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Dataset Title:  Pilot Whales Habitat-based Marine Mammal Density Models for the U.S. Atlantic:
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Institution:  Duke University Marine Geospatial Ecology Laboratory   (Dataset ID: ECMM_Pilot_whales)
Information:  Summary ? | License ? | FGDC | ISO 19115 | Metadata | Background (external link) | Files | Make a graph
 
Dimensions ? Start ? Stride ? Stop ?  Size ?    Spacing ?
 time (UTC) ?      1    (just one value)
  < slider >
 latitude (degrees_north) ?      503    -0.04889548 (even)
  < slider >
 longitude (degrees_east) ?      535    0.04889548 (even)
  < slider >
 
Grid Variables (which always also download all of the dimension variables) 
 a_5_percent (number of individual animals per 100 square km) ?
 a_95_percent (number of individual animals per 100 square km) ?
 cv (estimated coefficient of variation of density estimates, 1) ?
 density (number of individual animals per 100 square km) ?
 standard_error (number of individual animals per 100 square km) ?

File type: (more information)

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The Dataset Attribute Structure (.das) for this Dataset

Attributes {
  time {
    String _CoordinateAxisType "Time";
    Float64 _FillValue NaN;
    Float64 actual_range 1.2307248e+9, 1.2307248e+9;
    String axis "T";
    String climatology "climatology_bounds";
    String ioos_category "Time";
    String long_name "Time";
    String standard_name "time";
    String time_origin "01-JAN-1970 00:00:00";
    String units "seconds since 1970-01-01T00:00:00Z";
  }
  latitude {
    String _CoordinateAxisType "Lat";
    Float64 actual_range 23.156215948215642, 47.701744867003754;
    String axis "Y";
    String ioos_category "Location";
    String long_name "Latitude";
    String standard_name "latitude";
    String units "degrees_north";
  }
  longitude {
    String _CoordinateAxisType "Lon";
    Float64 actual_range -82.34740343532766, -56.23721928665664;
    String axis "X";
    String ioos_category "Location";
    String long_name "Longitude";
    String standard_name "longitude";
    String units "degrees_east";
  }
  a_5_percent {
    Float32 _FillValue -3.4e+38;
    String cell_methods "time: mean within years time time: mean over years";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "The lower 90% confidence interval around the density estimates. These have the same unit as the density values.";
    String ioos_category "Statistics";
    String LAYER_TYPE "athematic";
    String long_name "lower 90 percent confidence interval of density estimates";
    String standard_name "5_percent";
    String STATISTICS_HISTOBINVALUES "10108|9951|10837|6692|3591|2137|1511|972|606|468|354|304|276|206|191|165|150|142|113|132|113|102|95|61|83|66|66|80|50|55|55|43|48|40|37|24|34|34|24|41|18|30|23|24|26|24|14|15|26|16|8|20|17|17|9|15|15|14|18|14|23|10|18|12|14|7|13|10|13|14|10|10|8|19|8|10|8|9|10|7|4|8|8|13|5|11|9|3|11|9|7|8|7|5|10|5|4|1|5|4|8|4|4|7|7|1|1|5|5|4|2|3|2|1|3|6|4|2|1|2|3|3|0|1|2|1|1|3|2|2|0|0|1|0|0|2|1|2|4|0|0|4|1|0|0|0|2|1|1|1|1|0|0|0|1|0|1|0|0|1|0|0|0|1|1|3|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|1|";
    Float64 STATISTICS_HISTOMAX 38.559150569497;
    Float64 STATISTICS_HISTOMIN 5.1127310718435e-11;
    Int32 STATISTICS_HISTONUMBINS 256;
    Float64 STATISTICS_MAXIMUM 38.559150569497;
    Float64 STATISTICS_MEAN 0.66079678189513;
    Int32 STATISTICS_MEDIAN 0;
    Float64 STATISTICS_MINIMUM 5.1127303090659e-11;
    Int32 STATISTICS_MODE 0;
    Int32 STATISTICS_SKIPFACTORX 1;
    Int32 STATISTICS_SKIPFACTORY 1;
    Float64 STATISTICS_STDDEV 1.622756831496;
    String units "number of individual animals per 100 square km";
  }
  a_95_percent {
    Float32 _FillValue -3.4e+38;
