependent and fisheries-independent data
collected in California.

A second study (Braje et al. 2017) measured very long-term changes (over 10,000 years) to
population abundance and size structure of an ecologically and commercially important fish
species, California sheephead. Comparing zooarchaeological records from the Channel Islands
with contemporary samples, and using stable isotope analysis to measure food habits, these
authors provide a more accurate baseline of the size and diet of California sheephead, prior to the
development of a fishery in the early 20th century. They found that the average size of sheephead
along the northern Channel Islands today is significantly smaller than in the deep past. This may
be due to the targeting of large sheephead by modern commercial and recreational anglers, which
has culled many of the largest fish from the modern population. However, the authors also
provide evidence for the long-term continuity and stability of sheephead populations in the
northern Channel Islands, both in terms of relative abundances and average sizes with
fluctuations in time in both metrics, suggesting hope for the restoration of this fishery in the
Channel Islands region. This research is a rare example of long-term historical analysis
attempting to provide actionable data for modern fisheries management.

Despite a growing interest in historical information, and increasing discovery of a variety of non-
traditional data types, historical data are still not commonly utilized in marine management or

conservation decisions (McClenachan et al. 2012). These authors note several obstacles ranging
from funding limitations on gathering historical data in the first place to challenges of
incorporating non-traditional data into existing quantitative frameworks. Yet, when historical
long-term data are incorporated into marine population assessments (e.g., for fisheries or
extinction risk assessments), they often point to more severe population declines than in
assessments without long-term data (McClenachan et al. 2012). In fact, this problem of shifting

baselines in marine ecosystems and populations has been described by many authors (Pauly
1995; Dayton et al. 1998; Jackson et al. 2001; Pinnegar and Engelhard 2007) and has potentially
limited management and restoration efforts by identifying rebuilding targets that may be
dangerously low or simply underestimating the magnitude of declines. As we move forward
collecting and archiving data on marine and coastal ecosystems of the present, attention to the
current challenges of incorporating these data into conservation and decision-making may help to
overcome these limitations in the future. For example, accessibility and documentation (via
archiving and good metadata practices) might make data more discoverable to future historical
ecologists.

Importance of historical information in context of ocean change

The importance of taking a longer view of our coastal and marine ecosystems, especially in a
dynamic area like the northern Channel Islands cannot be overstated. Recent human-induced
climate fluctuations are layered on decadal (e.g., Pacific Decadal Oscillation) and shorter-term
(e.g., El Nino Southern Oscillation) timeframes. Anthropogenic activities have increased
dramatically in the region since the early 19th and 20th centuries with increases in fishing pressure
brought by the Chinese and Euro-American fisheries as the native Chumash populations were
reduced (Braje et al. 2017). More recently, commercial shipping, invasive species, pollution,
disease outbreaks and tourism have all increased, with largely unstudied impacts on the marine
and coastal systems. Several well-documented extirpations of marine species have occurred in
the Channel Islands region with varying effects on present day marine communities. One of the
best-documented examples involved the loss of a keystone predator in the system, the southern
sea otter (Enhydra lutris nereis), due to intensive hunting associated with the fur trade beginning

in the early-1800s (Braje et al. 2013). By 1830, southern sea otters were functionally extinct
throughout California. After protection in 1911 by the International Fur Seal Treaty, southern sea
otter populations have increased, albeit very slowly (USFWS 2015). Current community
structure of rocky reefs and kelp forests (essentially encompassing all modern kelp forest
monitoring time series) almost certainly reflects the loss of this top, keystone predator. However,
it has been suggested that southern California kelp forests may be more resilient to change than
other kelp forests in the range of the sea otter due to high levels of functional redundancy in
predators, including sheephead and spiny lobster (Steneck et al. 2002; Graham et al. 2008).

Should the sea otter expand its current range to the northern Channel Islands (a small re-
introduced population lives at San Nicolas Island), we might expect to see dramatic changes to

the kelp forest systems, perhaps a reflection of the historical state.

Another dramatic loss of a suite of species involved a combination of overfishing and disease.
Red and black abalone (Haliotis rufescens and H. cracherodii, respectively) were important food
sources for the Chumash Indians on Santa Cruz Island (Braje et al. 2009). With the loss of sea
otters described above, and declines in the Chumash population, two main predators on these
species, abalone experienced population explosions in the early 1800’s (Braje et al. 2009), with
black abalone reported to be stacked five deep in the intertidal on Santa Cruz Island. Beginning
in the 1960s, five species of abalone suffered serial depletion in the Channel Islands, attributed to
a combination of overharvest, disease, and a long-term warming trend leading to poor
recruitment (Leet et al. 1992; Engle 1994). One species of abalone, the white abalone was the
first marine invertebrate on the federal endangered species list. Very recent, anecdotal reports of
recovery of some species of abalone are encouraging but to date, the fishery for abalone south of

Point Conception remains closed. Conservation and management today, and into the future,
could benefit from a better understanding of the longer-term context of the region, including both
natural and human-induced fluctuations in populations and how marine communities were
structured. This does not mean that restoration to some previous state is either possible or even
desirable. However, knowing the bounds of fluctuations and their relationships to abiotic and
biotic factors over long time scales can guide restoration towards realistic endpoints.

Potential sources of historical data for northern Channel Islands

The northern Channel Islands provide rich opportunities for exploration and ‘rediscovery’.
Workshop participants identified many potential sources of information that could allow for
reconstruction of past environmental conditions and human uses of coastal and marine systems.
We grouped these potential sources into seven categories that span from ‘deep time, such as
information potentially obtained from reconstructed environmental records and archeological
surveys, to the more recent past, as potentially obtained from historical records, oral histories,
scientific surveys, imagery, and fishing data (Table 1). With these types of information sources,
it is then often possible to reconstruct historic baselines though temporal comparisons, time
series analysis, hindcasting, and space-for-time comparisons (Lotze and Worm 2009).

Some of these historic data sources are highly vulnerable to loss. For example, many of the
coastal archeological sites around the northern Channel Islands – sites that contain a rich archive
of data regarding both marine and terrestrial ecosystems – are experiencing ongoing destruction
due to storm surge and sea level rise (Reeder et al. 2012). The knowledge of many late-career
scientists who spent decades conducting research in the study area could be lost unless

investments are made in interviewing them as part of an “oral history” project and facilitating the
archiving of their field notes. We urge managers and scientists to prioritize data collection from
ephemeral sources that are susceptible to degradation or loss.

C. Minto, S.R. Palumbi, A.M. Parma, D. Ricard, A.A. Rosenberg, R. Watson, and D. Zeller.
2009. Rebuilding global fisheries. Science 325:578-585.

DOCUMENTATION OF THE PRESENT

Investment in long-term ecological studies and monitoring can have significant benefits in
tracking ecosystem changes through time, as well as informing environmental policy (Hughes et
al. 2017). Probably one of the most important actions we can take today to help the
conservationist or manager of the future is to comprehensively inventory and document today’s
marine and coastal ecosystems and make sure those data are archived well into the future. As we
considered how we could improve data collection and archiving in the present and for historical
ecologists’ use in the future, there was broad agreement among workshop participants that
completing a baseline on ocean conditions and ensuring stable support for long-term monitoring
are critical.

Completing ocean baseline and supporting long-term monitoring

There is a high density of academic institutions, state and federal agencies, and non-profits
located on the adjacent mainland who have conducted research or monitoring of coastal and
marine resources in the northern Channel Islands. In fact, a variety of long-term monitoring
programs are already in place (Table 2). Some of the best examples come from the multiple
programs that survey kelp forests and rocky intertidal areas. The implementation of MPAs
throughout California has provided impetus and funding for continuing and expanding many
existing long-term monitoring programs, as well as developing new monitoring in habitats where

programs did not already exist (e.g., deep-water, sandy beach), or adding alternative types of
data to assessments (e.g., social and economic data). In addition to the ‘benthic’ ecological
monitoring programs mentioned above, the region hosts some very comprehensive seabird and
marine mammal monitoring programs (Table 2). Finally, the area is also well studied from an
oceanographic perspective with many of the programs mentioned above also maintaining
instrumentation to measure, for example, temperature, wave exposure, salinity, oxygen and
currents.

Despite a relative wealth of existing data and monitoring programs in the coastal and marine
environment, workshop participants identified areas where present day monitoring or assessment
could be added or enhanced. When asked what data the marine scientist or manager of the future
would like to see collected now, several areas of inquiry emerged. First, measures of abiotic
habitat (e.g., extent, type, quality) are fundamental to understanding variation in biotic
communities over space and time. California has made substantial progress in completing

benthic habitat maps for the majority of the state using technology such as side-scan and multi-
beam sonar. Side scan and multi-beam sonar can provide important information on benthic

structure, erosion, geomorphological change, and patterns of island subsidence over time.
Unfortunately, one of the primary gaps in the statewide mapping process is in the area around the
northern Channel Islands. While substantial progress has been made recently and 70% of the
Sanctuary seafloor has been surveyed by high-resolution sonar, only 20% of the area contains an
actual habitat map developed by post-processing those data. The majority of the remaining
seafloor mapping gaps occur in shallower areas that are home to some of the most productive
and healthy kelp forest and rocky reef communities in the region. Completion of benthic habitat

mapping in this area would provide critical information to aid incident response and restoration
activities, inform protected resources and fishery management, and improve navigational safety.
These core products are building blocks for informed survey design and fundamental to
understanding species/habitat presence, abundance, and vulnerability.

Similarly, when investigating the drivers of change or spatial variation in biotic communities,
understanding anthropogenic activities at relevant spatial and temporal scales is critical. For
example, the widespread implementation of MPAs, a spatial management tool, should be
accompanied by data on fishing effort at similar spatial scales. Similar arguments can be made
for spatial data on other human uses including recreational activities, military actions, and energy
development. Expansion of long-term monitoring programs into new habitats (e.g., deep water)
initiated during the MPA baseline monitoring period should be continued. New technology is
continually advancing and one technique in particular, the use of soundscapes and audio
recordings, was identified by the group as having potential for use in the Channel Islands. Audio
has been used successfully for some time to assess marine cetaceans, but increasingly, sound is
being used to document seabird populations and the ‘health’ of whole ecosystems such as reefs or
estuaries (Buxton and Jones 2012; Lillis et al. 2014; Oppel et.al. 2014; Harris et al. 2016).

Prioritizing what needs to be done now to guide future management

Ecologists, conservation practitioners and natural resource managers agree that long-term
monitoring of the environment is critical for understanding and making decisions in complex
ecological systems (Lindenmayer and Likens 2009). Increasingly, the linkages between humans

and ecosystems are also recognized as important aspects to monitor (i.e., Social-Ecological
Systems (SES); Folke 2006; Ostrom 2009). However, resources to do long-term monitoring are
limited. Virtually all long-term, environmental or social monitoring programs face funding
challenges and as such, must evaluate where and when to allocate limited resources for
maximum benefit. The benefits of long-term monitoring programs and the value of the data
might not be realized until well into the future. Building monitoring programs that can address
both present day and future needs is a difficult, but important, undertaking. As a general rule,
developing criteria for data collection investments can help to clarify needs and increase the
future utility of monitoring programs.

Given the many ongoing monitoring programs in existence in the Channel Islands region,
potential criteria could be established to help guide and prioritize monitoring investments. These
criteria should include: 1) the length of existing time series; 2) filling key gaps, both disciplinary
and geographic (e.g., nearshore benthic habitat mapping, human use patterns, deep water
habitats); 3) monitoring of new stressors and emerging issues (e.g., climate change, ocean
acidification, plastic pollution, marine diseases, invasive species); and 4) incorporation of new
and cost-effective technologies (e.g., monitoring soundscapes with autonomous recording units;
eDNA for biodiversity monitoring; satellite imagery; new underwater visual technologies; drones
and UAVs; and the use of citizen science).

Other general features of successful monitoring programs include the ability to adapt. Long-term
monitoring programs are often plagued by poor planning from the outset and a lack of tractable
questions. Lindenmayer and Likens (2009) suggest a framework for adaptive monitoring that

stresses asking clear, tractable questions, developing solid, defensible statistical and data
collection methodologies, and most importantly, iterating the process, thereby allowing for
learning and adaptation. In the context of the northern Channel Islands, with its large number of
ongoing monitoring programs, consistency in methods but also foresight and flexibility to react
to changing conditions will be critical to gathering useful information.

In addition to monitoring programs, it is also critically important that individual scientists and
managers take responsibility for and take every opportunity to document their work, archive their
data, and preserve specimens in museums and institutions. If this were a regular practice and
expectation for all scientists, over time we would do a better job of accumulating information
about the systems of today. Some key institutions that currently house coastal and marine
specimens from the Channel Islands include the Santa Barbara Museum of Natural History, Los
Angeles County Museum, University of California (e.g., Jepson Herbaria), California Academy
of Sciences, San Francisco Maritime Museum, Western Foundation of Vertebrate Zoology,
Smithsonian Institution, NOAA National Centers for Coastal Ocean Science, and others.
Reviewing the myriad data archiving resources available to marine scientists is beyond the scope
of this paper but funding agencies and foundations as well as scientific publishing enterprises are
increasingly requiring data to be made discoverable and accessible through links to data
repositories when available (Table 2).

COORDINATION AND COLLABORATION

Two important themes that emerged from the workshop were: a) the need for increased
coordination and collaboration among groups doing ocean related work and b) the importance of

building and maintaining public support for research and monitoring. As mentioned above, the
Santa Barbara Channel region is relatively data rich compared to many marine regions of the
world, and while efforts have been made to coordinate research capacity and emerging data
streams, more can be done. Currently, the Sanctuary’s Research Activities Panel acts as an
informal clearinghouse for marine research in the Sanctuary, meeting at least once per year and
gathering many local researchers for roundtable discussions of findings. Data documentation and
discovery has also improved substantially over the past decade with most long-term monitoring
programs hosting and serving data via internet accessible portals (see links in Table 2). Next
steps might include the development of joint databases or repositories such as the Sanctuary
Integrated Monitoring Network (SiMON) portal or the inclusion of more disparate types of data
into Southern California Ocean Observing System (SCOOS).

While data availability into the future is key to guiding conservation and management, the idea
of having informed and invested stakeholders who support continued conservation and science
was viewed as equally important. The public has already invested in the Channel Islands, via
managing agencies such as the Sanctuary, National Park Service, U.S. Fish and Wildlife Service,
and the California Department of Fish and Wildlife; what is needed is to ensure those
investments last into the future. The northern Channel Islands are a special place to many
generations of stakeholders in that they are so close to such large population centers, they present
iconic land and seascapes, and have a rich cultural and natural history. Suggestions for building
public support for research and monitoring include durable outreach that tells compelling stories
of how research has contributed to ecosystem improvement, especially stories that can counter
the narrative that monitoring is boring and expensive (Suarez and Tsutsui 2004). Involvement of

citizens in research and monitoring programs can also help to build a strong and educated
constituency (Bonney et al. 2009). Citizen science is a growing enterprise and several existing
programs operate in the Channel Islands including Reef Check California which utilizes
recreational scuba divers to monitor kelp forests (Friewald et al. in review). Coordination at all
levels, from data collection, archiving and analysis, to outreach and public involvement will
increase the effectiveness of management and conservation in the region.

CONCLUDING REMARKS

Scientists and managers of today have an opportunity and a responsibility of leaving a legacy of
solid information, data, and collections to inform coastal and marine conservation and
management into the future. The workshop participants had many ideas for how to help the
scientist or manager of the future who will be looking back at our time and trying to understand
the ecosystems, culture, management context and decisions of our day. A handful of ‘no-regrets’
strategies surfaced that, if implemented, would provide a strong foundation upon which
scientists, conservationists, and managers of the future could use to understand the ecosystems of
our time. These recommendations include:
(1) Use hindcasting, modeling, and historic data to better understand the past coastal and
marine conditions and ecosystems around the northern Channel Islands, how those
ecosystems have changed over time, and how resilient they were in the past to climate
change, harvest, and species introductions or removals.
(2) Complete and archive today’s “baseline” information including filling key gaps like
seafloor mapping, surveying deeper unexplored sites, mapping human uses around the
islands, interviewing key stakeholders, and preserving specimens to leave future
scientists a thorough and useful record. We also need to make sure that we are adaptively
managing our monitoring programs and using the data to help drive management and
resource protection as new threats arise (e.g., invasive species, plastics, ocean
acidification).
(3) Promote a sense of individual scientist’s responsibility to document, archive, and
preserve data and specimens to make sure our colleagues in the future will be able to
locate and capitalize on collections, materials, and data from our time. By working with
oral historians and museum curators, we could collect and preserve the scientific stories
and specimens of our time. Such an archiving system can also help to connect researchers
and resource managers via joint data needs.
(4) Document today’s management decisions and their rationale, so that future generations
understand the management context of our time and why we made the management
decisions we did. This includes documenting smaller decisions (not necessarily captured
in the public record) and even when we decided not to take an action (e.g., to reduce
populations or remove an invasive species).
(5) Break down silos across disciplines (terrestrial/marine, benthic/pelagic,
ecology/archeology, etc.) to ensure that we are telling the whole story and able to
understand complex dynamics in our changing world. Particularly as ocean temperatures,
chemistry, currents, and species distributions change, we will need to understand the
impacts of those changes across many systems and over time.
(6) Build a constituency of public support for and investment in scientific monitoring,
research, and data collection through education, citizen science, and outreach to the many
people who have enjoyed the northern Channel Islands for generations. There are limited

funds for data collection and archiving and we need to identify new ways to engage the
public in this important work.

ACKNOWLEDGEMENTS

We thank the participants of the 2016 Island Rediscovery Workshop held January 28-29, 2016 at
the Santa Barbara Museum of Natural History and sponsored by The Nature Conservancy and
the Smithsonian Institution, as well as the participants at the Marine Rediscovery session held on
October 3, 2016 as part of the 9th Channel Islands Symposium. S. Ostermann helped with Table
2 and M. Cajandig helped with Figure 1. S. Morrison and two anonymous reviewers kindly
reviewed the draft manuscript.

FIGURE LEGEND

Figure 1. Map of study region showing the northern Channel Islands with state marine reserves
and conservation areas shown in outlines. Dotted line and dark shading delineates the Channel
Islands National Marine Sanctuary boundaries.

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June 2017 – Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017

Coastal Impact Assistance Program CIAP 2016 Survey 5 Final Technical Report

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 14

Visual Surveys of Fish, Macro-invertebrates and Associated Habitats Using a Remotely Operated Vehicle: Soquel Canyon to Point Buchon, September – October 2016
Coastal Impact Assistance Program
CIAP 2016 Survey 5 Final Technical Report
CDFW Contract # P1370005
Report Prepared by
Andrew Lauermann
& Heidi Lovig
June 22, 2017
Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 15

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

TABLE OF CONTENTS
LIST OF FIGURES ………………………………………………………………………………………………………………………….. 3
LIST OF TABLES ……………………………………………………………………………………………………………………………. 4
INTRODUCTION …………………………………………………………………………………………………………………………… 6
OBJECTIVES….. …………………………………………………………………………………………………………………………….. 6
PURPOSE…… ………………………………………………………………………………………………………………………………… 6
DATA COLLECTION METHODS ……………………………………………………………………………………………………… 8
ROV EQUIPMENT ………………………………………………………………………………………………………………………….. 8
ROV SAMPLING OPERATIONS ………………………………………………………………………………………………………. 9
SITE AND SURVEY LINE SELECTION ……………………………………………………………………………………………. 10
POST-PROCESSING METHODS …………………………………………………………………………………………………….. 12
ROV POSITIONAL DATA ……………………………………………………………………………………………………………….. 12
SUBSTRATE AND HABITAT …………………………………………………………………………………………………………… 12
FINFISH ENUMERATION ………………………………………………………………………………………………………………. 13
INVERTEBRATE ENUMERATION ………………………………………………………………………………………………….. 14
RESULTS ……………………………………………………………………………………………………………………………………….. 16
SURVEY TOTALS…………………………………………………………………………………………………………………………….. 16
SUBSTRATE AND HABITAT ……………………………………………………………………………………………………………. 16
FINFISH AND MACRO-INVERTEBRATE SUMMARIES ……………………………………………………………………. 19
FISH COUNTS ………………………………………………………………………………………………………………………………… 21
INVERTEBRATE COUNTS……………………………………………………………………………………………………………….. 25
INVERTEBRATE PATCH COVER …………………………………………………………………………………………………….. 29
PROJECT DELIVERABLES ……………………………………………………………………………………………………………… 32
MAPS …………………………………………………………………………………………………………………………………………….. 33
REFERENCES ………………………………………………………………………………………………………………………………… 40

“LIST OF FIGURES”

“Figure 1. Study locations (blue boxes) from Soquel Canyon to Point Buchon and the sites (red boxes) surveyed within each…………………………………………………….33
“Figure 2. ROV survey lines within the Soquel Canyon (SQ3) and Portuguese Ledge (PRL1, PRL2, PRL3) site boundaries………………………………………………………..34
Figure 3. ROV survey lines within the Pacific Grove (PG1, PG2), Asilomar (AS1, AS2, AS4), Point Lobos (PL1, PL4, PL7, PL11) and Carmel Bay (CB1) site boundaries…….35
Figure 4. ROV survey lines within the Point Sur (PS2, PS3, PS5) and Big Creek (BC7) site boundaries…………………………………………………………………………………….36
Figure 5. ROV survey lines within the Big Creek (BC1, BC2, BC3, BC4, BC5, BC6) site boundaries…………………………………………………………………………………………..37
Figure 6. ROV survey lines within the Piedras Blancas (PIE1, PIE2) site boundaries………………………………………………………………………………………………………………38
Figure 7. ROV survey lines within the Morro Bay (MB1, MB2, MB3, MB4), Church Rock (CR) and Point Buchon (PB2, PB5) site boundaries…………………………….39

“LIST OF TABLES”
“Table 1. Total distance of hard and/or mixed habitat, with min and max depth, from completed survey lines and the total number of fish and invertebrate transects generated from video collected at sites sampled in September and October, 2016……17”

“Table 2. Percentages of substrates and habitats for all survey lines completed and post processed at each of the sites sampled in September and October, 2016……………..18

Table 3. Total kilometers and total counts for finfish and invertebrates (inverts) and the average count per kilometer for fish and invertebrates at sites sampled in September and October, 2016……………………………………………………………………………..20”

“Table 4. Common and taxonomic names, course size (see methods) and depth range of quantified finfish (list sorted by count). Description of criteria used for complexes or unidentified groupings is included with database metadata provided to CDFW………..23

Table 5. Common and taxonomic names and depth range of quantified invertebrates (list sorted by count). Description of criteria used for complexes or unidentified groupings is included with database metadata provided to CDFW………………………27

Table 6. Invertebrate patch cover by site and species/groupings (see methods for a complete list). Total area of site is the sum total of the area (m2) surveyed and total area with invertebrate is the total area (m2) of the site that the invertebrate was present. Percent cover code is the average of all the cover codes for each patch by site and species………………………………………………………………………………………….30”

INTRODUCTION

The California Department of Fish and Wildlife (CDFW) and its partners have conducted video surveys using remotely operated vehicles (ROVs) in MPAs statewide since 2002. Utilizing Coastal Impact Assistance Program (CIAP) funding, CDFW has initiated a three year project to support ROV surveys within the state. The goal of this project is to complete quantitative baseline surveys of commercially and recreationally important fish and macro-invertebrate species in three regions: Southern California, Northern California, and North Central California. Data from completed surveys will be used to examine the condition of habitats important to managed species inside and outside of selected MPAs in each study region, as well as informing fishery and MPA management. Specifically, at-sea ROV surveys will target MPA and reference site (fished area) site pairs and other sites designated by CDFW. Survey data will be collected, post-processed, and summarized by Marine Applied Research and Exploration (MARE) and provided to CDFW to complete the following project objectives:

OBJECTIVES
1) Estimate fish and macro-invertebrate species density and relative abundance inside and outside of MPAs.
2) Determine size frequency distributions of ecologically important commercial and recreational species to one centimeter resolution using stereo cameras.
3) Provide spatial data to allow examination of the distribution of observed species in relation to other spatial datasets such as high resolution bathymetry, spatially derived habitat classification, and fishery dependent data.
4) Provide an archive of high quality video transects that capture the baseline ecological conditions for California’s MPAs
PURPOSE
The purpose of this report is to present detailed data collection and post-processing methods, and summarized post-processing results of data collected from Soquel Canyon to Point Buchon, surveyed in September and October 2016. Results focus on basic data summaries that are simply a starting point for further analysis, therefore no detailed comparison or statistical analyses are presented.

DATA COLLECTION METHODS

ROV EQUIPMENT

The ROV used in this study was a Deep Ocean Engineering Vector M4, named ROV Beagle, owned and operated by Marine Applied Research and Exploration. The ROV was equipped with a three-axis autopilot including a rate gyro-damped compass and altimeter. Together, these allowed the pilot to maintain a constant heading (± 1 degree) and constant altitude (± 0.3 m) with minimal corrections. In addition, a forward speed June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 16control was used to help the pilot maintain a consistent forward velocity between 0.25 and 0.5 m/sec. A pair of Tritech® 500 kHz ranging sonars, which measure distance across a range of 0.1–10 m using a 6° conical transducer, were used as the primary method for measuring transect width for both the forward an downward facing video. Each transducer was pointed at the center of view in each camera and was used to calculate the distance to middle of screen, which was subsequently converted to width using the known properties of each cameras field of view. Readings from these sonars were averaged five times per second and recorded at a one-second interval with all other sensor data. Measurements of transect width using a ranging sonar are accurate to ± 0.1 m (Karpov et al. 2006).

An ORE Offshore Trackpoint III® ultra-short baseline acoustic positioning system with ORE Offshore Motion Reference Unit (MRU) pitch and roll sensor was used to reference the ROV position relative to the ship’s Wide Area Augmentation System Global Positioning System (WAAS GPS). The ship’s heading was determined using a KVH magnetic compass. The Trackpoint III® positioning system calculated the XY position of the ROV relative to the ship at approximately two-second intervals. The ship-relative position was corrected to real world position and recorded in meters as X and Y using the World Geodetic System (WGS)1984 Universal Transverse Mercator (UTM) coordinate system using HYPACK® 6.2 hydrographic survey and navigation software. Measurements of ROV heading, depth, altitude, water temperature, camera tilt and ranging sonar distance both forward and downward to the substrate, were averaged over a one-second period and recorded along with the position data.

The ROV was equipped with three standard resolution and one high definition (HD) video color cameras: two locally recorded stereo cameras for highly accurate measurements of size and two primary data collections cameras; one facing forward (HD) and set approximately 30o below the horizon and the other pointing downwards. The two-camera system provided a continuous, slightly overlapping view. Video for both cameras was captured using vMix® recording software (codec H.264, 50 Mbps, 30fps, 1920 x 1080) and Pioneer DVR510 digital video disc recorders. In addition to capturing biological and habitat observations, the forward video was overlaid with an on screen display of text characters representing real time sensor data (time, depth, temperature, range, altitude, forward camera angle and heading). The ROV was also equipped with an HD still camera and strobe, which was locally were locally recorded on the vehicle. At the end of each survey day, imagery was downloaded and saved to a porTable hard drive.

GPS time was used to provide a basis for relating position, field data and video observations (Veisze and Karpov 2002). A Horita® GPS3 and WG-50 were used to generate on screen displays of GPS time, as well as output Society of Motion Picture and Television Engineers (SMPTE) linear time-code (LTC) for capture on SONY® DSR audio tracks at an interval of 1/30th of a second. This method was improved by customizing HYPACK® navigational software to link all data collected in the field to the GPS time. ROV tracked position and sensor data were recorded directly by HYPACK® as a time-linked text file. A redundant one-second time code file of sensor data was also collected in the field using a custom built on-screen display and operating system software with time code extracted from the system’s internal clock which was synced to GPS time.

All data collected by the ROV, along with subsequent observations extracted during post-processing of the video, was linked in a Microsoft Access® database using GPS time. Data management software, developed by MARE, was used to expand all data records to one second of Greenwich Mean Time (GMT) time code. During video post-processing, a Horita® Time Code Wedge (model number TCW50) was used in conjunction with a customized computer keyboard to record the audio time code in a Microsoft Access® database.

ROV SAMPLING OPERATIONS

ROV operations were conducted off the F/V Donna Kathleen, a 19 m research vessel owned and operated by Captain Robert Pedro. Surveys were conducted between the hours of 0800 and 1700 PST to avoid the low light conditions of dawn and dusk that might affect finfish abundance measurements and underwater visibility.

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The ROV was flown off the vessel’s port side using a “live boat” technique that employed a 317.5 kg (700 lb.) clump weight. Using this method, all but 45 m of the ROV umbilical was isolated from current-induced drag by coupling it with the clump weight cable and suspending the clump weight at least 10 m off the seafloor. The 45 m tether allowed the ROV pilot sufficient maneuverability to maintain a constant speed (0.5 to 0.75 m/sec) and a straight course down the planned survey line.

In addition, the ROV pilot and ship’s helm used real-time video displays of the location of the ship and the ROV, relative to the planned survey line, to navigate along the 500 m line. The ship’s captain used the displays to follow and maintain the position of the ship within 35 m of the ROV.

At each site, the ROV was flown along pre-planned survey lines. The ROV pilot maintained forward direction within ± 10 m of the planned line. The ranging sonars were fixed below and parallel to the camera between two forward-facing red lasers spaced 100 mm apart. The ROV pilot used the sonar readings to sustain a consistent transect width by maintaining the distance from the camera to the substrate (at the screen horizontal mid-point) between 1.5 and 3 m.

SITE AND SURVEY LINE SELECTION
Survey site selection was made by the CDFW lead scientist to collect baseline data on both soft and hard bottom habitats within select MPAs and outside fished reference areas from Soquel Canyon to Point Buchon (Figure 1). Prior to at-sea operations, planned survey lines within each site were selected and placed across the width of the site parallel to the prevailing depth contour and bathymetry. The locations of the survey lines were chosen by selecting the desired number of planned lines and then using a systematic random approach, distributing them across the site. Survey lines were numbered according to the distance along the site boundary running from shallow to deep. The number of survey lines planned at each site was determined by the CDFW lead scientist.

POST-PROCESSING METHODS

ROV POSITIONAL DATA
Acoustic tracking systems generate numerous erroneous positional fixes due to acoustic noise and other errors caused by vessel movement. For this reason positional data was post-processed to remove outliers. Positional information, in the form of XY metric coordinates, was filtered for outliers and smoothed using a 21-point running mean (Karpov et al. 2006). Planar length of positions tracked was calculated for each second and combined with width to calculate area surveyed per second. Gaps in the positional data that occurred due to deviations from quantitative protocols, such as pulls (ROV pulled back by ship induced tension on the 45 m tether), stops (ROV stops to let the ship catch up) or loss of target altitude caused by traveling over backsides of high relief structures (visual loss of 4 m target distance for more than 6 seconds which typically occurs on the downward slope of high relief habitat) were removed from the data to be used to generate quantitative transects along each survey line. The remaining usable portions of each survey line were then divided into two different transect types; fish density transects and invertebrate density transects. Details on each transect type are described later in the post-processing methods.

SUBSTRATE AND HABITAT
A protocol to characterize substrate observed in video along survey lines was developed to be compatible to a hierarchical classification system developed by GreenJune 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 18 et al. (1999). The video record was reviewed and substrate types were classified independently as rock, boulder, cobble, sand or mud. Rock was defined as any igneous, metamorphic or sedimentary substrate; boulder as rounded rock material that is between 0.25 and 3.0 m in diameter and clearly detached from the base substrate; cobble as broken or rounded rock material that is between 6 and 25 cm in diameter and clearly detached; sand as any granular material with a diameter less than 6 cm (may include organic debris such as shell or bone, gravel or pebble); and mud as fine silt like material.
During review of the video record, a transparency film overlay with guidelines approximating a 1.5 m wide swath was placed over a video monitor screen. Each of the substrate types are identified by the processor independently and were recorded as discrete segments of the transect by noting where it was present with a beginning and ending time code. Thus, the segments of substrate types may overlap each other along the survey line, creating areas of mixed substrate combinations (e.g. rock/sand, sand/cobble) along the transect.

A substrate segment was considered continuous until a break of two meters or greater occurred along the survey line or the substrate dropped below 20% of the total combined substrates for a distance of at least three meters. After the review process, the substrates were combined to create three independent habitat types: hard (rock and/or boulder), mixed (rock and/or boulder with cobble and/or sand and/or mud) or soft (cobble and/or sand and/or mud).

FINFISH ENUMERATION
Fish density transects used the entire forward cameras horizontal field of at the mid-screen and were calculated using a two-step approach. First, the usable portions of each survey line were divided into 25 m2 segments (subunits). Each subunit’s total percent hard and/or mixed habitat was then calculated and those with percentages below 50% hard or mixed were removed. Next, the remaining subunits were concatenated into 100 m2 transects (four sequential useable 25 m2 subunits) for use in density calculations. One spacer subunit was discarded between each transect to minimize bias of contiguous transects (spatial autocorrelation). Using this method of post-stratification generates hard substrate transects without the loss of rock/sand interface habitat which may be important to some species. All subunits and final transects are created using a labeling scheme that preserves the original data, thus future data analysis can stratify using other parameters or transect sizes.

Finfish video review and enumeration classified finfish to the lowest taxonomic level possible. Finfish that were not able to be classified to the species level were grouped into a complex of species, or recorded as unidentified. All finfish species and groupings were selected after a preliminary review of video prior to the formal enumeration processing. Several fish species were only enumerated as a complex due to visual characteristics and sizes that are difficult to discern from video and include: olive rockfish (Sebastes serranoides) and yellowtail rockfish (Sebastes flavidus), which were grouped together into the olive/yellowtail rockfish complex. Rosy rockfish (S. rosaceus) and starry rockfish (S. constellatus) were grouped into the Sebastomus rockfish complex. All combfish and eelpout species were enumerated using the combfish complex and eelpout complex respectively.

A screen overlay representing a diminishing perspective was used during fish review to approximate the transect width across the vertical viewing screen, calculated by the ranging sonar, at mid-screen (Karpov et al. 2006). The overlay served as a guide for determining if a fish was in or out of the ROV transect. Finfish enumeration was limited to a maximum distance of four meters. Using the sonar range value depicted on the screen as a gauge, the processor determined if a fish was within four meters as it entered the viewing area. Fish that entered the viewing area were only counted if more than half the fish crossed the overlay guidelines.

In order to accurately correlate the location of the fish with habitat, time code entry was made when the fish crossed the mid-screen line. For finfish that were within four meters, but swam away before they crossed the mid-screen line, time code entry was made when the location where the finfish had been observed reached the mid-screen point. All data entries were recorded in a Microsoft Access® database linked with the time code.
Fish size (total length) was estimated by the video observer with the use of two parallel lasers placed 10 cm apart aimed to hit the seafloor in the center of the video viewing screen of the forward facing camera. Fish sizes were estimated to the nearest cm and when possible tagged for future stereo sizing. Criteria for stereo sizing included fish orientation (almost perpendicular) and distance (within 2 meters) to the cameras. Only fish that were close to perpendicular and within the center of the viewing area were tagged for future stereo sizing.

INVERTEBRATE ENUMERATION
Invertebrate transects used only the field of view at the bottom of the viewing monitor, which was calculated using paired lasers as 45% of the mid screen width. Each transect was calculated by dividing the usable portions of each survey line into 30 m2 transects. The total percent hard and/or mixed habitat was then calculated. No transects were removed from the summaries based on habitat criteria.

Invertebrate video review and enumeration identified macro-invertebrates to the lowest taxonomic classification level possible, or grouped them into a complex of species. All invertebrate species and groupings were based on review of video prior to enumeration. Only macro-invertebrates with body forms and colors that were uniformly identifiable on video were selected to be enumerated (Gotshall 2005). Invertebrate species that form large colonial mats or cover large areas, were not enumerated as individuals, but rather identified as patches with discrete start and stop points along the transect and given a coverage code to quantify the total coverage within the viewing area of the patch. Patches were coded for percent cover using four groupings: 1) less than 25% cover, 2) between 25% and 50% cover, 3) between 50% and 75% cover, and 4) greater than 75% cover. Six species/groupings were quantified using these methods: Unidentified brachiopod species, mat-forming brittle star species, club-tipped anemone (Corynactus californica), market squid eggs, unidentified zoanthid species, and feather stars (class Crinoidea). All identifications to species level were based on visual attributes and should be considered the best possible identification based on appearance only.

A screen overlay was also used during invertebrate review and enumeration to approximate the transect width, calculated by the ranging sonar, at the bottom of the screen. The diminishing perspective overlay lines served as a guide for determining if an invertebrate was in or out of the ROV transect. The overlay used for invertebrate enumeration was the same as the overlay used in habitat classification, allowing for direct correlation of habitat to each invertebrate observation. In order to accurately correlate the location of the invertebrate with the habitat, time code entry was made when the invertebrate crossed the bottom of the screen line. All data entries were recorded in a Microsoft Access® database linked with the time code. Invertebrates that entered the viewing area were only counted if more than half the animal crossed the overlay guidelines at the bottom of the screen.

RESULTS

SURVEY TOTALS
ROV surveys were conducted from September 16, to October 14, 2016. A total of 97.4 km were surveyed and post-processed across 33 sites, distributed over 12 study locations (Table 1). A total of 68% of the area surveyed was made up of hard and/or mixed habitat types (66.4 km).
The number of transects (both fish and invertebrate) varied by site and was dependent on the number of survey lines planned, and the amount of available rocky habitat (fish transects only) at each site. A total of 1,023 post-stratified fish transects (100 m2) and 4,346 invertebrate transects (30 m2) were generated from the 146 survey lines sampled (Table 1).

SUBSTRATE AND HABITAT
Substrate and habitat composition for all study sites and survey lines processed are given in Table 2. The ‘Percent by substrate’ represents the ratio of the survey line that has a given substrate compared to the total line. Each substrate type (i.e. Rock, boulder, cobble, etc.) are not relative percentages to other substrate categories. Habitat percentages derived from substrate types and are presented as the proportion of the survey line that contained that specific habitat type.
Rock was the dominant substrate observed, accounting for an average of 67% of the total substrate coverage at each site. Sand and mud were observed next most commonly observed substrate types, accounting for 27% and 26% of the average total substrate coverage at each site, respectively. Boulder and cobble were the least observed substrates, accounting for an average of only 3% and 8% of the observed substrate at each site, respectively.
Hard habitat was the dominant habitat observed over all study sites, accounting for an average of 43% of the habitat surveyed at each site. Soft and mixed habitats were less common, accounting for an average of 33% and 24% of the habitat observed at each site, respectively.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 19
June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 20

FINFISH AND MACRO-INVERTEBRATE SUMMARIES

Total counts for fish and invertebrates, as well as counts per kilometer of transect surveyed by site, are given in Table 3.
More fish were counted at Point Sur, than any other study location. A total of 83,618 individuals were enumerated at all of the Point Sur sites combined, which represented 26% of the total number of fish counted at all survey locations. Point Sur also had a high average count of fish per km, with 6,709 fish per km at all sites combined. Point Lobos had the highest average counts of fish per km, just slightly more than Point Sur, with 6,993 fish counted per km. Soquel Canyon had the lowest number of fish enumerated, with a total count of only 1,330 fish at the SQ3 site.

Approximately two times more macro-invertebrates were counted at Portuguese Ledge, than at any other study location. A total of 21,072 individuals were enumerated (not including invertebrate patch cover) at all of the Portuguese Ledge sites combined, which represented approximately 24% of the total number of invertebrates counted at all survey locations. Over half of those were counted at just one site, PLR1. Big Creek study location had the second highest number of invertebrates, with a total of 17,168 counted at all sites combined.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 21

FISH COUNTS
A complete list of total counts for all 101 finfish species and groupings June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 22identified from video collected at all sites combined in September and October of 2016 are shown in Table 4. Of the 320,152 total finfish observed at all sites, the majority (95.5%) were identified as a rockfish species or grouping. Of the smaller rockfish species/groupings, YOY were the most commonly observed, accounting for over 80.5% of all fish observations.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 23While, the small schooling rockfish species/groupings (typically <15 cm), which included Shortbelly, Halfbanded, Squarespot, Pygmy and other unidentified small schooling rockfishes, were less common, accounting for 7.3% of all fish observations. Larger rockfish species (>15 cm) were also less commonly observed, accounting for 7.7% of all fish observations. Larger epi-benthic schooling rockfish (such as Blue, Black, Olive/Yellowtail and Widow rockfishes) represented the largest proportion of the large rockfish observations, accounting for 62.2% of the total large rockfish observations. Benthic and demersal rockfish (such as Vermilion, Gopher, Canary and Copper rockfishes) accounted for 25.6% of the total large rockfish observations. Due to the low visibility conditions of the North Coast, the remaining 12.2% of the large rockfish observed were classified as unidentified rockfish.

