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Short Citation:
Southeast Fisheries Science Center, 2022: Cetacean and sea turtle spatial density model outputs from visual observations using line-transect survey methods aboard NOAA vessel and aircraft platforms in the Gulf of Mexico from 2003-06-12 to 2019-07-31 (NCEI Accession 0256800), https://www.fisheries.noaa.gov/inport/item/67830.

Item Identification

Title: Cetacean and sea turtle spatial density model outputs from visual observations using line-transect survey methods aboard NOAA vessel and aircraft platforms in the Gulf of Mexico from 2003-06-12 to 2019-07-31 (NCEI Accession 0256800)
Status: Completed
Publication Date: 2022-07-29
Abstract:

Based on ship-based and aerial line-transect surveys conducted in the U.S. waters of the Gulf of Mexico between 2003 and 2019, the NOAA Southeast Fisheries Science Center (SEFSC) developed spatial density models (SDMs) for cetacean and sea turtle species for the entire Gulf of Mexico. SDMs were developed using a generalized additive modeling (GAM) framework to determine the relationship between species abundance and environmental variables (monthly averaged oceanographic conditions during 2015 - 2019). Models were extrapolated beyond the U.S. Gulf of Mexico to provide insight into potential high density areas throughout the Gulf of Mexico. However, extrapolations of this type should be interpreted with caution. This dataset includes 19 shapefiles for the SDMs for each cetacean and sea turtle species or species group.

Purpose:

