Marine Applied Research & Exploration

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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thesis, Illinois State University, USA. Unpublished [page number unkown].
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Zoologische Jahrbücher (Systematik) 35(2):219–270.
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2021-07-21T18:43:09-08:00August 19th, 2018|research|

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 12

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 13

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 14control 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.

June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 15
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 16 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 17
June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 18

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.

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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 20identified 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 21While, 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 22 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

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June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 24

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 25 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 26Urchins 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 27(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.

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June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 29

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 30The 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 31the 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 32one 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 33
June 2017 - Coastal Impact Assistance Program-E Soquel Canyon to Point Buchon 2017 34

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.

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

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

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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.

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

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

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

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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 42

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 43

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 44

METHODS

DATA COLLECTIONJune 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 45

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 46

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 47

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 48

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 49

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 50

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.

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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.

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

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Table 4. Continued.

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FISH AND INVERTEBRATE DENSITY

 

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

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 56Of 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 57higher 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 58Structure 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 59
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’.

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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

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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

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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).

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 69

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 79
2021-03-10T21:21:07-08:00June 1st, 2017|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 80

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).

April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 81

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 .

April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 82
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 83

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 84 April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 85

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.

April 2016 - It’s All About Your Network: Using ROVs to Assess Marine Protected Area Effectiveness 86

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: 87

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: 97For 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) 122

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) 123

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) 124

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) 125This 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) 127to 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) 128Insofar 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) 134estimated 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) 137video, 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) 140research 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) 141sessile 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) 142future 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) 194Despite 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) 207state 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) 218(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) 219Below 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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