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

Assessment of Warty Sea Cucumber Abundance at Anacapa Island

Final Report to:

Resources Legacy Fund Foundation

Grant #13319

March, 2019

Andrew Lauermann, Heidi Lovig, Greta Goshorn

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 4 ROV 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

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

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

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.

deepdirk2021-07-20T20:59:41-08:00March 1st, 2019|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

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.

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 14 control was used to help the pilot maintain a consistent forward velocity between 0.25 and 0.5 m/sec. A pair of Tritech® 500 kHz ranging sonars, which measure distance across a range of 0.1–10 m using a 6° conical transducer, were used as the primary method for measuring transect width for both the forward 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 Green June 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.

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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 20 identified 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 21 While, 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 total June 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 and June 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 26 Urchins 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 30 The 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 31 the 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 32 one 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.

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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.

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

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.

deepdirk2021-07-21T18:49:17-08:00June 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 5, 2017

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

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 COLLECTION

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 Operations

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 Enumeration

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

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

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).

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

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

SUBSTARTATE AND HABITAT

Substrate

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

Habitat

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

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

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

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

Fish

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 56 Of 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 57 higher 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 58 Structure 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 created June 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’.

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

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 67

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.

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.

June 2017 - Oceana Deep sea Coral and Sponge 2017 Final Report 78

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

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

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

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

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

Peter Etnoyer1

, Andrew Shuler2

, Janessy Frometa2

, Andrew Lauermann3

, Dirk Rosen3

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

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 83

Table of Contents

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

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

1. Expedition Overview

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

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

2. Narrative of Cruise Results

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

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

2.2 Objective 2: Conduct ROV seafloor surveys

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

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

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

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

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

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

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 84

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 85

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 86

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 87

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 88

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 89

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 90

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 91

8. Appendices

Appendix A: Operational notes

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

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

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

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

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

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

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 92

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 93

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 94

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 95

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 96

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 97

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 98

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

June 2016 - Cruise Report for ‘Patterns in Deep-Sea Corals’ Expedition 2016: NOAA ship Shearwater SW-16-08 99

craig lauderdale2021-03-10T21:24:06-08:00June 29th, 2016|research|

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

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

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

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 101

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 102
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 103

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 104

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 106

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

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.
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.
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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craig lauderdale2021-03-10T21:27:59-08:00April 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

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: 117 For 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

craig lauderdale2021-03-10T21:24:48-08:00June 29th, 2015|research|

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INTRODUCTION

METHODS

DATA COLLECTION

ROV Equipment

ROV Sampling Operations

POST-PROCESSING

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RESULTS

SURVEY TOTALS

SUBSTARTATE AND HABITAT

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Habitat

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Invertebrates

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REFERENCES

DOWNLOAD PDF

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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

DOWNLOAD PDF

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

Final Report to:

Resources Legacy Fund Foundation

Grant #13319

March, 2019

Andrew Lauermann, Heidi Lovig, Greta Goshorn

June 5, 2017

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

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

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