    String cell_methods "time: mean within years time time: mean over years";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "The upper 90% confidence interval around the density estimates. These have the same unit as the density values.";
    String ioos_category "Statistics";
    String LAYER_TYPE "athematic";
    String long_name "upper 90 percent confidence interval of density estimates";
    String standard_name "95_percent";
    String STATISTICS_HISTOBINVALUES "10068|12127|12183|4857|2821|1876|1356|875|558|406|359|306|263|255|216|175|198|143|131|124|109|78|72|77|66|54|56|47|40|47|34|43|27|29|45|29|29|37|20|23|30|22|17|18|18|22|27|15|14|16|20|19|13|7|4|11|11|7|14|15|15|9|9|14|8|10|7|7|9|8|6|6|4|6|7|6|9|7|6|5|5|8|2|3|2|6|6|1|2|8|5|2|6|3|1|10|4|3|3|5|1|2|1|0|2|4|4|5|4|3|3|1|1|1|4|2|1|2|0|1|1|3|2|1|4|2|3|2|1|0|2|1|3|1|0|1|0|1|1|0|0|1|1|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|1|0|2|1|0|0|0|1|0|0|0|1|1|2|0|0|0|0|0|1|0|0|0|0|0|0|0|1|0|1|0|0|0|1|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|0|0|0|0|1|";
    Float64 STATISTICS_HISTOMAX 364.60666352074;
    Float64 STATISTICS_HISTOMIN 1.245091008073e-8;
    Int32 STATISTICS_HISTONUMBINS 256;
    Float64 STATISTICS_MAXIMUM 364.60666352074;
    Float64 STATISTICS_MEAN 5.5072843074863;
    Int32 STATISTICS_MEDIAN 0;
    Float64 STATISTICS_MINIMUM 1.2450910054886e-8;
    Int32 STATISTICS_MODE 0;
    Int32 STATISTICS_SKIPFACTORX 1;
    Int32 STATISTICS_SKIPFACTORY 1;
    Float64 STATISTICS_STDDEV 13.802409012906;
    String units "number of individual animals per 100 square km";
  }
  cv {
    Float32 _FillValue -3.4e+38;
    String cell_methods "time: mean within years time time: mean over years";
    String description "The estimated coefficient of variation of the density estimates. These values are unitless and were computed as standard error divided by density.";
    String ioos_category "Physical Oceanography";
    String LAYER_TYPE "athematic";
    String long_name "estimated coefficient of variation of density estimates";
    String standard_name "cv";
    String STATISTICS_HISTOBINVALUES "1|9|46|67|98|159|240|323|390|427|630|667|811|1122|1410|1855|1975|2309|2592|2915|2715|2670|2295|1901|1520|1481|1315|1114|1056|964|946|964|929|725|594|608|654|623|587|543|564|481|575|431|416|351|338|356|329|264|194|207|204|144|137|98|107|99|98|93|83|78|84|76|82|80|83|68|71|59|67|59|65|53|61|55|64|54|53|55|53|35|43|49|34|40|31|33|48|30|46|33|31|32|27|23|34|34|28|30|29|27|15|32|23|22|19|20|17|26|18|16|21|14|24|19|25|21|19|20|16|20|18|19|9|10|15|12|23|9|10|7|14|12|12|10|8|10|14|17|7|20|12|13|15|10|13|17|8|12|11|15|8|7|11|12|13|13|8|8|6|13|8|5|9|8|7|9|12|2|6|4|5|7|4|13|6|4|5|3|3|4|5|3|5|5|2|3|6|3|1|1|2|0|2|0|0|1|0|3|1|2|0|0|1|0|0|0|1|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|";
    Float64 STATISTICS_HISTOMAX 3.9098048878211;
    Float64 STATISTICS_HISTOMIN 0.42313548060549;
    Int32 STATISTICS_HISTONUMBINS 256;
    Float64 STATISTICS_MAXIMUM 3.9098048878211;
    Float64 STATISTICS_MEAN 0.81869556900586;
    Int32 STATISTICS_MEDIAN 0;
    Float64 STATISTICS_MINIMUM 0.42313548060549;
    Int32 STATISTICS_MODE 0;
    Int32 STATISTICS_SKIPFACTORX 1;
    Int32 STATISTICS_SKIPFACTORY 1;
    Float64 STATISTICS_STDDEV 0.2971946779787;
    String units "1";
  }
  density {
    Float32 _FillValue -3.4e+38;
    String cell_methods "time: mean within years time time: mean over years";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "The estimated mean density per grid cell for the given month, averaged over all years the model was predicted. Density is expressed as the number of individual animals per 100 square km. To convert to individuals per 1 square km, divide the cell values by 100. To convert to individuals per grid cell, divide by 100 and multiply by 25, the cell area in km.";
    String ioos_category "Statistics";
    String LAYER_TYPE "athematic";
