67830
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 Set
Published / External
70317
Density of Cetaceans and Turtles in the Gulf of Mexico
Project
Completed
2022-07-29
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.
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..
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.
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]
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.
10.25921/efv4-9z56
NOAA
2022-07-29
Theme
Global Change Master Directory (GCMD) Data Center Keywords
DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce
Theme
Global Change Master Directory (GCMD) Data Center Keywords
DOC/NOAA/NESDIS/NODC > National Oceanographic Data Center, NESDIS, NOAA, U.S. Department of Commerce
Theme
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
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MAMMALS > CETACEANS
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MARINE MAMMALS
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MARINE MAMMALS > DOLPHINS
Theme
Global Change Master Directory (GCMD) Science Keywords
EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > REPTILES > TURTLES > SEA TURTLES
Theme
World Register of Marine Species (WoRMS)
Balaenoptera ricei
Theme
World Register of Marine Species (WoRMS)
Caretta caretta
Theme
World Register of Marine Species (WoRMS)
Chelonia mydas
Theme
World Register of Marine Species (WoRMS)
Dermochelys coriacea
Theme
World Register of Marine Species (WoRMS)
Feresa attenuata
Theme
World Register of Marine Species (WoRMS)
Globicephala
Theme
World Register of Marine Species (WoRMS)
Grampus griseus
Theme
World Register of Marine Species (WoRMS)
Kogia
Theme
World Register of Marine Species (WoRMS)
Lepidochelys kempii
Theme
World Register of Marine Species (WoRMS)
Mesoplodon
Theme
World Register of Marine Species (WoRMS)
Orcinus orca
Theme
World Register of Marine Species (WoRMS)
Peponocephala electra
Theme
World Register of Marine Species (WoRMS)
Physeter macrocephalus
Theme
World Register of Marine Species (WoRMS)
Pseudorca crassidens
Theme
World Register of Marine Species (WoRMS)
Stenella attenuata
Theme
World Register of Marine Species (WoRMS)
Stenella clymene
Theme
World Register of Marine Species (WoRMS)
Stenella coeruleoalba
Theme
World Register of Marine Species (WoRMS)
Stenella frontalis
Theme
World Register of Marine Species (WoRMS)
Stenella longirostris
Theme
World Register of Marine Species (WoRMS)
Tursiops truncatus
Theme
World Register of Marine Species (WoRMS)
Ziphius
Spatial
Global Change Master Directory (GCMD) Location Keywords
OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > CARIBBEAN SEA
Spatial
Global Change Master Directory (GCMD) Location Keywords
OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF MEXICO
Instrument
Global Change Master Directory (GCMD) Instrument Keywords
BINOCULAR > BINOCULAR
Instrument
Global Change Master Directory (GCMD) Instrument Keywords
INCLINOMETERS > INCLINOMETERS
Instrument
Global Change Master Directory (GCMD) Instrument Keywords
VISUAL OBSERVATIONS > VISUAL OBSERVATIONS
Platform
Global Change Master Directory (GCMD) Platform Keywords
DHC-6 > DeHavilland Twin Otter
Platform
Global Change Master Directory (GCMD) Platform Keywords
Ships
Theme
ESA/MMPA Permit Number
14450
Theme
ESA/MMPA Permit Number
779-1633
Theme
NCEI ACCESSION NUMBER
0256800
Theme
NCEI ACCESSION NUMBER
256800
Theme
NODC DATA TYPES THESAURUS
DOLPHINS
Theme
NODC DATA TYPES THESAURUS
MARINE MAMMALS
Theme
NODC DATA TYPES THESAURUS
SEA TURTLES
Theme
NODC DATA TYPES THESAURUS
cetacean
Theme
NODC DATA TYPES THESAURUS
species abundance
Theme
NODC PROJECT NAMES THESAURUS
Gulf of Mexico Marine Assessment Program for Protected Species (GOMMAPPS)
Temporal
2003-2019
Spatial
NODC SEA AREA NAMES THESAURUS
Caribbean Sea
Spatial
NODC SEA AREA NAMES THESAURUS
Gulf of Mexico
Instrument
NODC INSTRUMENT TYPES THESAURUS
BIG EYE BINOCULARS
Instrument
NODC INSTRUMENT TYPES THESAURUS
Distance Sampling
Instrument
NODC INSTRUMENT TYPES THESAURUS
Line Transect Sampling
Instrument
NODC INSTRUMENT TYPES THESAURUS
inclinometer
Instrument
NODC INSTRUMENT TYPES THESAURUS
visual estimate
Instrument
NODC INSTRUMENT TYPES THESAURUS
visual observation
Platform
NODC PLATFORM NAMES THESAURUS
NOAA Ship Gordon Gunter
Platform
NODC PLATFORM NAMES THESAURUS
NOAA Ship Pisces
National Centers for Environmental Information - Silver Spring, Maryland
Silver Spring
MD
NCEI Archive
Data Set
Mixed
As Needed
Litz, Jenny; Aichinger Dias, Laura; Rappucci, Gina; Martinez, Anthony; Soldevilla, Melissa; Garrison, Lance; Mullin, Keith; Barry, Kevin; Foster, Marjorie (2022)
67893
NCEI Accession 0256800 Zipped Data Files
Published / External
A total of 19 SDMs were developed for individual or groups of species, including:
