gov.noaa.nmfs.inport:67830 eng UTF8 dataset Mixed Southeast Fisheries Science Center (305)361-5761 75 Virginia Beach Drive Miami FL 33149 USA www.sefsc.noaa.gov WWW:LINK-1.0-http--link Website Website for this organization information 8:00 a.m. - 4:30 p.m. EST resourceProvider Dias, Laura A (305) 361-4269 75 Virginia Beach Drive Miami FL 33149 laura.dias@noaa.gov https://orcid.org/0000-0001-9378-4577 WWW:LINK-1.0-http--link ORCID Page Laura Dias Website listed for Dias, Laura A information pointOfContact 2026-03-04T19:17:26 ISO 19115-2 Geographic Information - Metadata Part 2 Extensions for imagery and gridded data ISO 19115-2:2009(E) 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) 2022-07-29 publication NOAA/NMFS/EDM 67830 NOAA 2022-07-29 inForce 10.25921/efv4-9z56 https://www.fisheries.noaa.gov/inport/item/67830 WWW:LINK-1.0-http--link Full Metadata Record View the complete metadata record on InPort for more information about this dataset. information Garrison, Lance 305-361-4488 305-361-4478 75 Virginia Beach Dr Miami FL 33149 Lance.Garrison@noaa.gov 8:00 AM - 4:30 PM EST/EDT author Litz, Jenny 305-361-4224 305-365-4102 75 Virginia Beach Drive Miami FL 33139 Jenny.Litz@noaa.gov author Rappucci, Gina (305) 361-4283 75 Virginia Beach Drive Miami FL 33149 gina.rappucci@noaa.gov author Dias, Laura A (305) 361-4269 75 Virginia Beach Drive Miami FL 33149 laura.dias@noaa.gov https://orcid.org/0000-0001-9378-4577 WWW:LINK-1.0-http--link ORCID Page Laura Dias Website listed for Dias, Laura A information author Soldevilla, Melissa 305-361-4238 75 Virginia Beach Drive Miami FL 33149 USA melissa.soldevilla@noaa.gov author Mullin, Keith D 228-549-1632 228-769-9200 3209 Frederic St. Pascagoula MS 39568 keith.d.mullin@noaa.gov author https://www.doi.org/10.25921/efv4-9z56 WWW:LINK-1.0-http--link Landing Page NCEI Accession 0256800 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) download 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] 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.. Litz, Jenny; Aichinger Dias, Laura; Rappucci, Gina; Martinez, Anthony; Soldevilla, Melissa; Garrison, Lance; Mullin, Keith; Barry, Kevin; Foster, Marjorie (2022) completed Litz, Jenny 305-361-4224 305-365-4102 75 Virginia Beach Drive Miami FL 33139 Jenny.Litz@noaa.gov custodian asNeeded DOC/NOAA/NESDIS/NCEI > National Centers for Environmental Information, NESDIS, NOAA, U.S. Department of Commerce DOC/NOAA/NESDIS/NODC > National Oceanographic Data Center, NESDIS, NOAA, U.S. Department of Commerce DOC/NOAA/NMFS/SEFSC > Southeast Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 17.0 EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MAMMALS > CETACEANS EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MARINE MAMMALS EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > MARINE MAMMALS > DOLPHINS EARTH SCIENCE > BIOLOGICAL CLASSIFICATION > ANIMALS/VERTEBRATES > REPTILES > TURTLES > SEA TURTLES theme Global Change Master Directory (GCMD) Science Keywords 17.0 Balaenoptera ricei Caretta caretta Chelonia mydas Dermochelys coriacea Feresa attenuata Globicephala Grampus griseus Kogia Lepidochelys kempii Mesoplodon Orcinus orca Peponocephala electra Physeter macrocephalus Pseudorca crassidens Stenella attenuata Stenella clymene Stenella coeruleoalba Stenella frontalis Stenella longirostris Tursiops truncatus Ziphius theme World Register of Marine Species (WoRMS) OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > CARIBBEAN SEA OCEAN > ATLANTIC OCEAN > NORTH ATLANTIC OCEAN > GULF