    String long_name "estimated mean density per grid cell";
    String standard_name "density";
    String STATISTICS_HISTOBINVALUES "9676|8677|10090|7523|3997|2348|1543|1177|790|540|407|353|290|267|213|223|196|180|149|121|120|119|98|103|85|75|64|64|64|44|43|42|56|52|35|34|39|26|30|34|33|17|22|33|25|20|21|28|27|21|15|23|19|16|22|13|13|15|16|4|17|16|8|13|8|11|19|9|11|9|11|12|10|10|6|13|9|10|8|12|6|9|11|10|9|8|9|6|7|9|8|6|7|6|5|4|5|7|4|5|0|5|7|3|4|7|1|10|3|2|8|2|3|2|3|3|4|3|2|2|2|7|4|6|3|4|3|2|2|1|2|0|3|1|1|0|0|4|1|0|2|4|1|0|3|1|1|0|0|0|0|3|0|1|0|1|0|3|1|0|1|1|0|0|0|1|2|2|0|0|0|0|0|2|0|0|0|0|0|0|0|1|0|1|0|0|0|1|1|0|0|0|2|0|0|0|1|0|1|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|1|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|";
    Float64 STATISTICS_HISTOMAX 100.57105450046;
    Float64 STATISTICS_HISTOMIN 7.9786055540154e-10;
    Int32 STATISTICS_HISTONUMBINS 256;
    Float64 STATISTICS_MAXIMUM 100.57105450046;
    Float64 STATISTICS_MEAN 1.8779495086908;
    Int32 STATISTICS_MEDIAN 0;
    Float64 STATISTICS_MINIMUM 7.9786054679418e-10;
    Int32 STATISTICS_MODE 0;
    Int32 STATISTICS_SKIPFACTORX 1;
    Int32 STATISTICS_SKIPFACTORY 1;
    Float64 STATISTICS_STDDEV 4.5303908667613;
    String units "number of individual animals per 100 square km";
  }
  standard_error {
    Float32 _FillValue -3.4e+38;
    String cell_methods "time: mean within years time time: mean over years";
    Float64 colorBarMaximum 100.0;
    Float64 colorBarMinimum 0.0;
    String description "estimated standard error of the density estimates. These have the same unit as the density rasters. This and the other uncertainty statistics below incorporated variance resulting from uncertainty in the models parameter estimates as well as variance resulting from temporal variations in dynamic covariates. The temporal variability incorporated depended on the covariates used. For models that utilized contemporaneous dynamic covariates, the variability included both seasonal and interannual variability. For models that utilized climatological dynamic covariates, it included seasonal variability only. For technical information on the method used to estimate uncertainty, please see Roberts et al. (2021).";
    String ioos_category "Statistics";
    String LAYER_TYPE "athematic";
    String long_name "estimated standard error of density estimates";
    String standard_name "standard_error";
    String STATISTICS_HISTOBINVALUES "10113|12659|12251|4487|2741|1827|1354|862|528|414|358|292|253|258|211|169|198|123|140|129|89|71|90|73|57|48|55|52|36|43|44|31|36|30|41|26|25|26|32|23|22|24|21|21|19|21|18|13|10|22|15|10|11|7|8|15|7|9|17|18|13|8|5|12|7|8|10|6|11|3|8|3|4|5|6|9|7|8|4|9|3|5|4|1|4|4|4|1|5|7|3|5|5|6|1|6|5|2|2|3|1|2|2|1|0|4|5|4|4|3|1|0|2|2|4|1|1|1|1|0|3|1|2|3|4|1|2|2|1|1|1|3|2|0|0|1|0|1|1|0|0|1|1|1|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|1|0|2|1|0|0|0|1|0|1|0|1|1|1|0|0|0|0|0|1|0|0|0|0|0|0|0|1|0|1|0|0|0|1|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|0|0|0|0|1|";
    Float64 STATISTICS_HISTOMAX 92.513645237423;
    Float64 STATISTICS_HISTOMIN 3.1194790639511e-9;
    Int32 STATISTICS_HISTONUMBINS 256;
    Float64 STATISTICS_MAXIMUM 92.513645237423;
    Float64 STATISTICS_MEAN 1.3618818628485;
    Int32 STATISTICS_MEDIAN 0;
    Float64 STATISTICS_MINIMUM 3.1194790656555e-9;
    Int32 STATISTICS_MODE 0;
    Int32 STATISTICS_SKIPFACTORX 1;
    Int32 STATISTICS_SKIPFACTORY 1;
    Float64 STATISTICS_STDDEV 3.4377777606424;
    String units "number of individual animals per 100 square km";
  }
  NC_GLOBAL {