1. Beaked whales (Ziphius and Mesoplodon spp.);
2. Pygmy or Dwarf sperm whales (Kogia spp.);
3. Blackfish (Orcinus orca, Peponocephala electra, Feresa attenuata and Pseudorca crassidens combined);
4. Pilot whales (Globicephala sp.);
5. Risso's dolphin (Grampus griseus);
6. Clymene dolphin (Stenella clymene);
7. Spinner dolphin (Stenella longirostris);
8. Striped dolphin (Stenella coeruleoalba);
9. Pantropical spotted dolphin (Stenella attenuata);
10. Oceanic Atlantic spotted dolphin (Stenella frontalis);
11. Shelf Atlantic spotted dolphin (Stenella frontalis);
12. Oceanic Common bottlenose dolphin (Tursiops truncatus);
13. Shelf Common bottlenose dolphin (Tursiops truncatus);
14. Sperm whale (Physeter macrocephalus);
15. Rice's whale (Balaenoptera ricei);
16. Green sea turtle (Chelonia mydas);
17. Kemp's Ridley sea turtle (Lepidochelys kempii);
18. Leatherback sea turtle (Dermochelys coriacea) and;
19. Loggerhead sea turtle (Caretta caretta).
Provided are 4 files for each species
.prj file
.dbf file
.shp file
.shs file
Models were extrapolated beyond the U.S. Gulf of Mexico to provide insight into potential high density areas throughout the Gulf. However, extrapolations of this type should be interpreted with caution.
Other
Zipped Shaped Fies
Author
2022
Person
Garrison, Lance
Lance.Garrison@noaa.gov
75 Virginia Beach Dr
Miami
FL
33149
305-361-4488
305-361-4478
8:00 AM - 4:30 PM EST/EDT
Author
2022
Person
Litz, Jenny
Jenny.Litz@noaa.gov
75 Virginia Beach Drive
Miami
FL
33139
305-361-4224
305-365-4102
Author
2022
Person
Rappucci, Gina
gina.rappucci@noaa.gov
75 Virginia Beach Drive
Miami
FL
33149
(305) 361-4283
Author
2022
Person
Dias, Laura A
laura.dias@noaa.gov
75 Virginia Beach Drive
Miami
FL
33149
(305) 361-4269
https://orcid.org/0000-0001-9378-4577
ORCID Page Laura Dias
Online Resource
Author
2022
Person
Martinez, Anthony
anthony.martinez@noaa.gov
75 Virginia Beach Drive
Miami
FL
33149
USA
305-361-4486
305-361-4478
Author
2022
Person
Soldevilla, Melissa
melissa.soldevilla@noaa.gov
75 Virginia Beach Drive
Miami
FL
33149
USA
305-361-4238
Author
2022
2023-07
Person
Barry, Kevin
kevin.barry@noaa.gov
3209 Frederic St.
Pascagoula
MS
39568
228-549-1608
228-769-9200
Author
2022
Person
Mullin, Keith D
keith.d.mullin@noaa.gov
3209 Frederic St.
Pascagoula
MS
39568
228-549-1632
228-769-9200
Data Steward
2022
Person
Litz, Jenny
Jenny.Litz@noaa.gov
75 Virginia Beach Drive
Miami
FL
33139
305-361-4224
305-365-4102
Distributor
2022
Organization
National Centers for Environmental Information - Silver Spring, Maryland
NCEI-MD
NOAA/NESDIS E/OC SSMC3, 4th Floor, 1351 East-West Highway
Silver Spring
MD
20910-3282
(301) 713-3277
Metadata Contact
2022
Person
Dias, Laura A
laura.dias@noaa.gov
75 Virginia Beach Drive
Miami
FL
33149
(305) 361-4269
https://orcid.org/0000-0001-9378-4577
ORCID Page Laura Dias
Online Resource
Ground Condition
-97.65
-80.366
30.983
17.766
Range
2003
2019
Unclassified
Open to everyone
Open To Everyone
2022
https://www.ncei.noaa.gov/archive/archive-management-system/OAS/bin/prd/jquery/accession/download/256800
2022
Organization
National Centers for Environmental Information - Silver Spring, Maryland
256800.2.2.tar.gz
NCEI Archived Data Accession
~ (184.776 MB)
https://www.doi.org/10.25921/efv4-9z56
Landing Page NCEI Accession 0256800
Online Resource
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)
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
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
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
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
No
Unknown
Yes
No
YES
NCEI-MD
Big Eye Binocular
instrument
binoculars
25x150 mm
NOAA Ship Gordon Gunter
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.
Big Eye Binocular
instrument
binoculars
25x150 mm
NOAA Twin Otter Aircraft
NOAA Twin Otter Aircraft
Big Eye Binocular
instrument
binoculars
25x150 mm
Pisces (PC)
8ce0b2c0-19fa-11e1-bddb-0800200c9a66
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.
Big Eye Binocular
instrument
binoculars
25x150 mm
67882
Document
0256800_lonlat.txt
67881
Document
0256800_map.jpg
67879
Document
EU7CXU-confirmation_email.txt
67883
Document
NOAA SEFSC Cetacean and Sea Turtle Spatial Density Models for the Gulf of Mexico.docx 2022-07-27 17:02 23K
67880
Document
journal.txt
67893
Entity
NCEI Accession 0256800 Zipped Data Files
gov.noaa.nmfs.inport:67830
Lee Weinberger
2022-09-06T09:29:42
Lee Weinberger
2023-07-23T11:19:08
2023-07-23
Southeast Fisheries Science Center
SEFSC
75 Virginia Beach Drive
Miami
FL
33149
USA
(305)361-5761
www.sefsc.noaa.gov
8:00 a.m. - 4:30 p.m. EST
1001
Public
No
2022-09-16
1 Year
2023-09-16