Non-rockfish species represented a substantially smaller proportion of the totalJune 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 24 fish observations, accounting for a combined total of just 4.5% of the total fish counts. Unrecognized and unidentified fish accounted for a substantial number (57.8%) of the non-rockfish species observations. Kelp and Painted Greenling, Lingcod, flatfish and surfperch made up approximately 23% of the total non-rockfish counts, or just 1% of the total fish observations.

Due to poor water visibility and video resolution limitations, positive identifications were not always possible and a proportion of the fish observations were classified as “unidentified”. In addition, smaller fish were more difficult to recognize than larger ones. When possible, unidentified observations were placed into groupings such as unidentified rockfish or unidentified flatfish. The unidentified categories of fish only accounted for a little over 4% of the total finfish observations

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 25
June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 26

INVERTEBRATE COUNTS
A complete list, including total counts of all 103 macro-invertebrate species andJune 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 27 groupings (not including invertebrate patches) identified from video collected from September and October of 2016, is given in Table 5.
Of the 88,236 individual invertebrates observed at all sites, sea stars (from 25 species/groupings) were the most abundant, accounting for 25.4% of all invertebrates enumerated. Two species, the bat star and the red sea star, accounted for nearly 80% of the total sea star observations (47.6% and 31.4% respectively). Other commonly observed sea stars included: the long legged sunflower star, the Henricia star complex, cookie star and fish eating star, which combined accounted for 15.4% of the total sea star observations. The remaining 19 species/groupings accounted for the other ~5.6% of sea star observations.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 28Urchins represented 19.8% of the total invertebrate observations, with 17,449 individuals enumerated from six species/groupings. White urchins were the most abundant, accounting for over 60% of the total urchin observations. The red sea urchin, purple sea urchin and fragile pink urchin were also frequently observed, accounting for 20.8%, 10.3% and 8.2% of the total urchin observations, respectively.
Corals and gorgonians represented 12.7% of the total invertebrate observations, with 11,191 individuals enumerated from 12 species/groupings. Red gorgonians were the most abundant, accounting for nearly 43% of all coral and gorgonian observations. The white sea pen, UI dead gorgonians, UI sea pens, and sea whips were also frequently observed, accounting for 22.2%, 18.3%, 7.9% and 6.3% of the total coral and gorgonian observations, respectively.

Other invertebrates that were commonly observed included anemones June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 29(from 10 species/groupings), crabs (7 species/ groupings), sea cucumbers (7 species/ groupings) and sponges (9 species groupings) which combined accounted for nearly 30% of the total invertebrate observations. The most abundant species from each were the white-plumed anemone, pelagic red crab, California sea cucumber and UI nipple sponge, which combined accounted for 20.3% of the total invertebrate observations.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 30
June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 31

INVERTEBRATE PATCH COVER
Invertebrate patch cover for four quantified species/groupings is given in Table 6. June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 32The club-tipped anemone was the most commonly observed invertebrate patch, observed on over 1,993 m2 and occurring at 25 of the 30 sites surveyed in September and October of 2016. The percent of total area containing club-tipped anemones was highest at Church Rock, where club-tipped anemones were present on over 12% of the total area surveyed there. They were also commonly observed at four of the Point Lobos sites covering 3.6% of the total area surveyed at all four sites combined.

Feather stars (Crinoidea) were observed at fewer sites (13) than club-tipped anemones, but covered just slightly less area, 1,701 m2. They were most abundant at June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 33the Portuguese Ledge study location, where they were observed at all 3 sites, covering 3.4% of the total area surveyed at all three sites combined.

Other patch-cover invertebrates observed include: brittle stars, UI zoanthids, UI brachiopoda, market squid eggs and Lophelia complex. Brittle stars covered a total of 546 m2 and were only observed at three sites, June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 34one in Point Lobos (PL4) and two at Big Creek (BC2 and BC3). UI zoanthids covered a total of 98 m2, and were only observed at three of the southern study locations, Big Creek (site BC6), Morro Bay (site MB3) and Church Rock (site CR). UI brachiopoda, market squid eggs and Lophelia complex were each present at only one site, and covered only 44 m2, 2 m2 and 25 m2, respectively.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 35
June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 36

PROJECT DELIVERABLES
MARE has delivered to the CDFW lead scientist six copies of the primary video (forward and downward facing) for the entire survey on DVD. Each copy has been provided in individual binders with a corresponding look-up catalog that provides survey location, date, dive number and DVD disc number. Each DVD has an accompanying storyboard detailing the ROV name, date, dive number, location, and transect ID number. In addition to the six DVD copies of the survey, MARE has also delivered a full copy of the master HD forward video on a portable hard. All video recordings contain a timecode audio track that can be used to automatically extract GPS time from the video.

In addition to the primary video record, MARE has also provided a complete hard drive copy of all high definition (HD) still photos, including the standard resolution stereographic video, collected during the survey. Stereographic video was recorded continuously during ROV dives, capturing more than 30 individual fish/km (for abundant fish species) with accuracy to 0.5 cm. All imagery has been provided on a PC based hard drive and each file has been labeled using a naming scheme that provides date and GPS timecode.

A copy of the master Microsoft Access database, which contains all the raw and post-processed data has also been provided to the CDFW lead scientist. These data will include ROV position (raw and cleaned), ROV sensor (depth, temperature, salinity, dissolved oxygen, forward and downward range, heading, pitch and roll), calculated transect width and area, substrate and habitat, fish and invertebrate identifications and invertebrate patch location and percent cover. Included in the processed position table are the computed transect identifications for both fish and invertebrate transects (see methods). Also provided to the CDFW lead scientist were the GIS shapefiles for all survey lines and site boundaries sampled.

MAPS
Maps of all study locations and sites surveyed within each location are given in Figures 1 – 6. All sites were surveyed in September and October 2016.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 37

Figure 1. Study locations (blue boxes) from Soquel Canyon to Point Buchon and the sites (red boxes) surveyed within each location.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 38

Figure 2. ROV survey lines within the Soquel Canyon (SQ3) and Portuguese Ledge (PRL1, PRL2, PRL3) site boundaries.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 39

Figure 3. ROV survey lines within the Pacific Grove (PG1, PG2), Asilomar (AS1, AS2, AS4), Point Lobos (PL1, PL4, PL7, PL11) and Carmel Bay (CB1) site boundaries.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 40

Figure 4. ROV survey lines within the Point Sur (PS2, PS3, PS5) and Big Creek (BC7) site boundaries.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 41

Figure 5. ROV survey lines within the Big Creek (BC1, BC2, BC3, BC4, BC5, BC6) site boundaries.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 42

Figure 6. ROV survey lines within the Piedras Blancas (PIE1, PIE2) site boundaries.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 43

Figure 7. ROV survey lines within the Morro Bay (MB1, MB2, MB3, MB4), Church Rock (CR) and Point Buchon (PB2, PB5) site boundaries.

REFERENCES

Greene, H.G., M.M. Yoklavich, R.M. Starr, V.M. O’Connell, W.W. Wakefield, D.E.
Sullivan, J.E. McRea Jr., and G.M. Cailliet. 1999. A classification scheme for deep
seafloor habitats: Oceanologica Acta 22(6):663–678.

Gotshall, D.W. 2005. Guide to marine invertebrates – Alaska to Baja California,
second edition (revised). Sea Challengers, Monterey, California, USA.

Karpov, K., A. Lauermann, M. Bergen, and M. Prall. 2006. Accuracy and
Precision of Measurements of Transect Length and Width Made with a
Remotely Operated Vehicle. Marine Technical Science Journal 40(3):79–85.

Veisze, P. and K. Karpov. 2002. Geopositioning a Remotely Operated Vehicle for
Marine Species and Habitat Analysis. Pages 105–115 in Undersea with GIS. Dawn J.
Wright, Editor. ESRI Press.

2021-07-21T18:49:17-08:00June 22nd, 2017|research|

June 2017 – Oceana Deep sea Coral and Sponge 2017 Final Report


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Oceana Deepsea Coral and Sponge 2017 Final Report

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 44

June 5, 2017

Andrew R. Lauermann, Heidi M. Lovig, Yuko Yokozawa, Johnathan Centoni, Greta Goshorn

 

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 45

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

TABLE OF CONTENTS

 

INTRODUCTION 4

METHODS 5

DATA COLLECTION 5

ROV Equipment 5

ROV Sampling Operations 6

POST-PROCESSING 6

Substrate and Habitat 7

Finfish and Invertebrate Enumeration 7

RESULTS 9

SURVEY TOTALS 9

SUBSTRTATE AND HABITAT 11

Substrate 11

Habitat 11

FISH AND INVERTEBRATE TOTAL COUNTS 11

Fish 11

Invertebrates 11

FISH AND INVERTEBRATE DENSITY 16

Fish 16

Invertebrates 16

MAPS OF TRANSECTS 20

Southeast Santa Rosa Island 21

Footprint Deep Ridge 22

West Santa Barbara Island 23

West Santa Barbara Island 24

West Santa Barbara Island 25

South Santa Barbara Island 26

West Butterfly Bank 27

UNIDENTIFIED SPECIES LIST 28

Anemones 28

Boot Sponges 28

UI Lobed Sponge 29

Other Sponges Observed 30

UI Bubblegum Coral 31

REFERENCES 32

INTRODUCTION

From August 7th through 11th of 2016, four study locations were surveyed using a remotely operated vehicle (ROV) within the Sothern California Bight. The goal of this Oceana lead expedition was to collect high definition video and still imagery within unique deep-water sponge and coral habitats. Study areas and dive locations were based on bathymetry mapping data and/or data from NOAA’s Deep Sea Coral National Observation Database. The data collection protocols used for this project were similar  to those used inside the Channel Islands National Marine Sanctuary, Monterey Bay National Marine Sanctuary, Farallon Islands National Marine Sanctuary, Cordell Bank National Marine Sanctuary and at over 175 sites in and adjacent to California’s marine protected areas network.

During the 5-day expedition, deep-water ROV surveys were conducted near Santa Rosa Island, Footprint MPA, Santa Barbara Island and Butterfly Bank. During each  dive, ROV survey lines were broken into 15-minute transects at the discretion of Oceana scientists onboard. Each 15-minute transect and the corresponding positional data were subsequently post-processed in the lab by Marine Applied Research and Exploration (MARE) using standardized methods that were developed in partnership by the California Department of Fish and Wildlife and MARE. These methods have been used since 2003 to process over 2,000 km of ROV video.

The following report describes the data collection and post-processing methods used for the survey. Data summaries are provided which highlight post-processing results and a complete database of all data collected will be provided to Oceana.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 46

METHODS

DATA COLLECTIONJune 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 47

ROV Equipment

An observation class ROV, the Beagle, was used to complete benthic surveys of select Southern California Bight study locations. The ROV was equipped with a three-axis autopilot including a rate gyro- damped compass and altimeter.  Together, these allowed the pilot to maintain a constant heading (± 1 degree) and constant altitude (± 0.3 m) with minimal corrections. In addition, a forward speed control was used to help the pilot maintain a consistent forward velocity between 0.25 and 0.5 m/sec while on transect. A Tritech® 500 kHz ranging sonar, which measure distance across a

range of 0.1–10 m using a 6° conical transducer, was used as the primary method for measuring transect width from the forward facing HD video. The transducer  was pointed at the center of the camera’s viewing area and was used to calculate the distance to middle of screen, which was subsequently converted to width using the known properties of the cameras field of view. Readings from the sonar were averaged five times per second and recorded at a one-second interval with all other sensor data. Measurements of transect width using a ranging sonar are accurate to ± 0.1 m (Karpov et al. 2006). ROV Beagle was also equipped with parallel lasers set with a 10 cm  spread and positioned to be visible in the field of view of the primary forward camera. These lasers provided a scalable reference of size when reviewing video.

An ORE Offshore Trackpoint III® ultra-short baseline acoustic positioning system with ORE Offshore Motion Reference Unit (MRU) pitch and roll sensor was used to reference the ROV position relative to the ship’s Wide Area Augmentation System Global Positioning System (WAAS GPS). The ship’s heading was determined using a KVH magnetic compass. The Trackpoint III® positioning system calculated the XY position of the ROV relative to the ship at approximately two-second intervals. The ship-relative position was corrected to real world position and recorded in meters as X and Y using the World Geodetic System (WGS)1984 Universal Transverse Mercator (UTM) coordinate system using HYPACK® 2013 hydrographic survey and navigation software. Measurements of ROV heading, depth, altitude, water temperature, camera tilt and ranging sonar distance were averaged over a one-second period and recorded along with the position data.

The ROV was equipped with four cameras, including one forward facing high definition (HD) camera, two standard definition cameras and one HD still camera. The primary

data collection camera (HD video camera) and HD still camera were oriented obliquely forward. All video and still images were linked using UTC timecode recorded as a video overlay or using the camera’s built-in time stamp which was set to UTC time each day.

 

All data collected by the ROV, along with subsequent observations extracted during post-processing of the video, was linked in a Microsoft Access® database using GPS time. GPS time was used to provide a basis for relating position, field data and video observations (Veisze and Karpov 2002). Data management software was used to expand all data records to one second of Greenwich Mean Time (GMT) time code. During video post-processing, a Horita® Time Code Wedge (model number TCW50) was used in conjunction with a customized computer keyboard to record the audio time code in a Microsoft Access® database.

 

ROV Sampling OperationsJune 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 48

R/V Shearwater, a 22 m NOAA research vessel, was used to complete the 2016 survey. At each site, the ROV was piloted along 15-minute transect lines (determined during dive) and was flown off the vessel’s stern using a “live boat” technique that employed a 317.5 kg (700 lb) clump weight. Using this method, all but 50 m of the ROV umbilical was isolated from current-induced drag by coupling it with the clump weight cable and suspending the clump weight at least 10 m off the seafloor. The 45 m tether allowed the ROV pilot sufficient

maneuverability to maintain a constant speed (0.5 to 0.75 m/sec) and a straight course down the planned survey line, while on transect.

 

The ship remained within 35 m of the ROV position at all times. To achieve this, an acoustic tracking system was used to calculate the position of the ROV relative to the ship. ROV position was calculated every two seconds and recorded along with UTC timecode using navigational software. Additionally, the ROV pilot and ship captain utilized real-time video displays of the location of the ship and the ROV, in relation to the planned transect line. A consistent transect width, from the forward camera’s field of view, was achieved using sonar readings to sustain a consistent distance from the camera to the substrate (at the screen horizontal mid-point) between 1.5 and 3 m. In areas with low visibility, BlueView multibeam sonar was used to navigate hazardous terrain.

 

POST-PROCESSING

Following data collection, the ROV position data was processed to remove outliers and data anomalies caused by acoustic noise and vessel movement, which are inherent in these systems (Karpov et al. 2006). In addition, deviations from sampling protocols

such as pulls (ROV pulled by the ship), stops (ROV stops to let the ship catch up), or loss of target altitude caused by traveling over backsides of high relief structures, were identified in the data and not used in calculations of density for fish and invertebrate species.

 

Substrate and Habitat

For each study area, all video collected was reviewed for up to six different substrate types: rock, boulder, cobble, gravel, sand and mud (Green et al. 1999). Each substrate was recorded as discrete segments by entering the beginning and ending UTC timecode. Substrate annotation was completed in a multi-viewing approach, in which each substrate type was recorded independently, enabling us to capture the often overlapping segments of substrates (Figure 1). These overlapping substrate segments allowed identification of mixed substrate areas along the transect line.

 

After the video review process, the substrate data was combined to create three independent habitat types: hard, soft, and mixed habitats (Figure 1). Rock and boulder were categorized as hard substrate types, while cobble, gravel, sand, and mud were all considered to be unconsolidated substrates and categorized as soft. Hard habitat was defined as any combination of the hard substrates, soft habitat as any combination of soft substrates, and mixed habitat as any combination of hard and soft substrates.

 

Finfish and Invertebrate EnumerationJune 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 49

After completion of habitat and substrate review, video was processed to collect data for use in estimating finfish and macro-invertebrate distribution, relative abundance and density. During the review process, both  the forward and down video files were simultaneously reviewed, yielding a continuous and slightly overlapping view of what was present in front of and below the ROV. This approach effectively increased the resolution of the visual survey, by identifying animals that were difficult to recognize in the forward camera, but were clearly visible and identifiable in the down camera.

 

During multiple subsequent viewings, finfish and macro-invertebrates were classified to the lowest taxonomic level possible. Observations that could not be classified  to species level were identified to a taxonomic complex, or recorded as unidentified (UI). During video review, both the HD video and HD still imagery were used to aid in species identification. Each fish or invertebrate observation was entered into a Microsoft Access® database along with UTC timecode, taxonomic name/grouping, sex/developmental stage (when applicable), and count. Fish, were sized using the two sets of parallel lasers to estimate total length. Not all fish were sizeable due to their position within the field of view of the ROV.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 50

Figure 1. (a) Basic ROV strip transect methodology used to collect video data along the sea floor, (b) overlapping base substrate layers produced during video processing and (c) habitat types (hard, mixed soft) derived from the overlapping base substrate layers after video processing is completed.

All clearly visible finfish and macro-invertebrates were enumerated from the video record. Invertebrate species that typically form large colonial mats or cover large areas and could not be counted individually were instead recorded as invertebrate layers (with discrete start and stop points and percent cover estimates for each segment). Invertebrate patch segments were coded for percent cover using four groupings: 1) less than 25% cover, 2) 25% to 50% cover, 3) 50% to 75% cover and 4) greater than 75% cover. Only data on individual invertebrate observations are presented in this report. Invertebrate patch data are provided as part of the final data submission for use in future analysis.

RESULTS

Due to technical difficulties with the ROV’s USBL tracking system, several ROV dives surveyed during the 2016 expedition do not have positional data. These dives include, dive #8 at East Butterfly Bank and dive #11 at South Santa Rosa Island. Because there was no base data to correlate video observations, dive #8 at East Butterfly Bank was not video post-processed. However, video collect on dive #11 at South Santa Rosa Island had already been processed when it was discovered that the positional files were corrupted. Therefore, fish and invertebrate observational data at South Santa Rosa Island will be included in the data package, but those observations are not presented in the results section of this report.

In addition, dive #6 at West Butterfly Bank was aborted before completing the transect; and no transects were defined during dive #10 at Footprint Ridge.

SURVEY TOTALS

Total number of fish and macro-invertebrates observed and sampling effort and are given in Table 1. Over 18,000 fish and macro-invertebrates were observed at depths ranging from 126 m to 379 m, and a total of 10.8 kilometers of seafloor was surveyed during the completion of 23 transects at all five study areas combined (Figure 2).

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 51

Table 1. Total sampling effort at five Southern California study areas, showing total distance, area, fish and macro-invertebrate counts and depth range.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 52

Figure 2. ROV dive locations for the five study areas video post-processed.

SUBSTARTATE AND HABITAT

Substrate

Substrate types observed on transects are not mutually exclusive and represent the proportion of the total surveyed transect distance that has a given substrate present (see methods for full description). Overall, mud, cobble and rock substrates were the most common (Table 2). Sand was only observed at Southeast Santa Rosa Island (the shallowest area surveyed).

Habitat

Habitat types derived from substrate data show that across all sites, soft and mixed habitats were the most common, combined accounting for between 81% – 100% of the habitat observed across all sites (Table 2). Hard habitats were the least common accounting for only 0% to 19 % of the available habitat across all sites.

Table 2. Percent substate and habitat types encountered at the five study areas.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 53

FISH AND INVERTEBRATE TOTAL COUNTS
Fish
Rockfish were the most commonly observed fish accounting for 92.7% of the total fish count at all study areas combined (Table 3). Halfbanded rockfish were the most abundant rockfish species, accounting for nearly 40% of all of the fish observations. The next most abundant species were the following rockfish: YOY, Swordspine rockfish, Sebastomus rockfish, UI rockfish and Pygmy rockfish which combined accounted for another 44% of all fish observations. Cowcod, a currently listed overfished species, was observed, representing 0.3% of the total count. The most abundant non-rockfish grouping was the combfish complex, accounting for 2.4% of the fish observations.

Invertebrates
Four species/groupings of macro-invertebrates accounted for approximately 65% of the total invertebrate counts (Table 4). The most abundant species observed was the fragile pink urchin, which accounted for approximately 26% of the overall count; followed by the squat lobster, UI lobed sponge and white slipper sea cucumber which accounted for the remaining 39%.

Over 3,400 structure forming sponges from 11 species/groupings were observed, accounting for 26% of the total invertebrate observations. Corals were commonly observed and represented 9% of the observations (11 species/groupings). Gorgonians were the most commonly observed coral type, with 3 species/groupings representing the majority of the observations: gray, red swiftia and yellow gorgonians. Fifteen species/groupings of sea stars were also observed, but represented less than 5% of the total macro-invertebrate observations.

Table 3. Overall fish counts are presented in order from highest to lowest abundance.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 54

Table 4. Overall macro-invertebrate counts are presented in order from highest to lowest abundance.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 55

Table 4. Continued.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 56

FISH AND INVERTEBRATE DENSITY

 

FishJune 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 57

At Southeast Santa Rosa Island, fish densities were higher than any other study area, with 53 fish/100 m2 (Table 5). Halfbanded rockfish represented the majority of the density, accounting for over 45 fish/100 m2. When Halfbanded rockfish are not included in the overall densities of each study area, West Santa Barbara Island has the highest overall density at almost 12 fish/100 m2. At West Butterfly Bank, the lowest overall fish density was observed with just over 2 fish per 100 m2.

 Halfbanded rockfish

After Halfbanded rockfish, the next most abundant species/groupings were YOY and swordspine rockfish at West Santa Barbara Island. Sebastomus rockfish, unidentified rockfish and small benthic fish were also common across all sites. Bank rockfish were observed at all sites except at Southeast Santa Rosa Island. Cowcod were only observed at South Santa Barbara Island.

The number of species observed at each study location varied greatly. June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 58Of the 46 species/groupings observed, 30 were observed at West Santa Barbara Island, the highest of all study areas. In contrast, the lowest number of fish species observed was at West Butterfly Bank, with only 11 species/groupings observed.

 

Invertebrates

Cowcod

 

The Footprint Deep Ridge study area had the highest overall macro-invertebrate density, with over 196 invertebrates/100 m2 (Table 6). At Footprint Deep Ridge, fragile pink urchin densities were the highest observed, with densities over 7 times higher than the next most abundant species/grouping, which was the squat lobster at West Butterfly Bank. West Santa Barbara Island had the most species/groupings of any study area surveyed with a total of 52 species/groupings (Table 6).

In contrast, Southeast Santa Rosa Island had the lowest number of invertebrate species/groupings observed and lowest total invertebrate density. At Southeast Santa Rosa Island, a total of 20 invertebrate species/groupings produced a total density of just over 8 invertebrates/100 m2. All other sites overall densities exceeded 33 invertebrates/100 m2.

Coral and sponge species were observed at all study areas, with some notable differences at each location. The gray gorgonian was only observed at West Santa

 

Barbara Island and Footprint Deep Ridge. Densities of the gray corals were almost 16 times June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 59higher at West Santa Barbara Island than at Footprint Deep Ridge. Black corals were found at both the Footprint Deep Ridge and Santa Barbara Island sites, though black corals were over four times denser at Footprint Deep Ridge.

 

Other corals observed included: an unidentified small orange gorgonian (UI orange gorgonian) at Footprint Deep Ridge and West Butterfly Bank, a yellow gorgonian observed at all locations except Footprint Deep Ridge, and the red swiftia gorgonian found at all study areas.

Gray gorgonian

 

 

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 60Structure forming sponges were observed at all study areas, with the highest density observed at West Butterfly Bank. At this site, three sponge types: the hairy boot sponge, UI laced sponge and UI lobed sponge accounted for over 38 sponges per 100m2. Trumpet sponges were unique to only West Butterfly Bank, while the UI large yellow sponge was only observed at West Santa Barbara Island.

UI hairy boot sponge

Sponge identification was based on morphology, which createdJune 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 61
a particular issue for one morphotype: the UI lobed sponge. UI lobed sponges were observed at all study areas, but the type of lobed sponge varied (see unidentified species list). Lobed sponges at West Butterfly Bank were almost entirely ‘Type 3’ lobed sponge, while at both Santa Barbara Island study areasthe lobed sponges were predominantly ‘Type 1’. At Southeast Santa Rosa Island, lobed sponges were entirely ‘Type 1’, while Footprint Deep Ridge was 50% ‘Type 1’ and 50% ‘Type 2’.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 62

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 63

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 64

MAPS OF TRANSECTS

 

Maps of ROV transects for all four study areas surveyed are shown in Figures 3 – 9. Each set of maps shows select invertebrates that were of species interest during the survey, and substrate types encountered along each transect.

 

Select invertebrates include: black corals, gorgonians (UI orange, red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

Southeast Santa Rosa Island

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 65

Figure 3. ROV transects at Southeast Santa Rosa Island showing select invertebrates (top) and substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange,  red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

Footprint Deep Ridge

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 66

Figure 4. ROV transects at Footprint Deep Ridge Island showing select invertebrates (top) and substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange,  red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

West Santa Barbara Island

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Figure 5. ROV transects at West Santa Barbara Island showing select invertebrates (top) and substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange, red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

 

West Santa Barbara Island

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Figure 6. ROV transects at West Santa Barbara Island showing select invertebrates (top) and substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange, red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

 

West Santa Barbara Island

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Figure 7. ROV transects at West Santa Barbara Island showing select invertebrates (top) and substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange, red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

 

South Santa Barbara Island

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Figure 8. ROV transects at South Santa Barbara Island showing select invertebrates (top) and  substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange,  red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

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Figure 9. ROV transects at West Butterfly Bank showing select invertebrates (top) and substrates encountered (bottom). Invertebrate grouping include: black corals, gorgonians (UI orange, red, yellow, gray, red swiftia and unidentified gorgonians), other corals (bubblegum and mushroom corals), basket stars and sponges (laced, large yellow, boot, hairy boot, branched, lobed, vase and trumpet sponges).

UNIDENTIFIED SPECIES LIST

Anemones

The three Unidentified anemone species were observed:

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UI anemone 1                                    UI anemone 2                             UI anemone 4

Boot Sponges

Two boot sponges were observed, one ‘hairy’ type and the more typically seen boot sponge:

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         UI hairy boot sponge                                                   UI boot sponge

 

UI Lobed Sponge

Three UI lobed sponges were observed. The visually estimated percent of UI lobed sponges for each type by location are given in Table 7.

Type 1: Forms a thicker, softer, more variable mat. It is variable color, and may have darker margins.

Type 2: Forms thin, rigid, sheet-like structures, and is off-white in color.

Type 3: Ossicles are large and clearly visible, and is bright white in color.

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Other Sponges Observed

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UI Bubblegum Coral

Of the 24 UI bubblegum coral observed, only one large, highly branched individual was enumerated across all sites (upper right photo). All other bubblegum coral observed resembled the other three photos shown here.

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REFERENCES

Greene, H.G., M.M. Yoklavich, R.M. Starr, V.M. O’Connell, W.W. Wakefield, D.E. Sullivan, J.E. McRea Jr., and G.M. Cailliet. 1999. A classification scheme for deep seafloor habitats: Oceanologica Acta 22(6):663–678.

Karpov, K., A. Lauermann, M. Bergen, and M. Prall. 2006. Accuracy and Precision of Measurements of Transect Length and Width Made with a Remotely Operated Vehicle. Marine Technical Science Journal 40(3):79–85.

Veisze, P. and K. Karpov. 2002. Geopositioning a Remotely Operated Vehicle for Marine Species and Habitat Analysis. Pages 105–115 in Undersea with GIS. Dawn J. Wright, Editor. ESRI Press.

 

 

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June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 81
2021-03-10T21:21:07-08:00June 1st, 2017|research|

May 2017 – North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems

North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 82

Lead PI: Andrew R. Lauermann
Co-PI: Dirk Rosen
Contributors:
Kelsey Martin-Harbick and Heidi Lovig – Marine Applied Research
and Exploration
Donna Kline and Rick Starr – Moss Landing Marine Laboratories
Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 83

Final Report: Mid-depth and Deep Subtidal Ecosystems – 2017
Baseline Characterization and Monitoring of the MPAs along
the North Coast: ROV Surveys of the Subtidal (20-500 m)

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

Final Report: Mid-depth and Deep Subtidal Ecosystems – 2017

ACKNOWLEDGEMENTS

Generous Funding Support Provided by:

California Ocean Protection Council
California Ocean Science Trust
California Sea Grant (Project #R/MPA-41A; Grant Number 12-029)
Campbell Foundation
J.W. and H.M. Goodman Family Charitable Foundation
The Seed Fund

Key Office and Field Support:

Yuko Yokozawa – MARE GIS and Data Management Specialist
Steve Holtz – MARE ROV Operations Deck Officer
Johnathan Centoni – MARE Senior Video Analyst
Megan Nativo – MARE Data Management Specialist
Andrea Jolley – MARE Senior Video Analyst
Allison Lui – MARE Video Analyst
Portia Saucedo – MARE Video Analyst
Jessica Coming – MARE Office Technician
Daniel Troxel – MARE Video Analyst
Samuel Parker – MARE Video Analyst

Key Partnerships:

Mike Prall – California Department of Fish and Wildlife
Robert Pedro – Captain R/V Miss Linda
Garry Taylor – First Mate R/V Miss Linda
Jerry Evans – Deck crew R/V Miss Linda
Mark Burnap – Deck crew R/V Miss Linda

“LIST OF FIGURES”

“Figure 1. Study locations (blue boxes) from Soquel Canyon to Point Buchon and the sites (red boxes) surveyed within each…………………………………………………….33
“Figure 2. ROV survey lines within the Soquel Canyon (SQ3) and Portuguese Ledge (PRL1, PRL2, PRL3) site boundaries………………………………………………………..34
Figure 3. ROV survey lines within the Pacific Grove (PG1, PG2), Asilomar (AS1, AS2, AS4), Point Lobos (PL1, PL4, PL7, PL11) and Carmel Bay (CB1) site boundaries…….35
Figure 4. ROV survey lines within the Point Sur (PS2, PS3, PS5) and Big Creek (BC7) site boundaries…………………………………………………………………………………….36
Figure 5. ROV survey lines within the Big Creek (BC1, BC2, BC3, BC4, BC5, BC6) site boundaries…………………………………………………………………………………………..37
Figure 6. ROV survey lines within the Piedras Blancas (PIE1, PIE2) site boundaries………………………………………………………………………………………………………………38
Figure 7. ROV survey lines within the Morro Bay (MB1, MB2, MB3, MB4), Church Rock (CR) and Point Buchon (PB2, PB5) site boundaries…………………………….39

TABLE OF CONTENTS
LIST OF FIGURES …………………………………………………………………………………………………….. 9
LIST OF TABLES……………………………………………………………………………………………………….14
EXECUTIVE SUMMARY …………………………………………………………………………………………….15
INTRODUCTION ……………………………………………………………………………………………………….20
Background ……………………………………………………………………………………………………………20
Study Region………………………………………………………………………………………………………….20
Goals and Objectives ………………………………………………………………………………………………21
METHODS………………………………………………………………………………………………………………..22
Study Design………………………………………………………………………………………………………….22
Study Locations …………………………………………………………………………………………………..22
Transect Selection ……………………………………………………………………………………………….22
Data Collection……………………………………………………………………………………………………….24
ROV Equipment…………………………………………………………………………………………………..24
ROV Applications…………………………………………………………………………………………………25
ROV Sampling Operations…………………………………………………………………………………….26
Post-Processing ……………………………………………………………………………………………………..26
Substrate and Habitat …………………………………………………………………………………………..27
Finfish and Invertebrate Enumeration ……………………………………………………………………..28
Analysis…………………………………………………………………………………………………………………29
Characterization of MPAs and Reference Areas ……………………………………………………….29
Analysis of Index Sites………………………………………………………………………………………….30
Fish Depth Distribution………………………………………………………………………………………….31
Regional Fish Size Distribution ………………………………………………………………………………32
Between Year Comparison ……………………………………………………………………………………33
RESULTS AND DISCUSSION……………………………………………………………………………………..35
Baseline Survey Totals…………………………………………………………………………………………….35
Fish Totals ………………………………………………………………………………………………………….37
Invertebrate Totals ……………………………………………………………………………………………….40
BASELINE CHARACTERIZATION OF STUDY AREAS……………………………………………………43
Point St. George Reef Offshore SMCA and Reference Area ………………………………………….43
Substrate ……………………………………………………………………………………………………………44
Habitat ……………………………………………………………………………………………………………….45
Fish……………………………………………………………………………………………………………………46
Invertebrates……………………………………………………………………………………………………….47
Reading Rock SMR and Reference Area ……………………………………………………………………48
Substrate ……………………………………………………………………………………………………………49
Habitat ……………………………………………………………………………………………………………….50
Fish……………………………………………………………………………………………………………………51
Invertebrates……………………………………………………………………………………………………….52
Mattole Canyon SMR and Reference Area………………………………………………………………….53
Substrate ……………………………………………………………………………………………………………54
Habitat ……………………………………………………………………………………………………………….55
Fish……………………………………………………………………………………………………………………56
Invertebrates……………………………………………………………………………………………………….57
Ten Mile State Marine Reserve and Reference Area…………………………………………………….58
Substrate ……………………………………………………………………………………………………………59
Habitat ……………………………………………………………………………………………………………….60
Fish……………………………………………………………………………………………………………………61
Invertebrates……………………………………………………………………………………………………….62
ANALYSIS OF INDEX SITES ………………………………………………………………………………………63
Fish Densities ……………………………………………………………………………………………………..63
Similarity Test ……………………………………………………………………………………………………..64
Point St. George Index Sites………………………………………………………………………………….65
Reading Rock Index Sites……………………………………………………………………………………..66
Mattole Canyon Index Sites …………………………………………………………………………………..66
Ten Mile Index Sites …………………………………………………………………………………………….66
FISH DEPTH DISTRIBUTION………………………………………………………………………………………68
Rocky Reef Transects ……………………………………………………………………………………………..69
Point St. George – Rocky Reef ……………………………………………………………………………….69
Reading Rock – Rocky Reef…………………………………………………………………………………..70
Mattole Canyon – Rocky Reef ………………………………………………………………………………..71
Ten Mile – Rocky Reef…………………………………………………………………………………………..72
Canyon Transects …………………………………………………………………………………………………..74
Mattole Canyon – Canyon ……………………………………………………………………………………..74
FISH SIZE DISTRIBUTION………………………………………………………………………………………….77
Laser-based Size Estimates…………………………………………………………………………………..77
Black Rockfish …………………………………………………………………………………………………….78
Blue Rockfish………………………………………………………………………………………………………79
Canary Rockfish…………………………………………………………………………………………………..80
Copper Rockfish ………………………………………………………………………………………………….81
Olive/Yellowtail Rockfish……………………………………………………………………………………….82
Quillback Rockfish ……………………………………………………………………………………………….83
Vermillion Rockfish ………………………………………………………………………………………………84
Yelloweye Rockfish………………………………………………………………………………………………85
Lingcod………………………………………………………………………………………………………………86
Kelp Greenling …………………………………………………………………………………………………….87
Analysis of Laser-based Sizing Technique……………………………………………………………….89
BETWEEN YEAR COMPARISON ………………………………………………………………………………..91
Rocky Reef Index Sites ……………………………………………………………………………………………91
Fish……………………………………………………………………………………………………………………91
Invertebrates……………………………………………………………………………………………………….91
Soft Bottom Transects ……………………………………………………………………………………………..93
MONITORING RECOMMENDATIONS………………………………………………………………………….94
FINANCIAL REPORT …………………………………………………………………………………………………97
LITERATURE CITED………………………………………………………………………………………………….98
APPENDIX 1. NCSR Fish Mean Densities (100 m2) by Transect Type for 2014 and 2015….100
APPENDIX 2. NCSR Invertebrate Mean Densities (100 m2) by Transect Type for 2014 and
2015……………………………………………………………………………………………………………………….102
APPENDIX 3. Full Baseline Characterizations by Study Location. ……………………………………104
Point St. George Reef Offshore SMCA and Reference Area ………………………………………..104
Survey Totals…………………………………………………………………………………………………….105
Substrate ………………………………………………………………………………………………………….105
Habitat ……………………………………………………………………………………………………………..106
Fish………………………………………………………………………………………………………………….108
Rocky Reef Fish…………………………………………………………………………………………………111
Soft Bottom Fish ………………………………………………………………………………………………..111
Invertebrates……………………………………………………………………………………………………..112
Rocky Reef Invertebrates…………………………………………………………………………………….115
Soft Bottom Invertebrates ……………………………………………………………………………………115
Reading Rock SMR and Reference Area ………………………………………………………………….116
Survey Totals…………………………………………………………………………………………………….117
Substrate ………………………………………………………………………………………………………….117
Habitat ……………………………………………………………………………………………………………..118
Fish………………………………………………………………………………………………………………….120
Rocky Reef Fish…………………………………………………………………………………………………123
Soft Bottom Fish ………………………………………………………………………………………………..123
Invertebrates……………………………………………………………………………………………………..124
Rocky Reef Invertebrates…………………………………………………………………………………….127
Soft Bottom Invertebrates ……………………………………………………………………………………127
Mattole Canyon SMR and Reference Area………………………………………………………………..129
Survey Totals…………………………………………………………………………………………………….130
Substrate ………………………………………………………………………………………………………….130
Habitat ……………………………………………………………………………………………………………..131
Fish………………………………………………………………………………………………………………….134
Rocky Reef Fish…………………………………………………………………………………………………137
Soft Bottom Fish ………………………………………………………………………………………………..137
Canyon Fish………………………………………………………………………………………………………137
Invertebrates……………………………………………………………………………………………………..139
Rocky Reef Invertebrates…………………………………………………………………………………….142
Soft Bottom Invertebrates ……………………………………………………………………………………142
Canyon Invertebrates………………………………………………………………………………………….143
Ten Mile State Marine Reserve and Reference Area…………………………………………………..144
Survey Totals…………………………………………………………………………………………………….145
Substrate ………………………………………………………………………………………………………….145
Habitat ……………………………………………………………………………………………………………..146
Fish………………………………………………………………………………………………………………….148
Rocky Reef Fish…………………………………………………………………………………………………151
Soft Bottom Fish ………………………………………………………………………………………………..151
Invertebrates……………………………………………………………………………………………………..152
Rocky Reef Invertebrates…………………………………………………………………………………….155
Soft Bottom Invertebrates ……………………………………………………………………………………155
APPENDIX 4. Rocky Reef Fish Communities and Analysis of Index Sites. ……………………….156
APPENDIX 5. Rock Reef Fish – Between Year Comparisons by Study Location………………..183
APPENDIX 6. Rocky Reef Invertebrates – Between Year Comparisons by Study Location….187
APPENDIX 7. Soft Bottom Fish – Between Year Comparisons by Study Location………………191
APPENDIX 8. Soft Bottom Invertebrates – Between Year Comparisons by Study Location….195

LIST OF FIGURES 

Figure E1. Mean densities per 100m2 of selected rocky reef rockfish, Kelp Greenling and Lingcod for regional averages for the NCSR (white) compared to Point St. George SMCA (blue), Reading Rock SMR (red), Mattole Canyon SMR (red) and Ten Mile SMR (red) and their respective reference areas (gray)……………………………………………..17 