    String acknowledgement "This project would not be possible without the contributions of many individuals and organizations. Above all, we acknowledge the work of those who collected, processed, and shared marine mammal and covariate data with us, and to those who funded the production of those data. In particular, we thank the observers, pilots, ship captains, and crew who collected the marine mammal observations that form the core of this analysis. Tables 4, 5, and 6 (See referenced citation Roberts et al. 2023) list the collaborating institutions, survey programs, and citations for marine mammal surveys used for the EC models. Tables 10 and 11 (See referenced citation Roberts et al. 2023) list those that were additionally used for the AFTT models. Table 2 (See referenced citation Roberts et al. 2023) lists the data sources and citations for covariates used in both models. Thank you all for the opportunity to analyze the data you produced; we hope you find this project a satisfactory outcome of your efforts. Many thanks to colleagues who shared additional data, reviewed portions of our work, provided valuable advice, or answered technical questions, including: Susan Barco, Suzanne Bates, Elizabeth Becker, Olly Boisseau, Gary Buchanan, Steve Buckland, Sam Chavez-Rosales, Danielle Cholewiak, Tim Cole, Peter Corkeron, Mark Cotter, Erin Cummings, Genevieve Davis, Rob DiGiovanni, Megan Ferguson, Karin Forney, Lance Garrison, Caroline Good, Tim Gowan, Phil Hammond, Jolie Harrison, Katie Jackson, Beth Josephson, Bob Kenney, Christin Khan, Scott Kraus, Erin LaBrecque, Claire Lacey, Sophie Laran, Ben Laws, Patrick Lehodey, Gwen Lockhart, Kate Lomac-MacNair, Tiago Marques, Ryan McAlarney, Bill McLellan, David L. Miller, Keith Mullin, Doug Nowacek, Orla O'Brien, Ann Pabst, Richard Pace, Debi Palka, Eric Patterson, Ester Quintana-Rizzo, Jessica Redfern, Vincent Ridoux, Doug Sigourney, Len Thomas, Sofie Van Parijs, Melanie White, Amy Whitt, and Ann Zoidis. We gratefully acknowledge Genevieve Davis and coauthors (Davis et al. 2017, 2020) for making passive acoustic monitoring data available for the purpose of evaluating baleen whale model predictions. These data appear in the accompanying taxon-specific reports for the baleen whales. Thanks also to our colleagues at MGEL who also assisted with data processing, analysis, model review, and project management, including Ana Ca¤adas, Jesse Cleary, Corrie Curtice, Ei Fujioka, and Rob Schick. Funding for this project was provided by United States Fleet Forces Command and was managed on their behalf by Naval Facilities Engineering Systems Command Atlantic. Development of the model for North Atlantic right whale was co-funded by NOAA under a cooperative research agreement. Certain data contributors requested that their programs or products be acknowledged in a specific way. We include these acknowledgements below. Virginia Aquarium & Marine Science Center?s Virginia CZM Wind Energy Area Surveys were funded by the Virginia Coastal Zone Management Program at the Department of Environmental Quality through Task 1 of Grant NA12NOS4190027 and Task 95.02 of Grant NA13NOS4190135 of the U.S. Department of Commerce, National Oceanic and Atmospheric Administration, under the Coastal Zone Management Act of 1972, as amended. The University of North Carolina Wilmington's Navy surveys were funded by U.S. Navy Fleet Forces Command with Joel Bell as the COTR. University of North Carolina Wilmington?s right whale surveys were funded by NOAA. New England Aquarium's surveys of the Massachusetts and Rhode Island Wind Energy Areas, known in this report as the NLPSC and MMS-WEA programs, were funded by Massachusetts Clean Energy Center and the Bureau of Ocean Energy Management. Odd Aksel Bergstad, Thomas de Lange Wenneck, Leif N?ttestad, and Gordon Waring contributed the MAR-ECO survey under the Norwegian License for Open Government data (NLOD). The REMMOA and SAMM surveys were contributed by Observatoire PELAGIS at the University of La Rochelle, France. Funding for the development of HYCOM has been provided by the National Ocean Partnership Program