The goal of this research was to develop Gulf-wide cetacean and sea turtle spatial density models (SDMs) based on line-transect surveys conducted in the U.S. waters of the Gulf of Mexico. Surveys used to develop the SDMs for species occupying continental shelf and oceanic waters of the Gulf of Mexico were conducted during the GoMMAPPS project and comparable-prior-year surveys. Aerial survey data from seasonal surveys conducted during 2011/2012 and 2017/2018 (GoMMAPPS Surveys) were used to develop SDMs for cetacean and sea turtle species over the continental shelf. Data collected from vessel surveys, including the two-team surveys conducted during summer 2017, winter 2018, and summer/fall 2018 (GoMMAPPS Surveys) and 2003, 2004, and 2009 (that included only one survey team), were used to develop SDMs for cetaceans in oceanic waters. In addition, for Rice's whales, surveys conducted in 2018 and 2019 were also used in developing the SDMs specific for this species. Habitat-based species distribution models were developed using a generalized additive modeling (GAM) framework to determine the relationship between cetacean and sea turtle abundance and environmental variables. Samples for modeling were created by summarizing survey effort and environmental variables with a hexagon grid developed by the Environmental Protection Agency expanded to fit the entire Gulf of Mexico. The grid was created in a Lambert azimuthal equal area projection and the area of each hexagon is 40 km2. For all hexagons that contained survey effort segments, cetacean and sea turtle density was calculated using total number of animals observed, segment effort length and average sighting condition covariates in the hexagon, and the parameters estimated in distance sampling abundance models. Oceanographic variables were used as dynamic covariates in SDMs and were obtained from multiple sources that included both remotely sensed data and hydrographic model output. Data products were obtained from their respective sources at varying temporal and spatial resolutions. To develop the explanatory variables for the SDMs, we summarized each data source spatially by overlaying the hexagon grid and calculating the average variable for each cell at the highest temporal resolution available. These data were then matched to the survey effort data so that each trackline segment in each grid cell. The survey effort segments were the sampling unit in the spatial density models (SDMs). For prediction maps, we developed monthly averages of the gridded data for all survey years from 2003-2018. Species were visually identified to the lowest taxonomic level possible. For sea turtles, oceanic dolphins and small whale species, sightings that could not be identified to the species level were apportioned among the identified species based upon spatial density models (SDMs) for these taxa groups (Hardshell sea turtle, Unidentified Stenellid Dolphins, Unidentified Dolphins, and Unidentified Small Whales). In addition, for beaked whales species, genera Ziphius and Mesoplodon, very few sightings could be identified to species, and therefore all species were combined into a common "beaked whale" category for this analysis. Likewise, killer whales, false killer whales, pygmy killer whales, and melon-headed whales were combined into a Blackfish category, given the relatively infrequent encounters with these species and difficulty to identify them to species level. The final resulting SDMs therefore account for both identified and unidentified sightings. Prediction maps were developed for each species or species group based upon the monthly averaged oceanographic conditions during 2015 - 2019. The appropriate SDM was used to predict animal density in each 40 km2 spatial cell for either shelf or oceanic waters for each month. The coefficient of variation (CV) of the density estimate (based upon uncertainty in the GAM model fit) is used to display the level of precision of the model and identify regions of high density and high uncertainty where model extrapolation is less reliable. Abundance estimates for each month are the sum of predicted abundance in each spatial cell. These estimates vary in response to dynamic oceanographic variables.; Data Quality Method: SDMs include a combination of two modeling approaches to address potential sources of bias and develop species-habitat relationships that are used to develop spatially and temporally explicit predictions of animal density. For aerial surveys, two survey teams were used in all surveys, and a combined MRDS model was developed to estimate detection probability in the survey strip. In the case of vessel surveys, a detection probability function was estimated using data from the flying bridge survey team for all surveys (2003-2018) using multiple covariate distance (MCDS) function models. While the probability of detection on the trackline was developed using MRDS methods from the 2017-2018 surveys. For each species or species group, the best multiple covariate distance sampling (MCDS) model was selected by first examining the distribution of perpendicular sighting distances (PSD) and selecting an appropriate right truncation distance and key function. Then, all combinations of detection covariates were considered, and the model with the lowest AIC was selected. For the MCDS model, the relationship between group size and detection distance was examined, and the log of group size was included as a covariate where there was a statistically significant correlation. Following selection of the MCDS portion of the model, detection probability covariates were considered for inclusion in the MRDS model along with distance from the trackline and observer platform (flying bridge or bridge wings). Following the selection of the best MRDS model, the second component of the SDM was implemented to develop species-habitat relationships. The sampling units for the SDM model were the segments of on-effort trackline within each grid cell for each survey. For each segment, the searched area was calculated as the product of the segment length, the surveyed strip width (based on the truncation distance from the MRDS model) and the estimated detection probability within the segment predicted from the MRDS model and the appropriate detection probability covariates on the survey strip. This searched area was included as an offset term in the SDM. The response variable was the total number of a particular species (or species group) observed on a given segment. A GAM was used to quantify the effect of habitat variables on animal density using a log count model assuming a Tweedie error distribution to account for overdispersed (i.e., zero-inflated) count data. An initial GAM model was fit using all available oceanographic and physiographic variables. A reduced model was then selected including only model terms with p-value < 0.2. This reduced model was compared to the full model using AIC to ensure selection of the best fitting, most parsimonious model. Model fit was assessed through the examination of randomized quantile residuals and the associated Q-Q plot for deviance residuals. While the two-team approach accounts for the likelihood of detection on the trackline of groups that are available at the surface, it does not account for those that are underwater while in the viewing area of the vessel (beaked and sperm whales). For these two taxa, we applied an additional correction for availability. Tag data that recorded sperm whale or beaked whale dive-surface behavior were reviewed to obtain estimated dive and surface durations. The resulting correction factor was included in the SDM to obtain an unbiased estimate of sperm whale and beaked whale density and abundance..

Notes:

All cetacean data were collected under the National Marine Fisheries Service (NMFS), the Marine Mammal Protection Act (MMPA) and Endangered Species Act (ESA) permit number: NMFS ESA/MMPA Permit No.779-1633 and No.14450.