Figure E2. Mean densities per 100m2 of selected rocky reef invertebrate species for regional averages for the NCSR (white) compared to Point St. George SMCA (blue), Reading Rock SMR (red), Mattole Canyon SMR (red) and Ten Mile SMR (red) and their respective reference areas (gray)……………………………………………………………18 

Figure 1. Example of transect allocation within soft bottom and rocky reef habitats (including index sites) inside and outside the Reading Rock SMR………………………23 

Figure 2. (a) Basic ROV strip transect methodology used to collect video data along the sea floor, (b) overlapping base substrate layers produced during video processing and (c) habitat types (hard, mixed soft) derived from the overlapping base substrate layers after video processing is completed. ………………………………………………..27 

Figure 3. ROV transect lines completed in 2014 and 2015 at (a) Point St. George Reef Offshore SMCA and reference area, (b) Reading Rock SMR and reference area (c) Mattole Canyon SMR and reference area and (d) Ten Mile SMR and reference area………………………………………………………………………………………………36 

Figure 4. Point St. George study area showing the rocky reef and surrounding soft bottom habitats in (a) the SMCA and (b) reference area………………………………….43 

Figure 5. Percent substrate (rock, boulder, cobble, gravel sand and mud) by transect type (rocky reef and soft bottom) for survey lines inside the (a) Point St. George SMCA and (b) reference area……………………………………………………………………………………….44 

Figure 6. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Point St. George Reef Offshore SMCA and (b) reference area for transect lines targeting: (I) the rocky reef and (II) the soft bottom habitats…….45 

Figure 7. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a) Point St. George SMCA and (b) reference area for 2014 and 2015. For a breakdown of the taxonomic composition of subgroups, see Appendix 4…………….46 

Figure 8. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside (a) Point St. George SMCA and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 4………………………………..47 

Figure 9. Reading Rock study location showing rocky reef and soft bottom habitats in (a) the reference area and (b) SMR. ………………………………………………………..48 

Figure 10. Percent substrate (rock, boulder, cobble, gravel sand and mud) by transect type (rocky reef and soft bottom) for survey lines inside the Reading Rock SMR and (b) reference area. ………………………………………………………………………………..49 

Figure 11. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Reading Rock SMR and (b) reference area, for transect lines targeting (I) rocky reef and (II) soft bottom habitats. ………………………………..50 

Figure 12. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a) Reading Rock SMR and (b) reference area in survey years 2014 and 2015 combined. For a breakdown of the taxonomic composition of subgroups, see Appendix 5. …………………………………………………………………………………….51 

Figure 13. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside (a) Reading Rock SMR and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 5……………….52 

Figure 14. Mattole Canyon study area showing the rocky reef and surrounding soft bottom habitats in (a) the SMR and (b) reference area……………………………………53 

Figure 15. Percent substrate (rock, boulder, cobble, gravel sand and mud) by transect type (rocky reef, soft bottom and canyon) for survey lines inside (a) Mattole Canyon SMR and (b) reference area………………………………………………………………….54 

Figure 16. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Mattole Canyon SMR (b) reference area for transect lines targeting: (I) the rocky reef, (II) soft bottom and (III) canyon habitats……………………55 

Figure 17. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a) Mattole Canyon SMR and (b) reference area for 2014 and 2015. For a breakdown of the taxonomic composition of subgroups, see Appendix 6……….56 

Figure 18. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside the (a) Mattole Canyon SMR and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 6……………….57 

Figure 19. Ten Mile study location showing rocky and soft bottom habitats in (a) the SMR and (b) reference area………………………………………………………………….58 

Figure 20. Percent substrate (rock, boulder, cobble, gravel sand and mud) by transect type (rocky reef and soft bottom) for survey lines inside the (a) Ten Mile SMR and (b) reference area………………………………………………………………………………………………59

Figure 21. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Ten Mile SMR and (b) reference area, for transect lines targeting (I) the rocky reef and (II) the soft bottom habitats………………………………60 

Figure 22. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a) Ten Mile SMR and (b) reference area for 2014 and 2015. For a breakdown of the taxonomic composition of subgroups, see Appendix 7……………….61 

Figure 23. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside the (a) Ten Mile SMR and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 7…………………………….62 

Figure 24. Density per 100 m2 of select rocky reef fishes at each MPA (SMR or SMCA) and reference area index site pair at Point St. George, Reading Rock, Mattole Canyon and Ten Mile……………………………………………………………………………………64 

Figure 25. Similarity (group average agglomerative clustering) among index site fish assemblages in MPA and reference area pairs, for Point St. George, Reading Rock, Mattole Canyon and Ten Mile. Analyses are based on densities for individual species and taxonomic groups (see methods for full list of taxonomic groups). Data were combined for observations over all substrates……………………………………………..65 

Figure 26. The total area of rocky reef transects surveyed per depth bin for each MPA: Point St. George SMCA (blue), and Reading Rock SMR, Mattole Canyon SMR and Ten Mile SMR (all SMRs in red) and their reference areas (gray)…………………………………..69 

Figure 27. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Point St. George SMCA and reference area………………………………………………………………………………………………70 

Figure 28. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Reading Rock SMR and reference area…………71 

Figure 29. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Mattole Canyon SMR and reference area………..72 

Figure 30. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Ten Mile SMR and reference area……………….73 

Figure 31. The total area surveyed per depth bin for canyon transects at Mattole Canyon SMR……………………………………………………………………………………74 

Figure 32. The density of each fish species per depth stratified bin, with bubble size as the relative density of fish in that depth bin. There was insufficient data (less than 200 m) for the 140-149 meter depth bin (indicated by the gray line). The shelf/canyon break occurred at about the 100 m mark (indicated by the red line)…………………………….76

Figure 33. Percent (%) size frequency of Black Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 41 cm (—) for females (Love et al 2002)……………………………………….78 

Figure 34. Percent (%) size frequency of Blue Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 29 cm (—) for females (CDFW 2016f)………………………………………….79 

Figure 35. Percent (%) size frequency of Canary Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 44.5 cm (—) for females (Stock assessment, Thorson and Wetzel 2016)…………………………………………………………………………………………….80 

Figure 36. The percent (%) frequency of size (cm) of Copper Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 31.4 cm (—) for females (Love et al 2002)………………………81 

Figure 37. Percent (%) size frequency of Olive/Yellowtail Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 33-35 cm (—) for female Olive Rockfish and 36-45 cm (—) for female Yellowtail Rockfish (Love et al 2002)………………………………………………………..82 

Figure 38. Percent (%) size frequency of Quillback Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 28 cm for females (—) (Love et al 2002)……………………………….83 

Figure 39. Percent (%) size frequency of Vermillion Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity (—) is 38.2 cm for females (Stock assessment, MacCall 2005)……….84 

Figure 40. Percent (%) size frequency of Yelloweye Rockfish at Point St. George (PSG), Reading Rock (RR) and Mattole Canyon (MC). Size at 50% sexual maturity is 39.6 cm (—) for females (Stock assessment, Stewart et al. 2009)……………………….85 

Figure 41. Percent (%) size frequency of Lingcod at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 57.1 cm (—) for females (Stock assessment, Hamel et al. 2009). The recreational minimum size is 55.88 cm (CDFW 2016e)……………………………………………………………86 

Figure 42. Percent (%) size frequency of Kelp Greenling at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 29.5 cm for females (—) (CDFW 2016f). The recreational minimum size is 30.48 cm (CDFW 2016f)………………………………………………………………………87

Figure 43. Comparisons of healthy (left photo) and wasting (right photo) sea stars including: (a) Stimpson’s sun star, (b) sunflower star and (c) the short spined sea star………………………………………………………………………………………………92 

Figure 44. Comparison of slipper sea cucumbers in (a) 2014 with their tentacles exposed, and (b) 2015 with their tentacles retracted………………………………………93 

LIST OF TABLES 

Table 1. Survey totals for ROV dives at Point St. George, Reading Rock, Mattole Canyon, Sea Lion Gulch and Ten Mile MPAs and paired reference areas for the 2014 and 2015 sampling years combined…………………………………………………………35 

Table 2. Total count, estimated size and depth of all fish observed from video collected in 2014 and 2015 within the NCSR………………………………………………………….38 

Table 3. Total count and depth range of all invertebrates observed from video collected in 2014 and 2015 within the NCSR………………………………………………………….41 

Table 4. Number of observations and mean density in all index sites per 100 m2 (+SE) for ten fish species selected for statistical comparisons among MPAs and their respective reference areas. Proportion of obs. is the proportion of non-YOY observations in the index sites only. Frequency of observation (FO) is the proportion of ROV transects in index sites in which the species occurred at least once………………63 

Table 5. The total area and depth range surveyed from rocky reef and canyon transects inside MPAs (SMCA or SMR) and their associated reference areas for Point St. George, Reading Rock, Mattole Canyon and Ten Mile………………………………………68 

Table 6. The mean total length of select fish species within each MPA (SMCA & SMR) and reference (Ref.) area for Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Dash marks indicate no individuals were counted at that study area. ‘N/A’ indicates too few fish were counted to report a mean……………77 

Table 7. Mean length comparison between laser-length-estimates and stereo-video measurements. P-value refers to the probability that the two methods were the same (Ho: μ1=μ2) using two-tailed paired-sample t-tests. Measurements are all in centimeters. Bolded numbers indicate significant differences at a probability of 0.05. Difference shows the difference between the means and the signs indicate direction of the laser-length-estimate difference relative to stereo-measurements…………………..89 

Table 8. Mean proportional difference in total length for laser-estimates from stereo- estimates by species for all analysts combined…………………………………………….90 

EXECUTIVE SUMMARY 

California’s network of Marine Protected Areas makes up 16% of the states coastal waters. May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 84This network was implemented in four uniquely distinct coastal regions. The final region to be implemented, the North Coast Study Region (NCSR), extends from the California-Oregon border to Alder Creek, Mendocino County. The NCSR has some of the least developed coastal areas in the state due to the remote, rugged coastline and frequently unfavorable ocean conditions, which limit access to much of the coastal and offshore waters. The NCSR lies within one of only four major temperate upwelling systems in the world, making it one of the most highly productive ecosystems that supports diverse and abundant assemblages of fish and invertebrate species. 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 85Marine Applied Research and Exploration (MARE) preformed quantitative baseline surveys within the NCSR in 2014 and 2015 with the overall goal to describe the condition of three distinctive priority ecosystem features within four MPAs and their adjacent reference study areas: a) mid-depth rock ecosystems, b) soft- bottom subtidal ecosystems, and c) deep ecosystems (including canyons). Long-term monitoring trends within these habitats will be compared to baseline conditions, assisting in evaluating MPA effectiveness. The four MPAs chosen for evaluation include: Point St. George Reef Offshore SMCA, Reading Rock State Marine Reserve, Mattole Canyon State Marine Reserve and Ten Mile State Marine Reserve. Outside reference areas with similar habitats and depths were also surveyed for comparison. 

During the first two years following implementation, benthic visual surveys May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 86were conducted using a remotely operated vehicle (ROV) to assess initial changes in fishes, macro-invertebrates and associated seafloor habitats. The ROV collected video and still imagery while moving along a fixed path (transect) along the sea floor. Video imagery collected was analyzed to characterize substrate, habitat types, habitat complexity (rugosity), and estimate finfish and macro-invertebrate distribution, relative abundance and density. In total, 60 ROV dives were completed surveying more than 106 km (19 ha) between 13 and 421 m deep. In addition, over 16,500 still photos were taken.

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 87Of the 101,666 fish observed over both years, over 85% were rockfish. Young of year rockfish (YOY) were the most numerous rockfish grouping observed; with over 61,000 recorded individuals, accounting for 60% of all of the fish observations. Larger rockfish represented only 14% of the rockfish identified, with four species/groupings accounting for 80% of the observations: Blue, Olive/Yellowtail, unidentified and Canary Rockfishes. Non-rockfish species represented 15% of the fish identifications, with two groupings accounting for 71% of the total observations: unidentified smelt and May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 88flatfish. Overall, fish species composition and density was similar between all MPA and reference area pairs within rocky reef and soft bottom habitats. One exception was documented at Point St. George Reef Offshore SMCA within rocky reef habitats, where rockfish densities were significantly lower in the reference area than the MPA (Figure E1). In addition, Point St. George Reef Offshore SMCA had the highest density of Yelloweye Rockfish, over two times more than any other study area (Figure E1). 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 89Of the 124,064 individual invertebrates enumerated, seven species/groupings represented the majority of the observations (approximately 89%) within the NCSR: white- plumed anemones, slipper and California sea cucumbers, short red gorgonians, California hydrocoral, sea stars, sea whips and sea pens. Overall, invertebrate species composition and density was similar between all MPA and reference pairs within rocky reef habitats (Figure E2). However, within soft-bottom habitats species composition and abundance varied greatly across study locations. 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 90

Figure E1. Mean densities per 100 m2 of selected rocky reef rockfish, Kelp Greenling and Lingcod for regional averages for the NCSR (white) compared to Point St. George Reef Offshore SMCA (blue), Reading Rock SMR (red), Mattole Canyon SMR (red) and Ten Mile SMR (red), and their respective reference areas (gray). Error bars represent ± 1 standard error. 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 91

Figure E2. Mean densities per 100 m2 of selected rocky reef invertebrate species for regional averages for the NCSR (white) compared to Point St. George Reef Offshore SMCA (blue), Reading Rock SMR (red), Mattole Canyon SMR (red) and Ten Mile SMR (red), and their respective reference areas (gray). Error bars represent ± 1 standard error. 

Initial changes between sampling years wereMay 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 92
compared for fish and invertebrate species
abundance and distribution. Overall, there were
few significant differences for either fish or
invertebrate species, with most having low initial
variability. One of the exceptions was a
considerable decline in sea star species across
all sites within the NCSR from 2014 to 2015.
During the 2014 survey, active signs of sea star
wasting disease were observed in several
species of sea stars. When we returned to the
same locations in 2015, these same species
were observed in very low numbers, or not at
all.

Based on survey results in the NCSR, candidate indicators were identified based on
their abundance, ease of identification and management concern for inclusion in a
video-based surveying program for future monitoring and management efforts in the
region. They are listed by ecosystem type below:

Mid-depth Rock Ecosystems 
Canary Rockfish
Copper Rockfish
Quillback Rockfish
Vermillion Rockfish
Yelloweye Rockfish
Lingcod Soft-bottom
Kelp Greenling
Soft-bottom Subtidal Ecosystems 
Flatfish Sea whip
Deep Canyon Ecosystems
Greenstriped Rockfish
Shortspine Thornyheads
Longspine Thornyheads
Sablefish
Flatfish

Mid-depth Rock Ecosystems
White-plumed anemones
CA sea cucumbers
Short red gorgonians
Sea stars (all species)
Basket stars
Subtidal Ecosystems
White sea pen
Orange sea pen
Sea whip
Red octopus
Dungeness crabs
Deep Canyon Ecosystems
White-plumed anemones
Short red gorgonians
Mushroom soft coral

While a set of indicator species was given, due to the limited knowledge we have about mid-depth and deep ecosystems it is highly recommended that long-term sampling continue to identify all fish and macro-invertebrate species and physical habitat characteristics as completed during the baseline assessment. 

INTRODUCTION

Background

California’s diverse marine territory stretches 13,688 square kilometers, with over 70% of the state’s marine seafloor habitats exceeding depths of 30 m. Vast stretches of unconsolidated sediment give way to patches of rocky outcroppings, pinnacles and steep walled canyons. More than 550 marine fish species and thousands of marine invertebrate species are found in California’s territorial waters (Froese 2016). Many of these species are only found within deep subtidal ecosystems, extending well beyond the reach of conventional SCUBA surveys. 

These deep marine ecosystems are only effectively accessible via manned or unmanned submersibles. Although less is known about California’s deep ecosystems than kelp forest ecosystems, they have been long targeted by commercial and recreational fisheries. Due to historic commercial fishing effort, many species were overfished, including Cowcod (Sebastes levis), Canary Rockfish (Sebastes pinniger), and Yelloweye Rockfish (Sebastes ruberrimus). The impacts on these fisheries were further exacerbated by California’s growing recreational fleet (Schroeder and Love 2002). 

Federal regulations now prohibit bottom fishing within certain depths. In response to critically low population sizes of seven overfished rockfish species, the Pacific Fishery Management Council enacted area closures in September of 2002. These areas, called the Rockfish Conservation Areas (RCAs), prohibit the take of groundfish across vast stretches of the west coast continental shelf. Within Northern California, RCA closures limit bottom fishing to waters shallower than 20 fathoms (~37 m). While current regulations protect much of Northern California’s deepwater fish populations, they still remain poorly studied. 

Recognizing the lack of visual data available on deep subtidal habitats, Marine Applied Research and Exploration (MARE) was founded in 2003 to explore and document deepwater ecosystems to assist in their conservation and management. MARE works collaboratively with state and federal agencies, academic institutions, and other non- governmental organizations. To date, MARE has documented over 2,700 kilometers of seafloor off California’s coast alone—much of which had never been viewed before. 

Study Region

In December 2012, the fourth California Marine Protected Area (MPA) region was implemented along the North coast of California. The North Coast Study Region (NCSR) extends from the California-Oregon border to Alder Creek, Mendocino County, encompassing 2,660 square kilometers of coastal waters (CMLPAI 2010). The remote coastal areas of the NCSR are some of the least populated in the state, with vast stretches of coastal mountains having little to no development, reducing access to much of the regions shoreline. Three major river systems discharge into the northern half of the NCSR: the Smith, Klamath, and Eel rivers. The Eel River has an average annual sediment discharge greater than any other river of its size in the contiguous United States (Wolman et al. 1990), impacting nearshore marine ecosystems of the NCSR. 

Soft-bottom habitats are the most common within the study region, while hard-bottom and deep submarine canyon habitats add relief and structural complexity. Strong onshore winds drive nutrient rich upwelling that combines with the California Current Large Marine Ecosystem to support an abundance of marine life. These oceanographic conditions of the NCSR support highly productive and diverse marine ecosystems. 

The remote, rugged coastline and frequently unfavorable ocean conditions limit access to much of the region. Historical data for deep subtidal ecosystems within the NCSR are primarily limited to fisheries-dependent data from the commercial and recreational sectors. Very few fisheries-independent surveys have been conducted within the NCSR prior to MPA implementation. 

Goals and Objectives

This report presents findings from visual surveys conducted as part of a two-year baseline study of selected MPAs within the NCSR. The data collected during this study has been integrated into a statewide dataset to provide a benchmark for evaluating the effectiveness of MPAs. The overall goal of this project is to describe the condition of three priority ecosystems within MPAs and adjacent reference study areas: mid-depth rock ecosystems, soft-bottom subtidal ecosystems, and deep ecosystems (including canyons). The specific objectives of this project include: 

1) Produce a quantitative baseline characterization of selected MPAs across the 

NCSR. 

2) Assess initial changes in fishes, macro-invertebrates and associated seafloor 

habitats in select MPAs during the first two years following implementation. 

3) Identify candidate system indicators for the NCSR. 

4) Inform future monitoring and management efforts in the region. 

Study Design

Benthic visual surveys of North coast MPAs were conducted using a remotely operated May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 93vehicle (ROV) that is owned and operated by MARE. The ROV configuration and sampling protocols for this project were based on those developed by the project’s principal investigators in partnership with the California Department of Fish and Wildlife. The baseline assessment protocols have been used to survey MPAs of the northern Channel Islands as well as North central coast, Central coast, and South coast MPA study regions. To date, over 1,800 km of seafloor have been surveyed statewide using similar survey design and data collection protocols. 

Study Locations For this baseline assessment, four MPAs were selected to cover both the northern and southern bioregions of the NCSR: Point St. George Reef Offshore State Marine Conservation Area, Reading Rock State Marine Reserve, Mattole Canyon State Marine Reserve and Ten Mile State Marine Reserve. Outside reference areas with similar habitats and depths were also surveyed for comparison. 

Transect Selection Two different sampling techniques were used to capture video imagery, characterization transects and index site transects. At each location we collected video across two different habitat types (rocky reef and soft bottom) for use in developing a basic characterization of the benthic habitat structures and species assemblages present. We also captured additional video data within defined rocky habitat sites (index sites) to increase the statistical power specifically for monitoring changes in species density at those sites. 

At each location, long characterization transect lines (~1 km) were planned both inside and outside of the MPA, to transverse rocky reef and soft bottom habitats. Within the rocky reef, transects were distributed to cover both the interior reef, as well as the transitional habitats found on the edges of the rocky reef (Figure 1). Transects were chosen based on the distribution of habitat types within each MPA and reference area. When possible, transects were placed near each other to maximize ROV bottom time. This sampling approach provided information that was used in the descriptive characterization of each MPA and reference area.

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 94

Figure 1. Example of transect allocation within soft bottom and rocky reef habitats (including index sites) inside and outside the Reading Rock SMR. 

At each study location, a 500 m wide by 1,000 m long index site was placed over selected rocky habitat (Figure 1). Six 500 m long transects stretching across the width of the site were selected each sampling year using a systematic random approach, in which the start location of the shallowest line was selected randomly and the remaining transects were equally spaced thereafter. This survey design has been used to monitor changes in species density for use in evaluation of MPA effectiveness and fisheries management throughout California’s MPA network. To date, 178 index sites have been established and surveyed statewide, some having been resurveyed up to seven times. 

Data Collection 

ROV Equipment MARE’s observation class ROV, Beagle, was used to complete May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 95benthic surveys of select North coast MPAs. The ROV was equipped with a three-axis autopilot including a rate gyro-damped compass and altimeter. Together, these allowed the pilot to maintain a constant heading (± 1 degree) and constant altitude (± 0.3 m) with minimal corrections. In addition, a forward speed control was used to help the pilot maintain a consistent forward velocity between 0.25 and 0.5 m/sec. A pair of Tritech® 500 kHz ranging sonars, which measure distance across a range of 0.1–10 m using a 6° conical transducer, were used as the primary method for measuring transect width for both the forward and downward facing video. Each transducer was pointed at the center of the viewing area in each camera and was used to calculate the distance to middle of screen, which was subsequently converted to width using the known properties of each cameras field of view. Readings from these sonars were averaged five times per second and recorded at a one-second interval with all other sensor data. Measurements of transect width using a ranging sonar are accurate to ± 0.1 m (Karpov et al. 2006). 

An ORE Offshore Trackpoint III® ultra-short baseline acoustic positioning system with ORE Offshore Motion Reference Unit (MRU) pitch and roll sensor was used to reference the ROV position relative to the ship’s Wide Area Augmentation System Global Positioning System (WAAS GPS). The ship’s heading was determined using a KVH magnetic compass. The Trackpoint III® positioning system calculated the XY position of the ROV relative to the ship at approximately two-second intervals. The ship-relative position was corrected to real world position and recorded in meters as X and Y using the World Geodetic System (WGS)1984 Universal Transverse Mercator (UTM) coordinate system using HYPACK® 6.2 hydrographic survey and navigation software. Measurements of ROV heading, depth, altitude, water temperature, camera tilt and ranging sonar distance both forward and downward to the substrate, were averaged over a one-second period and recorded along with the position data.

The ROV was equipped with six cameras, including two standard definition primary cameras, two standard definition stereo sizing cameras, one high definition (HD) video camera and one HD still camera. The primary data collection cameras were oriented forward and down, with slightly overlapping fields of view. Both still and video HD cameras were oriented forward. Video for both cameras was captured on SONY® DSR 45 digital video tape recorders and Pioneer DVR510 digital video disc recorders. The two stereo sizing cameras were oriented forward facing with overlap for use in standardizing size measurements of fishes. All video and still images were linked using UTC timecode recorded as a video overlay or using the camera’s built-in time stamp which was set to UTC time each day. 

GPS time was used to provide a basis for relating position, sensor data and video observations (Veisze and Karpov 2002). A Horita® GPS3 and WG-50 were used to generate on screen displays of GPS time, as well as output Society of Motion Picture and Television Engineers (SMPTE) linear time-code (LTC) for capture on SONY® DSR audio tracks at an interval of 1/30th of a second. This method was improved by customizing HYPACK® navigational software to link all data collected in the field to the GPS time. ROV tracked position and sensor data were recorded directly by HYPACK® as a time-linked text file. A redundant one-second time code file of sensor data was also collected in the field using a custom built on-screen display and operating system software with time code extracted from the system’s internal clock which was synced to GPS time. 

All data collected by the ROV, along with subsequent observations extracted during post-processing of the video, was linked in a Microsoft Access® database using GPS time. Data management software was used to expand all data records to one second of Greenwich Mean Time (GMT) time code. During video post-processing, a Horita® Time Code Wedge (model number TCW50) was used in conjunction with a customized computer keyboard to record the audio time code in a Microsoft Access® database. 

ROV Beagle was also equipped with two sets of parallel lasers, three sonar units, and a Sea-Bird CTD with dissolved oxygen sensor. The parallel lasers were set with a 10 cm spread and positioned to be visible in the field of view of the primary forward and down facing cameras. These lasers provided a scalable reference of size when reviewing the video. The two ranging sonars also aligned with the forward and down facing cameras, allowed the ROV pilot to maintain a constant height off the bottom; they were also used to calculate the area covered (Karpov et al. 2006). 

ROV Applications ROVs are a non-obtrusive monitoring tool that can be used to collect detailed information on the entire benthic ecosystem, rather than just select metrics or indicators. ROVs can be equipped with not only cameras, but also monitoring probes such as oxygen and salinity sensors. This enables them to collect additional information from the surrounding environment beyond video. Additionally, ROVs can be equipped with manipulating arms that can be used to collect samples from the environment. These features make ROVs an all-around good choice for monitoring benthic ecosystems.

ROVs however are not currently very effective at collecting video data on fishes that school off the bottom. Therefore, data collected using the ROVs may not provide an accurate measure of biomass on epibenthic schooling fish species like Blue, Black and Olive/Yellowtail Rockfishes that tend to school around tall rock outcroppings 

ROV Sampling Operations R/V Miss Linda, a 24 m research vessel owned and May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 96operated by Captain Robert Pedro, was used to complete both the 2014 and 2015 surveys. Surveys were conducted between the hours of 0800 and 1700 PST to avoid the low light conditions of dawn and dusk that might affect finfish abundance measurements and underwater visibility. At each site, the ROV was piloted along pre-planned transect lines and was flown off the vessel’s port side using a “live boat” technique that employed a 317.5 kg (700 lb) clump weight. Using this method, all but 45 m of the ROV umbilical was isolated from current-induced drag by coupling it with the clump weight cable and suspending the clump weight at least 10 m off the seafloor. The 45 m tether allowed the ROV pilot sufficient maneuverability to maintain a constant speed (0.5 to 0.75 m/sec) and a straight course down the planned survey line. 

The ship remained within 35 m of the ROV position at all times. To achieve this, an acoustic tracking system was used to calculate the position of the ROV relative to the ship. ROV position was calculated every two seconds and recorded along with UTC timecode using navigational software. Additionally, the ROV pilot and ship captain utilized real-time video displays of the location of the ship and the ROV, in relation to the planned transect line. A consistent transect width, from the forward camera’s field of view, was achieved using the ranging sonars to maintain a constant distance and altitude from the substrate. The ranging sonars were fixed below and parallel to the camera between two forward-facing red lasers spaced 100 mm apart. The ROV pilot used the sonar readings to sustain a consistent transect width by maintaining the distance from the camera to the substrate (at the screen horizontal mid-point) between 1.5 and 3 m. In areas with low visibility, a BlueView multibeam sonar was used to navigate hazardous terrain. All sonar and CTD data were recorded at one second intervals along with UTC timecode. 

Post-Processing Following the survey, the ROV position data was processed to remove outliers and data anomalies caused by acoustic noise and vessel movement, which are inherent in these systems (Karpov et al. 2006). In addition, deviations from sampling protocols such as pulls (ROV pulled by the ship), stops (ROV stops to let the ship catch up), or loss of target altitude caused by traveling over backsides of high relief structures, were identified in the data and not used in calculations of density for fish and invertebrate species.

Substrate and Habitat For each study area, all video collected was reviewed for up to six different substrate types: rock, boulder, cobble, gravel, sand and mud (Green et al. 1999). Each substrate patch was recorded as discrete segments by entering the beginning and ending UTC timecode. Substrate annotation was completed in a multi-viewing approach, in which each substrate type was recorded independently, enabling us to capture the often overlapping segments of substrates (Figure 2). These overlapping substrate segments allowed identification of mixed substrate areas along the transect line. 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 97

Figure 2. (a) Basic ROV strip transect methodology used to collect video data along the sea floor, (b) overlapping base substrate layers produced during video processing and (c) habitat types (hard, mixed soft) derived from the overlapping base substrate layers after video processing is completed.

 After the video review process, the substrate data was combined to create three May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 98independent habitat types: hard, soft, and mixed habitats (Figure 2). Rock and boulder were categorized as hard substrate types, while cobble, gravel, sand, and mud were all considered to be unconsolidated substrates and categorized as soft. Hard habitat was defined as any combination of the hard substrates, soft habitat as any combination of soft substrates, and mixed habitat as any combination of hard and soft substrates. 

The video record was then reviewed two more times to identify the primary and secondary substrates along the survey line, and to capture the habitat complexity (rugosity). The video was also reviewed to classify the complexity of the habitat as it relates to fish and their ability to find refuge. Four levels of rugosity were used, and include: no rugosity (no refuge), low rugosity (refuge for 5-15 cm fish), medium rugosity (refuge for 15-25 cm fish), and high rugosity (refuge for >25 cm fish). Only base substrate, habitat, and rugosity data are presented in this report. Primary/secondary substrate data are provided as part of the final data submission for use in future analysis. 

Finfish and Invertebrate Enumeration After completion of habitat and substrate review, video was processed to collect data for use in estimating finfish and macro-invertebrate distribution, relative abundance and density. During the review process, both the forward and down video files were simultaneously reviewed, yielding a continuous and slightly overlapping view of what was present in front of and below the ROV. This approach effectively increased the resolution of the visual survey, by identifying animals that were difficult to recognize in the forward camera, but were clearly visible and identifiable in the down camera. 

During multiple subsequent viewings, finfish and macro-invertebrates were classified to the lowest taxonomic level possible. Observations that could not be classified to species level were identified to a taxonomic complex, or recorded as unidentified (UI). During video review, both the HD video and HD still imagery were used to aid in species identification. Each fish or invertebrate observation was entered into a Microsoft Access database along with UTC timecode, taxonomic name/grouping, sex/developmental stage (when applicable), and count. Fish, were sized using the two sets of parallel lasers to estimate total length. Not all fish were sizeable due to their position within the field of view of the ROV. 

All clearly visible finfish and macro-invertebrates were enumerated from the video record. Invertebrate species that typically form large colonial mats or cover large areas and could not be counted individually were instead recorded as invertebrate layers (with discrete start and stop points and percent cover estimates for each segment).

Invertebrate patch segments were coded for percent cover using four groupings: 1) less than 25% cover, 2) 25% to 50% cover, 3) 50% to 75% cover and 4) greater than 75% cover. Only data on individual invertebrate observations are presented in this report. Invertebrate patch data are provided as part of the final data submission for use in future analysis. 

Analysis 

Characterization of MPAs and Reference Areas For each MPA and paired reference area, baseline data collected over the 2014 and 2015 sampling years were combined to describe the physical and biological characteristics of three ecosystem features: mid-depth rock and soft bottom habitats, and deep canyon habitats. Data were summarized to highlight the profundity of information generated from this baseline project. Characterizations are restricted to describing species composition and abundance within each study area, as well as the similarities and differences between MPA pairs, and not to compare regional MPAs to each other. Abbreviated descriptions highlighting key findings at each study location are given in the main body of this report. Detailed characterizations are also provided in Appendix 3, which include fish and invertebrate species counts and mean densities for each MPA and reference area. 

Derived habitats are summarized by transect type (rocky reef, soft bottom and canyon) and presented as a percentage of the total transect distance for all transects combined. Fish and invertebrate mean densities for each habitat type (presented in Appendix 1 for fish and Appendix 2 for invertebrates) were calculated for each transect as: total individuals / total area of transect and expressed as individuals/100 m2

For each study area, fish and invertebrate densities were summarized into subgroupings. Each fish and invertebrate subgroup was selected for the purposes of displaying all fish and invertebrate density data and were not based on management importance. All fish observed were summarized into one of seven subgroups that include rockfish (schooling and non-schooling larger species), small schooling rockfish (dwarf type species), young of year rockfish (YOY), Lingcod (Ophiodon elongatus), Kelp Greenling (Hexagrammos decagrammus), flatfish (Pleuronectidae) and ‘all other fish’. 

Invertebrates were grouped into seven mobile and seven sessile macro-invertebrate subgroupings. Mobile subgroups include California sea cucumbers (Parastichopus californicus), octopuses, sea stars, urchins, Dungeness crabs (Cancer magister), basket stars (Gorgonocephalus eucnemis), and ‘other mobile invertebrates’. Sessile subgroups include white-plumed anemones (Metridum farcimen), branched sea cucumbers, whips and pens, gorgonians, sponges, and ‘other sessile invertebrates’. For breakdown of taxonomic composition of subgroups see Table 2 for fish and Table 3 for invertebrates.

Analysis of Index Sites To assess the relationship between occupancy and abundance of fishes across the NCMPA region, and within each of the selected MPAs and their outside reference areas, analyses were conducted on the combined 2014-2015 dataset at three different levels of ecological organization: 1) all fishes combined to represent the entire assemblage (multivariate analyses), 2) fishes separated into taxonomic or functional groups (multivariate analyses) and 3) individual species analyses for the 10 most abundant, reliably identifiable fish species. Additionally these groups were evaluated at three levels: regional (MPA location), treatment (inside/outside of MPA pairs), and habitat (rock, soft and canyon). The canyon habitat was considered unique, and was evaluated separately as the depth range and topography were significantly different from rock and soft shelf habitats. 

Multivariate analyses – The initial objective was to characterize the overall similarity of MPA locations and their paired reference site in the NCSR. Average agglomerative clustering of taxa densities at the transect level was used to determine how overall assemblage structure varied by MPA (regional), treatments (inside and outside reference) and habitats (rock, soft and canyon); and to evaluate the similarity of assemblages among MPA locations. We did this by grouping all ROV transect data in two ways. Mean densities for each group or species observed were calculated for soft, rock and canyon habitat transects, inside and outside each MPA. Densities were calculated by dividing the number of individuals observed by the area covered for each transect, creating a density matrix. Square root transformed densities were used to calculate a Bray-Curtis Similarity (Krebs 1999) matrix, used for average agglomerative clustering. 

A number of individual taxa had very low numbers of observations, or were difficult to identify to species level. Therefore, we completed the same analysis for taxa densities after grouping all species into higher level taxa such as genus, family, or functional group, including: Chondrichthyans (sharks, rays and ratfish), flatfishes, young of the year rockfish (YOY), Sebastomus Rockfish, small schooling rockfish (Pygmy, Halfbanded, Squarespot, Shortbelly, and unidentified small schooling), demersal non- aggregating rockfishes (Aurora, Brown, China, Copper, Darkblotched, Gopher, Greenspotted, Greenstriped, Quillback, Redbanded, Sharpchin, Stripetail, Tiger, and Yelloweye), epibenthic aggregating rockfishes (Black, Blue, Bocaccio, Canary, Chilipepper, Olive/Yellowtail, Vermilion and Widow), seaperches, combfishes, small benthic fishes (eelpouts, gobies, sculpins, and poachers), other benthic fishes (Sablefish, hagfishes, thornyheads and sand lance), and other fishes (Pacific Tomcod, Pacific Hake, salmonids, smelts, sunfish, and cods). 

Similar analyses were completed using only index site species occurrence data. Mean densities and frequency of occurrence were calculated for each species or taxon within each of the index sites. Similarity analyses and statistical comparisons were restricted to species or species groups that occurred on ROV transects within the index sites, and those species considered resident or semi-resident. Migratory or highly mobile species such as Ocean Sunfish, Sixgill Shark, Sablefish, smelts, Shortbelly Rockfish, and other schooling pelagics were removed. Individual species or taxa were grouped as previously described either taxonomically or functionally when observations were low. Similarly, small schooling rockfishes, other than Shortbelly Rockfish, were grouped for analyses as they have similar appearance and they occupy similar habitat in loosely aggregated schools. Kelp Greenling and Lingcod were analyzed as individual taxa due to occupying different ecological niches. At the depths in which the index sites were located (20-70 m), two Sebastomus species were expected to be observed – Starry and Rosy Rockfishes. These two species were combined with the Sebastomus Rockfish complex (hereafter referred to as Sebastomus Rockfish) to reduce ambiguity in calculations. Unidentified taxa were either eliminated or incorporated into appropriate higher level taxonomic groups. Analyses were conducted for transect-level densities, as well as individually for each substrate type. 

Individual species analyses – General linear modeling (GLM) was used with analysis of variance (ANOVA) and post-hoc multiple comparisons to investigate the relationships among square root transformed densities of individual fish species by treatment, MPA and between the two sample years. Species were selected based on abundance and frequency of observation in index sites and restricted to resident or semi-resident species. 

ODDS Analyses – We used odds-ratio analysis to determine if individual species were using hard substrates similarly among the four MPAs in the paired Index sites. This analysis is used to measure the odds of an outcome (yes or no) given a two-way treatment. We used number of observations over hard substrate (number of yes’s) or not (number of no’s) in Index sites as the outcomes in each treatment – inside and outside the MPAs. The resulting number is calculated: Odds ratio = A*D/B*C. A result near 1 would indicate that a species is observed over substrates similarly both inside and outside the MPA. Greater than 1 would indicate that the species is more likely to use hard substrates inside than outside and less than one more likely to use hard substrates in the outside treatment. The results of this analysis are not included in the main body of this report. 

A full report on analyses conducted in the evaluation of index sites can be found in Appendix 4. 

Fish Depth Distribution The depth distribution of selected fish species across all rocky reef transects (characterization and index site transects combined) was assessed for all MPA and reference areas in the NCSR. Depth distribution of select fish species across the Mattole Canyon SMR was assessed using only those transects that targeted the canyon. 

Fishes that were relatively high in abundance, and were of management concern, were selected for enumeration. Fish assessed from rocky reef transects include: Black Rockfish, Canary Rockfish, Copper Rockfish, Quillback Rockfish, Sebastomus Rockfish, Vermilion Rockfish, Yelloweye Rockfish, Lingcod, and Kelp Greenling. Fish assessed in canyon transects include all of the aforementioned species, as well as the following abundant, relatively deep water species: Greenstriped Rockfish, thornyhead complex (which includes Shortspine Thornyheads, and Longspine Thornyheads), and flatfish (including, Rock Sole, Slender Sole, Curlfin Turbot, Spotted Turbot, Pacific Halibut, Dover Sole, unidentified sanddabs, English Sole, Petrale Sole, and Rex Sole, as well as unidentified flatfish). Additionally, five flatfish species/groupings that had a higher identification rate were shown and include: Dover Sole, unidentified sanddabs, English Sole, Petrale Sole, and Rex Sole. 

To account for differences in density of fish along a depth gradient, transects in rocky reefs were stratified into 10 m depth bins. Transects targeting canyons were stratified into either 10 or 50 m bins. For the shallower portion of the canyon (50 to 149 m), depth was broken into 10 m bins; for the deeper portions of the canyon (150 to 450 m), 50 m depth bins were used. The total usable transect area was summarized within each depth bin (see ROV Positional Data methods section). Only those depth bins in which at least 200 m2 was surveyed were used for density calculations. Density was calculated as: total fish observed/total area surveyed and was expressed as fish/100 m2, for each depth bin. 

Regional Fish Size Distribution Fish size (total length) was approximated using two parallel lasers mounted to the ROV’s forward and down facing cameras. The lasers were placed 10 cm apart in the center of the video-viewing screen providing a scalable reference size. Estimates of fish total length were made using the lasers as a guide (laser-based size estimate) when the lasers made contact with the fish or when the lasers were visible on adjacent substrate or other fish. Length measurements were made to the nearest 1 cm and applied to all fish deemed sizeable by the trained video analysts. 