OF AMERICA place Global Change Master Directory (GCMD) Location Keywords 20.8 BINOCULAR > BINOCULAR INCLINOMETERS > INCLINOMETERS VISUAL OBSERVATIONS > VISUAL OBSERVATIONS instrument Global Change Master Directory (GCMD) Instrument Keywords 17.2 DHC-6 > DeHavilland Twin Otter Ships platform Global Change Master Directory (GCMD) Platform Keywords 17.2 14450 779-1633 theme ESA/MMPA Permit Number 0256800 256800 theme NCEI ACCESSION NUMBER DOLPHINS MARINE MAMMALS SEA TURTLES cetacean species abundance theme NODC DATA TYPES THESAURUS Gulf of Mexico Marine Assessment Program for Protected Species (GOMMAPPS) theme NODC PROJECT NAMES THESAURUS Caribbean Sea Gulf of Mexico place NODC SEA AREA NAMES THESAURUS BIG EYE BINOCULARS Distance Sampling Line Transect Sampling inclinometer visual estimate visual observation instrument NODC INSTRUMENT TYPES THESAURUS NOAA Ship Gordon Gunter NOAA Ship Pisces platform NODC PLATFORM NAMES THESAURUS 2003-2019 temporal DOC/NOAA/NMFS/SEFSC > Southeast Fisheries Science Center, National Marine Fisheries Service, NOAA, U.S. Department of Commerce dataCentre Global Change Master Directory (GCMD) Data Center Keywords 2017-04-24 publication 8.5 Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA) https://forum.earthdata.nasa.gov/app.php/tag/GCMD%2BKeywords GCMD Keyword Forum Page Global Change Master Directory (GCMD). 2025. GCMD Keywords, Version 22. Greenbelt, MD: Earth Science Data and Information System, Earth Science Projects Division, Goddard Space Flight Center (GSFC), National Aeronautics and Space Administration (NASA). URL (GCMD Keyword Forum Page): https://forum.earthdata.nasa.gov/app.php/tag/GCMD+Keywords information custodian Density of Cetaceans and Turtles in the Gulf of Mexico project InPort otherRestrictions Cite As: Southeast Fisheries Science Center, [Date of Access]: 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 Date Range], https://www.fisheries.noaa.gov/inport/item/67830. NOAA provides no warranty, nor accepts any liability occurring from any incomplete, incorrect, or misleading data, or from any incorrect, incomplete, or misleading use of the data. It is the responsibility of the user to determine whether or not the data is suitable for the intended purpose. otherRestrictions Access Constraints: Open To Everyone unclassified NOAA Data Management Plan (DMP) NOAA/NMFS/EDM 67830 https://www.fisheries.noaa.gov/inportserve/waf/noaa/nmfs/sefsc/dmp/pdf/67830.pdf WWW:LINK-1.0-http--link NOAA Data Management Plan (DMP) NOAA Data Management Plan for this record on InPort. information crossReference eng; US oceans -97.65 -80.366 17.766 30.983 | Currentness: Ground Condition 2003 2019 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. false eng false Other NCEI Accession 0256800 Zipped Data Files 2023-07-23 publication NCEI Archived Data Accession NOAA National Centers for Environmental Information ncei.info@noaa.gov https://www.ncei.noaa.gov/contact WWW:LINK-1.0-http--link NCEI Contact Information Information for contacts at NCEI. information distributor https://www.ncei.noaa.gov/archive/archive-management-system/OAS/bin/prd/jquery/accession/download/256800 WWW:LINK-1.0-http--link 256800.2.2.tar.gz download dataset 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 Big Eye Binocular 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 binoculars 25x150 mm NOAA Twin Otter Aircraft NOAA Twin Otter Aircraft Big Eye Binocular binoculars 25x150 mm Pisces (PC) 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 binoculars 25x150 mm