Other Citation Details:

Cite as: Litz, Jenny; Aichinger Dias, Laura; Rappucci, Gina; Martinez, Anthony; Soldevilla, Melissa; Garrison, Lance; Mullin, Keith; Barry, Kevin; Foster, Marjorie (2022). Cetacean and sea turtle spatial density model outputs from visual observations using line-transect survey methods aboard NOAA vessel and aircraft platforms in the Gulf of Mexico from 2003-06-12 to 2019-07-31 (NCEI Accession 0256800). [indicate subset used]. NOAA National Centers for Environmental Information. Dataset. https://doi.org/10.25921/efv4-9z56. Accessed [date]

Supplemental Information:

Related Funding Agencies: U.S. Department of Interior (DOI), Bureau of Ocean Energy Management (BOEM), the U.S. Department of Commerce (DOC), National Oceanic and Atmospheric Administration (NOAA), National Marine Fisheries Service (NMFS), Southeast Fisheries Science Center (SEFSC), NOAA Office of Response and Restoration (ORR), United States Navy and the NOAA RESTORE Science Program.

DOI (Digital Object Identifier): 10.25921/efv4-9z56
DOI Registration Authority: NOAA
DOI Issue Date: 2022-07-29

Keywords

Theme Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Data Center Keywords
DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
Global Change Master Directory (GCMD) Data Center Keywords
DOC/NOAA/NESDIS/NODC > National Oceanographic Data Center, NESDIS, NOAA, U.S. Department of Commerce
Global Change Master Directory (GCMD) Data Center Keywords
DOC/NOAA/NMFS/SEFSC > Southeast Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MAMMALS > CETACEANS
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MARINE MAMMALS
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MARINE MAMMALS > DOLPHINS
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > REPTILES > TURTLES > SEA TURTLES
World Register of Marine Species (WoRMS)
Balaenoptera ricei View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Caretta caretta View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Chelonia mydas View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Dermochelys coriacea View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Feresa attenuata View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Globicephala View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Grampus griseus View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Kogia View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Lepidochelys kempii View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Mesoplodon View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Orcinus orca View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Peponocephala electra View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Physeter macrocephalus View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Pseudorca crassidens View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Stenella attenuata View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Stenella clymene View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Stenella coeruleoalba View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Stenella frontalis View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Stenella longirostris View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Tursiops truncatus View WoRMS Aphia Record
World Register of Marine Species (WoRMS)
Ziphius View WoRMS Aphia Record
UNCONTROLLED
ESA/MMPA Permit Number 14450
ESA/MMPA Permit Number 779-1633
NCEI ACCESSION NUMBER 0256800
NCEI ACCESSION NUMBER 256800
NODC DATA TYPES THESAURUS cetacean
NODC DATA TYPES THESAURUS DOLPHINS
NODC DATA TYPES THESAURUS MARINE MAMMALS
NODC DATA TYPES THESAURUS SEA TURTLES
NODC DATA TYPES THESAURUS species abundance
NODC PROJECT NAMES THESAURUS Gulf of Mexico Marine Assessment Program for Protected Species (GOMMAPPS)

Temporal Keywords

Thesaurus Keyword
UNCONTROLLED
None 2003-2019

Spatial Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Location Keywords
OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > CARIBBEAN SEA
Global Change Master Directory (GCMD) Location Keywords
OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF MEXICO
UNCONTROLLED
NODC SEA AREA NAMES THESAURUS Caribbean Sea
NODC SEA AREA NAMES THESAURUS Gulf of Mexico

Instrument Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Instrument Keywords
BINOCULAR > BINOCULAR
Global Change Master Directory (GCMD) Instrument Keywords
INCLINOMETERS
Global Change Master Directory (GCMD) Instrument Keywords
VISUAL OBSERVATIONS
UNCONTROLLED
NODC INSTRUMENT TYPES THESAURUS BIG EYE BINOCULARS
NODC INSTRUMENT TYPES THESAURUS Distance Sampling
NODC INSTRUMENT TYPES THESAURUS inclinometer
NODC INSTRUMENT TYPES THESAURUS Line Transect Sampling
NODC INSTRUMENT TYPES THESAURUS visual estimate
NODC INSTRUMENT TYPES THESAURUS visual observation