Ten species were selected for analysis: Black Rockfish, Blue Rockfish, Canary Rockfish, Copper Rockfish, Olive/Yellowtail Rockfish, Quillback Rockfish, Vermilion Rockfish, Yelloweye Rockfish, Lingcod, and Kelp Greenling (see table 2 for species names). Mean laser-based size estimates for these species were calculated for each MPA and reference area. Because there was little difference overall in mean total length between MPA and reference areas for the ten fish species presented, length data for MPA and reference area pairs were combined to show the size frequency for each of the four study locations in the NCSR. Percent size frequency is presented in 5 cm bins, and size at which 50% of the females of the population reach sexual maturity, is referenced for each species/grouping presented (Love et al. 2002; Thorson and Wetzel 2016; MacCall 2005; Stewart 2009; CDFW 2016f). 

To test the accuracy of the laser-based sizing technique used in this report, stereo video that was collected concurrently with the primary forward facing video was compared by independent analysts. Fish size (total length) was measured using commercially available SeaGIS EventMeasure® software (www.seagis.com.au/event). Eleven fish species were selected for comparison and include: Lingcod, Kelp Greenling, and the following rockfishes: Black, Blue, Canary, Copper, Olive/Yellowtail, Quillback, Rosy, Vermillion, and Yelloweye Rockfish.

Video collected using the ROV Beagle’s stereo-video cameras was provided to Moss Landing Marine Lab (MLML) analysts for processing. Fish that were previously given a laser-based size estimate were located in the stereo-video files using the same timecode that was recorded in the primary forward-facing camera. Using EventMeasure® software, fish that appeared to be the same individual as previously sized using the laser-based method were measured. Only fish that met the software requirement of head and tail being visible in both cameras simultaneously were sized. To assess potential differences between the two techniques: 

1) Mean total lengths of fish species measured using both methods were compared 

using two-tailed paired-sample t-tests. 

2) Laser-estimated total lengths were subtracted from stereo-estimates of fish species measured using both methods. Then we looked at the mean proportional differences, using the equation: 

Proportional difference = (difference / stereo measurement) * 100 

Between Year Comparison The differences between 2014 and 2015 baseline survey years were compared for select MPAs and their respective reference areas. Two types of transects were analyzed for the between year comparisons: transects surveyed in the rocky reef index sites and transects surveyed in soft bottom habitats. Fish and macro-invertebrate species abundance were analyzed for between year differences at each survey location. As there were no substantial differences in habitat composition between 2014 and 2015 for any of the survey locations, habitat will not be compared between years. 

To show the percentage difference between the two sampling years for both rocky reef index and soft bottom transects, Initial Variability was calculated with the equation: 

Absolute value of ((mean density 2015 – mean density 2014) / mean density 2014) 

For rocky reef index sites only, we tested for differences in density between years inside the MPAs and their reference sites using t-tests for select fish and invertebrate species (soft bottom sample sizes were insufficient). Tables with initial variability and t-test results are in Appendices 5-8. 

Fish species/groupings were chosen for between year comparison totaling the counts of all fish species for all sites and looking at species that were relatively high in abundance and of management concern. Fish species chosen for between year comparisons in rocky reef index sites include the following rockfish species: Black, Blue, Brown, Canary, Copper, Olive/Yellowtail, Quillback, Sebastomus, Shortbelly, small schooling, Vermilion, Yelloweye, unidentified (UI), young of year (YOY); and the following non- rockfish species: Kelp Greenling, Lingcod, and flatfish. Fish species chosen for between year comparisons in soft bottom transects include: combfish complex, Dover Sole, English Sole, Lingcod, Pacific Hake, Petrale Sole, Rex Sole, UI cod, UI eel pout,

UI flatfish, UI sanddab, UI small benthic fish and UI smelt (see table 2 for scientific names). 

Select macro-invertebrate species that were relatively high in abundance were also chosen for comparison. Macro-invertebrate species selected for between year comparisons in rocky reef index sites include the following: basket star, California hydrocoral, California sea cucumber, cushion star, fish eating star, Henricia complex, leather star, rainbow star, red sea star, red sea urchin, short red gorgonian, short spined sea star, slipper sea cucumber, spiny/thorny star complex, Stimson’s sun star, sunflower star, white branched cucumber, and white-plumed anemone. Macro- invertebrate species chosen for between year comparisons in soft bottom transects include: Dungeness crab, orange sea pen, Pleurobranchaea californica, red octopus, sand star, sand-rose anemone, sea whip, white sea pen and white-plumed anemone (see table 3 for scientific names). 

RESULTS AND DISCUSSION 

Baseline Survey Totals The baseline assessment of deep subtidal ecosystems within the North Coast Study Region was conducted between September 12 and October 9 2014, and October 6 to October 18 2015. Surveys were completed over a total of 24 operational days at sea (excluding weather and travel days) and covered nine different study areas: Point St. George SMCA and reference area, Reading Rock SMR and reference area, Mattole Canyon SMR and reference area, Sea Lion Gulch SMR, and Ten Mile SMR and reference area (Figure 3). In 2014, 31 ROV dives were completed, surveying over 59 km of benthic habitats between 13 and 421 meters in depth. In 2015 we returned to the same sites and completed 29 dives, surveying 47 km of transects between 24 and 364 meters in depth. 

Poor weather conditions and reduced visibility did not allow subsequent surveys of the 2015 planned transects within the Point St. George SMCA reference area. Therefore, two dives inside the Sea Lion Gulch SMR were re-surveyed within a site previously surveyed in 2014 as part of a CDFW statewide survey contract. Sea Lion Gulch SMR results are presented in this section only. 

In total, 60 ROV dives were completed covering more than 106 km (19 ha) of sea floor (Table 1). Over 101,000 fish and 124,000 invertebrates were enumerated from the videos. In addition, over 16,500 HD still photos were taken during 2014-2015 survey. 

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Table 1. Survey totals for ROV dives at Point St. George, Reading Rock, Mattole Canyon, Sea Lion Gulch and Ten Mile MPAs and paired reference areas for the 2014 and 2015 sampling years combined. 

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Figure 3. ROV transect lines completed in 2014 and 2015 at (a) Point St. George Reef Offshore SMCA and reference area, (b) Reading Rock SMR and reference area, (c) Mattole Canyon SMR and reference area and (d) Ten Mile SMR and reference area. 

Fish Totals For a full list of scientific names, see Table 2; fish will be referred to by common name throughout this report. For all sites and survey years combined, a total of 66 individual fish species and another 26 groupings were identified (Table 2). Of the 101,666 fish observed over both years, over 85% were rockfish. Young of year rockfish (YOY) were the most numerous fish observed; with over 61,000 recorded individuals, they accounted for 60% of all of the fish observations, and 71% of all rockfish observations. Small schooling rockfish were also abundant and with over 14,500 observed across both years, accounted for 17% of the rockfish observations. Small schooling rockfish include Shortbelly, Halfbanded, Squarespot, and Pygmy Rockfishes, as well as those fish that could only be classified as unidentified small schooling rockfish. 

Observations of larger rockfish (both aggregating and non-aggregating species/groupings) represented only 14% of the total rockfish observations, with four species/groupings accounting for 80% of the observations: Blue, Olive/Yellowtail, unidentified and Canary Rockfishes. Canary Rockfish, a species that was listed as overfished until the end of 2016, was one of the more abundant species identified, with almost 1,600 individuals observed over the length of the survey. Yelloweye Rockfish, a currently listed overfished species, accounted for 220 individuals. 

Non-rockfish species represented 15% of the total fish identified, with two groupings accounting for 71% of the total observations: unidentified smelt and flatfish (all species/groupings combined). Unidentified smelt had the highest count within the non- rockfish grouping, with just under 7,000 observed individuals. A total of 14 species/groupings of flatfish were observed with combined total counts equaling 4,171 fish. 

For a full list of fish species and their overall densities by study site (MPA or reference) and transect type (rocky reef, soft bottom, or canyon), see Appendix 3.

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Table 2. Total count, estimated size and depth of all fish observed from video collected in 2014 and 2015 within the NCSR. 

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Invertebrate Totals For a full list of scientific names, see Table 3; invertebrates will be referred to by common name throughout this report. For all sites and survey years combined, a total of 70 individual macro-invertebrate species and another 29 groupings were identified (Table 3). Of the 124,064 individual invertebrates enumerated, seven species/groupings represented the majority of the observations (approximately 89%). Over 27% of the invertebrates identified were white-plumed anemones, which accounted for 86% of all anemone observations. The next most abundant invertebrates were slipper and California sea cucumbers, which combined, accounted for 40% of the total invertebrate observations. Two rocky reef coral species were also commonly observed: the short red gorgonian and California hydrocoral. Combined, these two species accounted for 11% of the total invertebrate observations. Sea stars represented 8% of the total invertebrate observations, with two species/groupings accounting for 61% of the total sea star observations: red sea stars and the Henricia complex. Lastly, two soft bottom coral species, sea whips and sea pens, accounted for 3% of the total invertebrate observations. 

For a full list of macro-invertebrate species and their overall densities by study area (MPA or reference) and transect type (rocky reef, soft bottom, or canyon), see Appendix 3. 

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Table 3. Total count and depth range of all invertebrates observed from video collected in 2014 and 2015 within the NCSR. 

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BASELINE CHARACTERIZATION OF STUDY AREAS 

The following MPA and reference area characterizations are abbreviated descriptions which include key findings for both the 2014 and 2015 survey years combined. In-depth characterizations for each MPA and reference pair are presented in Appendix 3. 

Point St. George Reef Offshore SMCA and Reference Area Located northeast of Crescent City, California, the Point St. George Reef Offshore State Marine Conservation Area (PSG SMCA) protects 24.7 square kilometers of marine habitats with depths ranging from 55 to 125 m (CDFW 2016b). The MPA is predominantly soft habitat (96%), but also protects the tip of a large offshore rocky reef (Figure 4). All fishing is prohibited within the SMCA with the exceptions of salmon by trolling and Dungeness crab by trapping. In addition to these exceptions, two federally recognized tribes, Elk Valley Rancheria and Tolowa Dee-ni’ Nation, are exempt from the area and take regulations of the PSG SMCA, but still must comply with all other existing regulations, including the Rockfish Conservation Areas, which have prohibited the take of groundfish in depths exceeding 20 fathoms (~37 m) since 2002. 

Located 6.3 km southeast of the PSG SMCA, a rocky reef and the surrounding soft bottom habitats were selected as a reference area for comparison (Figure 4). The reference area was selected based on similar habitats and depths (determined from multibeam mapping imagery) as inside its corresponding MPA. There are no state regulations specific to the reference area, but federal regulations prohibit the take of groundfish as part of the Rockfish Conservation Areas. Annual sampling within the reference area was planned to mirror survey efforts inside the SMCA.

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Figure 4. Point St. George study area showing the rocky reef and surrounding soft bottom habitats in (a) the SMCA and (b) reference area. 

Substrate Inside the SMCA and reference area, transects that targeted the rocky reef were primarily composed of rock and mud, while soft bottom transects were mainly composed of mud (Figure 5). Rocky reef habitats within both study areas were heavily influenced by sedimentation. Fine particulate material was suspended a few meters off the sea floor, and covered both rock and soft bottom surfaces in a thick layer of fine sediment and detritus. Only the vertical surfaces or tops of the highest relief rock outcroppings were free of these deposits. The density of suspended material was dependent on ocean conditions. Sampling at the reference site in 2015 was halted when large ocean swells moved into the study location causing visibility to decrease from a few meters to zero overnight. Future monitoring of the Point St. George study areas may encounter similar conditions. 

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Figure 5. Percent substrate (rock, boulder, cobble, gravel, sand and mud) by transect type (rocky reef and soft bottom) for survey lines inside the (a) Point St. George SMCA and (b) reference area

Habitat Overall, inside the SMCA and reference area, the habitat and rugosity within both rocky reef and soft bottom transects were comparable (Figure 6). Within the rocky reef, both study areas were mainly composed of hard and soft habitats, which combined represented 89% of the habitat at the SMR and 86% at the reference area. Outside the rocky reef transects targeting soft bottom habitats within the SMR and reference area were classified as 100% soft habitat. 

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Figure 6. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Point St. George Reef Offshore SMCA and (b) reference area for transect lines targeting: (I) the rocky reef and (II) the soft bottom habitats.

Fish The rocky reef of both study areas was characterized by rockfish species, Lingcod and Kelp Greenling (Figure 7). Rockfish densities were approximately three times lower in the rocky reef of the reference area, when compared to the SMCA. In addition, observed rockfish species richness was lower inside the reference area. The majority of rockfish identified within both study areas were epibenthic aggregating species such as Black, Blue and Olive/Yellowtail Rockfish, which were observed in large numbers near the tops of high relief rocky outcroppings. Canary Rockfish, a semi-aggregating species, were observed in high densities near the bottom, especially around sand channels within the rocky reef. Yelloweye and Quillback Rockfish were also common, with the highest regional rocky reef density of both species occurring at these two study areas. Yelloweye Rockfish densities within the SMCA were two times higher than observed anywhere else during this project. Soft bottom habitats were dominated by few species compared to rocky habitats, with flatfish and unidentified eel pouts being characteristic of both areas. 

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Figure 7. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a) Point St. George SMCA and (b) reference area for 2014 and 2015. For a breakdown of the taxonomic composition of subgroups, see Appendix 3. 

Invertebrates Invertebrate species composition within rocky reef habitats of both May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 109study areas was similar (Figure 8). Five macro-invertebrate species dominated observations within the rocky reef of both the SMCA and reference area: white-plumed anemones, slipper sea cucumbers, California sea cucumbers, short red gorgonians and red sea stars. While not characteristic of both study areas, basket stars were also common within the rocky reef of the SMCA. 

Soft bottom habitats were dominated by few species compared to rocky habitats (Figure 8). Dungeness crabs and red octopus were characteristic of both study areas accounting for over 80% of the total mobile invertebrate density. While, two groups, sea whips and pens, and white-plumed anemones accounted for 97% of the total sessile invertebrate density.

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Figure 8. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside (a) Point St. George SMCA and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 3.

Reading Rock SMR and Reference Area Reading Rock State Marine Reserve (SMR) is located just south of Reading Rock approximately 8 kilometers off the coast of Prairie Creek Redwoods State Park, in Humboldt County, CA (Figure 9). The SMR encompasses approximately 25 square kilometers of sea floor with depths ranging from 44 m to 77 m. It is mainly comprised of soft bottom habitats (98%), but also includes a small portion of rocky reef habitat (2%) that encompasses Reading Rock, but does not include the above-surface visible portion of the rock (CDFW 2016c). 

The Reading Rock reference area is located 0.95 kilometers north of the Reading Rock SMR. The reference area was selected to encompass similar habitats and depths (determined from multibeam mapping imagery) as those found within the MPA. There are no state regulations specific to the reference area, but federal regulations prohibit commercial or recreational the take of groundfish as part of the Rockfish Conservation Areas. Annual sampling within the reference area was planned to mirror survey efforts inside the SMR.

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Figure 9. Reading Rock study location showing rocky reef and soft bottom habitats in (a) the reference area and (b) SMR

Substrate Inside the SMR and reference area, transects that targeted the May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 112rocky reef were composed of all 6 substrate types (Figure 10). However, the reference area contained greater amounts of boulder, cobble and gravel at the transitional portions of the rocky reef than the SMR. Transects targeting soft bottom habitats within the SMR and reference area were entirely composed of mud substrate. 

During both survey years, there was better visibility at the reference area than inside the SMR. Visibility at the SMR ranged from 1 to 1.5 m, while at the reference area it ranged from 2 to 2.5 m. In addition, rocky substrates observed within the reference area were less sediment impacted than those within the SMR. These observations may indicate that the reference area, located on the north side of the rocky reef, may be subject to heavy currents and/or storm surges that carry away loose sediment and detritus which is deposited on the southern side of the reef in the SMR. 

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Figure 10. Percent substrate (rock, boulder, cobble, gravel, sand and mud) by transect type (rocky reef and soft bottom) for survey lines inside the Reading Rock SMR and (b) reference area. 

Habitat Overall, inside the SMCA and reference area, the habitat and rugosity within both rocky reef and soft bottom transects were comparable (Figure 11). Rocky reef transects within the SMR and reference areas were predominantly hard and mixed habitat combined, while soft bottom transects within the SMR and reference area were classified as 100% soft habitat. 

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Figure 11. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Reading Rock SMR and (b) reference area, for transect lines targeting (I) rocky reef and (II) soft bottom habitats 

Fish Fish species composition between the two study areas was similar. May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 115Rockfish species, Lingcod and Kelp Greenling characterized the rocky reef, even though their densities were quite low (Figure 12). Five species/groupings of rockfish accounted for 76% of the overall rockfish subgrouping density in the SMR, and over 65% in the reference area: unidentified rockfish, Olive/Yellowtail, Black, Blue, and Canary Rockfish. The epibenthic aggregating species including Blue Rockfish and Olive/Yellowtail Rockfish were commonly observed schooling around the tops of larger rock outcroppings. Another semi-aggregating species, the Canary Rockfish, was observed schooling near the sea floor close to the transition from soft bottom to rocky reef. Canary Rockfish were also observed within the rocky reef itself, but in lower numbers. Additional benthic rockfish species, such as Yelloweye Rockfish, Quillback Rockfish, Vermilion Rockfish and Rosy Rockfish, were observed intermixed throughout the rocky reef in both study areas. 

Surveys of soft bottom habitat were primarily dominated by flatfish and the ‘all other fish’ subgroup, of which unidentified smelt represented over 98% of the observations within both study areas. Smelt may be characteristic of the soft bottom habitats surrounding Reading Rock and are known to spawn on the nearby beaches.

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Figure 12. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a) Reading Rock SMR and (b) reference area for 2014 and 2015. For a breakdown of the taxonomic composition of subgroups, see Appendix 3. 

Invertebrates There were approximately 2.7 times as many invertebrates enumerated at the reference area as the SMR, however species composition was similar within both study areas (Figure 13). Within both areas, five macro-invertebrate species/groupings characterized the rocky reef: slipper sea cucumber, white-plumed anemone, California sea cucumber, red sea star and the Henricia sea star complex. 

Soft bottom habitats at the SMR and reference area were also characterized by few species. Sea whips and pens, and white-plumed anemones were the dominant sessile invertebrates, accounting for over 99% of the total sessile invertebrate density in soft bottom habitats at both areas. While no rocky substrates were observed on soft bottom transects, it is possible that cobble or large shell debris are buried just beneath the surface of the mud, providing attachment structure for the white-plumed anemones. The dominant mobile invertebrates included red octopus and Pleurobranchaea californica, which occurred in similar densities at both study areas. Sand stars were also common, but were three times as numerous at the reference area as the SMR. 

Figure 13. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside (a) Reading Rock SMR and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 3.

Mattole Canyon SMR and Reference Area Mattole Canyon State Marine Reserve is located offshore of the Mattole River estuary and California’s Lost Coast region, a portion of California’s North Coast that is sparsely populated with limited coastal access (Figure 14). Mattole Canyon SMR protects 25.4 square kilometers of marine habitats ranges in depth from 25 m to 502 m (CDFW 2016a). The SMR is predominately soft habitat (94%), but it also includes several rocky habitats (6%). Approximately 14% of the area of the SMR is deep submarine canyons, which makes it unlike any other MPA we surveyed within the NCSR. 

The Mattole Canyon reference area is located just 0.3 kilometers south of Mattole Canyon SMR and includes a portion of the same rocky reef structure (Figure 14). The reference area was selected to encompass similar habitats and depths (determined from multibeam mapping imagery) as those found within the MPA. There are no state regulations specific to the reference area, but federal regulations prohibit the take of groundfish as part of the Rock Fish Conservation Areas. Annual sampling within the reference area was planned to mirror survey efforts inside the SMR. 

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Figure 14. Mattole Canyon study area showing the rocky reef and surrounding soft bottom habitats in (a) the SMR and (b) reference area.

Substrate Within both study areas, transects targeting the rocky reef were similar, and were primarily composed of rock with sand and mud (Figure 15). Transects that targeted the canyon were also similar, and were mainly composed of mud with smaller amounts of rock and cobble depending on the study area. In contrast, soft bottom habitats in the two areas were distinctly different. The SMR had large amounts of scattered exposed rocky patches, creating mixed habitats unlike any other soft bottom area we surveyed regionally, including the reference area which was mainly composed of sand. 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 118Strong currents and large swells were common during our surveys of this location, along with strong afternoon winds and seas. These currents appeared to be characteristic of the area, as evident by the large, deep scour depressions around rock outcroppings and near the transitions between soft bottom and rocky reef. Dives targeting the canyon wall were difficult to complete due to the strong currents that swept across the shelf and accelerated down into the canyon. On the canyon floor we observed currents flushing organic materials out into deeper waters. Weather conditions changed rapidly and were not always consistent with predicted weather reports, making it a difficult location to sample. The typical work day for Mattole Canyon was short, requiring additional days beyond what was planned for this study location. 

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Figure 15. Percent substrate (rock, boulder, cobble, gravel, sand and mud) by transect type (rocky reef, soft bottom and canyon) for survey lines inside (a) Mattole Canyon SMR and (b) reference area.

Habitat Inside the SMR and reference area, transects targeting the rocky reef were composed of nearly equal parts of hard, mixed and soft habitats and were similar in rugosity (Figure 16). However, transects targeting soft bottom and canyon transects at the two study areas were not similar. In the SMR, both transect types were mainly composed of soft habitats with smaller amounts of mixed and hard habitats. Whereas, at the reference area, both transect types were almost exclusively soft only habitat. 

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Figure 16. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Mattole Canyon SMR (b) reference area for transects lines targeting: (I) the rocky reef, (II) soft bottom and (III) canyon habitats. 

Fish Fish species composition on rocky reef transects was similar in both study areas (Figure 17). YOY was the most abundant subgrouping and accounting for half of the total fish density at both areas. While, the same species of aggregating rockfish: Blue, Black, Canary, Widow and Olive/Yellowtail Rockfishes accounted for 75% and 85% of the rockfish observations in the reference area and SMR respectively. 

Transects targeting soft bottom habitats inside the SMR had the highest observed densities of rockfish, compared to all other study areas and habitat types. YOY rockfish densities were also 1.7 times higher than any other study area surveyed. Shortbelly Rockfish accounted for the majority of the small schooling rockfish observations in both study areas, but were twice as abundant in the reference area than the SMR. 

At the SMR, Sablefish and skates were commonly observed on dives that targeted the canyon floor. Moving up the sides of the canyon, rock outcroppings and compacted sediment shelves broke up the otherwise steep walls of the canyon where thornyheads, Greenstriped Rockfish and flatfish species were common. Just below the transitional point between the flat shelf and canyon, Canary, Olive/Yellowtail and Yelloweye Rockfishes were found sheltering from stronger currents above. Only one canyon dive was completed in the reference area. The slope of the canyon wall was considerably less steep, and currents there were greatly reduced. Spiny Dogfish, flatfish and Pacific Hake were the most abundant fish. 

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Invertebrates Invertebrate species composition within transects targeting the rocky reef of both study areas was similar (Figure 18). White-plumed anemones, California sea cucumbers, short red gorgonians and California hydrocorals were among the most abundant species observed at both areas. Sea star species and sponges were also common. 

Species composition on transects targeting soft bottom habitats within the SMR and reference area were fairly different. This was likely due to the differences in substrate composition between the two areas, with the SMR having many scattered rocky patches that hosted a greater abundance and diversity of sea stars, anemones, sponges and other invertebrates than the reference area that was composed of only soft habitats. May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 122

The same was true for transect targeting the canyon, with the SMR having a greater number and abundance of species than the reference area. However, anemones, white plumed anemones and red octopus were common in both study areas.

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Figure 18. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside the (a) Mattole Canyon SMR and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 3.

Ten Mile State Marine Reserve and Reference Area The Ten Mile State Marine Reserve (TM SMR) is located approximately 14.5 kilometers north of Fort Bragg, California, and encompasses 31 square kilometers of marine habitats (CDFW 2016d). The SMR spans 5 km of shoreline and shares its southern border with Ten Mile Beach State Marine Conservation Area. With depths ranging from 0 to 105 meters, the SMR is comprised of approximately 86% soft habitat, 8% rocky habitat and 6% unidentified habitat (Figure 19). The Ten Mile SMR was the only MPA we surveyed as part of the baseline program that previously was open to bottom fishing in its shallower waters prior to MPA implementation in 2014. Fishing deeper than 37 m was prohibited in 2002 through implementation of the Rockfish Conservation Areas by Pacific States Marine Fisheries Council. 

Located 2.2 kilometers south of TM SMR, a rocky reef and surrounding soft bottom habitats were selected as the Ten Mile reference area for comparison (Figure 19). The reference area was selected based on similar habitats and depths (determined from multibeam mapping imagery) as inside its corresponding SMR. There are no state regulations specific to the reference area, but federal regulations prohibit the take of groundfish deeper than 37 m as part of the Rock Fish Conservation Areas. Annual sampling within the reference area was planned to mirror survey efforts inside the SMR. 

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Figure 19. Ten Mile study location showing rocky and soft bottom habitats in (a) the SMR and (b) reference area.

Substrate Overall, substrate composition at the SMR and reference area May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 125was similar (Figure 20). At both areas, transects that targeted the rocky reef were mainly composed of rock with smaller amounts of sand and mud. Rock surfaces had less sedimentation and detritus buildup than the two northernmost study locations. These cleaner rocky surfaces hosted encrusting coralline algae in the shallower portions of the rocky reef, which was not observed at any of the other study locations. We also observed less suspended fine particulate material, which may have accounted for the better water visibility, that was typically 4 to 6 m, compared to 1 to 3 m observed at other locations such as Point St. George. Transects that targeted the soft bottom were composed exclusively of sand or mud at both study areas. 

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Figure 20. Percent substrate (rock, boulder, cobble, gravel, sand and mud) by transect type (rocky reef and soft bottom) for survey lines inside the (a) Ten Mile SMR and (b) reference area.

Habitat Overall, inside the SMR and reference area, transects that targeted the rocky reef and soft bottom habitats and rugosity were comparible (Figure 21). Rocky reef transects within the SMR and reference areas were mainly composed of hard and soft habitats, which combined represented, 84% of the habitat at the SMR and 88% at the reference area. While soft bottom transects within the SMR and reference area were classified as 100% soft habitat. 

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Figure 21. Percent habitat type (hard, mixed and soft) and percent rugosity (high, medium, low and flat) at (a) Ten Mile SMR and (b) reference area, for transect lines targeting (I) the rocky reef and (II) the soft bottom habitats.

Fish Fish species composition and abundance were similar within the SMR and reference area (Figure 22). Rockfish were common and, along with Lingcod and Kelp Greenling, characterized the rocky reef. Epibenthic aggregating rockfish species were the most abundant rockfish, with Blue, Canary and unidentified rockfish being the most common species at both study locations. YOY were also very common within the rocky reef, with densities higher than at any other study are pair. 

Fish observed in the soft bottom habitats were similar within both study areas, May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 128and were mainly composed of flatfish and ‘all other fish’. The ‘all other fish’ subgroup was most notably different between the two areas. Unidentified smelt were observed in large numbers at the reference area accounting for 90% of the ‘all other fish’ density, compared to only 18% within the SMCA. 

May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 129

Figure 22. Mean density of fish subgroupings observed within rocky reef and soft bottom transects at (a)
Ten Mile SMR and (b) reference area for 2014 and 2015. For a breakdown of the taxonomic composition
of subgroups, see Appendix 3.

Invertebrates Invertebrate species composition within both the rocky reef and May 2017 - North Coast Baseline Program Final Report: Mid-depth and Deep Subtidal Ecosystems 130soft bottom habitats was similar between the two study areas (Figure 23). Within the rocky reef, like the northernmost two MPAs we studied, white-plumed anemones and slipper sea cucumbers were the characteristic sessile macro-invertebrates, while California sea cucumbers were the characteristic mobile invertebrate. However, unlike the northernmost MPAs, sponges and other anemones were also abundant in the rocky reef at the Ten Mile study location. 

Within the SMR, red sea urchins were also observed in much higher densities than compared to the reference area. The higher urchin observations are likely a result of the shallower depths surveyed at the SMR, compared to the reference area, where very few red urchins were observed. 

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Figure 23. Mobile and sessile invertebrate mean densities for rocky reef and soft bottom transects inside the (a) Ten Mile SMR and (b) reference area. For a breakdown of the taxonomic composition of subgroups, see Appendix 3.

ANALYSIS OF INDEX SITES 

Fish species distribution and abundance are important considerations for MPA placement; they influence their effectiveness and are characteristics used to assess MPA performance. We used visual species observations directed at paired index sites to establish nearshore rocky reef fish assemblage metrics. These metrics can be monitored over time to inform performance assessment and adaptive management. The paired index sites where chosen to be representative of the general rocky reef habitat at each of the four locations (Point St. George, Reading Rock, Mattole Canyon and Ten Mile), inside the MPAs and outside of the MPAs in their respective reference areas. Ten rocky reef fish species/groupings were selected for in-depth density analyses to establish baseline metrics for future comparisons (Table 4). 

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Table 4. Number of observations and mean density at all index sites per 100 m2 (+SE) for ten fish species selected for statistical comparisons among MPAs and their respective reference areas. Proportion of obs. is the proportion of non-YOY observations in the index sites only. Frequency of observation (FO) is the proportion of ROV transects in index sites in which the species occurred at least once. 

Fish Densities Overall, individual species densities were low at all locations (<1 per 100 m2), with the highest densities occurring at Point St. George SMCA and Ten Mile SMR (Figure 24). While densities differed significantly for nearly all species among the MPA locations, they were the same inside each MPA and reference area pair except Point St. George. The Olive/Yellowtail Rockfish was common, and observed in the highest density at Point St. George.

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Figure 24. Density per 100 m2

of select rocky reef fishes at each MPA (SMR or SMCA) and reference

area index site pair at Point St. George, Reading Rock, Mattole Canyon and Ten Mile.

Similarity Test
Based on the results of the Bray-Curtis Similarity Test (group average agglomerative
clustering) among index site fish assemblages we found three of the four MPA and
reference area index site pairs were well placed, which will allow for robust comparisons
in long-term monitoring in the North Coast Study Region. However, assemblage
similarity was the lowest between the Point St. George SMCA and reference area index
sites.

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Figure 25. Similarity (group average agglomerative clustering) among index site fish assemblages in MPA and reference area pairs, for Point St. George, Reading Rock, Mattole Canyon and Ten Mile. Analyses are based on densities for individual species and taxonomic groups (see methods for full list of taxonomic groups). Data were combined for observations over all substrates. 

Point St. George Index Sites The Point St. George SMCA index site spans the most exposed portion of the reef. The reference area index site is located approximately 16 km southeast along another strip of reef that is somewhat protected from the predominant northwest winds and currents. The two index sites both range from 50-70 m in depth. 

The SMCA and reference area index sites showed the least similarity between fish species assemblages (60% overall and 40% over rock substrates) and the most significant differences in species densities of any other MPA/reference area index site pair. The highest densities of Canary, Blue and Olive/Yellowtail Rockfish were observed at the SMCA index site, while the lowest densities of Kelp Greenling and Lingcod were also observed there. Additionally, Copper and Widow Rockfish were observed at the SMCA index site but were absent at the reference site. Black Rockfish were also present at the reference site, but not at the SMCA site. While a greater percentage of hard rocky habitats were surveyed at the reference site, generally higher densities of most rockfishes, flatfishes, Lingcod, and Kelp Greenling were observed at the SMCA site. Only Tiger Rockfish, Quillback Rockfish, and small benthic fishes showed higher densities at the reference area index site. 

Differences in geographical orientation and resulting physical conditions may have influenced the differences observed between the index sites at Point St. George. The SMCA’s position at the outer edge of the reef makes it difficult to find a reference site with similar habitat conditions. It is recommended that the Point St. George reference area be re-evaluated and potentially moved to a location closer to the MPA to increase comparability to the SMCA in both assemblage and species densities, but this may not be feasible. During the 2014 cruise, several other locations near the PSG SMCA were surveyed with the ROV as a part of a California Department of Fish and Wildlife survey of the North Coast Region. Two additional sites located off Point St. George SMCA and two sites just south of Crescent City were surveyed using the ROV. These locations were also considered as a possible reference area for the SMCA, though none of them were a suitable match. Even though there are differences in the fish species assemblages and habitat conditions, the baseline data collected at each site should still provide some metrics for monitoring change over time. 

Reading Rock Index Sites Reading Rock’s SMR index site is positioned on the southern tip of a small offshore elliptical reef and the reference area index site is located on the northern edge of the same reef just 1,500 m from the SMR site. Species assemblages were more than 80% similar at the SMR and reference area index sites. All fish species densities were low at both Reading Rock index sites. Lingcod and Blue Rockfish exhibited the highest densities both at the SMR and reference site. Black Rockfish were more common at the SMR site, and Canary Rockfish were more common at the reference site. All ten species chosen for metric establishment were observed in small numbers at Reading Rock. Statistical differences in densities were observed for Vermilion Rockfish (none observed at the SMR site) and Black Rockfish; density for both species was higher at the SMR index site. 

Mattole Canyon Index Sites Mattole Canyon’s two index sites were positioned less than 500 m apart on the southern side of the canyon head, with depths ranging from 20-60 m. Index site assemblages at this location were very similar overall, greater than 80%. Blue, Black, and Canary Rockfish, as well as Kelp Greenling and Lingcod, were observed in the highest densities at these sites. Kelp Greenling densities at Mattole Canyon were highest of all four MPA locations. There were no density differences between the SMR and reference area sites at this location for the ten selected species. 

Ten Mile Index Sites Ten Mile’s SMR index site is located offshore of the Ten Mile estuary and contains a higher percentage of rocky reef than the other MPA’s surveyed. The SMR index site is located on the southern edge of the reef, while the reference site is located approximately 8 km south on the north edge of another reef in the same depth range (40-60 m). At Ten Mile, we found relatively high densities of Blue and Canary Rockfish in both index sites, many of which were juvenile and sub-adult fishes. A very large number of YOY and various small individuals were also observed at the Ten Mile location compared to the other three sites. 

FISH DEPTH DISTRIBUTION 

The depth distribution of select fish species/groupings across rocky reef transects are presented here for Point St. George, Reading Rock, Mattole Canyon and Ten Mile MPAs and their paired reference areas (see methods for a list of fish species). In addition, the depth distribution of select fish across canyon transects are shown for Mattole Canyon SMR. Only one exploratory canyon transect was surveyed in the Mattole Canyon reference area, therefore the depth distribution of fish within the canyon of the reference area are not presented. Due to an absence in species diversity, with 2 categories ‘unidentified flatfish’ and ‘all other fish’ accounting for 98% of the fish observed on soft bottom transects, results for soft bottom transects are not shown. 

Depth distributions of select fish species are presented for all rocky reef transects surveyed (index sites and characterization transects combined) for each study area. During the planning phase, effort was made to place index sites in the most prominent rocky reef habitat within the 40-60 m depth range in each MPA. Index site placement was not intended to cover the full range of depths in which rocky habitat was predicted (using multibeam mapping) in each MPA, but to cover similar depth ranges at all study areas. Paired reference areas were subsequently selected to provide comparable rocky habitat within the same depth range as the MPA index site. 

The total area and range of depths surveyed for each MPA and reference area pair, and the depth range of each index site is given in Table 5. Effort was made to survey a similar amount of area within each MPA and reference area pair and to survey, as much as possible, the full range of depths in which rocky habitat was predicted using characterization transects. Additionally, we attempted to survey similar depth ranges between each MPA pair, although this was not always possible as rocky reef and canyon habitat did not always occur within the same range of depths. For shallower rocky habitat, the ROV’s operational capacity was limited to approximately 15 m. 

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Table 5. The total area and depth range surveyed from rocky reef and canyon transects inside MPAs (SMCA or SMR) and their associated reference areas for Point St. George, Reading Rock, Mattole Canyon and Ten Mile.

To show the density of fish along a vertical gradient, depth was stratified into 10 m bins for rocky reef transects and 10 and 50 m bins for canyon transects. The total area surveyed per depth bin at each site is shown in Figure 26 for rocky habitat transects and Figure 31 for canyon transects. The distribution and density of select fish species were plotted for each depth bin and are shown in Figures 27-30. 

Rocky Reef Transects 

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Figure 26. The total area of rocky reef transects surveyed per depth bin for each MPA for Point St. George SMCA (blue), and Reading Rock SMR, Mattole Canyon SMR and Ten Mile SMR (all SMRs in red) and their reference areas (gray).

Depth distributions for select fish species are presented for all MPA and reference area pairs surveyed. Data is presented as a reference for the depths surveyed within the rocky habitat, and to show overall density by species/grouping across those depths. Additionally, the depth range for index sites within each study area are presented to show the expected distribution of select fish within each index site at paired MPA and reference areas. 

Point St. George – Rocky Reef Rocky reef habitat at Point St. George SMCA and reference area encompass a limited range of depths (Figure 26). Less than 200 m2 was surveyed in the 40-49 m bin at both the SMCA and references areas, therefore, these data were not included in Figure 27. Depth bins ranged from 50-79 m at the SMCA and from 50-69 m at the reference area. The depth range of the Index site placed over rocky features within reference area overlap the depths surveyed within the SMCA and appear to be representative of the distribution of rocky habitats within both study areas. 

Overall, the SMCA and reference area appeared to have similar distributions of fish in each of the depth stratified bins. The most notable difference was for Olive/Yellowtail Rockfish, where at the SMR densities are greater in the 50-59 m depth bin, while at the reference area they are greater in the 60-69 m depth bin. 

Figure 27. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Point St. George SMCA and reference area. 

Reading Rock – Rocky Reef Reading Rock SMR and reference area also encompass a limited range of depths (Figure 26). At these two study areas, less than 200 m2 were surveyed in the 30-39 m bin in the SMR, and in the 30-39 and 60-69 m depth bins in the reference area. Consequently, this data was not included in density calculations for Figure 28. Depth bins in the SMR ranged from 40-69 m, and 40-59 m in the reference area. The depth range of index sites placed over rocky features within the SMR and reference area overlapped much of the depths surveyed within the SMR and are more representative of the distribution of rocky habitats within both study areas. Again, the SMR and reference sites appeared to have similar distributions of fish in each of the depth stratified bins. The most notable differences are for Blue Rockfish, where densities appear to be higher in the 40-49 m depth bins and for Canary Rockfish and the Olive/Yellowtail Rockfish complex, where density appears to increase with depth. Also notable, there are no observations of Black, Blue, Copper, Quillback or Sebastomus Rockfish in the 60-69 m depth bin within the SMR. 

Figure 28. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Reading Rock SMR and reference area. 

Mattole Canyon – Rocky Reef Mattole Canyon rocky reef habitat encompassed a wider range of depths than the northern two sites (Figure 29). Less than 200 m2 was surveyed in the 20-29 m and 80- 89 m depth bins at the SMR site, and in the 60-69 m, 70-79 m and 80-89 m depth bins at the reference site; these data were not included in density calculations for Figure 29. Depth bins ranged from 30-79 m at the SMR and 20-59 m at the reference area. 

Overall, the following notable trends were seen at Mattole Canyon SMR and reference sites: Sebastomus, Vermilion, and Yelloweye Rockfish were present at nearly all depths in the SMR site; however, they were not observed at the reference site, with the exception of Vermilion Rockfish being present in one depth bin (30-39 m). Olive/Yellowtail Rockfish density increased with depth at the SMR site, but at the reference site, density remained low across most depth bins. Kelp Greenling and Lingcod were present at all depths in both the SMR and reference sites with Lingcod density increasing with depth. Canary Rockfish were common at both the SMR and reference sites in all depth bins 30 m and deeper. Index sites placed in the Mattole Canyon SMR did not fully overlap the surveyed depth range, and are therefore not completely representative of the available rocky reef habitat within the SMR. Additionally, the index site placed at the reference area

covered a shallower range of depths than the index site within the SMR. Overall fish distribution also appears to be different within each site, with fewer species observed at the reference site. These differences are most notable for some of the non-aggregating rockfish species, such as Sebastomus, Vermilion, and Yelloweye Rockfish. Given these differences, future monitoring plans should consider expanding the range of depths surveyed beyond the index sites to capture the full distribution of species within the SMR and reference area at the Mattole Canyon study location. 