and the Office of Naval Research. Data assimilative products using HYCOM are funded by the U.S. Navy. The 1/12 degree global HYCOM+NCODA Ocean Reanalysis was funded by the U.S. Navy and the Modeling and Simulation Coordination Office. Computer time was made available by the DoD High Performance Computing Modernization Program. The output is publicly available at https://hycom.org. The Ssalto/Duacs altimeter products were produced and distributed by the Copernicus Marine and Environment Monitoring Service (CMEMS) (https://marine.copernicus.eu). The altimetry and the Mesoscale Eddy Trajectory Atlas products were produced by Ssalto/Duacs and distributed by AVISO+ (https://www.aviso.altimetry.fr) with support from CNES, in collaboration with Oregon State University with support from NASA. CCMP vector wind analyses are produced by Remote Sensing Systems. Data are available at https://www.remss.com. This study has been conducted using E.U. Copernicus Marine Service Information, including SEAPODYM (doi: 10.48670/moi-00020) and Copernicus GlobColour (CMEMS product code OCEANCOLOUR_GLO_CHL_L4_REP_OBSERVATIONS_009_082).";
    String cdm_data_type "Grid";
    String contributor_name "Jason J. Roberts, Tina M. Yack, Patrick N. Halpin, Benjamin D. Best, Laura Mannocci, Ei Fujioka, Debra L. Palka, Lance P. Garrison, Keith D. Mullin, Timothy V. N. Cole, Christin B. Khan, William A. McLellan, D. Ann Pabst & Gwen G. Lockhart";
    String Conventions "ACDD-1.3, CF-1.11, COARDS";
    String creator_email "If you have any questions about this model or its files, please contact Jason Roberts (jason.roberts@duke.edu) and Tina Yack (tina.yack@duke.edu).";
    String creator_institution "Marine Geospatial Ecology Laboratory, Duke University, Durham, NC 27708, USA";
    String creator_name "Jason J. Roberts";
    String creator_type "person";
    String creator_url "https://mgel.env.duke.edu/";
    String date_created "2023-05-27";
    String defaultGraphQuery "&.draw=surface&.vars=longitude|latitude|density&.colorBar=KT_dense|||0|5|&.bgColor=0xffccccff";
    Float64 Easternmost_Easting -56.23721928665664;
    String geospatial_bounds_crs "EPSG:4326";
    Float64 geospatial_lat_max 47.701744867003754;
    Float64 geospatial_lat_min 23.156215948215642;
    Float64 geospatial_lat_resolution 0.04889547593384086;
    String geospatial_lat_units "degrees_north";
    Float64 geospatial_lon_max -56.23721928665664;
    Float64 geospatial_lon_min -82.34740343532766;
    Float64 geospatial_lon_resolution 0.048895475933840866;
    String geospatial_lon_units "degrees_east";
    String history 
"Version 1 (2014-09-01): Initial version.  Version 2 (2014-10-23): Added Palka (2006) survey-specific g(0) estimates. Updated distance to eddy predictors using Chelton et al.'s 2014 database. Removed distance to eddy predictors from shelf model; added distance to canyon predictor. Removed wind speed predictor from all models. Fixed missing pixels in several climatological predictors, which led to not all segments being utilized. Eliminated Cape Cod Bay subregion (combined it with Shelf).  Version 3 (2014-11-19): Reconfigured detection hierarchy and adjusted NARWSS detection functions based on additional information from Tim Cole. Removed CumVGPM180 predictor. Updated documentation.  Version 4 (2014-12-04): Fixed bug that applied the wrong detection function to segments NE_narwss_1999_widgeon_hapo dataset. Refitted model. Updated documentation.  Version 4.1 (2015-03-06): Updated the documentation. No changes to the model.  Version 4.2 (2015-05-14): Updated calculation of CVs. Switched density rasters to logarithmic breaks. No changes to the model.  Version 4.3 (2015-09-30): Updated the documentation. No changes to the model. Model files released as supplementary information to Roberts et al. (2016).  