Platform Keywords

Thesaurus Keyword
Global Change Master Directory (GCMD) Platform Keywords
DHC-6 > DeHavilland Twin Otter
Global Change Master Directory (GCMD) Platform Keywords
SHIPS
UNCONTROLLED
NODC PLATFORM NAMES THESAURUS NOAA Ship Gordon Gunter
NODC PLATFORM NAMES THESAURUS NOAA Ship Pisces

Physical Location

Organization: National Centers for Environmental Information - Silver Spring, Maryland
City: Silver Spring
State/Province: MD
Location Description:

NCEI Archive

Data Set Information

Data Set Scope Code: Data Set
Data Set Type: Mixed
Maintenance Frequency: As Needed
Data Set Credit: Litz, Jenny; Aichinger Dias, Laura; Rappucci, Gina; Martinez, Anthony; Soldevilla, Melissa; Garrison, Lance; Mullin, Keith; Barry, Kevin; Foster, Marjorie (2022)

Support Roles

Author

CC ID: 1183256
Date Effective From: 2022
Date Effective To:
Contact (Person): Garrison, Lance
Address: 75 Virginia Beach Dr
Miami, FL 33149
Email Address: Lance.Garrison@noaa.gov
Phone: 305-361-4488
Fax: 305-361-4478
Business Hours: 8:00 AM - 4:30 PM EST/EDT

Author

CC ID: 1183215
Date Effective From: 2022
Date Effective To:
Contact (Person): Litz, Jenny
Address: 75 Virginia Beach Drive
Miami, FL 33139
Email Address: Jenny.Litz@noaa.gov
Phone: 305-361-4224
Fax: 305-365-4102

Author

CC ID: 1183216
Date Effective From: 2022
Date Effective To:
Contact (Person): Rappucci, Gina
Address: 75 Virginia Beach Drive
Miami, FL 33149
Email Address: gina.rappucci@noaa.gov
Phone: (305) 361-4283

Author

CC ID: 1183217
Date Effective From: 2022
Date Effective To:
Contact (Person): Dias, Laura A
Address: 75 Virginia Beach Drive
Miami, FL 33149
Email Address: laura.dias@noaa.gov
Phone: (305) 361-4269

Author

CC ID: 1183218
Date Effective From: 2022
Date Effective To:
Contact (Person): Martinez, Anthony
Address: 75 Virginia Beach Drive
Miami, FL 33149
USA
Email Address: anthony.martinez@noaa.gov
Phone: 305-361-4486
Fax: 305-361-4478

Author

CC ID: 1183219
Date Effective From: 2022
Date Effective To:
Contact (Person): Soldevilla, Melissa
Address: 75 Virginia Beach Drive
Miami, FL 33149
USA
Email Address: melissa.soldevilla@noaa.gov
Phone: 305-361-4238

Author

CC ID: 1183221
Date Effective From: 2022
Date Effective To:
Contact (Person): Barry, Kevin
Address: 3209 Frederic St.
Pascagoula, MS 39568
Email Address: kevin.barry@noaa.gov
Phone: 228-549-1608
Fax: 228-769-9200

Author

CC ID: 1183220
Date Effective From: 2022
Date Effective To:
Contact (Person): Mullin, Keith D
Address: 3209 Frederic St.
Pascagoula, MS 39568
Email Address: keith.d.mullin@noaa.gov
Phone: 228-549-1632
Fax: 228-769-9200

Data Steward

CC ID: 1184376
Date Effective From: 2022
Date Effective To:
Contact (Person): Litz, Jenny
Address: 75 Virginia Beach Drive
Miami, FL 33139
Email Address: Jenny.Litz@noaa.gov
Phone: 305-361-4224
Fax: 305-365-4102

Distributor

CC ID: 1184369
Date Effective From: 2022
Date Effective To:
Contact (Organization): National Centers for Environmental Information - Silver Spring, Maryland (NCEI-MD)
Address: NOAA/NESDIS E/OC SSMC3, 4th Floor, 1351 East-West Highway
Silver Spring, MD 20910-3282
Phone: (301) 713-3277