Figure 29. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Mattole Canyon SMR and reference area. 

Ten Mile – Rocky Reef Ten Mile’s rocky reef habitat encompassed a wider range of depths than the other sites surveyed (Figure 26). Less than 200 m2 were surveyed in the 70-79 m and 80-89 m depth bins in SMR, and 10-19 m and 20-29 m depth bins in the reference area; these data were not included in density calculations for Figure 30. Depth bins ranged from 10-69 m deep in the SMR and 30-89 m deep in the reference area. 

For both the SMR and reference area, Blue Rockfish densities increased as depth decreased, while Canary Rockfish showed the opposite, and increased in density with depth. Black Rockfish were only observed in the SMR and only at depths shallower than 49 m, with the highest densities observed at the shallowest depth bin surveyed (10-19 m). The Sebastomus Rockfish complex was observed at both sites, but only at depths greater than 40 m. 

The index site placed in the Ten Mile SMR did not fully overlap the surveyed depth range, and is therefore not representative of the available rocky reef habitat (for depths greater than 20 m) within the SMR. The index site placed within the reference area did fully overlap with the depth range of the SMR index site, as did the fish distributions observed within both sites. As currently situated, both index sites are a good match and will allow for monitoring long-term trends in both areas. 

Within the SMR, available rocky reef habitats extend shallower than the range of depths at the index site. Therefore the index site may not be suitable for detecting the shallower range of species observed in the SMR. For example, Black Rockfish, which were more abundant in the shallow areas of the rocky reef, may not be observed within the index site. The opposite occurred at the reference area, where surveyed depths extended deeper than the index site. Given these differences, future monitoring plans should consider expanding the range of depths surveyed beyond the index site to capture the full distribution of species within the SMR and reference area. 

Figure 30. Density of select fish species per depth stratified bin, with bubble size representing their relative density for Ten Mile SMR and reference area. 

Canyon Transects 

Figure 31. The total area surveyed per depth bin for canyon transects at Mattole Canyon SMR. 

Mattole Canyon – Canyon Within the Mattole Canyon SMR transects, canyon habitat depths ranged from 52-420 m. Effort is shown in Figure 31 and surveyed depths are broken into 10 m bins from 50- 149 m, and into 50 m bins from 150-449 m in depth. Less than 200 m2 were surveyed in the 140-149 m bin. As a result, these data were not included in density calculations for Figure 32. Although index sites were not placed in the canyon, Figure 32 shows the distribution at which select species occur in the canyon, which may be used for future monitoring. 

Overall, the occurrence and relative densities of several species showed marked differences between shallow (<100 m) and deep zones (>100 m) where the shelf/canyon interface occurs (indicated by a red line in Figure 32). The following notable trends were present in the rockfish species surveyed: Canary Rockfish are relatively high in density in the shallower depth bins surveyed and decrease in density until just after the shelf/canyon break at 110-119 m, where they were no longer present. Olive/Yellowtail Rockfish showed the highest density around the shelf/canyon interface, but were also observed in the shallowest depth bin (50-59 m). Yelloweye Rockfish were observed with similar densities around the shelf/canyon break from 80-119 m, while Greenstriped Rockfish occurred from just above the shelf break down to 249 m. Black, Blue, Copper, and Vermilion Rockfish were not present on any of the canyon transects. 

Thornyheads occurred exclusively in the deeper ranges of the canyon, within the typical range expected. Lingcod occurred in a wide range of depths, but were observed in much higher densities in the shallower (50-89 m) depth bins. While Lingcod densities were lower around the shelf/canyon break, they were observed to a depth of 300 m. No Lingcod were observed between 120 m and 139 m. Kelp Greenling were only observed in the shallowest depth bins, from 50-89 m. 

The ‘all flatfish’ grouping shown in Figure 32 includes all observations of unidentified flatfish plus all flatfish identified to species level (see Appendix 6 for a full list of species). Additionally, the five more commonly observed flatfish species that were identified to species level are also shown, although their densities only represent the proportion that was identified. Overall, flatfish were observed from 70-449 m, with the highest density of flatfish observed in the 150-199 m depth range. Dover Sole only occurred at the canyon-shelf interface and deeper, while sanddabs only occurred at the canyon-shelf interface, and shallower. English Sole and Petrale Sole were observed mainly in the mid-ranged depths, while the Rex Sole was observed exclusively in the deeper ranges of the canyon. 

Overall, the interface between the shelf and canyon appears to be an important habitat feature for some of the species presented. Yelloweye Rockfish were only observed near the canyon-shelf interface, from 80 to 119 m. For other species, such as Canary and Olive/Yellowtail Rockfish, densities decrease with depth and eventually disappear at the canyon-shelf interface. The opposite was true for Greenstriped Rockfish and Dover Sole, which increased in density deeper than the canyon-shelf interface. Future monitoring plans for Mattole Canyon SMR should consider capturing the full extent of the canyon, with importance placed on capturing information on either side of the canyon-self interface. 

Figure 32. The density of select fish species per depth stratified bin, with bubble size as the relative density of fish in that depth bin. There was insufficient data (less than 200 m surveyed) for the 140-149 meter depth bin (indicated by the gray line). The shelf/canyon break occurred at about the 100 m mark (indicated by the red line). 

FISH SIZE DISTRIBUTION 

Laser-based Size Estimates Mean visual size estimates for ten select species of fish (Black, Blue, Canary, Copper, Olive/Yellowtail, Quillback, Vermillion, and Yelloweye Rockfish, and Lingcod and Kelp Greenling) are presented in Table 7. 

Table 6. The mean total length of select fish species within each MPA (SMCA & SMR) and reference (Ref.) area: Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). A dash mark indicates no individuals were counted at that study area. ‘N/A’ indicates too few fish were counted to report a mean. 

Overall, the ten species show little difference in mean total length between MPA and reference area pairs. For the rockfish species, the largest mean size difference between a MPA and reference area was found at Mattole Canyon, where Blue Rockfish mean total lengths differed by 11.9 cm. Surveys at the Mattole Canyon reference area had a shallower depth range than Mattole Canyon SMR (see table 5 in the depth section). Since smaller juvenile Blue Rockfish were typically seen at shallower depths, this likely accounts for the large difference in the mean density between the two areas. All other rockfish mean differences ranged from 0.2 cm to 4.6 cm. 

Lingcod showed a large difference in mean total length between study areas at Mattole Canyon, where the means differed by 10.6 cm. At all other study area pairs, the difference in the means was 2.3 cm or less. Kelp Greenling showed the smallest difference in mean total length between study areas, with a 1.4 cm difference at Point St. George, and a 0.1 cm to 0.6 cm difference at all other study areas. 

Because there was little difference overall in mean total length between MPA and reference areas for the ten fish species presented, lengths for MPA and reference pairs were combined to show the size frequency for each of the 4 study locations: Point St. George, Reading Rock, Mattole Canyon and Ten Mile (Figures 33-42). Percent size frequency is presented in 5 cm bins and size at which 50% of the females of the population reach sexual maturity is referenced in each of the size frequency graphs with dashed lines (Love et al. 2002; Thorson and Wetzel 2016; MacCall 2005; Stewart 2009; CDFW 2016f). 77

Black Rockfish No smaller size classes (10-19 cm) of Black Rockfish were identified at any of the four study locations (Figure 33). Mature fish over 35 cm represented 72% to 100% of the population depending on the location. There were no Black Rockfish observations at the Ten Mile reference area, while Point St. George and Ten Mile SMR had relatively few observations of Black Rockfish at 20 and 22 fish respectively, when compared with Reading Rock and Mattole Canyon that had 97 and 138 fish respectively. 

Figure33. Percent (%) size frequency of Black Rockfish at Point St. George (PSG), Reading 

The above photo is a 44 cm Black Rockfish from Mattole Canyon. 

Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 41 cm (—) for females (Love et al. 2002). 

Blue Rockfish Mattole Canyon and Ten Mile locations had the highest proportion of smaller size classes (10 – 24 cm) of Blue Rockfish, representing 39% to 51% of the population at each site respectively (Figure 34). This result was expected, as Mattole Canyon and Ten Mile surveys encompassed a shallower range of depths, where smaller juvenile Blue Rockfish were typically observed. Mature fish over 29 cm represented 41% to 62% of the population depending on the site. 

Juvenile Blue Rockfish, as seen in Photo A of a 13 cm Blue Rockfish from Ten Mile, were commonly observed at the two southern sites, Mattole Canyon and Ten Mile. Photo B is of a 33 cm Blue Rockfish from Ten Mile. 

Figure 34. Percent (%) size frequency of Blue Rockfish at Point St. George (PSG), Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 29 cm (—) for females (CDFW 2016f). 

Canary Rockfish The majority of Canary Rockfish seen, 90% to 97% depending on the site, were less than 39 cm in total length (Figure 35). Depending on the study location, only 3% to 11% of the population represented sexually mature fish over 40 cm. At the Reading Rock study location, the smaller size class (10-14 cm) represented nearly 20% of total observations, while they represented less than 10% of the observations at the other three study areas. 

Juvenile Canary Rockfish exhibit a large black spot on the spiny dorsal fin as seen in Photo A of a 13 cm Canary Rockfish from Ten Mile. As Canary Rockfish mature they may retain 

Figure 35. Percent (%) size frequency of remnants of the black spot as seen in Photo B of 

Canary Rockfish at Point St. George (PSG), a 26 cm sub adult from Ten Mile. Photo C is a 45 cm adult, the size at which 50% of females are sexually mature. 

Reading Rock (RR), Mattole Canyon (MC) and Ten Mile (TM). Size at 50% sexual maturity is 44.5 cm (—) for females (Stock assessment; Thorson and Wetzel 2016). 

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June 2016 – Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08

Cruise Report for ‘Patterns in Deep-Sea Corals’
Expedition 2016: NOAA ship Shearwater SW-16-08

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 137
June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 138

Disclaimer:
This publication does not constitute an endorsement of any commercial product or intend to be an opinion beyond scientific or other results obtained by the National Oceanic and Atmospheric Administration (NOAA). No reference shall be made to NOAA, or this publication furnished by NOAA, to any advertising or sales promotion which would indicate or imply that NOAA recommends or endorses any proprietary product mentioned herein, or which has as its purpose an interest to cause the advertised product to be used or purchased because of this publication.

The recommended citation for this report is:
Etnoyer PJ, Shuler AJ, Frometa J, Lauermann A, & Rosen D (2017). Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08. NOS NCCOS 233, NOAA National Ocean Service, Charleston, SC 29412. 21 pp.Cover image credit: Marine Applied Research and Exploration/NOAA.

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 139

Cruise Report for ‘Patterns in Deep-Sea Corals’
Expedition 2016: NOAA ship Shearwater SW-16-08

Peter Etnoyer1

, Andrew Shuler2

, Janessy Frometa2

, Andrew Lauermann3

, Dirk Rosen3

1 NOAA National Centers for Coastal Ocean Science, 219 Fort Johnson Rd., Charleston, SC 29412
2 JHT, Inc, 219 Fort Johnson Rd., Charleston, SC 29412
3
Marine Applied Research and Exploration. 1230 Brickyard Cove Road #101, Richmond, CA 94801

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 140

Table of Contents

1. Expedition Overview………………………………………………………………………………………………..1
2. Narrative of Cruise Results………………………………………………………………………………………1
2.1 Objective 1: recover previously deployed temperature loggers …………………………….1
2.2 Objective 2: conduct ROV seafloor surveys ……………………………………………………….1
2.3 Objective 3: collect live Acanthogorgia sp. corals for laboratory studies ………………1
3. Discussion………………………………………………………………………………………………………………..2
4. Acknowledgements…………………………………………………………………………………………………..2
5. References ……………………………………………………………………………………………………………….2
6. Tables………………………………………………………………………………………………………………………3
7. Figures …………………………………………………………………………………………………………………….6
8. Appendices ……………………………………………………………………………………………………………10
Appendix A: Operational Notes……………………………………………………………………………..10
Appendix B: Individual temperature logger site information, images and data. …………..12

Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater
SW-16-08

1. Expedition Overview

The 2016 ‘Patterns in Deep-Sea Corals’ expedition set out aboard the NOAA Ship Shearwater inAugust to study the distribution, ecology, and health of deep-water (30-300 m) gorgonian corals in response to the 2015 El Niño event. The research team consisted of staff from NOAA National Centers for Coastal Ocean Science (NCCOS) and Marine Applied Research and Education (MARE; Table 1). The study used the remotely operated vehicle (ROV) Beagle to recover previously deployed temperature loggers (Caldow et al. 2015) and to conduct video transects for the purpose of density estimation and health assessments.
The primary scientific objectives of the expedition were to: 1) recover temperature loggers that were deployed in the spring and fall of 2015 in order to assess temperature anomalies; 2) characterize deep- sea coral ecosystems in newly mapped areas of the Channel Islands National Marine Sanctuary

(CINMS) (Figures 1-4); and 3) collect live Acanthogorgia sp. corals for laboratory studies on temperature.

2. Narrative of Cruise Results

The expedition’s scientific objectives were successfully met thanks in large part to good weather and few technical difficulties. In addition to the scientific objectives, several outreach activities were completed during the expedition, including. A dockside presentation for six people in Santa Barbara Harbor, and an at sea day for seven people, during which they were able to come aboard the NOAA Ship Shearwater and participate in a ROV dive. The VIP party included representatives from Conservation International, Rockefeller Foundation, Coral Reef Watch, and others. 2.1 Objective 1: Recover previously deployed temperature loggers The ROV recovered all four temperature loggers from depths ranging between 20-100 m. Data was successfully downloaded from each logger, and plotted across time (Figure 5 and Appendix A). Temperatures averaged between 14-15 0C at 20 m, with a maximum of 19 0C in July. Temperatures at 50 m exceeded 15 0C on average, but never reached the 19 0C threshold observed at 20 m.

Temperatures showed little temporal variation at 100 m, and ranged between ~10-12 0C. In the future, this temperature data will be analyzed in more detail in order to identify trends and anomalies. This analysis will also incorporate temperature data collected from CTD casts near the Channel Islands, and
other sources.

2.2 Objective 2: Conduct ROV seafloor surveys

Of the 14 ROV dives conducted over the course of the expedition, the majority took place over the newly mapped areas north and south of Santa Rosa Island (Figures 2-4; Table 3). The total bottom time was 17 hours and 51 minutes, during which 30 video transects were completed (Table 4). Video data collected during the ROV transects will be analyzed in order to determine species composition, health and densities of deep-water corals. This data will become publicly available within one year through the NOAA Deep Sea Coral Data Portal (https://deepseacoraldata.noaa.gov/). 2.3 Objective 3: Collect live Acanthogorgia sp. corals for laboratory studies The team successfully collected two live colonies of Acanthogorgia sp. octocorals from 200 m. Upon retrieval from the ROV, each colony was split into six fragments. Coral fragments were shipped to both the Claremont College in California, and the Deep Coral Ecology Laboratory in Charleston, SC.

The live corals arrived at their respective institutions within 24 h of shipment, and were successfully acclimated into an aquarium environment (Figures 7-8). While the original goal was to collect four small colonies, the colonies collected were large enough to provide enough material for laboratory
experimentation.

3. Discussion
The successful recovery of all temperature loggers is an important accomplishment, particularly since three of the four loggers were deployed from a ship. Additionally, we were able to successfully download data from all temperature loggers, indicating that they hold up well under the conditions and
duration of our deployment. It is important to point out that the temperature logger deployed at the shallowest depth (20 m) had substantial overgrowth by encrusting fauna, whereas overgrowth was minimal in the other three loggers. Therefore, future deployments of these devices at depths shallower than 50 m should consider providing some means to deter fouling, with either external housing or anti-fouling paint.

The ROV dives focused on habitat characterization and dive time was split between transects and exploration. This split approach allowed the science team to obtain quantitative information on the coral communities during transects, as well as provided time to explore the newly-mapped environment more freely. The use of dedicated transects also facilitated the process of estimating octocoral density, by ensuring consistent speed, altitude, and direction.
The collection of live corals from deeper than 50 m is another important accomplishment of this expedition. One of the dives was dedicated exclusively for specimen collections, and this approach was critical in reducing undue stress to the organisms. Future collections of live material should consider a
similar approach.

4. Acknowledgements
The authors would like to acknowledge the support and guidance of the Channel Islands National Marine Sanctuary staff especially Chris Caldow, Julie Bursek, and Ryan Freedman. It is also important to note the skill and expertise of the crew of the NOAA Ship Shearwater, specificallyCaptain Terrance Shinn, First Mate Charles Lara, and Lieutenant junior grade Elizabeth Mackie. Equally as important were team members Steve Holz and Rick Botman of Marine Applied Research and Exploration for their critical support to this mission. These individuals were instrumental to the smooth deployment and operation of the ROV Beagle and the success of this expedition.

5. References
Caldow, C., P. J. Etnoyer, L. Kracker. 2015. Cruise Report for ‘Patterns in Deep-Sea Corals’
Expedition: NOAA ship Bell M. Shimada SH-15-03. NOAA Technical Memorandum NOS NCCOS
200. 15 pp. Silver Spring, MD.
OSPAR. 2010. Background Document for Coral Gardens. Publication number 486. OSPAR
Biodiversity Series. https://www.ospar.org/documents?v=7217

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8. Appendices

Appendix A: Operational notes

July 31, 2016. Mobilization began at 0830 at Santa Barbara Harbor. JHT/NOAA staff members
loaded science gear and purchased food. MARE staff members loaded and set up the ROV and
associated equipment. After mobilization was complete, Rosen and Etnoyer provided an outreach
event for six current and potential MARE donors on the NOAA Ship Shearwater dock, which
included a presentation of the mission goals.

August 1, 2016. The expedition got off to a rough start, as the vessel hit a piling and bent the tracking
pivot irreparably. Ed Liquorek, the brother of a local angler, fabricated a new pivot. The NOAA Ship
Shearwater left the dock at 1300 and transited to the north side of Anacapa Island, arriving by 1530.
The ROV was deployed by 1630 to retrieve temperature loggers at 20 m. The ROV encountered a
large black seabass as soon as the ROV reached bottom. The team retrieved two temperature loggers
(B and P) during the first dive. A large air bubble seeped into the main tether compensator overnight.
Lauermann and Rosen had purged the bubble prior to the ROV deployment, but it reappeared after the
20 m dive, 55 m dive (logger D retrieval), and 110 m dive (logger C retrieval at NMFS sled site). This
marked the first use of HD video for the live feed from the ROV. The focus was acceptable, but the
color appeared washed out at times. Overall, it was much improved over standard definition. The
final ROV dive of the day was completed by 2000 and the manipulator skid was removed since all
temperature loggers had been recovered. The NOAA Ship Shearwater transited to South Santa Rosa
to anchor overnight.

August 2, 2016. The tether compensator was purged of air in transit to the north side of Santa Rosa.
The ROV was first deployed at 0800. Three dives were conducted through the course of the day, for a
total of 12 transects of 15-minute duration each, in addition to general exploration at three different
sites. The three dives were at 80 m, 70 m and 65 m. The tether needed to be purged after each dive,
because the piston completely bottomed out after each dive. To improve the quality of the HD feed
and video, the white balance was adjusted using white plastic bags on the clump shroud. This
improved the color of the video. During the dives, some Adelogorgia gorgonians were noted on
ridges, along with an abundance of Eugorgia gorgonians, both of which appeared healthy. In addition
to these corals, the team noted a few spots with many lingcod, copper, starry, and a few gopher
rockfish, bocaccio and sheephead. ROV pilots noted that moving the vertical thruster forward this
winter helped make the ROV perform better straight up and down, and moving the altimeter forward
improved auto-altitude function over moderate terrain. The HMI lights on the ROV became erratic
through the course of the day and did not stay on. With the low light HD camera, and the reds of the
tungsten light still allowing for good photos to be captured, the need for the HMIs was questionable.
The ROV team used a new AA Beacon, and it performed adequately down to 70 m. The ROV was
recovered and operations were concluded by 1800. The NOAA Ship Shearwater anchored at
Johnsons’ Lee, Santa Rosa for the evening. Elephant seals were heard billowing throughout the night.
August 3, 2016. The weather remained good allowing for continued exploration of new SE Santa
Rosa sites. The ROV was first deployed at South Santa Rosa at 0800 and conducted four dives with
14 transects of 15-minute duration at four different localities at depths of 95m, 105m, 85m and 90m..
Many corals were observed, several at densities consistent with Coral Gardens (1/m2 over distances of
at least 100 m) (OSPAR 2010). There was some noticeable injury to gorgonians from zooanthids,
some toppled colonies were documented, as well as two white nudibranchs, and a crab photographed
utilizing sponges. These dives also documented several ledges and uplifted shelves that made great
coral habitat. Fish documented on these dives included two cowcod, a wolf eel, and many rockfish.
The last dive of the day had good visibility (30 m) at 0200. During dive operations there was one
ROV power outage, however, the team recovered from this within 2 min. The main pressure balance
oil filled junction was still taking in air, but not as much as previous days, though the piston bottomed
out each dive. The use of HMIs was abandoned. Weather deteriorated throughout the day.

August 4, 2016. Deployed ROV at South Santa Rosa at 0800. ROV Beagle completed dives over
areas that had previously been mapped with backscatter and contained substantial hard-bottom
habitats. One dive started at 85 m, and another dive at 110 m. Conducted four transects of 15-minutes
duration near South Santa Rosa during these two dives. A few potential coral gardens were identified,
but several of these showed signs of injury and yellow zooanthid overgrowth. Then the ship moved to
220 m to collect two live Acanthogorgia sp. colonies. The ROV camera flooded with oil and as a
result the first attempt was aborted. The ROV team then replaced the flooded HD camera with a Sidus standard definition video camera and finished the job. The second attempt resulted in the collection of two Acanthogorgia colonies. Upon successful collection of these colonies, the ROV was recovered and back aboard by 1500. The NOAA Ship Shearwater transited to Ventura Harbor and arrived at 1700.

August 5, 2016. In an effort to further the outreach efforts of the expeditions, VIPs Boltz, Hannah, Teplitz, Ledvina, Graham, Chacin, Robertson, and MARE Director of Donor Relations Phil Stevens, boarded the ship by 0800, and departed for Anacapa Island to explore the Anacapa/Footprint essential fish habitat (EFH) by 0900. The team deployed the ROV at Footprint and conducted an approximately two hour dive up to the NMFS sled, then moved to the lee side of Anacapa, near the net in order to let the VIPs operate the ROV under supervision of the ROV team. Each guest steered the ROV for 4-5 min, which received an enthusiastic response. The NOAA Ship Shearwater returned to Ventura by 1700 to drop off the VIPs, and then the vessel returned to Santa Barbara for its next expedition.

Appendix B: Individual temperature logger site information, images and data.
Shallow target: Loggers B (Star-Oddi logger, silver) and P (Hobo logger, black)
Site: AI-1
Line: 100
Depth: 21 m
Latitude: 34.017364
Longitude: -119.440728
Deployment Method: Shipside
Deployment Date: November 12, 201515

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United States Department of Commerce
Wilbur Ross
Secretary of Commerce
National Oceanic and Atmospheric Administration
Benjamin Friedman
Deputy Under Secretary for Operations
and Acting Administrator
National Ocean Service
Russell Callender
Assistant Administrator

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2021-03-10T21:24:06-08:00June 29th, 2016|research|

April 2016 – It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness


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It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness

Dirk Rosen

Marine Applied Research and Exploration (MARE) Richmond, California, USA

dirk@maregroup.org

Andrew Lauermann

Marine Applied Research and Exploration (MARE) Eureka, California, USA

andy@maregroup.org

April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 157

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

Abstract— California implemented the State’s first network of Marine Protected Areas (MPAs) within the nearshore waters of the northern Channel Islands in 2003. These protections serve as a tool to help ensure the long-term sustainability of marine populations and act as a living laboratory to better understand outside impacts on marine life. California’s network operates synergistically to meet the objectives that a single reserve might not. In 2006 and 2007, NOAA expanded this network of thirteen MPAs into the Channel Islands National Marine Sanctuary’s deeper waters, at the time, making them the largest integrated system of MPAs of the continental United States. Historically, marine habitats around the Channel Islands were well surveyed by scuba divers to a depth of 20 meters, but the deeper waters remained poorly studied. Together, the California Department of Fish and Wildlife, the Channel Islands National Marine Sanctuary and Marine Applied Research and Exploration (MARE) developed a long-term Remotely Operated Vehicle (ROV) program to monitor the changes these MPAs show over time. ROV configuration, survey design and protocols, as well as data post processing and analysis techniques, were developed to specifically evaluate how marine populations respond to the establishment of a network of MPAs.

To capture the ecological condition of Channel Islands MPAs at the time of implementation, the ROVs were configured to capture both fish and invertebrate data concurrently. Each ROV was equipped with both forward and downward facing video cameras, which provided a continuous view in front of and below the ROV. Ranging sonars aligned with both video cameras were used to calculate video transect width and an ultra-long baseline tracking system was used to calculate transect length and geo-reference the imagery. This allowed us to calculate species densities and relative abundance. Oceanographic parameters were collected by Sea-Bird conductivity, temperature, depth and dissolved oxygen sensors. Stereo video cameras were recently added for accurate sizing of fish and invertebrates.

ROV survey sites were initially identified with acoustic bottom maps and then confirmed with exploratory ROV dive surveys. A total of eighteen potential sites were evaluated, with ten being selected for continued monitoring (five site pairs). Inside-outside site pairs were selected for long-term

survey based upon similarity in the types and amounts of rocky substrate present, proximity to one another, and depth. The same ten sites were surveyed annually from 2005-2009, providing a solid baseline for assessing changes in marine populations. Analysis of this data showed little if any change in densities of rockfish species targeted by the commercial and recreational fisheries. In 2014 and 2015, MARE returned to re-survey the same ten historical sites. Preliminary analysis of the 2014 and 2015 data indicates that many of these rockfish species have shown a dramatic increase when compared to baseline densities inside and outside the reserves.

California has now expanded upon this network, bringing its total to 124 MPAs, comprising 16% of states waters along its 1,100 mile coastline. This makes California’s network one of the world’s largest established MPA networks—but not without controversy. Fishermen, stakeholders and marine managers vary in how they embrace network benefits to marine populations and the economic communities that depend on them. Over 65% of California’s MPA protection falls within water depths exceeding 20 meters. Understanding how these deepsea ecosystems respond to a network approach of protection is critical in evaluating not only the effectiveness of California’s MPAs, but also for understanding the spatial and temporal scale at which these networks respond. The positive change in rockfish abundance currently observed at the Northern Channel Islands provides the first opportunity to test the effect networked MPAs have on local populations, and how these areas work cooperatively to rebuild and protect critical marine populations.

Keywords—MPA; ROV; marine protected area; assess MPA effectiveness; MARE; remotely operated vehicle; spillover; network effect;

INTRODUCTION  In early 2003, just prior to the implementation of the Channel Islands Marine Protected Areas (MPA) network, NOAA and the California Department of Fish and Wildlife (CDFW), invited Channel Islands National Marine Sanctuary (CINMS) researchers and other interested parties to a workshop in Santa Barbara, California. An exhaustive record of all research undertaken in the CINMS had been compiled,and was provided to all participants prior to the workshop. After encouragement to partner on research and economize and share data and ship time, the group was split into various break-out groups. One of the groups, the deep subtidal group, noted that one of the biggest data gaps in the CINMS was biological and habitat data below diver depths (18 m or 60 feet). The need for deep water data within the CINMS initiated a new partnership to fill this data gap between a state agency and a startup NGO.Working together, CDFW and Marine Applied Research and Exploration (MARE) cooperatively deployed remotely operated vehicles (ROVs) into the deep waters (>20 m) inside and outside of the soon-to-be established marine reserves. CDFW led a group to develop ROV methods and protocols, based upon accepted diver protocols and ROV protocols used in other areas. The ROV data collection and post processing methods were field tested and honed in the CINMS in 2003 and 2004. Sampling was conducted at 18 prospective sites across the four northern Channel Islands (San Miguel, Santa Rosa, Santa Cruz and Anacapa Islands), including sites which would extend existing diver survey sites into much deeper water. In 2005, ten sites were permanently selected for monitoring and surveyed annually from 2005-2009, creating the baseline for monitoring change during future ROV surveys. In 2014 and 2015, five years after the initial baseline period, we returned again to complete two more annual surveys of each of the ten sites. Preliminary results for all seven years of surveys are presented here. Detailed analysis of this recently post-processed data is ongoing, but initial results indicate a positive change in species densities over time.

EQUIPMENT 

    • The ROV benthic fish and macro invertebrate surveys began with the CDFW observation class ROV Bob, a Phantom HD2+2 built by Deep Ocean Engineering and modified by CDFW. In 2008 the more capable ROV Beagle, also built by Deep Ocean Engineering, and modified by MARE based upon lessons learned, was brought online, and began performing Channel Islands MPA surveys in 2009. Both ROVs have in excess of 91 kg (200 lbs) of forward bollard pull thrust, enabling maneuverability in heavy currents at depth while pulling their umbilicals through the water.

ROV Bob

ROV Bob was equipped with three color standard definition cameras and rated to 1,000 feet (300m) deep. Lighting was provided by 3 x 150 Watt Tungsten Halogen lights. The primary data collection cameras were aligned forward and downward facing, overlapping just slightly in field of view. The remaining camera was pointed aft, behind the ROV. All video recordings were linked using UTC timecode recorded as a video overlay and recorded on an audio track for easy extraction during post-processing.

ROV Bob was also equipped with two sets of parallel lasers, three sonars, and a location tracking system. The parallel

lasers were set with a 10 cm spread and oriented to be visible in the field of view of the primary forward and downward facing cameras. These lasers provided a scalable reference of size when reviewing the video. The two ranging sonars, also aligned with the forward and downward facing cameras, helped us maintain a constant height off the bottom and were used to calculate the area covered [1]. In areas with low visibility, an Imagenex sector scan sonar was used to navigate hazardous terrain. Sonar data were recorded at one second intervals along with UTC timecode. A Trackpoint II ultrashort baseline tracking system was used to obtain locational subsea position of the ROV with UTC timecode which was recorded every 2 seconds.

ROV Beagle

ROV Beagle is equipped with seven cameras, including five standard resolution cameras, one high definition (HD) video camera, and one HD still camera, and rated to 3,280 feet (1,000m) deep. Lighting is provided by 2 x 200 Watt HMI lights and 3 x 150 Watt Tungsten Halogen lights. Beagle’s primary data collection cameras were aligned forward and downward facing, overlapping just slightly in field of view. Both the HD still and HD video cameras were aligned forward facing. Two of the remaining cameras (both aligned forward facing) were used to capture stereo imagery, enabling us to collect highly accurate size and distance measurements [2]. The remaining camera was oriented aft. All video and still images were linked using UTC timecode recorded as a video overlay or using the camera’s built-in time stamp. ROV Beagle is also equipped with two sets of parallel lasers, three sonars, a Sea-Bird CTD with a dissolved oxygen sensor, and a tracking system. The parallel lasers were set with a 10 cm spread and oriented with the forward and downward facing cameras. The two ranging sonars, also aligned with the forward and downward facing cameras, helped us maintain altitude off the bottom and were used to calculate the area surveyed [1]. In areas with low visibility, a Blueview multibeam sonar was used to navigate hazardous terrain. Sonar and CTD data were recorded at one second intervals along with UTC timecode. A Trackpoint III ultrashort baseline tracking system was

Site and Survey Line Selection

Where Multibeam or sidescan mapping bathymetry was available, eighteen potential study areas were selected as potential long-term monitoring sites based on apparent rocky habitat. Following the initial two year exploratory phase, six MPAs and four reference areas (5 pairs) were selected for long-term monitoring. Four no-take State Marine Reserves (SMRs) were paired with four fished sites of similar habitat and close proximity; one SMR was paired with a State Marine Conservation Area (SMCA) where limited take is allowed. The selected sites are: Anacapa Island SMR and SMCA, Gull Island SMR and East Point, Carrington Point SMR and Rodes

Reef, South Point SMR and Cluster Point, and Harris Point SMR and Castle Rock (Figure 1).

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Figure 1. Ten ROV survey site locations that were sampled annually from 2005 through 2009 and in 2014 and 2015.

Within rocky habitats, both inside and outside of the MPAs, data collection was focused in defined sampling sites for use in monitoring changes in species density over time. At each location, a 500 m wide rectangular survey site was placed over the prominent rocky habitat. Each survey site was placed perpendicular to the prevailing bottom contours and spanned the target depth range of 20 to 80 meters. Using a stratified random approach, 500 m long transects, which spanned the width of the site, were selected each sampling year. The number of lines selected was determined based on the amount of rocky substrate present within each site, with the goal to collect a total of at least 3.5 linear km of rocky or mixed rock and sand habitat.

ROV Sampling Operations

At each site, the ROV was flown along the pre-planned survey lines, maintaining a constant forward speed and direction within ± 10 m of the planned survey line. It was imperative that the ship be within 35 m of the ROV position at all times to avoid pulling the ROV off transect. To stay on transect, the ROV pilot and ship captain used real-time video displays of the location of the ship and the ROV, relative to the planned survey line. A consistent transect width, as calculated from the forward camera’s field of view, was achieved using the ranging sonars to maintain a constant viewing distance from the substrate.

ROV Positional Data Post-processing

An acoustic tracking system was used to calculate the position of the ROV relative to the ship. ROV position was calculated every two seconds and recorded along with UTC timecode using navigational software which also integrated GPS position to provide real-time ROV position on the seafloor. Following the survey, the ROV position data was processed to remove outliers and data anomalies caused by acoustic noise and vessel movement, which are inherent in these systems [1]. In addition, deviations from sampling protocols such as pulls (ROV pulled by the ship), stops (ROV stops to let the ship catch up), or loss of target altitude caused by traveling over backsides of high relief structures, were identified in the data and excluded from calculations of fish species density.

Substrate and Habitat Post-processing

All video collected was reviewed and substrate types were classified independently as rock, boulder, cobble, gravel, sand, or mud using a method developed by Green et al. [3]. Each substrate type was recorded as discrete segments by entering the beginning and ending UTC timecode. Each substrate type was recorded independently, often resulting in overlapping segments of substrates. These overlapping substrate segments allowed us to identify areas of mixed substrate combinations along the survey line.

After the video review process, the substrate combinations were combined to create three independent habitat types: hard, soft, and mixed habitats. Rock and boulder were categorized as hard substrate types, while cobble, gravel, mud, and sand were all considered to be unconsolidated substrates and categorized as soft. Hard habitat was defined as any combination of the hard substrates, soft habitat as any combination of soft substrates, and mixed habitat as any combination of hard and soft substrates.

Finfish Enumeration

After completion of video review for habitat and substrate, all video was processed to estimate finfish and macro- invertebrate distribution, relative abundance, and density. During three separate viewings of the video, finfish and macro-invertebrates were classified to the lowest taxonomic level possible. Observations that could not be classified to species level were identified into a species complex, grouped based on morphology, or recorded as unidentified. During video review, both the HD video and HD still imagery were used to aid in species identifications. Each fish or invertebrate observation was entered into a database along with UTC timecode, taxonomic name/grouping, sex/developmental stage (when applicable), and count. For fish only, size was estimated using the two sets of parallel lasers as a gauge. When applicable, estimates of total length were recorded with each fish observation. All clearly visible finfish were enumerated from the video record .

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Figure 2. Typical video post-processing station.

METHODS

Data Analysis

Fish density transects were calculated using the entire forward camera’s horizontal field of view at the mid-screen. A two-step approach was used to calculate fish transects. First, the usable portions of each survey line were divided into 25 m2 segments (subunits). Each subunit’s total percent hard and/or mixed habitat was then calculated and those with percentages below 50% hard or mixed habitat were removed. Next, the remaining subunits were concatenated into 100 m2 transects (four sequential useable 25 m2 subunits) for use in density calculations. One spacer subunit was discarded between each transect to minimize bias of contiguous transects (spatial autocorrelation). Using this method of post- stratification generates hard substrate transects without the loss of rock/sand interface habitat, which may be important to some species.

For the purposes of this paper, no invertebrate results will be reported. Only five fish species are presented and include: gopher rockfish (Sebastes carnatus), copper rockfish (Sebastes caurinus), vermilion rockfish (Sebastes miniatus), lingcod (Ophiodon elongates), and California sheephead (Semicossyphus pulcher). These five species were selected based on their distribution across all sites, abundance at our survey depths, and their value to commercial and recreational fisheries; thus these species may get the most benefit from protection.

From the ten sites surveyed, only the four SMR and fished reference site pairs will be presented here. The SMR and SMCA site pair results will not be included at this time. All transect data for each site and species have been grouped into either baseline data (2005-2009) or monitoring data (2014- 2015). For each site and year, a total of 50 randomly selected transects were used to calculate densities for all five species. Descriptive statistics were calculated for each site and grouping (baseline vs monitoring).

RESULTS 

From 2005 to 2009, all eight paired sites were sampled annually using an ROV. Over 300 km of video transects were collected, post-processed, and archived. Annual sampling levels were similar and averaged 62 linear km of transects per year (SD = 5.949 km; Table 1). After analysis of the video collected during the baseline period (2005-2009), a total of 4,799 fish were identified as one of the five species presented here (average of 960 total fish per year; SD = 180). After processing video for 2014 and 2015, a total of 5,192 fish were counted for both years combined for all five species combined.

Table 1. Annual survey totals (total kilometers, total hectares and total fish counts for all five species presented) at the four combined reserve sites and four combined fished sites from 2005 to 2009 and 2014 to 2015.April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 160

The average densities for all fished sites and all reserve sites for each survey year are shown in Table 2. Overall densities (total species count/total survey area for combined reserve and fished sites) showed little change throughout the baseline years (2005-2009). In 2014 and 2015, increases in average density for gopher, copper, and vermilion rockfish, as well as lingcod and California sheephead were observed. These averaged densities across all site types (reserve and fished), show that reserve sites had higher densities than the fished sites for each of these five species in 2014 and 2015.April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 161 April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 162

Table 2. Average densities at fished and reserve sites for each of the five species during the baseline period (2005-2009) and during the first long-term monitoring surveys of the same 8 sites (2014 & 2015).

Mean densities for each species at fished and reserve sites by survey site and survey period (baseline and long-term monitoring) are shown in Figure 3. Mean densities for the 2014 and 2015 survey years were higher than the mean densities during the baseline period for all species at both fished and reserve sites at all site pairs. Densities were mostly higher at all reserve sites, when compared to their fished reference sites, for all site pairs and species during the baseline period with the exception of CA sheephead at the Gull Island SMR and Carrington Point SMR site pairs. California sheephead densities at these two site pairs were higher in the fished sites compared to reserve sites for the baseline years.

In 2014 and 2015, densities at the reserve sites were higher than those at fished sites for every site pair except the Carrington Point SMR site pair. At Carrington Point in 2014- 2015, the three rockfish species, as well as lingcod, had lower densities at the reserve site than in the fished reference site. California sheephead were the exception and showed higher densities in 2014-2015 in the reserve site, when compared to the fished reference site.

When comparing differences in species density over time or between fished and reserve sites, copper and vermillion rockfish show the biggest changes. Copper rockfish densities at the Gull Island SMR site jumped from 0.08 fish/100 m2 (SE

Fished Reserve

2014-2015, a difference of 1.47 fish/100 m2. There was a 1.41 fish/100 m2 difference in copper rockfish densities between the fished and the reserve site as well. Vermillion rockfish saw similar differences in densities between the fished and the reserve site at the Gull Island SMR pair, with the reserve site density being 1.43 fish/100 m2 higher than the fished reference site.

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Figure 3. Comparison of mean density (with standard error) between fished and reserve site pairs for all five species during the baseline and the first long- term monitoring survey.

DISCUSSION

At the Carrington Point SMR site pair, copper rockfish had a

1.13 fish/100 m2 increase in density from the baseline to the 2014-2015 surveys. This increase put the fished site density

0.63 fish/100 m2 above the density at the reserve site for 2014- 2015 surveys.

Vermillion rockfish at the San Miguel SMR site pair had the biggest differences in densities both between sites and between years. The reserve site increased from 0.968 fish/100 m2 (SE = 0.092) in 2005-2009 to 2.54 fish/100 m2 (SE =

0.357) in 2014-2015, a difference of 1.57 fish/100 m2. Density of vermillion rockfish at the reserve site in 2014-2015 was also much higher than the fished site (0.4 fish/100 m2; SE = 0.09) at the San Miguel SMR site pair, with a difference of

2.14 fish/100 m2.

Preliminary results suggest that for all five species presented, the overall mean densities have increased notably since the baseline period (2005-2009). This is in contrast to the baseline period, where during the five years of survey, no prominent change in mean densities was observed. For four of the five species presented (gopher rockfish, copper rockfish, vermilion rockfish, and lingcod), densities have increased substantially since the baseline period (Table 2). The increase observed for these four species during the 2014 and 2015 survey seasons suggests that there was likely a successful recruitment event for the three rockfish species and lingcod. California sheephead also showed a net increase in overall density since the baseline period, but not as substantial as rockfish and lingcod.

At Gull Island SMR and Harris Point SMR, mean densities show major increases since the baseline surveys at the two reserve sites, when compared to the fished reference sites. At these two study areas, the relatively large increase in species density inside the reserve sites compared to the fished sites may indicate that the MPAs are, at least in part, driving this growth.

In contrast, at the Carrington Point SMR, all species seem to be more abundant inside the fished reference site, with the exception of California sheephead, which show a stronger increase in the reserve site. The drastic increase in species density within the fished site was an unexpected result and it is not clear what might be driving it.

As the data presented has not undergone rigorous analysis yet to account for depth, habitat and fishing pressure differences at the individual site level, results must be interpreted as preliminary. The changes in mean densities for the five species presented do, however, indicate an overall increase in density for these species at all sites. Determination of an MPA effect on rebuilding fish populations around the Channel Islands will require continued monitoring to track trends over time.

We plan to return to the Channel Islands sites in 2017, to repeat the surveys at our ten historical sites. This and future site surveys should allow us to identify any new trends to fish and invertebrate densities over time.

ACKNOWLEDGMENTS

MARE would like to thank the following agencies and organizations for supporting this project:

California Department of Fish and Wildlife, California Coastal Conservancy, California Ocean Science Trust, the Channel Islands National Marine Sanctuary, the National Oceanic and Atmospheric Administration, and The Nature Conservancy.

MARE would also like to thank the following sponsors for supporting this project:

California Ocean Protection Council, the Paul M. Angell Family Foundation, Baum Foundation, Bonnell Cove Foundation, HRH Foundation, Dirk and Charlene Kabcenell Foundation, National Fish and Wildlife Foundation and the Resources Legacy Fund.

REFERENCES

  1. K. Karpov, A. Lauermann, M. Bergen, and M. Prall, “Accuracy and precision of measurements of transect length and width made with a remotely operated vehicle,” Marine Technical Science Journal 40(3), 2006, pp. 79–85.

  2. M. Bower, D. Gaines, K. Wilson, J. Wullschleger, M. Dzul, M. Quist, and S. Dinsmore, “Accuracy and precision of visual estimates and photogrammetric measurements of the length of a small-bodied fish. North American Journal of Fisheries Management”, 2011, 31(1): pp. 138-143.

  3. Greene, H.G., M.M. Yoklavich, R.M. Starr, V.M. O’Connell, W.W. Wakefield, D.E. Sullivan, J.E. McRea Jr., and G.M. Cailliet, “A classification scheme for deepseafloor habitats,” Oceanologica Acta 22(6), 1999 pp. 663–678.

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2021-03-10T21:27:59-08:00April 18th, 2016|research|

June 2015 – A COMPARATIVE ASSESSMENT OF UNDERWATER VISUAL SURVEY TOOLS:

NOAA Technical Memorandum NMFS

A COMPARATIVE ASSESSMENT OF UNDERWATER

VISUAL SURVEY TOOLS:

RESULTS OF A WORKSHOP AND USER QUESTIONNAIRE

JUNE 2015

Mary Yoklavich
Jennifer Reynolds
Dirk Rosen

NOAA-TM-NMFS-SWFSC-547

U.S. DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
National Marine Fisheries Service
Southwest Fisheries Science Center

NOAA Technical Memorandum NMFS

The National Oceanic and Atmospheric Administration (NOAA), organized in 1970,
has evolved into an agency which establishes national policies and manages and
conserves our oceanic, coastal, and atmospheric resources. An organizational
element within NOAA, the Office of Fisheries is responsible for fisheries policy and
the direction of the National Marine Fisheries Service (NMFS).
In addition to its formal publications, the NMFS uses the NOAA Technical
Memorandum series to issue informal scientific and technical publications when
complete formal review and editorial processing are not appropriate or feasible.
Documents within this series, however, reflect sound professional work and may
be referenced in the formal scientific and technical literature.
SWFSC Technical Memorandums are accessible online at the SWFSC web site
(http://swfsc.noaa.gov). Print copies are available from the National Technical
Information Service, 5285 Port Royal Road, Springfield, VA 22161
(http://www.ntis.gov).

A COMPARATIVE ASSESSMENT OF UNDERWATER

VISUAL SURVEY TOOLS:

RESULTS OF A WORKSHOP AND USER QUESTIONNAIRE

Mary Yoklavich 1

, Jennifer Reynolds 2

, and Dirk Rosen 3

1
Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine
Fisheries Service, NOAA, 110 Shaffer Road, Santa Cruz, CA 95060
2
School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, P.O. Box

757220, Fairbanks, AK 99775-7220

3
Marine Applied Research and Exploration, 1230 Brickyard Cove Road #101,

Richmond, CA 94801

June 2015 - A COMPARATIVE ASSESSMENT OF UNDERWATER VISUAL SURVEY TOOLS: 164

NOAA-TM-NMFS-SWFSC-547

U.S. DEPARTMENT OF COMMERCE
National Oceanic and Atmospheric Administration
National Marine Fisheries Service
Southwest Fisheries Science Center

A Comparative Assessment of Underwater Visual Survey Tools:

Results of a workshop and user questionnaire

Mary Yoklavich1

, Jennifer Reynolds2

, and Dirk Rosen3

1 Fisheries Ecology Division, Southwest Fisheries Science Center, National Marine
Fisheries Service, NOAA, 110 Shaffer Road, Santa Cruz, CA 95060
2 School of Fisheries and Ocean Sciences, University of Alaska Fairbanks, P.O. Box

757220, Fairbanks, AK 99775-7220

3 Marine Applied Research and Exploration, 1230 Brickyard Cove Road #101,

Richmond, CA 94801

EXECUTIVE SUMMARY:

Visual surveys of seafloor habitats and associated organisms are being used more commonly in marine science, and yet researchers and resource managers
continue to struggle in choosing among available underwater tools and technologies. In this report, we present the results of a comprehensive questionnaire and corresponding workshop that address the capabilities, limitations, operational considerations, and cost for five mobile, visual tools used in survey mode: remotely operated vehicles (ROV); autonomous underwater vehicles (AUV); human-occupied vehicles (HOV); towed camera sleds (TCS); and human divers (scuba). These tools were considered specifically in the context of their use during standardized surveys of benthic organisms (i.e., fishes, megafaunal invertebrates) and their seafloor habitats.
A broad group of marine scientists, engineers, resource managers, and public policy experts from government, non-government, and academic institutes responded to the questionnaire (n = 116) and attended the workshop (n = 48). Most participants had five or more years of experience using the various survey tools, primarily to improve abundance estimates for managed species in untrawlable habitats, to evaluate species-habitat interactions, to ground truth geophysical mapping, and to monitor performance of marine protected areas.Cost was identified as the primary consideration when selecting a survey tool.

The operating limitations of the survey tool, the organisms and habitats of interest, and the availability of the tools and support vessels all are important criteria when evaluating cost and benefits among tools. Examples of such trade-offs include:

o Cost and complexity of the vehicle and the field operations (including size of the support vessel) increase with the depth of the survey.

o ROVs emerge as the most common compromise among functionality, cost, and availability, but can have problems with tether management that may lead to behavioral changes of targeted species, habitat disturbance, and vehicle entanglement or loss.

o Surveys of diverse communities in complex environments, or studies requiring minimal disturbance to the behavior of the organisms, are best conducted with HOVs (>30 m depth) and scuba (<30 m depth), regardless of cost.

o TCS and some AUVs are relatively inexpensive tools to use for assessment of habitats (often providing high-resolution images), but are less effective in rugged terrain and have limited or no capabilities to sample seafloor macrofauna. From questionnaire responses and workshop discussions, some practical guidance on what is needed to advance the use of visual survey tools and improve data collection for a variety of science and management applications includes these highlights:

o A long-term commitment to fund visual surveys for research purposes is needed in order for these tools and the resultant data to be useful in effective management of marine resources.

o The marine science community is seriously challenged by the lack of visual survey tools available to address our mandates. The most conspicuous example is that small, reliable HOVs are no longer available to conduct research on the U.S. continental shelf and slope.

o A foremost misconception regarding the use of visual survey tools is that all tools are of equal value for any particular study or circumstance. Instead, tool selection should be optimized for survey conditions and objectives.

o There is a need for survey vehicles that are designed to perform optimally in rugged terrain and strong currents, and to collect voucher specimens for species
identification.

o There are limited options when matching the capabilities of a support vessel to the survey tool. For example, moderately sized ships with dynamic positioning systems and specialized cranes are needed to effectively operate some vehicles (e.g. HOVs and larger ROVs).

o Mapping the sea floor, particularly in areas where fisheries science and ecosystem management will benefit, is needed for efficient and effective survey design and monitoring using these visual tools. Interpretation of maps of seafloor characteristics requires visual ground truthing.

ACKNOWLEDGEMENTS:

We thank those who responded to our lengthy questionnaire and participants of the workshop. We thank Lisa Krigsman (NMFS SWFSC) and Tom Laidig (NMFS SWFSC) for their assistance in summarizing and visualizing information for this report and for help in convening the workshop. Many thanks to the Monterey Bay Aquarium Research Institute and Moss Landing Marine Laboratories for serving as workshop venues. This work was co-sponsored by
NOAA West Coast and Polar Regions Undersea Research Center, NOAA Fisheries Advanced Sampling Technology Working Group, and California Ocean Science Trust. Thanks to several undersea industry vendors for sponsoring the evening social event.

Table of Contents
EXECUTIVE SUMMARY …………………………………………………………………………………………………………………….2
ACKNOWLEDGEMENTS……………………………………………………………………………………………………………………3
INTRODUCTION………………………………………………………………………………………………………………………………..5
THE WORKSHOP QUESTIONNAIRE………………………………………………………………………………………………..5
The respondents ……………………………………………………………………………………………………………………………………. 7
Survey tools being used ………………………………………………………………………………………………………………………….. 7
Costs of the survey tools……………………………………………………………………………………………………………………….. 10
Specifications for surveys and the tools…………………………………………………………………………………………………… 13
Reasons for tool selection……………………………………………………………………………………………………………………… 15
Future considerations…………………………………………………………………………………………………………………………… 17
Improvements to tools………………………………………………………………………………………………………………………. 17
Future applications …………………………………………………………………………………………………………………………… 18
Guidance to managers, operators, field scientists…………………………………………………………………………………. 22
Research priorities ……………………………………………………………………………………………………………………………. 24
Gaps in capability and availability ……………………………………………………………………………………………………….. 24
Innovations………………………………………………………………………………………………………………………………………. 25
THE WORKSHOP …………………………………………………………………………………………………………………………….26
Tradeoffs in tool capabilities………………………………………………………………………………………………………………….. 27
Tradeoffs in tool applications…………………………………………………………………………………………………………………. 29
Stock assessments…………………………………………………………………………………………………………………………….. 29
Species-habitat associations ………………………………………………………………………………………………………………. 31
Marine protected areas …………………………………………………………………………………………………………………….. 31
Impact to habitats…………………………………………………………………………………………………………………………….. 32
Emerging technologies………………………………………………………………………………………………………………………….. 32
REFERENCES……………………………………………………………………………………………………………………………………34
APPENDICES ……………………………………………………………………………………………………………………………………35
Appendix 1: Specifications of tools…………………………………………………………………………………………………………. 35
Appendix 2:
Workshop participants………………………………………………………………………………………………………………. 43
Workshop vendors……………………………………………………………………………………………………………………. 44

REFERENCES 32

INTRODUCTION
Visual surveys of seafloor habitats and associated organisms are being used more commonly in marine research and resource management. Results of such surveys are being used to improve stock assessments and provide fishery-independent abundance estimates; characterize fish and habitat associations; groundtruth geophysical mapping of the seafloor; quantify diversity and structure in marine benthic communities; identify impacts of human
activities; delineate and monitor marine protected areas. However, the cost and capabilities of the tools required for such surveys range widely, and matching research and management needs with these rapidly evolving tools and technologies can be a complex task. Prior working groups have addressed related topics (Somerton and Glenhill 2005; DFO 2010; Goncalves et al. 2011; Harvey and Cappo 2001), as did two more recent workshops focused on visual
methods to assess groundfish species (Green et al. 2014) and undersea imaging as part of a benthic monitoring strategy (New Jersey Sea Grant 2014). The outcome of those discussions did not include direct comparisons or guidance on choosing among the tools available for visual surveys. Researchers and managers continue to struggle with this issue.

To assist researchers and resource managers in their choice of underwater vehicles, we first developed an online questionnaire directed at the capabilities, limitations and gaps, operational considerations, and cost of technologies available for visual surveys of benthic marine communities. This questionnaire was distributed to a broad group of marine scientists, engineers, and managers that either use visual survey tools or fund projects that include such
surveys. The results from this questionnaire were used to inform a workshop, for which we convened a smaller group to further examine the uses, specifications, and limitations of underwater visual survey tools. The questionnaire and workshop were focused on the use of mobile tools to visually survey seafloor communities. Our goal was to provide a reference document of practical guidance to field scientists, data analysts, resource managers, and
funding agents on choosing the most effective and efficient visual tools to survey fishes, invertebrates, and the geologic and oceanographic components of seafloor habitats. We also identified gaps and future needs for visual survey tools, and include information on the tradeoff between cost and capability when selecting these tools.

WORKSHOP QUESTIONNAIRE

We developed 217 questions, some of which required multiple-choice answers or essay (free- form) responses. Questions were designed to gather information on the expertise of each respondent, the type of survey tool(s) routinely used, purpose of surveys, rationale for selecting the tool, and specifications (including cost and availability) required for operating the tools. Other questions were intended to solicit suggestions on improving the survey tools to optimize data collection and level of operational satisfaction. Some of the questions were contextual, with one answer prompting a second related response with additional detail. Some
questions were not appropriate for all respondents; we asked that the respondent complete as much of the questionnaire as possible, but leave blank those questions they could not answer. There was an opportunity with almost all questions to comment further. Respondents could pause for multiple, indeterminate amounts of time in order to gather information for their answers without losing previous entries.

The mobile visual survey tools that we considered in the pre-workshop questionnaire were categorized as: remotely operated vehicles (ROV) used in both shallow and deep water; autonomous underwater vehicles (AUV); human-occupied vehicles (HOV); towed camera sleds (TCS); and human divers recording data (scuba). These five survey tools were considered specifically in the context of their use during standardized surveys on the seafloor.
Questions on camera system specifications were included, as this topic can apply to the five visual survey tools. Our interest in these five tools was motivated by the need of management agencies for mobile tools to conduct visual surveys of demersal megafaunal organisms (fishes and invertebrates) and associated habitats (including geologic, biological, and oceanographic features). Terms of reference for the questionnaire did not include acoustic methods (except
as they are integrated into mobile platforms), search and recovery, exploration, fixed-tool systems such as baited camera stations, and seafloor observatories. Post-processing image analysis and database management were not addressed directly in this questionnaire, although many respondents suggested improvements to the processing, archiving, and accessibility of visual data.
We made the questionnaire available online via Survey Monkey (https://surveymonkey.com/).
We invited 168 individuals from a broad group of marine scientists, engineers, and managers across the U.S. to respond. In addition, we asked all of these people to alert others that may be interested in participating. Potential respondents to the questionnaire did not need to be experts on visual surveys, but we targeted users and operators of these tools, engineers, program managers, resource managers, and appropriate funding agents – anyone who
collects visual survey data, makes management or funding decisions about conducting visual surveys, or uses the results of visual surveys in a professional capacity.
The questionnaire was designed to gather information on
• background and expertise of the respondents, relative to their interest in visual survey tools;
• tools currently being used and for what purpose;
• cost to operate the tools;
• necessary specifications of the tools and the surveys;
• gaps in capabilities and availability of the tools; and
• future research priorities and needed technologies

Who were the respondents?

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A total of 116 individuals participated in the questionnaire. Almost 50% of the respondents classified themselves as having expertise related to fisheries science, and 25% were marine biologists or biological oceanographers. The remaining participants represented a diversity of disciplines, including geologic, chemical, and physical oceanography, engineering, survey tool operators, public policy, and resource management. Most respondents (n = 99) had field experience with visual survey tools.

What survey tools are being used and why?

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Respondents were asked to identify their primary and secondary (if applicable) survey tool. ROVs were selected most often as both a primary (40 users) and secondary (13 users) survey tool. TCS and scuba were used as either a primary or secondary survey tool by 34 and 30 respondents, respectively. Human-occupied submersibles (HOV) were used either as a primary or secondary survey tool by 17 participants. Nine respondents used AUVs as a primary or secondary survey tool.

Combining responses on primary and secondary tools, more than 70% of the participants had over 5 years of experience working with the various survey tools.

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Combining the responses from the primary and secondary tool users, most respondents recently used their survey tool > 20 days per year. Scuba and ROVs had the highest rate of use (> 20 days/year), and 2 respondents used scuba, towed cameras, and ROVs in conjunction with each other at shallow depths.

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Combining the responses from the primary and secondary tool users, the main objective for those using a HOV and ROV was to collect data on species-habitat associations and ecosystem relationships. This also was a main objective for many of those using scuba, along with evaluating the effectiveness of marine protected areas (MPA). Several respondents also were using ROVs to groundtruth seafloor habitat maps or evaluate MPA effectiveness. Most respondents that used towed camera sleds were either ground-truthing seafloor habitat maps or studying species-habitat associations and ecosystem relationships. AUVs mainly were used either to map seafloor habitats or to engineer and test new designs for the vehicle. Collecting data for fisheries stock assessments was a main objective of some respondents conducting visual surveys using each of the five categories of tools.

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The cost of survey tools

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Scuba, TCS, AUV, and ROV survey tools largely are owned and operated by the respondents and/or their affiliated organizations. Most HOVs (and some ROVs) are leased or contracted, with the contractor operating the vehicle. A small number of respondents rent and operate TCS or ROVs.

From respondents that own their survey tool, the most common initial purchase cost for scuba was $1,000-5,000 and $5,000-50,000 for a TCS. Purchase cost of an ROV ranged broadly from the price category of $5,000-50,000 to >$1,000,000. AUV prices were similar to that of ROVs. [All costs are in 2011 dollars.]

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From respondents that own their survey tool, most scuba users spent < $500 to maintain their equipment (including insurance) per year, though a few spent up to $10,000. TCS users usually spent $500 – $5,000 on maintenance. The cost to maintain an ROV or AUV ranged between $500 and >$50,000 per year.

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Most scuba and TCS users spend <$500/day (24 hr) to deploy, operate, and retrieve their survey gear (not including ship costs). These same activities commonly cost $500-6,000/day when surveying with an ROV. The daily cost to deploy, operate, and retrieve an AUV on average was <$500/24 hrs, but one AUV user reported these costs to be $6,000 – 10,000/day.

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Leased or rented HOVs most commonly cost $6,000-10,000/day to deploy, operate, and retrieve (not including daily ship cost). It typically cost $10,000-15,000/day to deploy, operate, and retrieve leased or rented ROVs.

June 2015 - A COMPARATIVE ASSESSMENT OF UNDERWATER VISUAL SURVEY TOOLS: 174For shallow working depths it appears that the number of ROV users who own this tool equals the number of ROV users who lease/rent. For working in deeper depths (>50m) it appears that more users own, however in very deep depths (>1000m) more people lease/rent, than own.

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What are the specifications for the surveys and the tools?

The responses on specifications of each survey tool were summarized from both primary and secondary tool users. Topics include requirements of personnel, pre- and post-cruise planning, support vessel, survey equipment, data and sample collection, navigation, still and video imagery, lighting, and tool impacts and possible biases. See Appendix 1 for this information.
Most respondents typically survey during daytime regardless of the type of tool. The exception is TCS operators, who responded more often that they work both day and night; this also is the case for some respondents that use ROVs and AUVs. Typical survey speed was lowest with scuba and AUV (0-0.3 m/sec). Survey speed using ROVs and TCS most often was 0.3 – 0.5 m /sec, and HOV users mostly surveyed at the highest speed (0.5-1.0 m/sec). A few respondents use TCS, ROV, and AUV at speeds >1.0 m/sec.

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Scuba users commonly spent less than 4 hours collecting data per day, while operators of the other survey tools most often spent 5-8 hours or more in data collection.

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A straight line was the most common transect type being conducted by most tools. AUVs mostly followed the terrain around objects.

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Reasons for tool selection.
The main reasons for selecting a tool varied by survey tool.

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Respondents provided information on their level of satisfaction with the survey tools in meeting various objectives.

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Most respondents thought that the biggest misconception among field scientists and managers regarding use of visual survey tools is the idea that all tools are created equal.

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Future needs associated with these survey tools

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Improvements to tools

Seventy-one respondents answered questions on improvements to ROV, TCS, HOV, and scuba survey tools. No respondents provided input on improvements to AUVs. Improved camera quality and lighting were the most common responses among all users. The second most common suggestion for improvement was tool specific. TCS and ROV users wanted to see improvement in the quality of the cables. HOV users wanted to see improved battery life and scuba users would like to reduce the amount of bubbles produced by using rebreathers.
Almost all users mentioned the issue of cost and navigation. Number of responses is in parentheses.

Future Applications
Most respondents (70%) anticipate that they will use additional tools and associated data in the future.

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Most respondents anticipated their use of some type of survey tool in the future. AUV, ROV, and TCS were the most likely types of tools to be used.

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Over 50% of the respondents anticipate using visual survey tools and data for additional applications beyond current uses.

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Species habitat associations and ecosystem relationships, fisheries stock assessment, and basic marine biology and ecology were the most anticipated future applications for visual survey tools.

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Other specific applications included:
• Long-term monitoring, detection of change in the environment
• Marine archaeology and forensics
• Temporal observations
• In situ experiments
• Cameras linked to web to collect data from imagery by “citizen scientists”

Nearly 40% of 69 respondents selected cost of using the tool as the biggest issue when selecting a survey tool for future projects. Operating limitations of the tool, organisms of interest, trade-offs among tools, and availability of survey tool and support vessel also were selection criteria for 10-15% of the respondents.

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Guidance to managers, operators, and field scientists Fifty-nine participants provided input on topics that managers should pay more attention to, as relevant to visual surveys. Their main advice to resource managers included:

• Visual surveys can play an important role in improving abundance estimates, especially in habitats that are not easily sampled with conventional gear (such as trawl nets)

• Species-habitat interactions and long-term monitoring of seafloor communities are top research priorities for visual surveys

o Particularly important to use visual surveys for untrawlable habitats, depleted species, marine protected areas, and in support of stock assessments

• A long-term commitment for visual surveys is needed for these data to be useful in effective management of marine resources

• Evaluate survey tools for cost effectiveness, statistical robustness, biases, and implementation of optimal survey designs

• Visual surveys are expensive

o Ensure data are collected and processed efficiently and made available for timely scientific and policy decisions

o Coordinate researchers to conduct cost-effective surveys

o Place more emphasis on publication of survey results

o Resultant data products should be of sufficient quality to support effective policy decisions

• Visual survey technologies are changing and improving at a rapid pace

o Ensure that survey tool operators are adequately instructed on scientific requirements of the surveys

• Mapping of seafloor (particularly at depths 3-20 m and at depths beyond state waters) is needed for efficient survey design and monitoring

• Whatever tool is used, objectives need to be clear and obtainable by the selected tool.

• Video and still imagery provides an archival record that can be used to address future management issue Fifty-eight participants provided input on topics that survey tool operators should pay more attention to. Their main advice to operators included:

• Ensure that the survey tool is appropriate for the objectives of the study

o Optimize tools for the survey conditions

o Listen to the scientist’s needs

o Increase flexibility of on-scene tool modification

• Recognize the limitations of your particular survey tools

o Communicate those limitations to scientist before designing the surveys

o Improve tools for changing needs of the scientists

o Understand biases associated with the survey tool

• Improve quality and usefulness of data being collected

o Quantify area swept

o Quantify avoidance and attraction of target species to the survey tool

o Determine impacts of lighting, noise, disturbance on target organism

o Deliver timely data

o Develop rigorous, repeatable transect methods

o Compile data in geo-referenced databases

• Operator should ask for an evaluation after each cruise Fifty-six participants provided input on what field scientists and survey tool users should pay more attention to.

Their main advice to these groups included:

• Maximize the return on cost of vehicle and ship time:

o Careful planning; define the objective of the survey

o Recognize limitations and capabilities of survey tools

o Include back-up tools and equipment in estimated costs/budget

• Ensure that the survey tool is appropriate for the objectives of the study

o Optimize tools for the survey conditions

o Most shallow-water ROVs working at <200 m depth are underpowered and have difficulty working in currents

o If working in sub-optimal conditions (high currents, low visibility), don’t expect to collect usable data

• Support seafloor mapping initiatives to produce high-resolution bathymetric maps of areas where fisheries science and ecosystem management will benefit

• Improve quality and usefulness of data being collected o Accurate quantification of area swept and size of organisms

o Quantify biases associated with avoidance and attraction of target species to the survey tool

o Assess precision and accuracy associated with the survey data

o Assess assumptions related to the methods being employed

o Share data and metadata o Compile data in geo-referenced databases

o Conduct intercalibration studies among visual survey tools

o Process and deliver timely dataFuture research priorities

Fifty-two participants provided input on research priorities for future visual surveys:
• Coastwide, longterm monitoring of seafloor communities in order to:
o Detect changes over broad spatial and temporal scales
o Determine the nature and extent of impacts to seafloor communities
o Characterize species-habitat interactions; estimates of habitat-specific abundance
o Determine effectiveness of marine protected areas and manage whole ecosystems
o Support stock assessments
• Calibration of survey tools
o Estimates of bias and uncertainty in data from each survey tool
o Standardized field protocols, survey designs, and types of data products
o Spatially specific statistical analyses
o Assess environmental impacts (i.e., noise, lights, actions) of each vehicles
• Increase collections of organisms to verify identifications in visual surveys
• Spatial integration of small-scale surveys with landscape-scale habitats
• Improved data accessibility, including methods to efficiently process, archive, and
access large amounts of visual data
• Increased collaboration among biologists and oceanographers
• Improved scientific discovery with the integration of data generated by heterogeneous visual survey tools
• Increased outreach to ensure distribution of research findings to managers and stakeholder groups

Gaps in Capability and Availability

Forty-seven participants provided input on gaps in the capability and availability of the tools in order to conduct future research, including:
• Small, reliable research HOVs (e.g., Delta) are no longer available
• Long term deployable camera systems (i.e., on benthic landers or AUVs) are not widely available
• Low-light camera systems are not typically available on contracted vehicles
• Some oceanographic hydrodynamic towed platforms exist, but are expensive to purchase and need retrofitting for digital video/still imagery
• Bridge the gap between studio 3D imagery systems and real-life applications
• Data Collection
o Accurate habitat maps over broad spatial scales are not available
o Specimen collection especially in deep water is not easily accomplishedo Need more vehicles designed to perform optimally in rugged terrain and strong
currents
o Difficult to identify and measure species, and determine their age and sex from imagery
o Need USBL system with tunable amplification
o Skilled technical staff are needed to operate tools and to process large amounts of imagery data
• Mismatch in type of available survey tool and support vessel capabilities
o Often need ships with dynamic positioning systems to effectively operate some vehicles
o Scheduling large oceanographic support vessels is often problematic
• Evaluation of impacts of the vehicles (e.g., noise, lights, action) on the habitats and organisms being surveyed has not been determined
• Data processing, archiving, and serving could be integrated into data acquisition software
• Dealing with large quantities of visual data is difficult
• Research programs are not fully committed to ongoing systematic visual survey

Future Innovations

Fifty-nine participants provided input on new capabilities or innovations that could be developed in the near future to reduce survey costs and improve the quality of the data.

Suggestions include:
• improved underwater geo-referencing of data collection
• improved methods to estimate area swept on transects
• improved methods to estimate size of organisms
• improved low light cameras
• improved processing (time and accuracy) of underwater imagery
• rapid counting of targets
• auto-altitude sensor
• smaller vehicle-based dynamic positioning systems as currently used on work-class ROVs
• cheaper/smaller technologies to account for layback of towed vehicles
• USBL systems with “tunable” sound amplification for shallow water work (e.g., so as to not be in violation of the MMPA and ESA threshold of 80 dB when working around marine mammals)
• real-time topside 3D navigation of vehicles using oblique-perspective view in GIS software with multibeam bathymetry basemap• infrared sensors or ultrasonic cameras to survey at night without lights (to study fish
behavior)
• lower power requirements, longer battery/power life; we need a revolution in battery
technology similar to what has occurred in microprocessors and flash memory
• affordable, user friendly, off the shelf stereo video systems
• hybrid ROV’s, that maintain high bandwidth communications and control, but are not
tethered to expensive ships.
• ultra-quiet electric thruster motors
• the Triton 36,000/3 new technology could significantly increase the practicality of HOVs
for deep habitat surveys
• advances in adaptive sampling/behavior of autonomous vehicles
• improved performance and operating cost of laser line scanning
• semi-autonomous vehicles with ‘light’ wire ‘tethers’
• lower cost, lighter weight, shallow water (<100m) visual survey tool deployed from a
low-cost ship of opportunity
• lighter scuba tanks
• improved storage solutions for HD video
• systems that allow easy data archiving and accessibility

WORKSHOP

A 2-day workshop was convened by Jennifer Reynolds, Dirk Rosen, and Mary Yoklavich on 22-23 February 2011 at Monterey Bay Aquarium Research Institute (MBARI), Moss Landing, CA. The visual survey tools and associated methods discussed at this workshop were the same as those considered in the questionnaire: both shallow- and deep-water ROV, AUV, HOV, TCS, and scuba, specifically used in systematic survey mode.

The workshop was attended by 48 marine scientists, engineers, resource managers, and public policy experts representing six NOAA Fisheries Science Centers; NOAA Fisheries Office of Science and Technology and Office of Habitat Conservation Deep-sea Coral Research and Technology Program; NOAA National Ocean Service National Marine Sanctuaries; Bureau of Ocean Energy Management; U.S. Geological Survey; Fisheries and Oceans Canada; Washington (WDFW), Oregon (ODFW), and California Departments of Fish and Wildlife (CDFW); eight U.S. universities; University of Western Australia; four marine
science and technology institutes; and three non-government organizations (see Appendix 2 for list of attendees and affiliations). The workshop agenda included presentations to introduce visual tools and applications, a review and discussion of questionnaire results, and facilitated breakout discussions. An evening social was sponsored by vendors of marine technologies at Moss Landing Marine Laboratories (see Appendix 2 for list of vendors) and a tour of MBARI
was conducted during the workshop

Introductions to the five visual survey tools were presented in a plenary session, followed by a question-answer period,: Imaging AUVs was delivered by Hanumant Singh (Woods Hole Oceanographic Institution) ROVs: a versatile tool for marine scientists was delivered by Dirk Rosen (Marine Applied
Research and Exploration), John Butler (NOAA Fisheries Southwest Fishery Science Center) and Bob Pacunski (WDFW) Mobile underwater survey tools using video: manned submersibles, towed camera systems, critter cameras, and scuba was delivered by Frank Parrish (NOAA Fisheries Pacific Islands Fishery Science Center)
Additional plenary presentations included:

Use of visual surveys to improve stock assessments of demersal species, delivered by Waldo Wakefield (NOAA Fisheries Northwest Fisheries Science Center)
Results from a questionnaire to assess visual tools for surveying seafloor habitats and species, delivered by Mary Yoklavich (NOAA Fisheries Southwest Fisheries Science Center)
The breakout sessions were designed for workshop participants of various expertise and backgrounds to evaluate the survey tools, their applications, and tradeoffs. Session 1 comprised five separate groups, each discussing advantages and drawbacks of one of the five visual survey tools. These groups considered optimal scenarios of operation for each tool, data best collected by each tool, specifications and limitations of the tools, and tradeoffs between cost and benefits. Session 2 comprised five separate groups, each discussing tradeoffs among the tools. Session 3 comprised four separate groups, each discussing the use and tradeoffs of the tools for four applications (i.e., stock assessments; species-habitat associations; marine protected areas; impacts to benthic habitats). An additional breakout group discussed marine engineering and emerging technologies.

Tradeoffs in Capabilities Among Tools

Each tool is associated with a set of benefits and limitations that need to be considered along with the goals and objectives of the survey and the availability funds. As important is the consideration of the survey specifications, such as type of habitat and depth capabilities, required level of resolution in resultant data, and amount of uncertainty (error) that can be tolerated in the data. A matrix to evaluate the survey tools, based on the following attributes, was developed from
the discussions in Break-out Sessions 1 and 2:
• Diversity of observational data types (e.g., counts, behaviors, taxa interactions, habitat associations), determined by the ability to collect data and make changes with some dexterity
• Operational flexibility, considering availability of tool, number of qualified people tooperate and collect data, and availability and type of necessary support vessel
• Operational complexity, considering ability to collect samples, control, maneuverability
• Spatial area covered (number of meters; from discrete to continuous spatial data)
• Taxonomic resolution (identification of species and functional groups)
• Depth of operation (from High=broad range to Low=only shallow)
• Topographic relief (ability to work in complex, rugose habitats)
• Level of risk (considering expense and potential loss of tool)

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To summarize discussions from Break-out Sessions 1 and 2:
• Cost and complexity of the vehicle and operations, and the size of the support vessel,
increase with depth of the survey
o Increased size, complexity, and cost of the vehicle can compromise its
transportability and the ability to operate from a variety of support platforms
• Availability of the tools and support vessels is a major consideration
o The marine research community is in need of small research HOVs to continue
surveys on continental shelf and upper slope (to 500 m depth)
o Researchers often design their surveys to match available tools, rather than select
the best tool for their survey design
• Humans using HOVs and scuba can adapt to changes in survey design at finer
temporal and spatial scales than when using an ROV, AUV, and TCS
• Data from highly diverse communities in highly complex environments or requiring
human observations and no interference from tethers (e.g., in situ behavior of the
organisms) are best collected with HOVs (>30 m depth) and scuba (<30 m depth)
• HOVs do not work well in shallow water (<20 m); strong currents; limited visibility due to
fog (recovery issues) or mud/silt substrata; high seas (limits deployment/recovery)
• ROV and TCS have unlimited bottom time, as they are powered via tether to ship
• ROVs and TCSs can have problems with tether management, leading to habitat and species disturbance, entanglement, and loss of vehicle
• Challenges for small ROVs include: surveying cryptic species, pelagic fishes, and small organisms; operating in high currents and in kelp or eelgrass
• AUV and TCS are useful to groundtruth habitat maps and survey narrow cable routes
• ‘Swimmer’ AUVs can provide broad areal coverage, particularly with multibeam sonar
• ‘Swimmer’ AUVs not particularly suitable to rugged terrain
• Hovering AUVs do not cover large areas, but can provide high-resolution images
• AUVs have limited or no sampling ability, especially of seafloor organisms/habitats
• AUVs are limited by high currents, rugged topography, battery cycle time, and are less flexible to make changes during a mission
• TCS are a relatively inexpensive method for rapid assessment of habitat, however:
o there are operational differences among towed, drift, and drop cameras
o it is difficult to revisit a specific area of interest
o this tool is less effective in rugged terrain
o there are limited sampling capabilities
• Camera-based tools (ROV, AUV, and TCS) lack peripheral vision (rely on 2D images)
• Scuba is useful in shallow, complex habitats, but is usually limited to <30 m depth and relatively calm and clear sea conditions. Diving in remote areas away from decompression facilities and diver fatigue also are limitations to scuba surveys.
• Deciding the required level of identification and quantification of organisms will help in selecting the survey tool:
o Presence/absence data (only need identification of target organisms)
o Relative abundance data (need identification and counts)
o Density data (need identification, counts and estimate of survey effort)
o Total abundance data (need identification, counts, survey effort, and estimate of totalarea)
o Biomass data (need identification, counts, survey effort, estimate of total area, and measurement of targeted organism)

Tradeoffs in Applications of Tools

Discussion in Break-out Session 3 focused on tradeoffs in applying the survey tools to stock assessments, species-habitat associations; marine protected areas; and impacts to benthic habitats. For each application, the groups considered what tools have been used and which ones worked best; what type of capabilities are most important; and what is need to improve the use of the tools.

Application: stock assessments
The minimum needs for using any of the visual survey tools for stock assessments are the ability to:
• Reliably identify target species at life stage of interest
• Develop standardized methods for repeatable surveys over time
• Estimate size composition and survey effort
• Execute a survey design that insures statistical analyses
• Evaluate assumptions and estimate uncertainty
• Recognize and correct for habitat-specific biases in
o Species detection and identification
o Attraction and avoidance to survey vehicle
o Underwater measurements (size of and distance to organisms)
o Habitat selectivity (ability to survey high-relief habitats; deep water; patchy distributions)
• Integrate habitat information on a spatial scale relevant to the stock
o To improve survey design
o To estimate absolute abundance
Data used in stock assessments undergo high levels of scientific scrutiny (e.g., reviews by Center of Independent Experts and Fishery Council committees). There are limited examples of the use of data from visual survey tools in stock assessments, including:
• ROV used to assess California white abalone (Haliotis sorenseni)
• Scuba used in Southeast Region and Pacific Islands to assess reef fishes (Black grouper [Mycteroperca bonaci]; Yellowtail); in Alaska to assess Pacific Herring (Clupea pallasii) eggs; in Alaska and Northeast to assess invertebrates
• An HOV used in Alaska to assess Yelloweye rockfish (Sebastes ruberrimus); in California to assess Cowcod (S. levis)
• A drop camera used in Northeast Region to assess Atlantic sea scallops (Placopecten magellanicus)
• No example of AUV used in stock assessments
A matrix, organized by nearshore/offshore depths and rough/flat substrata, was developed to indicate appropriateness of and issues associated with each survey tool, relevant to their use in stock assessments (X= appropriate tool, with limitations particular to each survey tool noted):

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Application: species-habitat associations

A matrix was developed to characterize the relative magnitude (low, moderate, high) of the following capabilities and considerations, when applying each tool to the study of specieshabitat associations:
• Level of habitat disturbance associated with each tool
• Ability to accurately measure, count, and identify targeted organisms
• Usefulness to measure and map habitats
• Ability to estimate distance underwater
• Ability to georeference data
• Cost of operations/day
• Initial cost of investment
• Amount of training required to operate the tool

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Application: Marine Protected Areas (MPAs)

There are two sets of complementary objectives to consider when selecting a tool to survey MPAs:
• Conservation Objectives: survey a broad suite of species; metrics are abundance, densities, size, presence/absence; requires repeatability on an ecosystem  level
• Fisheries Management Objectives: single species (e.g., data poor taxa); Ecosystembased Fishery Management; metrics are abundance, densities, size, presence/absence, and extent of habitats; requires repeatability on level of habitat-specific species

Survey design for both objectives includes monitoring change (trends) inside and outside the MPAs, and before and after MPA implementation. Issues particularly relevant in making these comparisons include positional accuracy, standardization of survey methods, and changes in technology over time of the surveys. The minimum needs for using any of the visual survey tools to monitor MPAs are similar to those listed for stock assessment applications (see
above).
Application: Impacts to Benthic Habitats
All the visual survey tools have been used by the participants in the breakout session to examine various impacts on benthic habitat, including trawling, cable laying, lost gear, marine debris, offshore infrastructure, and sewage outfalls/outflows. Metrics included change to community structure and rate of recovery from impact. The group agreed that the appropriate use of each tool to assess impacts is dependent on habitat type.
Examples of tools used to assess impacts on benthic habitats include:
• ROV used to assess trawling impacts on the seafloor and to monitor habitat recovery. ROVs were equipped with downward looking video and still cameras with paired lasers, and forward-looking oblique video and still camera with paired lasers.
• ROV used to assess topographic change and biogenic structure associated with fouling.
• A drift camera used to assess topographic change and biogenic structure associated with fouling. The imagery was comparable between ROV and drift camera. The drift camera, once in the water, was easy to use, but the ROV was more functional.
• Scuba was used to remove a large amount of marine debris from an atoll in Hawaii. This task could be done only by divers (area inaccessible to large vessels and gear).
• HOV used to monitor re-growth of coral in the precious-coral fishery. Corals occur in steep areas with high current flow; ROV and AUV were unable to maintain station.
• An ROV was used to look at the impacts of cable laying on sponges and their recovery rate.
• No examples were given for use of an AUV, but future applications were easily envisioned as long as the AUV could be operated at a slow speed and was equipped with oblique cameras.