Metadata Contact

CC ID: 1184379
Date Effective From: 2022
Date Effective To:
Contact (Person): Dias, Laura A
Address: 75 Virginia Beach Drive
Miami, FL 33149
Email Address: laura.dias@noaa.gov
Phone: (305) 361-4269

Extents

Currentness Reference: Ground Condition

Extent Group 1

Extent Group 1 / Geographic Area 1

CC ID: 1184375
W° Bound: -97.65
E° Bound: -80.366
N° Bound: 30.983
S° Bound: 17.766

Extent Group 1 / Time Frame 1

CC ID: 1184378
Time Frame Type: Range
Start: 2003
End: 2019

Access Information

Security Class: Unclassified
Data Access Policy:

Open to everyone

Data Access Constraints:

Open To Everyone

Distribution Information

Distribution 1

CC ID: 1184371
Start Date: 2022
End Date: Present
Download URL: https://www.ncei.noaa.gov/archive/archive-management-system/OAS/bin/prd/jquery/accession/download/256800
Distributor: National Centers for Environmental Information - Silver Spring, Maryland (NCEI-MD) (2022 - Present)
File Name: 256800.2.2.tar.gz
File Type: NCEI Archived Data Accession
File Size: ~ (184.776 MB)

URLs

URL 1

CC ID: 1183466
URL: https://www.doi.org/10.25921/efv4-9z56
Name: Landing Page NCEI Accession 0256800
URL Type:
Online Resource
Description:

Cetacean and sea turtle spatial density model outputs from visual observations using line-transect survey methods aboard NOAA vessel and aircraft platforms in the Gulf of Mexico from 2003-06-12 to 2019-07-31 (NCEI Accession 0256800)

Data Quality

Accuracy:

SDMs include a combination of two modeling approaches to address potential sources of bias and develop species-habitat relationships that are used to develop spatially and temporally explicit predictions of animal density. For aerial surveys, two survey teams were used in all surveys, and a combined MRDS model was developed to estimate detection probability in the survey strip. In the case of vessel surveys, a detection probability function was estimated using data from the flying bridge survey team for all surveys (2003-2018) using multiple covariate distance (MCDS) function models. While the probability of detection on the trackline was developed using MRDS methods from the 2017-2018 surveys.

For each species or species group, the best multiple covariate distance sampling (MCDS) model was selected by first examining the distribution of perpendicular sighting distances (PSD) and selecting an appropriate right truncation distance and key function. Then, all combinations of detection covariates were considered, and the model with the lowest AIC was selected. For the MCDS model, the relationship between group size and detection distance was examined, and the log of group size was included as a covariate where there was a statistically significant correlation. Following selection of the MCDS portion of the model, detection probability covariates were considered for inclusion in the MRDS model along with distance from the trackline and observer platform (flying bridge or bridge wings

Completeness Measure:

While the two-team approach accounts for the likelihood of detection on the trackline of groups that are available at the surface, it does not account for those that are underwater while in the viewing area of the vessel (beaked and sperm whales). For these two taxa, we applied an additional correction for availability. Tag data that recorded sperm whale or beaked whale dive-surface behavior were reviewed to obtain estimated dive and surface durations. The resulting correction factor was included in the SDM to obtain an unbiased estimate of sperm whale and beaked whale density and abundance

Conceptual Consistency:

For sea turtles, oceanic dolphins and small whale species, sightings that could not be identified to the species level were apportioned among the identified species based upon spatial density models (SDMs) for these taxagroups (Hardshell sea turtle, Unidentified Stenellid Dolphins, Unidentified Dolphins, and Unidentified Small Whales). In addition, for beaked whales species, genera Ziphius and Mesoplodon, very few sightings could be identified to species, and therefore all species were combined into a common 'beaked' whale" category for this analysis. Likewise, killer whales, false killer whales, pygmy killer whales, and melon-headed whales were combined into a 'Blackfish' category, given the relatively infrequent encounters with these species and difficulty to identify them to species level. The final resulting SDMs therefore account for both identified and unidentified sightings