Engineering and emerging technologies
A Break-out Session comprised almost entirely of marine engineers and designers discussed potential improvements to visual tools, designing and conducting the surveys, and data collection and processing.
The main drivers of change to visual tools include:
• Inexpensive computing with lower power consumption (performance per watt)
• Computer-automated methods, which could be accelerated with input from scientists to algorithms on organism identification

• Real-time modifications based on survey mission and goals
• Some amount of subsea data processing, resulting in less information to transmit and control in real time
To improve the use of these survey tools for all applications, some needs include:
• Higher degree of automation to reduce boat and human costs
• Minimize cost of ship time
• Standardization of high-definition (HD) stereo cameras and data recording, with onscreen overlay
• Improved communication between scientists and engineers (such as occurred in this workshop)
• Engineers and scientists working collaboratively to address best practices for a survey
• Embracing proven new technologies, such as parallel computing
• Hardening the product (equipment, processes, and techniques) for easier field deployment

Emerging technologies that could improve existing survey tools include innovations in:
• Battery technologies (e.g., employing lithium instead of lead acid batteries)
• Communication equipment for data transmission and display
• Low-power components (e.g., LED, optical communications, graphic processing)
• Cloud decentralized data storage and super-computing power
• Computerized scaling and measurements of underwater organisms and other targets
Current challenges to the improvement of underwater science technology:
• Underwater visual tools are custom built, resulting in little opportunity to standardize survey operations
• There seems to be some scientific resistance to auto-identification of organisms
• It has been difficult for engineers to work with mid-career scientists, who don’t want to risk changing from existing survey tools and protocols to new or emerging technologies
• Difficulty in designing and building tools and technologies to the specifications of the scientists, as specifications and goals can be changed mid-project without complete consideration
• Equipment is often used in the field before it is fully developed, which can result in tension between engineers and scientists when things go wrong

REFERENCES

DFO (Department of Fisheries and Oceans). 2010. Proceedings of the workshop to review the assessment protocols on benthic habitat in the Northeast Pacific, March 16-17 2010. DFO Canadian Science Advisory Secretariat Proceedings Ser. 2010.

Goncalves, J.M.S., L. Bentes, P. Monteiro, F. Oliveira, and F. Tempera (Eds.). 2011. MeshAtlantic Workshop Report: Video Survey Techniques. MWR_VST December 2011, University of Algarve, Centre of Marine Sciences, Faro, Portugal. 18 pp.

Green, K., D. Lowry, and L. Yamanaka. 2014. Proceedings of the: Visual survey methods workshop. Report to US-Canada Technical Sub-Committee (TSC) of the Canada-US Groundfish Committee. 79 pp.

Harvey, E.S. and Cappo, M. 2001. Direct sensing of the size frequency and abundance of target and non-target fauna in Australian Fisheries. 4-7 September 2000, Rottnest Island, Western Australia. Fisheries Research and Development Corporation. 187 pp, ISBN 1 74052 057 2.

New Jersey Sea Grant. 2014. Undersea imaging workshop. January 14-15, 2014. Red Bank, NJ. 36 pp.

Somerton, D.A. and C.T. Glenhill (Eds.). 2005. Report of the National Marine Fisheries Service workshop on underwater video analysis. U.S. Department of Commerce, NOAA Technical Memorandum NMFS-F/SPO-68, 69 pp.

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APPENDIX 2. List of workshop participants and vendors.

Participant Names Participant Affiliations

Jim Bohnsack Southeast Fisheries Science Center, NOAA Fisheries
Jim Boutillier Fisheries & Oceans Canada, Pacific Biological Station
Steve Brown Office of Science and Technology, NOAA Fisheries
Ann Bull Pacific Region Office Environment, Bureau Ocean & Energy Management
John Butler Southwest Fisheries Science Center, NOAA Fisheries
Mark Carr University of California Santa Cruz
Dave Christie University of Alaska Fairbanks
Liz Clarke Northwest Fisheries Science Center, NOAA Fisheries
Guy Cochrane U.S. Geological Survey, Coastal & Marine Geology
Mike Donnellan Oregon Department of Fish and Wildlife
Mary Gleason The Nature Conservancy
H.Gary Greene Tombolo Habitat Institute and Moss Landing Marine Laboratories
Churchill Grimes Southwest Fisheries Science Center, NOAA Fisheries
Euan Harvey University of Western Australia
Jim Hastie Northwest Fisheries Science Center, NOAA Fisheries
Jon Howland Woods Hole Oceanographic Institution
Steve Katz NOAA Channel Islands National Marine Sanctuary
Bill Kirkwood Monterey Bay Aquarium Research Institute
Lisa Krigsman Southwest Fisheries Science Center, NOAA Fisheries
Tom Laidig Southwest Fisheries Science Center, NOAA Fisheries
Andy Lauermann Marine Applied Research & Exploration
James Lindholm California State University Monterey Bay
Milton Love University of California Santa Barbara
Andy Maffei Woods Hole Oceanographic Institution
Skyli McAfee California Ocean Science Trust
Bob McConnaughey Alaska Fisheries Science Center, NOAA Fisheries
William Michaels Northeast Fisheries Science Center, NOAA Fisheries
Victoria O’Connell Sitka Sound Science Center
Jeff Ota nVidia Corporation
Bob Pacunski Washington Department of Fish & Wildlife
Frank Parrish Pacific Islands Fisheries Science Center, NOAA Fisheries
Shirley Pomponi Florida Atlantic University / Harbor Branch
Mike Prall California Department of Fish & Wildlife
Jennifer Reynolds University of Alaska Fairbanks
Chris Rooper Alaska Fisheries Science Center, NOAA Fisheries
Dirk Rosen Marine Applied Research & Exploration
Donna Schroeder Pacific Region Office Environment, Bureau Ocean & Energy Management
Hanu Singh Woods Hole Oceanographic Institution
Rick Starr California Sea Grant and Moss Landing Marine Laboratories
Ian Stewart Northwest Fisheries Science Center, NOAA Fisheries
Kevin Stokesbury University of Massachusetts
Charles Thompson Southeast Fisheries Science Center, NOAA Fisheries
John Tomczuk NOAA Ocean Exploration Program
Waldo Wakefield Northwest Fisheries Science Center, NOAA Fisheries
Geoff Wheat University Alaska Fairbanks, Monterey Bay Aquarium Research Institute
Liz Whiteman California Ocean Science Trust
Lynne Yamanaka Fisheries & Oceans Canada, Pacific Biological Station
Mary Yoklavich Southwest Fisheries Science Center, NOAA Fisheries

VENDORS PRODUCT

Deep Ocean Engineering/Falmouth Scientific ROVs
Deep Sea Systems International ROVs
Desert Star Systems Electronic tags; acoustic modems, recorders, and
positioning; scuba systems
Kongsberg Maritime Cameras, lights
Ocean Innovations Underwater equipment and marine technology
Sidus Solutions Cameras, lights

2021-03-10T21:24:48-08:00June 29th, 2015|research|

Jan 2015 – South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m)

South Coast Marine Protected Areas Baseline
Characterization and Monitoring of Mid-Depth Rocky

and Soft-Bottom Ecosystems

(20-350m)

Final Report to California Sea Grant
Project #R/MPA-26A; Grant Number: MPA 10-049

31 January 2015

Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 199

James Lindholm, Ashley Knight, Flower Moye, Alli N. Cramer, Joshua Smith, Heather Bolton, Michael Esgro, Sarah Finstad, Rhiannon McCollough, & Molly Fredle

– Institute for Applied Marine Ecology, CSU Monterey Bay

Dirk Rosen & Andy Lauermann

– Marine Applied Research and Exploration

Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 200

Marine Applied Research and Exploration
320 2nd Street, Suite 1C, Eureka, CA 95501 (707) 269-0800
www.maregroup.org

Acknowledgements

Generous support for this research provided by:

California Ocean Protection Council
California Ocean Science Trust
California Sea Grant (Project No. R/MPA-8; JBL Award No. 09-015)
Undergraduate Research Opportunities Center at California State University Monterey Bay
James W. Rote Professorship of Marine Science and Policy at CSU Monterey Bay
Margolis Foundation
Pacific Life Foundation

Unspecified donors to Marine Applied Research and Exploration
Key field and lab support:

CSUMB Students: Bryon Downey, Devon Warawa, Matthew Jew, Stephen Loiacono,
Jessica Watson, Elizabeth Lopez, Lauren Boye, Emily Aiken, Megan Bassett, Alexandra
Daly, and Danielle Fabian

MARE Staff: Steve Holz, David Jeffrey, AJ Reiter, Yuko Yokozawa, and Rick Botman

Crew of the F/V Donna Kathleen: Tim, Donna & Tyler Maricich

Fish identification and expertise: Dr. Robert Lea

Table of Contents

List of Table and Figures …………………………………………………………………………………… 5
Executive Summary …………………………………………………………………………………………. 8
Summary of Fishes Observed………………………………………………………………. 12
Introduction ……………………………………………………………………………………………… 19

Methods
Field Data Collection…………………………………………………………………………… 21
Imagery Processing …………………………………………………………………………… 22
Summary Characteristics ……………………………………………………………………. 25
Results
Point Vicente: Point Vicente and Abalone Cove MPAs …………………………….. 27
Catalina Island: Farnsworth Bank MPAs…………………………………………………. 39
Laguna: Crystal Cove, Laguna Beach, and Dana Point MPAs …………………… 56
La Jolla: Matlahuayl and San-Diego-Scripps Coastal MPAs………………………. 68
Analytical products derived from baseline data ………………………………………………….. 87
Vertical Distribution of Benthic Organisms on the
Outer Continental Slope (S. Finstad) …………………………………………… 88
Distribution of Prawns Across Benthic Habitats in
Southern California (R. McCollough) …………………………………………… 92
Moving forward with long-term monitoring……………………………………………………….. 95

Fishes
Aurora/Splitnose Rockfish Complex…………………………………………….. 97
California Sheephead ……………………………………………………………….. 98
Halfbanded Rockfish ………………………………………………………………… 99
Lingcod …………………………………………………………………………………. 100
Pink Surfperch………………………………………………………………………… 101
Sanddab Complex (Citharichthys spp.)………………………………………. 102
Squarespot Rockfish ………………………………………………………………. 103
Vermilion/Canary/Yelloweye Rockfish Complex ………………………….. 104
Mobile Invertebrates
Ridgeback Prawns ………………………………………………………………….. 105
Spot Prawns…………………………………………………………………………… 106
California Sea Cucumber ………………………………………………………… 107
Structure-forming Invertebrates
California Hydrocoral ………………………………………………………………. 108
Sea Whips and Pens……………………………………………………………….. 109
Gorgonians…………………………………………………………………………….. 110
Conclusion ……………………………………………………………………………………………. 112
Financial Reports
Institute for Applied Marine Ecology at CSU Monterey Bay ……………………. 113
Marine Applied Research and Exploration …………………………………………… 114
References …………………………………………………………………………………………….. 115

Appendix
Operations Log
Summary of daily operations – Year 1………………………………………………….. 117
Summary of daily operations – Year 2………………………………………………….. 118

Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 201

List of Tables and Figures
Tables

Table 1. Fishes observed at each study site ………………………………………………………. 12
Table 2. Mobile invertebrates observed at each study site …………………………………. 14
Table 3. GLM results – All sites combined ………………………………………………………. 17
Table 4. Type and relief criteria for all substrate types………………………………………. 23
Table 5. Sessile invertebrate groupings……………………………………………………………. 23
Table 6. Count, relative abundance, density, and size frequency of fishes observed at the
Point Vicente Study Site. ……………………………………………………………………… 33
Table 7. Variability in fish densities between years at Point Vicente…………………….. 36
Table 8. GLM results – Point Vicente……………………………………………………………….. 38
Table 9. Count, relative abundance, density, and size frequency of fishes observed at the
Catalina Study Site. ……………………………………………………………………………………….. 45
Table 10. Variability in fish densities between years at Catalina …………………………. 48
Table 11. GLM results – Catalina …………………………………………………………………….. 50
Table 12. Count, relative abundance, density, and size frequency of all fishes observed at
the Laguna Area study site ……………………………………………………………………………… 62
Table 13. Variability in fish densities between years at Laguna …………………………… 65
Table 14. GLM results – Laguna ……………………………………………………………………… 67
Table 15. Count, relative abundance, density, and size frequency of all fishes observed at
the La Jolla Area study site …………………………………………………………………………….. 74
Table 16. Results of ANOVA tests for differences in richness and abundance in La Jolla
vertical transects …………………………………………………………………………………………… 82
Table 17. GLM results – Richness and abundance in La Jolla vertical transects ……. 82
Table 18. Variability in fish densities between years at La Jolla ………………………….. 84
Table 19. GLM results – La Jolla ……………………………………………………………………… 86
Table A1. Summary of daily operations for November 2011 ……………………………….. 116
Table A2. Summary of daily operations for November-December 2012 ………………. 117

Figures

Figure 1. Map of the four study site locations as part of the baseline characterization .. 9
Figure 2. ROV Beagle and support vessel F/V Donna Kathleen ………………………………. 21
Figure 3. Bathymetry-derived substrate types at Pt. Vicente…………………………………… 28
Figure 4. Imagery of fishes observed at Pt. Vicente ……………………………………………….. 29
Figure 5. Imagery of mobile invertebrates observed at Pt. Vicente ………………………….. 30
Figure 6. Imagery of sessile invertebrates observed at Pt. Vicente…………………………… 31
Figure 7. Proportions of organisms and substrates at Pt. Vicente……………………………. 32
Figure 8. Proportion of observed substrate types at Pt. Vicente………………………………. 35
Figure 9. Bathymetry-derived substrate types at Catalina……………………………………… 40
Figure 10. Imagery of fishes observed at Catalina ………………………………………………… 41
Figure 11. Imagery of mobile invertebrates observed at Catalina …………………………… 42
Figure 12. Imagery of sessile invertebrates observed at Catalina …………………………… 43
Figure 13. Proportions of organisms and substrates at Catalina ……………………………. 44
Figure 14. Proportion of observed substrate types at Catalina……………………………….. 47
Figure 15. Input rasters used for a) depth, b) VRM, and c) slope……………………………. 51
Figure 16. California Sheephead suitable habitat at Catalina ………………………………… 52
Figure 17. Pink Surfperch suitable habitat at Catalina ………………………………………….. 52
Figure 18. Lingcod suitable habitat at Catalina…………………………………………………….. 53
Figure 19. Sanddab (Citharichthys spp.) suitable habitat at Catalina …………………….. 53
Figure 20. Halfbanded Rockfish suitable habitat at Catalina ………………………………… 54
Figure 21. Squarespotted Rockfish suitable habitat at Catalina …………………………….. 54
Figure 22. Canary/Vermilion/Yelloweye Complex suitable habitat at Catalina ………. 55
Figure 23. Bathymetry-derived substrate types at Laguna ……………………………………. 57
Figure 24. Imagery of fishes observed at Laguna. ……………………………………………….. 58
Figure 25. Imagery of mobile invertebrates observed at Laguna……………………………. 59
Figure 26. Imagery of sessile invertebrates observed at Laguna …………………………… 60
Figure 27. Proportions of organisms and substrates at Laguna …………………………….. 61
Figure 28. Proportion of observed substrate types at Laguna ……………………………….. 64
Figure 29. Bathymetry-derived substrate types at La Jolla …………………………………… 69
Figure 30. Imagery of fishes observed at La Jolla. ……………………………………………….. 70
Figure 31. Imagery of mobile invertebrates observed at La Jolla …………………………… 71
Figure 32. Imagery of sessile invertebrates observed at La Jolla……………………………. 72
Figure 33. Proportions of organisms and substrates at La Jolla…………………………….. 73
Figure 34. Vertical transects study site within the La Jolla and Scripps Canyons ……. 77
Figure 35. 3D rendition of multi-beam bathymetry of the Canyons……………………….. 78
Figure 36. Sampling effort for Canyon transects …………………………………………………. 78
Figure 37. Densities of commonly observed fish species ………………………………………. 79
Figure 38. Pearson correlation coefficients between all study factors species ………… 80
Figure 39. Bar graphs of demersal fish species richness and abundance………………… 81
Figure 40. Proportion of observed substrate types at La Jolla………………………………. 83
Figure 41. Locations of vertical transects …………………………………………………………… 89
Figure 42. Area surveyed on vertical transects by depth ……………………………………… 89
Figure 43. Density of most abundant fish species on vertical transects ………………… 90
Figure 44. Density of rockfish species on vertical transects …………………………………. 90
Figure 45. Density of mobile invertebrate species on vertical transects ………………… 91
Figure 46. Prawn distribution at Point Vicente ………………………………………………….. 93
Figure 47. Prawn distribution at Laguna …………………………………………………………… 93
Figure 48. Prawn distribution at La Jolla ………………………………………………………….. 93
Figure 49. Habitat suitability maps of prawns at La Jolla …………………………………… 94

Executive Summary

Background – Seafloor habitats deeper than 100 meters make up an estimated 29% (1840 km2) of state waters in southern California, yet they are sampled with far less frequency when compared to shallower waters due to the many challenges associated with sampling in deep water. This difference in the frequency of sampling is concerning given the many economically and ecologically important organisms, along with the unique
and productive habitats in which they occur, that are found below 100 m. With the creation of the new network of marine protected areas, over 35% (330 km2) of the State’s shelf and slope deeper than 100 m are now protected within State Marine Reserves and Conservation Areas.

Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 202This report summarizes the results of a multi-year study (September 2011 – January 2015) to characterize mid-depth rocky reef and soft bottom ecosystems in the California Marine Life Protection Act’s South Coast (SC) Study Region. Our specific objective was to characterize the seafloor habitats and associated biological communities within and adjacent to the State Marine Reserves (SMRs) and Conservation Areas (SMCAs) at the time of implementation.
Study Sites – The SC Study Region encompasses nearly 475 km of linear coastline ranging from Point Conception in the north to the Mexican border in the south, with another 400 km included in the northern Channel Islands which have been well studied by on-going monitoring efforts conducted by the National Park Service, the National Marine Sanctuary Program, and many academic institutions. For the present project three locations were selected to broadly represent the distinct biogeographic zones across the southern California Bight, including mainland sites at Point Vicente (north) and La Jolla (south), as well as an off-shore location at Farnsworth Bank off the backside of Catalina Island (Figure 1). These sites were sampled in 2011 and 2012.

Generous additional support from private donors allowed us to sample additional sites within and adjacent to the Laguna Beach/Crystal Cove/Dana Point MPAs in 2011. In 2012, San Clemente Island was also added to the baseline characterization with generous support from the US Department of Defense. The results of that effort will be reported elsewhere in 2015.

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Figure 1. Map of the four study site locations as part of the baseline characterization of the mid-depth rocky reef and soft bottom ecosystems, including the Laguna Beach MPAs added in 2011.

Results – Our approach to characterization involved the collection of videographic and still photographic imagery at each location using a remotely operated vehicle (ROV). Data extracted from this permanent imagery archive were used to summarize the ecological conditions inside SMRs and SMCAs, and at comparable sites distant from both, over a one-year baseline from November 2011 – November 2012. During that baseline period we conducted a total of 102 ROV transects across the four geographic locations, totaling 12,810 still photographs and 97.5 hours of video.

We observed a total of 51,192 fish across habitats ranging from unconsolidated sediments Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 204to rocky reefs, and the transitional areas in between. At the northernmost mainland site (Point Vicente), Halfbanded Rockfish were the most abundant of the 16,853 fish we observed. It is important to note that we were prevented from sampling the limited rocky reef areas along the mainland due to the significant entanglement hazards created by Giant Kelp (Macrocystis pyrifera) and lobster pots. In the south (La Jolla), which included both shelf sites as well as sites deep within the submarine canyons, Halfbanded Rockfish also dominated the 16,867 fish observed, despite very challenging sampling conditions. Indeed, to account for the great difficulties we encountered sampling the deep submarine canyons, we developed a new sampling protocol described below in the section on Analytical products derived from baseline data. Of the 15,837 fish observed at the Farnsworth Bank MPAs along the southwest coast of Catalina Island, where visibility was generally excellent, Blacksmith were the most numerous (n=3,458). We also observed thousands of invertebrates, both mobile and sessile, across the study area.

Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 205Insofar as this project was dedicated to a baseline characterization in support of future monitoring efforts, we targeted as many fishes (ranging from species to morphological groups) listed in the South Coast Monitoring Plan as could be sampled effectively with an ROV. We sampled a total of 13 (76.5%) of the fishes and fish groupings (e.g. “Rockfishes”) included in the monitoring plan, under ecosystems surveyed by the ROV (Table 1). Further, we sampled a total of 71% of invertebrate species and groups described in the monitoring plan (Table 2). Suggestions for Future Monitoring – Anticipating the challenge of sustaining a long-term monitoring effort well beyond the baseline provided here, we propose the following list of species/taxonomic groups for inclusion in a video-based monitoring program. These species, including both fishes and invertebrates, are a) observed in numbers that are appropriate for a variety of statistical analyses and b) are capable of being identified with a high level of confidence from imagery alone.

Fishes
Aurora/Splitnose Rockfish Complex
California Sheephead
Halfbanded Rockfish
Lingcod
Sanddab Complex (Citharichthys spp.)
Pink Surfperch
Squarespot Rockfish
Vermilion/Canary/Yelloweye Rockfish Complex
Mobile Invertebrates
Ridgeback Prawns
Spot Prawns
California Sea Cucumber
Structure-forming Invertebrates
California Hydrocoral
Sea Pens and Whips
Gorgonians

Table 1. Fishes observed at each study site. Groupings along the left column are based on the morphologies described in Humann and DeLoach (2008).

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Table 1 cont’d. Fishes observed at each study site. Groupings along the left column are based on the morphological classifications described in Humann and DeLoach (2008).

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Sharks & Rays Silvery Swimmers Eeels & Eel-like Bottom-dwellers Odd-shaped Bottom-dwellers Odd-shaped & Other Swimmers Flatfish / Bottom-dwellers

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Table 2. Mobile invertebrates observed at each study site.

The list is a first pass at species and species complexes, including fishes as well as mobile and sessile invertebrates, which are capable of being monitored using
videographic techniques and were observed during the baseline characterization effort along the South Coast. While we expect that many scientists could reach agreement on some of the organisms on this list, it is also likely that much discussion could been gendered to flesh this group out further. What we provide here is intended as a point of departure for discussion as each of the MLPA regions moves beyond baseline characterization.

An example of one of the species complexes that we recommend for long-term monitoring, the Aurora/Splitnose Rockfish complex, is included below. Additional pages for the other species pages are included in the section on Moving Forward with Long-term Monitoring.

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Initial Comparisons – This project, as described above, was conceived and implemented as a one-year baseline against which any future changes could be compared. Given that our sampling was conducted essentially at the moment of designation for the South Coast MPAs, we were not primarily focused on either inter-annual or inside/out comparisons. However, as questions inevitably arise about differences between sampling years, and inside MPAs and outside MPAs, we conducted summary analyses for both. Differences between years varied considerably across species and locations between 2010 and 2011. Specific differences are detailed in tables associated with each sampling location below, as are figures depicting any differences in the percentage of habitat sampled between years. We attribute the many differences between years primarily to the fact that we sampled in different locations in each of the two years in order to cover as much of the area as possible over the one-year baseline. The precise location of transects each year for each location are also provided below.

To explore differences between organisms inside and out of MPAs we pooled both years and focused on the species/complexes suggested for long-term monitoring above. Generalized Linear Models were run on the pooled data to explore any differences between organisms inside and out of the MPAs at each location. Table 3 below summarizes the combined differences for each of the seven fish categories.

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Table 3. GLM results showing differences in density for seven of the suggested long-term monitoring fishes across all four sites.

The MPA treatment (in/out) was not significant when all study sites were pooled. The substrate parameter (hard/soft) played a significant role in the model for describing the distribution for Sheephead (p = 0.0008) and Squarespot Rockfish (p = 0.02; Table 3).The coefficient values suggest that California Sheephead were more abundant inside MPAs overall (large, positive number), while Squarespot Rockfish were more abundant outside. As we note below, the limited extent of rocky substrate in the subtidal south of Point Conception was not evenly distributed inside and out of the MPAs that we sampled. For instance, nearly all of the rocky substrate found in the vicinity of Farnsworth Bank on the backside of Catalina Island is found inside the Offshore SMCA, making a true comparison of in to out impossible for a fish like California Sheephead, which has a known proclivity for rocky substrate. As such, it will be critical in the coming
years to evaluate changes in fish abundance and density across a heterogeneous landscape with caution.

Final Thoughts – Participants in the project represented a broad collaborative partnership among academia, non-profit organizations, state and federal agencies, and members of the fishing community, constituents that have not always collaborated effectively. All project imagery resides at the Institute for Applied Marine Ecology at California State University Monterey Bay (CSUMB) and at Marine Applied Research MPA Treatment Substrate Treatment
and Exploration (MARE). All baseline data collected as part of this project will be uploaded to the MPA Monitoring Enterprise’s Ocean Spaces website.
We also have a number of longer term analyses underway, two of which are described below in the Analytical products derived from baseline data. These projects explore the distribution and habitat utilization of fishes and key mobile invertebrates at multiple locations across the study area using the high-resolution bathymetric maps produced by the California State Mapping Project. The final results of these projects and more will be available for the five year review of the south coast MPAs.

Introduction

Seafloor habitats deeper than 100 meters water depth make up an Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 211estimated 29% (1840 km2) of state waters in southern California, yet they are sampled with far less frequency when compared to shallower waters due to the many challenges associated with sampling in deep water.
This difference in the frequency of sampling is concerning given the many economically and ecologically important organisms, along with the unique and productive habitats in which they occur, that are found below 100 m. With the creation of the new network of marine protected areas, over 35% (330 km2) of the State’s shelf and slope deeper than 100 m are now protected within State Marine Reserves and
Conservation Areas.
This report summarizes the results of a multi-year study (September 2011 – January 2015) to characterize mid-depth rocky reef and soft bottom ecosystems in the California Marine Life Protection Act’s South Coast (SC) Study Region. Our specific objective was to characterize the seafloor habitats and associated biological communities within and adjacent to the State Marine Reserves (SMRs) and Conservation Areas (SMCAs) at the
time of implementation.
The SC Study Region encompasses nearly 475 km of linear coastline ranging from Point Conception in the north to the Mexican border in the south, with another 400 km in the northern Channel Islands which have been well studied by on-going monitoring efforts conducted by the National Park Service, the National Marine Sanctuary Program, and many academic institutions. For the present project three locations were selected to
broadly represent the distinct biogeographic zones across the southern California Bight, including mainland sites at Point Vicente (north) and La Jolla (south), as well as an off-shore location at Farnsworth Bank off the backside of Catalina Island (Figure 1). These sites were sampled in 2011 and 2012.

Generous additional support from private donors allowed us to sample additional sites within and adjacent to the Laguna Beach/Crystal Cove/Dana Point MPAs in 2011. In 2012, the island of San Clemente was also added to the baseline characterization in 2012 and 2013 with generous support from the US Department of Defense. The results of that effort will be reported elsewhere in 2015.

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Methods

Field Data Collection

Underwater surveys were conducted at each location within the SC Study Region using the Vector M4 ROV Beagle (owned and operated by MARE onboard F/V Donna Kathleen, Figure 2). The ROV configuration and sampling protocol were based on
previous and on-going studies conducted by the PIs (Lindholm et al. 2004; de Marignac et al. 2009; Tamsett et al. 2010).

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Figure 2. (A) The Vector M4 ROV Beagle and (B) F/V Donna Kathleen served as the support vessel for ROV operations.

The ROV was equipped with five cameras (forward-looking standard-definition Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 214video, forward-looking high-definition video, down-looking standard-definition video, digital still (forward or down positional), and rear facing video), two quartz halogen and HMI lights, paired forward- and down-looking sizing lasers (spaced at 10 cm), and a strobe for still photos. The ROV was also equipped with an altimeter, forward-facing multibeam sonar, CTD, and dissolved oxygen meter. The position of the ROV on the seafloor was maintained by the Trackpoint III® acoustic positioning system with the resulting coordinates logged into Hypack® navigational software. The ROV was ‘flown’ over
the seafloor at a mean altitude of 0.9 m and a A B speed of approximately 0.67 knots. Sampling effort was based on relatively long ROV
transects distributed across a study site. The distribution of transects was stratified in order to encompass both unconsolidated soft and hard substrate environments and the transitional areas in between. Transect length depended on local conditions and the extent of substrate coverage in the study area, but generally exceeded 1 km. Continuous video imagery was recorded from forward- and down-looking cameras to digital tape.

Imagery Processing

Forward-looking video was used for the collection of data on mobile and sessile organisms. The following data were recorded directly into a Microsoft Access database for each individual organism we encountered: time of occurrence, identification (to the most accurate taxonomic group possible), identification quality, organism size, and the microhabitat and relief immediately surrounding the organism.
Time of occurrence was later linked with ROV tracking data to geo-reference each observation. Identification quality was assessed on a scale from one to five (1 = uncertain and 5 = certain), and represented our measure of confidence for all fish species/genus
observations. Fish identifications were confirmed where possible with colleagues and experts on California fishes (primarily Dr. Robert Lea, former CDFW fishery biologist) to ensure data accuracy.
Organism sizes were estimated to the nearest 5 cm using the paired lasers spaced 10 cm apart as a reference. Microhabitat and relief were identified using pre-defined categories and protocols based on Greene et al. (1999) and Tissot et al. (2006). Both primary (<50%) and secondary (<20%) microhabitats types were identified. (See Table 4 for definitions of microhabitat and relief categories.)

Table 4. Type and relief criteria for all substrate types. Forward-facing video was also used for collection of data on sessile invertebrates.

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Occurrence of selected sessile invertebrate groupings (Table 5) was noted as present or absent in 10-second non-overlapping video quadrats along each transect. Quadrats began at the first observation of a target organism and continued until a break in the occurrence of the organisms. Subsequent quadrats resumed at the next observation of a target organism.

Table 5. Sessile invertebrate groupings. Downward-facing video was used to quantify seafloor substrates at a “patch scale”.

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A substrate patch was defined as continuous, uniform substrate for at least 10 seconds of constant forward motion (average ROV speed = 0.67 kts). Broad-scale substrate categories were used to define the following substrate categories: ‘Soft’ (unconsolidated sediments), ‘Hard’ (rocks and reef), and ‘Mixed’ (equal portions of ‘Hard’ and ‘Soft’ in a patch). A 10-second patch was required to have >60% of the area of ‘Soft’ or ‘Hard’bottom to be classified as such. If the patch had between 40-60% of the area of both, it was classified as ‘Mixed’. Still images (and, occasionally, downward-facing video) provided an opportunity to positively identify fish and invertebrates that were frequently
not possible to identify from video alone. Still images were collected opportunistically along each transect.

As this was a baseline characterization effort rather than a hypothesis driven Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 217research project, we sought to let the data drive the scale of the analyses rather than constraining the analyses to our a prior understanding of a particular species’ distribution. For on-going analyses of project data (summarized in a separate section below), sub-sampling of transect data occurred post hoc for selected species or taxonomic groups based on their distribution and considering the extent to which spatial autocorrelation influenced the data (Hallenbeck et al. 2012). Consequently,
the number of replicates for each analysis depended on the size of the sampling units identified post hoc within known habitat and depth zones.

Summary Characteristics of Each Location Surveyed

The following sections include details of baseline characterization and monitoring at each of the four sites surveyed in this study.
Summary of Substrates – available vs. surveyed – as determined by multibeam sonar bathymetry data – Utilizing multibeam sonar data products (“substrate” rasters) from the habitat package provided by the California Seafloor Mapping Program1, as well as previous mapping contributions (i.e., USGS), we calculated the area of “rough” (high rugosity) and “smooth” (low rugosity) substrates at each study site. We used these area
values (km2) as a proxy to estimate the available substrates at each study site and within each MPA. They are reported as the total available substrates at each MPA in a study site and “unprotected” (non-MPA) areas that fall within our study site delineation.
Additionally, we plotted our geo-referenced ROV transect lines over these maps and extracted area values (km2) for the actual surveyed areas, again for the MPAs, and the unprotected areas.

Summary Proportions of Fishes, Invertebrates, and Substrates – Substrate patch data are reported as total linear kilometers surveyed. Above each substrate type are a series of pie charts representing the proportions of fishes and select mobile and Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 218sessile invertebrate
groups found over that type of substrate. All fishes observed at a study site were grouped into major morphological groupings (based on Humann and DeLoach 2008). A detailed list of species and genera that fall into each morphological group used can be found in
Table 1. Mobile (Table 2) and sessile (Table 4) invertebrates are represented as broad taxonomic and morphological groupings, based on species that were easily discernible in the video (i.e., not frequently cryptic and/or camouflaged).

Fish Abundance, Density, and Size-class Frequency Tables – Data on fishes are reported as relative abundance, density, and size class frequency for species, species complexes (e.g., Aurora/Splitnose Rockfish), and other major groupings (e.g., rockfishes, eelpouts,
combfish). While a complete listing of all observed fishes are cataloged in Table 1, these tables only include metrics of fishes with at least 5 individuals observed across all study sites and years. Relative abundance describes the abundance of each fish in the table relative to all others observed at that site. Densities were calculated per transect and then averaged across transects for each site. Size class frequency is based on 5 cm size class estimates and grouped into 10 cm bins. Fishes described in the management plan as focal species and groups for density, abundance, and size structure metrics are noted by footnotes to refer to each ecosystem the Monitoring Plan.

Variability Between Years and In/Out of MPAs – This project, as described above, was conceived and implemented as a one-year baseline against which any Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 219future changes could be compared. As such, our sampling with the ROV at each location 2011 and 2012 was not intended to flesh out any differences between the two sampling periods. Further, given that our sampling was conducted essentially at the moment of designation for the MPAs, we were not focused on any “MPA effects” either. However, as questions inevitably arise about differences between sampling years, and between
inside MPAs and outside MPAs, we have included a brief summary of the differences in our observations of selected organisms and substrate attributes between years and inside and out of MPAs for each section. Given the long ecological timelines along which we would expect any MPA effect to be identified, we caution the reader against making too much of the percentage differences reported below for each site over the course a single year.

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Point Vicente: Point Vicente SMCA and Abalone Cove SMCA

The Point Vicente study site encompassed the primarily soft-sediment region of the shelf just above the muddy slope that extends out within both SMCAs. In 2011 some transects were conducted in the nearshore rocky kelp forested areas. Difficulty flying the ROV in kelp restricted the majority of transects to the soft sediment shelf and upper slope. Paired transects were conducted inside and outside the north and south bounds of the MPAs.
Due to poor visibility in shallower areas in 2012, most transects for this year of the study were conducted in deeper waters near or along the slope.

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Figure 3. Bathymetry-derived substrate types at Point Vicente. Low rugosity substrates dominated the study site at Point Vicente. Unsurprisingly, survey effort was well matched with the available substrate for MPAs and unprotected areas.

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Figure 4. Imagery of fishes observed at Point Vicente. Halfbanded Rockfish (Sebastes semicinctus) were the most abundant species in Pt. Vicente (top). Shortspine Combfish (Zaniolepis frenata) were also seen in the ubiquitous ‘Soft’ substrates (middle). Rockfish from the Sebastomus complex (center of bottom image) were a less common occurrence.

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Figure 5. Imagery of mobile invertebrates observed at Point Vicente. Small octopus were frequently seen on ‘Soft’ substrates (top). Sea Cucumbers were restricted to ‘Soft’ substrates (middle). Ridgeback Prawns (Sicyonia ingentis) were seen on ‘Soft’ substrates (bottom).

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Figure 6. Imagery of sessile invertebrates observed at Point Vicente. Gorgonians occurred on ‘Hard’ substrates – a rare occurrence in Point Vicente (top). Sea Pens were frequently observed (middle). Giant Plumed Anemones (Metridium farcimen) were one of many anemone species seen (bottom).

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Figure 7. Proportions of organisms and substrates. ‘Soft’ substrates dominated this site. ‘Heavy Bodied’ fishes were observed the most frequently across all substrates, with ‘Elongated Bottom-Dwellers’ the next most abundant. The highest diversity of both Mobile Invertebrates occurred on ‘Soft’ substrates, while the highest diversity of Sessile Invertebrates was found over ‘Hard’ substrates.

Fish Abundance, Density, and Size-class Frequency

Table 6. Count, relative abundance, density, and size frequency of fishes observed at the Point Vicente Study Site.

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Table 6 cont’d. Count, relative abundance, density, and size frequency of the fishes observed at the Point Vicente Study Site.

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Variability Between Years

This project, as described above, was conceived and implemented as a one-year baseline against which any future changes could be compared. Given that our sampling was conducted essentially at the moment of designation for the SC MPAs, we were not focused on any “MPA effects” either. Further, as depicted below in Figure 8 for Point Vicente, in selected cases sampling was not equivalent from one year to the next. However, as questions inevitably arise about differences between sampling years, and between inside MPAs and outside MPAs, we have included a brief summary of the
differences in our observations of selected organisms and substrate attributes between years.

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Figure 8. Proportion of observed substrate types between years and protection status at Point Vicente. The majority of substrate observed was ‘Soft’ substrate. The only non-’Soft’ substrate surveyed occurred in 2011, with the sole ‘Hard’ substrate within protected areas.

Table 7. Variability between years and density in protected and unprotected areas for observed fishes at Point Vicente study site.

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Table 7 cont’d. Variability between years and density in protected and unprotected areas for observed fishes at Point Vicente.

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Variability Inside and Out of MPAs

To interpret the densities of fishes observed inside vs. outside MPAs, as well as over hard vs. soft substrates, we used a generalized linear model (GLM), such that: Density ~ μ + exp [ β1 (Treatment) + β2 (Substrate) + ɛ Where μ = model intercept, exp = negative binomial correction, βx = regression coefficient, and ɛ = unexplained error. We used a negative binomial correction to account for zero-inflated data for each of the seven fish or fish groups.
The model output provides the relative influence of each treatment (inside vs. outside, hard vs. soft) on the overall abundance of each species/complex. It does not tell us if there is a significant difference between terms (e.g., in vs. out), but it is useful for
determining potential factors that may be driving observed patterns in abundance. At the time of baseline data collection, the MPA treatment (in/out) was only significant for Pink Surfperch (p = 0.03). No significant difference between densities over hard and soft substrates was observed for any species. The substrate parameter (hard/soft) did not play a significant role in describing the distribution of any species/complexes (Table
8).

Table 8. GLM results showing differences in density for the suggested long-term monitoring fishes observed at Point Vicente.

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Catalina Island: Farnsworth Bank Onshore and Offshore SMCAs

The Catalina study site focused on the two Farnsworth Bank SMCAs on the southwestern coast of Catalina Island. Transects were organized to survey similar substrates inside and outside of the SMCAs. Because the majority of the area of the rocky bank itself is enclosed within the SMCA, the rocky area to the north of the protected area was also surveyed. The offshore SMCA also contains deeper canyon areas to the west, and the
heads of several of these canyons were surveyed as well.

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Figure 9. Bathymetry-derived substrate types at Catalina. Low rugosity substrates dominated both the MPAs and the unprotected area at the Catalina study site. High rugosity areas were surveyed disproportionally more than were available, mostly concentrated over Farnsworth Bank and the paired transects over high rugosity in the unprotected area.

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Figure 10. Imagery of fishes observed at Catalina. Lingcod (Ophiodon elongatus) were commonly seen in Farnsworth Bank rocky habitats (top). Pacific Electric Rays (Torpedo californica) were observed primarily over soft sediments (middle). California Scorpionfish (Scorpaena californica) were found on ‘Hard’ substrates – camouflaging well with the Bank’s sessile invertebrates.

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Figure 11. Imagery of mobile invertebrates observed at Catalina. Octopus were frequently observed over ‘Soft’ substrates (top). Mantis Shrimp (Hemisquilla ensigera) were most often observed at the Catalina study sites (middle). California Spiny Lobsters (Panulirus interruptus) were common in the nooks and crevices of rocky habitats (bottom).

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Figure 12. Imagery of sessile invertebrates observed at Catalina. California Hydrocoral (Stylaster californicus) were seen only at Farnsworth Bank (top). Sea Pens were common on ‘Soft’ substrate (middle). ‘Hard’ substrates contained Gorgonians of many sizes, colors, and morphologies (bottom).

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Figure 13. Proportions of organisms and substrates. ‘Soft’ substrates dominated this site. Fishes in the ‘Heavy Bodies’ group were most common across all substrate types, with ‘Elongated Bottom-Dwellers’ second most abundant on ‘Hard’ and ‘Mixed’ substrates. The highest diversity of both Mobile and Sessile invertebrates occurred over ‘Soft’ substrates.

Table 9. Count, relative abundance, density, and size frequency of fishes observed at the Catalina Study Site.

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Table 9 cont’d. Count, relative abundance, density, and size frequency of fishes observed at the Catalina Island study site.

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Variability Between Years

This project, as described above, was conceived and implemented as a one-year baseline against which any future changes could be compared. Given that our sampling was conducted essentially at the moment of designation for the SC MPAs, we were not focused on any “MPA effects” either. Further, as depicted below in Figure 14 for Catalina, in selected cases sampling was not equivalent from one year to the next. However, as questions inevitably arise about differences between sampling years, and between inside MPAs and outside MPAs, we have included a brief summary of the differences in our observations of selected organisms and substrate attributes between years.

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Figure 14. Proportion of observed substrate types between years and protection status at Catalina. The majority of substrate observed in both years was ‘Soft’. In 2011 the more ‘Mixed’ substrate was observed, while in 2012, more ‘Hard’ was observed.

Table 10. Variability between years and density in protected and unprotected areas for all fishes observed at the Catalina Island study site.

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Table 10 cont’d. Variability between years and density in protected and unprotected areas for all fishes observed at the Catalina Island study site.

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Variability Inside and Out of MPAs

To interpret the densities of fishes observed inside vs. outside MPAs, as well as over hard vs. soft substrates, we used a generalized linear model (GLM), such that: Density ~ μ + exp [ β1 (Treatment) + β2 (Substrate) + ɛ Where μ = model intercept, exp = negative binomial correction, βx = regression coefficient, and ɛ = unexplained error. We used a negative binomial correction to account for zero-inflated data for each of the seven fish or fish groups.
The model output provides the relative influence of each treatment (inside vs. outside, hard vs. soft) on the overall abundance of each species/complex. It does not tell us if there is a significant difference between terms (e.g., in vs. out), but it is useful for
determining potential factors that may be driving observed patterns in abundance. At the time of baseline data collection, the MPA treatment (in/out) was not significant for any of the suggested long-term monitoring organisms. Substrate (hard/soft) played a significant role in describing only the distribution of Squarespot Rockfish (p = 0.02)

Table 11. GLM results showing differences in density for seven of the suggested long- term monitoring fishes at Catalina.

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Habitat Suitability at Farnsworth Bank SMCAs

The Farnsworth Bank habitat suitability maps are based on GLMs fitted from the observed occurrences of each species throughout the study area with 5m bathymetry data. We used vector ruggedness measure (VRM; a rugosity measurement), slope, and depth as parameters in the Marine Geospatial Ecology Tool (MGET) in ArcGIS (Figure 15). We then used a backward stepwise model comparison to create individual models for each species (Figures 16-22). To extract only the areas of most suitable habitat, we used a cutoff value unique to each
species determined by an ROC curve (receiver operating characteristic curve) provided by the model’s output. This cutoff value provided the spatial structure to calculate areas of suitable habitat in the MPAs and in the entire study site. The highlighted habitat indicates areas of higher probability of occurrence (or more ‘suitable’ habitat) based on these parameters.

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Figure 16. California Sheephead suitable habitat at Catalina. Results indicated that areas of high rugosity were most suitable, and these areas are concentrated in the offshore SMCA at Farnsworth Bank.

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Figure 17. Pink Surfperch suitable habitat at Catalina. Results indicated that areas deeper areas of smooth, gradual slope were most suitable, and these areas are concentrated between Farnsworth Bank and the continental shelf.

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Figure 18. Lingcod suitable habitat at Catalina. Results indicated that areas of high rugosity and moderate to high slope were most suitable, including the steep area in deeper waters off the shelf.

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Figure 19. Sanddab (Citharichthys spp.) suitable habitat at Catalina. Results indicated that the flat, smooth areas were most suitable.

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Figure 20. Halfbanded Rockfish suitable habitat at Catalina. Results indicated that the areas of smooth, gradual slope surrounding the Farnsworth Bank Feature were most suitable.

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Figure 21. Squarespot Rockfish suitable habitat at Catalina. Results indicated that areas deeper areas of smooth, gradual slope were most suitable, including the edge of the shelf.

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Figure 22. Canary/Vermilion/Yelloweye Complex suitable habitat at Catalina. Results indicated that areas high rugosity and steep slope were most suitable, including the edge of the shelf.

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Laguna: Crystal Cove SMCA, Laguna Beach SMR/SMCA, and Dana Point SMCA

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Transects at the Laguna study site were focused both on shallow rocky reefs as well are soft substrate further offshore. In the deeper transects in soft sediments, transects were paired to survey both inside and outside MPAs on similar contours (~150m depth). Nearer to shore, the shallower transects were focused on rocky reefs, which were all located within MPAs. Despite a limited sampling time within only one sampling year, effort in this site was spread widely across a roughly 26km stretch of coastline.

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Figure 23. Bathymetry-derived substrate types at Laguna. Low rugosity substrates dominated both the MPAs and the unprotected area at the Laguna study site. The majority of high rugosity substrates were concentrated in nearshore rocky reefs of the MPAs. Nearshore transects targeted these areas while offshore transects were over low rugosity. Substrate data for Crystal Cove SMCA were not available.

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Figure 24. Imagery of fishes observed at Laguna. Slender Sole (Lyopsetta exilis) were ubiquitous on ‘Soft’ substrates (top). Pink Surfperch (Zalembius rosaceus) were rarely observed (middle). California Lizardfish (Synodus lucioceps) were common over ‘Soft’ substrates (bottom).

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Figure 25. Imagery of mobile invertebrates observed at Laguna. Octopus were common on ‘Soft’ substrate (top) and often camouflaged with the sediment (middle). Crabs were the most common mobile invertebrate seen at this site (bottom).

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Figure 26. Imagery of sessile invertebrates observed at Laguna. Sea Pens were found on ‘Soft’ substrates (top). ‘Hard’ substrates supported a diversity of Gorgonians (middle). Other corals were also seen on ‘Hard’ substrates (bottom).

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Figure 27. Proportions of organisms and substrates. ‘Soft’ substrates dominated this site. Fishes in the ‘Odd-Shaped Bottom-Dwellers’ group were most common across ‘Hard’ and ‘Mixed’ substrates, with ‘Elongated Bottom-Dwellers’ most common over ‘Soft’ substrates. The highest diversity of both Mobile and Sessile invertebrates occurred over ‘Soft’ substrates, with a notable lack of Mobile Invertebrates on either ‘Hard’ or ‘Mixed’ substrates.

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Table 12. Count, relative abundance, density, and size frequency of all fishes observed at the Laguna Area study site.

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Table 12 cont’d. Count, relative abundance, density, and size frequency of all fishes observed at the Laguna Area study site.

Variability Between Years

This project, as described above, was conceived and implemented as a one-year baseline against which any future changes could be compared. Given that our sampling was conducted essentially at the moment of designation for the SC MPAs, we were not focused on any “MPA effects” either. Further, as depicted below in Figure 28 for Laguna, in selected cases sampling was not equivalent from one year to the next. However, as questions inevitably arise about differences between sampling years, and between inside MPAs and outside MPAs, we have included a brief summary of the differences in our observations of selected organisms and substrate attributes between years.

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Figure 28. Proportion of observed substrate types between years and protection status at Laguna. The majority of substrates observed in 2011 were ‘Soft’. The only ‘Hard’ and ‘Mixed’ substrate surveyed in Laguna were within protected zones. No data were collected in 2012 at this site.

Table 13. Variability between years and density in protected and unprotected areas for all fishes observed at the Laguna Area study site.

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Table 13 continued. Variability between years and density in protected and unprotected areas for all fishes observed at the Laguna Area study site.

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Variability Inside and Out of MPAs

To interpret the densities of fishes observed inside vs. outside MPAs, as well as over hard vs. soft substrates, we used a generalized linear model (GLM), such that: Density ~ μ + exp [ β1 (Treatment) + β2 (Substrate) + ɛ Where μ = model intercept, exp = negative binomial correction, βx = regression
coefficient, and ɛ = unexplained error. We used a negative binomial correction to account for zero-inflated data for each of the seven fish or fish groups.
The model output provides the relative influence of each treatment (inside vs. outside, hard vs. soft) on the overall abundance of each species/complex. It does not tell us if there is a significant difference between terms (e.g., in vs. out), but it is useful for determining potential factors that may be driving observed patterns in abundance. At the time of baseline data collection, neither the MPA treatment (in/out) nor substrate (soft/hard) were significant for any of the suggested long-term monitoring organisms.

Table 14. GLM results showing differences in density for seven of the suggested long- term monitoring fishes at Laguna.

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La Jolla: Matlahuayl SMR and San Diego-Scripps Coastal SMCA

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The La Jolla study site included Scripps and La Jolla submarine Canyons as well as the unconsolidated sediments along the shelf above the canyons. Paired transects were conducted inside and outside the SMCA, but the extreme slope of canyon walls was difficult to navigate and collect video data and thus these areas were surveyed using a separate protocol in which imagery was collected moving up along a vertical wall rather than along the horizontal seafloor. These vertical transects are discussed separately in an additional section below.

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Figure 29. Bathymetry-derived substrate types at La Jolla. Low rugosity substrates dominated both the MPAs and the unprotected area at the Laguna study site.

The majority of high rugosity areas were inside the La Jolla and Scripps Canyons. Survey effort was high in these areas and thus proportionally more high rugosity substrate was surveyed in the MPAs.

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Figure 30. Imagery of fishes observed at La Jolla. Garibaldi (Hypsypops rubicundus) were frequent in rocky areas (top). Greenstriped Rockfish (Sebastes elongatus) were rarely encountered (middle). California Sheephead (Semicossyphus pulcher) were the most common kelp forest species observed (bottom).

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Figure 31. Imagery of mobile invertebrates observed at La Jolla. Sea Cucumbers were restricted to ‘Soft’ substrates (top). Spot Prawns (Pandalus platyceros) were most abundant near La Jolla canyon (middle). Sheep Crab (Loxorhynchus grandis) were one of many crab species observed (bottom).

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Figure 32. Imagery of sessile invertebrates observed at La Jolla. The Sea Dandelion (Dromelia sp.), a benthic siphonophore, was observed most frequently at the La Jolla study sites (top). Sponges of many kinds were seen on both ‘Soft’ and ‘Hard’ substrates (middle). Gorgonians were abundant on all substrate types, but were most common in rocky habitats (bottom).

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Figure 33. Proportions of organisms and substrates. ‘Soft’ substrates dominated at this site. Fishes in the ‘Heavy Bodies’ group were most common across all substrates, with ‘Elongated Bottom-Dwellers’ second most abundant on ‘Mixed’ and ‘Soft’ substrates. The highest diversity of both Mobile and Sessile Invertebrates occurred over ‘Mixed’ substrates.

Table 15. Count, relative abundance, density, and size frequency of all fishes observed at the La Jolla Area study site.

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Table 15 cont’d. Count, relative abundance, density, and size frequency of all fishes observed at the La Jolla Area study site.

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Vertical Distribution and Composition of Demersal Fish Communities Along the Walls of the La Jolla and Scripps Submarine Canyons

The geographic extent and distribution of many coastal marine fish assemblages are strongly driven by habitat features, particularly among demersal fishes that live along the seafloor. Ecologists have long recognized the importance of characterizing fish habitat associations, especially for management and the design and implementation of marine protected areas (e.g., Carr 2013; Starr 2010). Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 271Despite this importance, little is known about the structure, distribution, and
habitat suitability of fish communities in submarine canyons. As such, improved understanding of the spatial distribution
and habitat associations of demersal fishes in submarine canyons will aid policy makers in developing improved management strategies and suitability
models. The subtidal comprises nearly 70 percent of California’s coastal waters and is essential habitat for the state’s commercial
fish species (Yoklavich et al. 2011). The active continental margin of the California coast is cut by eight submarine canyons, many of which extend from the shore to the deep abyssal plain.

We sampled the demersal fish community of the La Jolla submarine canyon in the San-Diego-Scripps Coastal Marine Conservation Area (SMCA) and the Matlahuayl State

Marine Reserve (SMR). In addition to the ROV sampling protocols described above, transects were conducted at the La Jolla study site using a modified protocol to capture the steep walls of the submarine canyons present in the MPAs. The La Jolla canyon is composed of two main branches that extend from the shore to the continental slope. The Scripps canyon in the north (32°52’N, 117°16’W) is located in the San Diego-Scripps Coastal State Marine Conservation Area (SMCA) and the La Jolla canyon in the south (32°51’N, 117°16’W) in the Matlahuayl State Marine Reserve (SMR) (Figure 34). Our study area covered the headward portion of each canyon, between 20 and 300 m water depth. The habitat contained within this site is managed under both state and federal
jurisdiction. Substrate type across the study region is generally composed of hard rocky outcrops along steep canyon walls with even proportions of loose cobble and soft substrate.

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Figure 34. Study site within the La Jolla and Scripps canyons.

Species richness, abundance, and habitat (slope and ruggedness) were quantified and mapped using ArcGIS. Thirty-seven species of demersal fishes representing 17 families were obtained from 21 vertical transects. Species composition was assessed in three depth-stratified bins (100 m per bin) along, and to either side, of the canyon walls. Although sampling effort decreased with depth, species richness (number of species per depth bin) increased along this gradient. Ongoing analyses of physical properties (e.g., temperature, slope, substrate complexity) within the canyon’s flow-field will provide more
detailed insight into factors that facilitate the structure of demersal fish communities.

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Figure 35. 3D rendition of multi-beam bathymetry from CSUMB’s Seafloor Mapping Lab was used to generate a physical model profiling the headward portion of each canyon’s geomorphology for A) Scripps Canyon and B) La Jolla Canyon. Transect lines are drawn in orange (2011) and yellow (2012). The color gradient was scaled to 15 depth-stratified bins in 20 m intervals. For each transect, the ROV was flown from the bottom of the canyon to the top of the canyon’s ledge, while forward looking video faced the canyonwall. Data were extracted from video imagery using a forward-facing camera, but a second camera pointed at 45 degrees above the horizontal also recorded imagery.

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Figure 36. Sampling effort for vertical transects. The greatest sampling effort was applied to depths 60-140 m. Effort was standardized as richness (number of species) per linear meter of the geospatial hypotenuse traveled by the ROV along the canyon walls. Although sampling effort was less at depths below 140 m, species richness increased with depth. The greatest species richness was observed in the 260 m depth bin. Depth bins were later grouped into three stratified bins to accommodate equal variance in sampling effort, hereafter referred to as shallow, mid, and deep.

Species composition

Family Scorpaenidae was the most speciose family (15 species), followed by Hexagrammidae (4 species) and Pleuronectidae (3 species). In general, Aurora/Splitnose and Vermilion Rockfish were observed at high densities within narrow depth ranges (Figure 37). Halfbanded Rockfish and California Lizardfish densities were evenly distributed across the depth gradient. Blackeye Goby and Hundred-fathom Codling densities exhibited a clear inverse relationship with depth. Densities of Blackeye Goby decreased along a depth gradient from 20-170 m. Conversely, Hundred-fathom Codling
density steadily increased from 170-270 m. The greatest total number of species was observed at depths between 200-280m.

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Figure 37. Densities of commonly observed fish species for 15 depth-stratified bins across 21 transects in the La Jolla and Scripps Canyons.

Vertical patterns in richness and abundance

Abundance and richness (number of species per depth bin) were correlated (Figure 38) and exhibited similar spatial patterns in shallow and mid depths (0-200 m); however, abundance and richness showed a clear divergence in depths greater than 200 m (Figure 39). ANOVAs revealed a significant difference in richness among the different depth strata, but no significant difference was found between abundance and depth (Table 16). The greatest species richness was observed in the deep 300 m bin. Despite the lack of a significant relationship between abundance and depth, abundance appeared to be greatest in depths shallower than 200 m (Figure 39). It should also be noted that abundance and richness co-varied with each other and were independently strongly correlated with depth (Figure 38).

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Figure 39. Bar graphs of demeral fish species richness and abundance across 3 depth- stratified bins (100 m, 200 m, 300 m) along the walls of the La Jolla and Scripps Canyons.

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Generalized Linear Models (GLMs) were used to determine the best predictors of species richness and abundance across depth, temperature, slope, and ruggedness gradients using a poisson error structure defined as: Richness, Abundance = exp [μ + ẞ0*(depth) + ẞ1*(temperature) + ẞ2*(slope) + ẞ3*(ruggedness) + ɛ] Where μ = model intercept, ẞx = regression coefficient (i.e., relative influence of treatment), and ɛ = unexplained model error. Akaike’s Information Criterion (AIC) was used to select the most robust predictive models for species richness and abundance. Results showed that depth, slope, and ruggedness were relatively strong significant predictors of species richness and abundance (Tables 16 and 17). Among all factors analyzed in this study, depth had the greatest influence on species richness, but did not significantly contribute to variation in abundance. These trends suggest that variation in canyon dynamics across depth strata may facilitate different community structures, but have little effect on overall abundance. Slope and ruggedness were the strongest
predictors of abundance and also significantly influenced species richness. In both models, temperature did not significantly contribute to any variation in species richness or abundance.

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Table 16. Results of ANOVA tests for differences in richness and abundance between three depth-stratified bins.

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Table 17. Regression coefficients from GLM’s for richness and abundance.

The La Jolla and Scripps submarine canyons were comparatively high in demersal fish species richness (37 species) when compared to the entire South Coast study region (51 species); however, richness in the canyon was low when compared to other shelf studies around the southern California Bight. For example, an eleven-year submersible study in similar depths (19-365 m) found more than 137 species on the continental shelf (Love et al. 2009). This study suggested selective fishing pressure on large adult fish may increase species richness by allowing other smaller species to thrive. The overall low species richness and high abundance observed in the canyon may be due to the lack of fishing pressure, which could be naturally mediated by the physical steepness of the canyon walls (Yoklavich et al. 2011). Further analyses of canyon fish communities and their responsiveness to marine protected areas is necessary to provide a more detailed
insight into demersal fish community structure between depth strata, and along the canyon walls.

Variability Between Years

This project, as described above, was conceived and implemented as a one-year baseline against which any future changes could be compared. Given that our sampling was conducted essentially at the moment of designation for the SC MPAs, we were not focused on any “MPA effects” either. Further, as depicted below in Figure 40 for La Jolla, in selected cases sampling was not equivalent from one year to the next. However, as questions inevitably arise about differences between sampling years, and between inside MPAs and outside MPAs, we have included a brief summary of the differences in our observations of selected organisms and substrate attributes between years.

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Figure 40. Proportion of observed substrate types between years and protection status at La Jolla. The majority of substrates observed for both years were ‘Soft.’ ‘Hard’ substratewas less common in 2011 data than in 2012, particularly in the MPAs.

Table 18. Variability between years and density in protected and unprotected areas for all fishes observed at the La Jolla Area study site.

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Table 18 continued. Variability between years and density in protected and unprotected areas for all fishes observed at the La Jolla Area study site.

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Variability Inside and Out of MPAs

To interpret the densities of fishes observed inside vs. outside MPAs, as well as over hard vs. soft substrates, we used a generalized linear model (GLM), such that: Density ~ μ + exp [ β1 (Treatment) + β2 (Substrate) + ɛ
Where μ = model intercept, exp = negative binomial correction, βx = regression coefficient, and ɛ = unexplained error. We used a negative binomial correction to account for zero-inflated data for each of the seven fish or fish groups. The model output provides the relative influence of each treatment (inside vs. outside, hard vs. soft) on the overall abundance of each species/complex. It does not tell us if there is a significant difference between terms (e.g., in vs. out), but it is useful for determining potential factors that may be driving observed patterns in abundance. At the time of baseline data collection, the MPA treatment (in/out) was not significant for any of the suggested long-term monitoring organisms. Substrate (hard/soft) played a significant role in describing only the distribution of Halfbanded Rockfish (p = 3.95E-06)

Table 19. GLM results showing differences in density for seven of the suggested long- term monitoring fishes at Catalina.

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Analytical Products Derived from Baseline Data

One of our primary goals beyond the collection of the baseline data described throughout this report was to utilize those data for synthetic analyses that will allow us to extrapolate beyond the relatively limited scope of our actual sampling to areas and MPAs that were not sampled. Perhaps the most effective approach to achieving this goal has been to marry the precisely geo-referenced ROV-derived data with the topographic maps generated as part of the California Seafloor Mapping Project, provided at two meter resolution for nearly all of California Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 284state waters. Below are brief descriptions of two such on-going projects, one that describes the distributions of fishes and invertebrates with depth along the shelf and slope elsewhere throughout the sampled areas, and one that
depicts the distributions of two key invertebrate species throughout the sampled areas. Further, the photographic and videographic imagery collected by this project is now part of a permanent archive of imagery housed at the Institute for Applied Marine Ecology at CSUMB and with MARE. In total, the archive now includes over 60,400 still photographs and more than 600 hours of video collected across the North Central Coast, Central Coast, and South Coast Study Regions of the Marine Life Protection Act, as well as the recent addition of San Clemente Island.

Distribution of Selected Fishes and Invertebrates on the Outer Continental Shelf and Slope – Sarah Finstad

The goal of this project is to identify patterns of depth-stratified community structure within South Coast marine protected areas. The shallow continental shelf rapidly drops off close to shore in many parts of southern California and a nontrivial portion of South Coast MPAs contain these deep, slope habitats. Much of our understanding of deep-sea communities comes from fisheries data and research trawls, which fail to provide fine- scale information on community structure in these habitats. If we are to appropriately manage the species that occur along the deep slope, it is critical that we understand the
patterns of community structure. The ROV video transects of deep-sea ecosystems within the South Coast region provide an excellent opportunity to enhance our understanding of these rarely seen habitats. Vertical (traveling upslope) ROV video transects of slope habitats were collected at 15 locations within the four study sites. Survey effort (area surveyed) was estimated within each 10 m depth bin using values collected from video imagery and ROV navigation data. The survey effort value was used to standardize count data to densities, which yielded values in the form of number of individuals per square meter surveyed at a particular depth. Density was calculated for values across all transects for the seven most abundant fish species, most rockfish species, and select mobile invertebrates. Future work on this project will include a similarity analysis to identify unique communities and modeling to determine which environmental factors are primarily driving community divisions. Additional analyses will also include available substrate values into the effort standardization process.

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Figure 41. Locations of vertical transects.

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Figure 42. Area surveyed on vertical transects by depth, with different shades of blue representing the study sites. Point Vicente and Catalina transects generally covered greater depths, while Laguna and La Jolla transects generally covered shallower depths. The greatest sampling effort occurred over moderate depths, between approximately 70 and 200 m. Ten meter depth bins were used for tabulation.

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Figure 43. Density of the most abundant fish species on vertical transects by depth.

Highest densities were observed in Aurora/Splitnose Rockfish, Dogface Witch-eel, and Halfbanded Rockfish. Aurora/Splitnose Rockfish maximum observed density occurred at a depth of 350 meters, Dogface Witch-eel maximum observed density occurred at a depth of 380 m, and Halfbanded Rockfish maximum observed density occurred at a depth of 50 m. Halfbanded Rockfish showed a general decline in density with depth, while Aurora/Splitnose Rockfish and Dogface Witch-eel showed a general increase in density with depth. California Lizardfish were observed at a relatively constant density between 70 and 160 m. Only fish positively identified to species were included.

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Figure 44. Density of rockfish species on vertical transects by depth. Rockfish were observed over the entire surveyed depth range, with the greatest densities at the shallowest and deepest parts of the observed range. Aurora/Splitnose and Halfbanded Rockfish had the highest observed densities, which occurred at a depth of 350 and 50 m, respectively. Sebastomus spp., Greenstripe Rockfish, and Stripetail Rockfish occurred over the same approximate depth range (100 – 270 m) with similar densities. Swordspine Rockfish were observed at a relatively constant density over a narrow depth range (180 – 250 m). Only rockfish species where n>5 were included.

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Figure 45. Observed density of mobile invertebrate species on vertical transects by depth. Highest densities were observed in Ridgeback Prawns, Spot Prawns, and Squat Lobsters, at 170, 240, and 260 m, respectively. Octopus were observed at a relatively constant density across the depth range surveyed. Crabs were observed across the entire depth range surveyed, but with a patchy distribution. Spot Prawns were observed in two patches, from 60 to 90 m and from 160 to 260 m. Ridgeback Prawns and Spot Prawns both were displayed a maximum observed density near the midpoint of their observed ranges. Some species of mobile invertebrates observed on vertical transects were not included in this analysis.

Distribution of prawns across benthic habitats in Southern California – Rhiannon McCollough

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Prawns are an important commercial fishing industry in Southern California. A better understanding of the habitat features with which prawns associate
will provide a stronger foundation for conserving and managing them and other related species, particularly where spatial management regimes such as marine protected areas (MPAs) are either in place or planned. In this study, geo-referenced points of both Spot Prawns (Pandalus platyceros) and Ridgeback Prawns (Sicyonia ingentis) were collected with the use of videographic imagery taken with a remotely operated vehicle (ROV) inside and adjacent to MPAs off the Southern California coast at Point Vicente, La Jolla and along the Laguna Beach shoreline. The georeferenced observations and the habitat attributes, depth and
slope, were mapped with the use of ArcGIS. Marine Geospatial Ecology Tools (MGET) in ArcGIS will also be used in future analyses to better understand the influences these and other attributes have on both prawn species’ distribution within and across all sites. A preliminary example of this is shown with the La Jolla Study Site (Figure 49). Overall, prawns were seen ranging in depths from 80-240m and slopes from 0-85o . Most commonly, Ridgeback Prawns occurred most commonly at depths of 140-200m and slopes of 10-20o, while Spot Prawns occurred most commonly at deeper depths of 160-220m, and at steeper slopes of 25-45o. The following are the depth and slopebreakdowns for each site.

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Figure 46. At the Point Vicente Study Site prawns were observed at depths ranging from 100-240m and slopes from 5-50o. Specifically, Ridgeback Prawns (n=512) were observed in more shallow areas (max depth = 200m) and along less steep slopes (10- 50o), while Spot Prawns (n=12) were observed deeper (200-240m) and steeper (15-35o).

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Figure 47. At the Laguna Study Site prawns were observed at depths ranging from 140-220m and slopes from 10-20o. Specifically, Ridgeback Prawns (n=418) were observedover a greater depth (140-220m) and slope range (10-20o) than Spot Prawns (n=4; 210-220m; 10o).

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Figure 48. At the La Jolla Study Site prawns were observed at depths ranging from 70-240m and slopes of 0-80o. Specifically, Ridgeback Prawns (n=238) were observed inmore shallow areas (max depth = 200), while Spot Prawns (n=390) were observeddeeper (70-240m). Both Species were observed over the same slope range (0-80o).

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Figure 49. Habitat suitability maps were created with parameters of depth and slope topredict the likelihood of Spot Prawn (left) and Ridgeback Prawn (right) presence at the LaJolla study site. Areas with high likelihood of occurrence are depicted in red, while lowlikelihood of occurrence is in yellow. Spot Prawns have a greater likelihood of occurrencedeep in the canyon, while Ridgeback Prawns are more likely to occur along the canyon’sshelf break. Neither prawn species is likely to be seen on the shallow, less sloped areaspreceding the canyon drop.

Moving Forward with Long-term Monitoring

Now that the baseline characterization of the South Coast Study Region is complete,opportunities for long-term monitoring can be considered. It appears clear from the past three years that the increasing participation of citizen science groups in monitoring activities is going to provide at least some support for monitoring in the nearshore ecosystems, including the sandy and rocky intertidal (various programs), kelp forests(primarily Reef Check California), and sea birds (various programs). These programs have the advantage of covering fairly large areas at little to no cost to the state. There are also several long-term monitoring programs in place by academic and government agencies in the region.

In the deeper ecosystems off-shore, those generally below the effective depth of SCUBA sampling Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 295(such as the areas sampled for this report) the likelihood of a strong citizen-based monitoring program coming to the fore is probably very low; working in the deep water is costly, including vessel support, vehicle support (ROV, submersible, camera sled), and the personnel necessary to operate both. And yet, despite the associated cost, the non-invasive sampling of marine ecosystems using imagery platforms has important advantages with so many marine populations at historically-low levels.

We believe it is critical to continue to sample in the deep subtidal, but precisely how that sampling will be conducted depends very much on the intersection of ecosystems/species/habitats with budgets and timelines. For instance, we know from the
results of other projects that ROV surveys would need to occur more frequently (than the once per year conducted during the baseline) to capture the key attributes of many targeted ecosystems and/or species in the resolution necessary to support monitoring. But such sampling would require a non-trivial adjustment in the project budget. Those budgetary issues might be addressed by a different and potentially less expensive tool
(such as camera sled, video lander, or other platforms for video cameras), but the different tool would raise other operational questions that would have to be addressed.
Given all these variables and the nearly infinite number of combinations that would need to be considered to develop a comprehensive monitoring plan, we finish here by discussing which species and/or species complexes could be monitored effectively, leaving the how to future discussions. Based on our experience thus far, we think that one approach may be to identify thosespecies (fishes and invertebrates) that are a) observed in numbers that are appropriate for particular statistical analyses and b) are capable of being identified with a high level of confidence from imagery alone. This list will vary depending on the ecosystem, the imagery platform, and the visibility on any given day, and it may not necessarily include many of the species of interest for managers. However, it may provide an option for moving forward nonetheless.

Jan 2015 - South Coast Marine Protected Areas Baseline Characterization and Monitoring of Mid-Depth Rocky and Soft-Bottom Ecosystems (20-350m) 296Below we provide a first pass at a group of species and species complexes, including fishes as well as mobile and sessile invertebrates, that are capable of being monitored in this way and were observed during the baseline characterization effort in the South Coast. While we expect that many scientists could reach agreement on some of the organisms on this list, it is also likely that much discussion could be engendered to flesh this group out further. What we provide here is intended as a point of departure for discussion as each of the MLPA regions moves beyond baseline characterization.

Fishes – These eight species/species complexes were present in large numbers at one or more of the four study areas. Further, all are readily identifiable from video and/or still photographs.

Aurora/Splitnose Rockfish Complex…………………………………………….. 97
California Sheephead ……………………………………………………………….. 98
Halfbanded Rockfish ………………………………………………………………… 99
Lingcod …………………………………………………………………………………. 100
Pink Surfperch………………………………………………………………………… 101

Sanddab Complex (Citharichthys spp.)………………………………………. 102
Squarespot Rockfish ………………………………………………………………. 103
Vermilion/Canary/Yelloweye Rockfish Complex ………………………….. 104

Mobile Invertebrates – Similar to fishes above, these mobile invertebrates were both seen frequently across the study areas.

Ridgeback Prawn ……………………………………………………………………. 105
Spot Prawn…………………………………………………………………………….. 106
California Sea Cucumber ………………………………………………………… 107

Structure-forming Invertebrates – This category presents perhaps the greatest challenge. There are a great many species that could be included here, many of which have been observed serving as biogenic habitat for demersal fishes.

California Hydrocoral ………………………………………………………………. 108
Sea Whips and Pens……………………………………………………………….. 109
Gorgonians…………………………………………………………………………….. 110

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Conclusion

Participants in this baseline project represented a broad collaborative partnership among academia, non-profit organizations, state and federal agencies, and members of the fishing community, constituents that have not always collaborated effectively. All project imagery resides at the Institute for Applied Marine Ecology at California State University Monterey Bay (CSUMB) and at Marine Applied Research and Exploration (MARE). All baseline data collected as part of this project will be uploaded to the MPA Monitoring Enterprise’s Ocean Spaces website. We also have a number of longer term analyses underway, two of which are described above in the Analytical products derived from baseline data. These projects explore the distribution and habitat utilization of fishes and key mobile invertebrates at multiple locations across the study area using the high-resolution bathymetric maps produced by the California State Mapping Project. The final results of these projects and more will be available for the five year review of the south coast MPAs.

Financial Reports

Institute for Applied Marine Ecology (IfAME) at CSU Monterey Bay

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Salary and benefits – Spending on salary closely matched the budgeted amount over the course of the grant period. However, benefits were paid at a higher rate than anticipated due to the annual fluctuation of fringe rates administered by the University Corporation. In general, salaries were paid to the PI for project supervision and oversight, to research staff for data management, analysis, and reporting, and to graduate student assistants for data collection and entry and QA/QC checking of baseline survey data. Note: some of the variance in the current budget is the result of a lag in internal CSUMB budget processes.
We expect the final report budget to be complete. Supplies – Funding was spent on computers, hard drives and tapes for data (imagery) storage, video recording equipment, and other items required for collecting data in the field and processing imagery in the lab.
Travel – Funding supported staff and student assistant travel to/from study sites for data collection and to conferences and PI meetings for sharing of results and collaborative discussions.
Funds and descriptions refer to expenditures as of 12/31/2014.Subsequent expenditures will utilize the remaining funds via the no-cost extension (granted through 6/30/2015).

Marine Applied Research and Explorations (MARE)

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Salaries and Benefits: Spending on salary matched the budgeted amount over the course of the grant period. In general, salaries were paid to the co-PI for project supervision and oversight, to offshore ROV operations staff for operations at sea (preparing and mobilizing the ROV aboard ship, operating the ROV offshore, and demobilizing equipment back to the workshop), research staff for navigational geo- referencing of transect locations surveyed, and review of the final report.

Supplies: Funding was spent on video recording tapes and DVDs, consumables such as zip-ties, potting compound, replacing failed underwater matable connectors and electrical joystick, electrical adaptors, stereo sizing software, and other items required for collecting data in the field.
Travel: Funding supported staff and subcontractor travel to/from study sites for data collection and to conferences and PI meetings for sharing of results and collaborative discussions.
Other Costs: Funding was spent primarily on lease of the ROV for offshore operations, and standby readiness of a standby ROV to make use of contracted ship time, and a motorized launch to ferry staff from ship to port.
Ship Time: Funding was used to lease the F/V Donna Kathleen, for mobilization, operational and weather days performing offshore ROV surveys, and demobilization of equipment back ashore.
Funds and descriptions refer to expenditures as of 12/31/2014.Subsequent expenditures will utilize the remaining funds via the no-cost extension (granted through 6/30/2015).

References
Butler JL, Love MS, Laidig TE. 2012. A Guide to the Rockfishes, Thornyheads, and Scorpionfishes of the Northeast Pacific. London: Univeristy of California Press. 184p. Carr MH. 2013. State of the California Central Coast: results from baseline monitoring of marine protected areas 2007–2012. California Ocean Science Trust and California Department of Fish and Wildlife, California, USA.

de Marignac J, Hyland J, Lindholm J, DeVogelaere A, Balthis WL, Kline D. 2009. A comparison of seafloor habitats and associated benthic fauna in areas open and closed to bottom trawling along the central California continental shelf. Marine Sanctuaries Conservation Series NMSP-09. U.S. Department of Commerce, National Oceanic and Atmospheric Administration, National Marine Sanctuary Program, Silver Spring, MD. 42 pp.

Greene HG, Yoklavich MM, Starr RM, O’Connell VM, Wakefield WW, Sullivan DE, McRea Jr. JE, and Cailliet GM. 1999. A classification scheme for deep seafloor habitats. Oeanologica Acta 22(6): 663-678.

Humann P, DeLoach N. 2008. Coastal Fish Identification: California to Alaska. Jacksonville: New World Publications. 277p.

Hallenbeck T, Kvitek R, Lindholm J. 2012. Rippled scour depressions add ecologically significant heterogeneity to soft bottom habitats on the continental shelf. Marine Ecology Progress Series 468: 119-133.

Kramer DE, Barss WH, Paust BC, Bracken BE. 1995. Guide to Northeast Pacific Flatfishes: Families Bothidae , Cynoglossidae, and Pleuronectidae. Fairbanks: Alaska Sea Grant College Program. 112p.

Lamb A and BP Hanby. 2005. Marine Life of the Pacific Northwest. British Columbia, Canada: Harbour Publishing. 398pp.
Larson ML. 2001. Spot Prawn. In: Leet WS, Dewees CM, Klingbeil R, Larson EJ, editors. California’s Living Marine Resources: A Status Report. California:
Department of Fish and Game; p 121-123.

Lindholm J, Auster P, Valentine P. 2004. Role of a large marine protected area for conserving landscape attributes of sand habitats on Georges Bank (NW Atlantic). Marine Ecology Progress Series 269: 61-68.

Love MS, Yoklavich M, Schroeder DM. 2009. Demersal fish assemblages in the Southern California Bight based on visual surveys in deep water. Environmental
Biology of Fishes, 84:55-68

Love MS. 2011. Certainly More Than You Want to Know About The Fishes of the Pacific Coast: A Postmodern Experience. Santa Barbara, CA: Really Big Press.
672p.

Starr, RM. 2010. Baseline surveys of nearshore fishes in and near Central California marine protected areas 2007-2009. California Sea Grant College Program.

Sunada JS, Richards JB. 2001. Ridgeback Prawn. In: Leet WS, Dewees CM, Klingbeil R, Larson EJ, editors. California’s Living Marine Resources: A Status Report. California: Department of Fish and Game; p 124-126.

Tamsett A, Heinonen K, Auster PJ, Lindholm J. 2010. Dynamics of hard substratum communities inside and outside of a fisheries closed area in Stellwagen Bank National Marine Sanctuary (Gulf of Maine, NW Atlantic). Marine Sanctuaries Conservation Series ONMS-10-05. 53pp.

Tissot BM, Yoklavich MM, Love MS, York K, Amend M. 2006. Benthic invertebrates that form habitat on deep banks off southern California, with special reference to deep sea coral. Fish Bulletin 104:167-181.

Yoklavich MM, Greene HG, Gailliet GM, Sullivan DE, Lea RN, Love MS. 2011. Habitat associations of deep-water rockfishes in a submarine canyon: an example of a natural refuge. Fish Bulletin, 98(3)

Appendix – ROV Operations

Imagery Collection Cruise aboard F/V Donna Kathleen: 04 – 19 November 2011
This log describes the first of two cruises conducted for the larger study. It represents the first baseline survey through which we refined the sampling regime and subsequent data collection and analyses from the imagery gathered. A day-by-day breakdown ofoperations completed is provided in Table X below.

Table A1. Summary of daily operations for November 2011.

Imagery Collection Cruise aboard F/V Donna Kathleen: 11 November – December 2012
This log describes the first of two cruises conducted for the larger study. It represents the first baseline survey through which we refined the sampling regime and subsequent data collection and analyses from the imagery gathered. A day-by-day breakdown of operations completed is provided in Table X below.

Table A2. Summary of daily operations for November-December 2012.

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