Quality Control Procedures Employed:

For aerial surveys, two survey teams were used in all surveys, and a combined MRDS model was developed to estimate detection probability in the survey strip. In the case of vessel surveys, a detection probability function was estimated using data from the flying bridge survey team for all surveys (2003-2018) using multiple covariate distance (MCDS) function models. While the probability of detection on the trackline was developed using MRDS methods from the 2017-2018 surveys. For each species or species group, the best multiple covariate distance sampling (MCDS) model was selected by first examining the distribution of perpendicular sighting distances (PSD) and selecting an appropriate right truncation distance and key function. Then, all combinations of detection covariates were considered, and the model with the lowest AIC was selected. For the MCDS model, the relationship between group size and detection distance was examined, and the log of group size was included as a covariate where there was a statistically significant correlation

Data Management

Have Resources for Management of these Data Been Identified?: No
Approximate Percentage of Budget for these Data Devoted to Data Management: Unknown
Do these Data Comply with the Data Access Directive?: Yes
Is Access to the Data Limited Based on an Approved Waiver?: No
If Distributor (Data Hosting Service) is Needed, Please Indicate: YES
Actual or Planned Long-Term Data Archive Location: NCEI-MD

Acquisition Information

Instruments

Instrument 1

CC ID: 1183944
Identifier: Big Eye Binocular
Instrument / Gear: Instrument
Instrument Type: binoculars
Description:

25x150 mm

Platforms

Platform 1

CC ID: 1183945
Identifier: NOAA Ship Gordon Gunter
Description:

The Gordon Gunter primarily serves the NMFS Pascagoula Laboratory in Mississippi. The Gordon Gunter is a 224-ft. multi-use platform. It is equipped with a thermosalinograph, CTD, fluorometer, and other oceanographic instruments that monitor atmospheric and oceanic conditions while traveling. A variety of research gears are deployed from the vessel including stern trawling, longlining, plankton tows, and dredging. The Gordon Gunter operates in all three SEFSC research areas.

Mounted Instrument 1

Identifier: Big Eye Binocular

Platform 2

CC ID: 1183947
Identifier: NOAA Twin Otter Aircraft
Description:

NOAA Twin Otter Aircraft

Mounted Instrument 1

Identifier: Big Eye Binocular

Platform 3

CC ID: 1184372
Identifier: Pisces (PC)
Docucomp UUID: 8ce0b2c0-19fa-11e1-bddb-0800200c9a66
Description:

The Pisces supports NOAA's mission to protect, restore, and manage the use of living marine, coastal, and ocean resources through ecosystem-based management. Her primary objective is to study, monitor, and collect data on a wide range of sea life and ocean conditions, primarily in U.S. waters from the Gulf of Mexico, Caribbean, and South Atlantic to North Carolina. The region includes important commercial and recreational fisheries, and is one of the world's best known and most productive marine areas. The data collected by the ship is used by scientists who study variation in ocean conditions and sea life to better inform the nation's decision makers about such issues as sustainable fisheries, ecosystem structure and function, fish habitats and habitat restoration, coral reefs, and protected species status. Pisces also observes weather, sea state, and other environmental conditions, conducts habitat assessments, and survey marine mammal and marine bird populations.

Mounted Instrument 1

Identifier: Big Eye Binocular

Catalog Details

Catalog Item ID: 67830
GUID: gov.noaa.nmfs.inport:67830
Metadata Record Created By: Lee M Weinberger
Metadata Record Created: 2022-09-06 09:29+0000
Metadata Record Last Modified By: Lee M Weinberger
Metadata Record Last Modified: 2022-10-06 08:04+0000
Metadata Record Published: 2022-09-23
Owner Org: SEFSC
Metadata Publication Status: Published Externally
Do Not Publish?: N
Metadata Last Review Date: 2022-09-16
Metadata Review Frequency: 1 Year
Metadata Next Review Date: 2023-09-16