Version 5 (2017-06-01): Began update to Roberts et al. (2015) model. Introduced new surveys from AMAPPS, NARWSS, UNCW, VAMSC, and the SEUS NARW teams. Updated modeling methodology. Refitted detection functions and spatial models from scratch using new and reprocessed covariates.  Version 6 (2017-08-08): Combined \"Shelf\" and \"Slope and Abyss\" subregions into single \"Surveyed Area\" subregion, to try to eliminate extreme extrapolations in very cold water. Model released as part of a scheduled update to the U.S. Navy Marine Species Density Database (NMSDD).  Version 7 (2022-06-20): This model is a major update over the prior version, with substantial additional data, improved statistical methods, and an increased spatial resolution. It was released as part of the final delivery of the U.S. Navy Marine Species Density Database (NMSDD) for the Atlantic Fleet Testing and Training (AFTT) Phase IV Environmental Impact Statement. Several new collaborators joined and contributed survey data: New York State Department of Environmental Conservation, TetraTech, HDR, and Marine Conservation Research. We incorporated additional surveys from all continuing and new collaborators through the end of 2020. (Because some environmental covariates were only available through 2019, certain models only extend through 2019.) We increased the spatial resolution to 5 km and, at NOAA's request, we extended the model further inshore from New York through Maine. We reformulated and refitted all detection functions and spatial models. We updated all enviromental covariates to newer products, when available, and added several covariates to the set of candidates. For models that incorporated dynamic covariates, we estimated model uncertainty using a new method that accounts for both model parameter error and temporal variability.  Version 7.1 (2023-05-27): Completed the supplementary report documenting the details of this model. The model itself was not changed.   NETCDF conversion:Raw data provided at https://seamap.env.duke.edu/models/Duke/EC/ were converted from raster images having an Anderson equal area projection into python xarray objects and reprojected to WGS-1984.  See crs attribute for more details regarding the geographic project. Multiple raster files for monthly density estimates where merged into a single .nc file having time dimension and month coordinate. For datasets with multiple eras, only the most recent era is represented here. Data conversion to CF-NetCDF from raster files was performed by james.caplinger@NOAA.gov
2024-10-06T22:17:29Z (local files)
2024-10-06T22:17:29Z https://coastwatch.pfeg.noaa.gov/erddap/griddap/ECMM_Pilot_whales.das";
    String id "ECMM_densityModel_Pilotwhales";
    String infoUrl "https://seamap.env.duke.edu/models/Duke/EC/";
    String institution "Duke University Marine Geospatial Ecology Laboratory";
    String key_words "Globicephala spp.,Density models, Line-transect surveys, Passive acoustic monitoring, Abundance estimation, Generalized additive models";
    String keywords "5_percent, 95_percent, atlantic, based, cell, coefficient, confidence, data, density, duke, ecology, error, estimated, estimates, geospatial, gom, grid, gulf, habitat, habitat-based, interval, laboratory, latest, lower, mammal, marine, mean, mexico, models, oceanography, per, percent, physical, physical oceanography, standard, standard_error, statistics, time, university, upper, US, variation, versions";
    String license "This document and the accompanying files are Copyright (C) 2022 by the Duke University Marine Geospatial Ecology Laboratory and are licensed under a Creative Commons Attribution 4.0 International License(https://creativecommons.org/licenses/by/4.0/).";
    String metadata_link "https://seamap.env.duke.edu/models/Duke/EC/";
    String naming_authority "edu.duke.env.seamap";
    Float64 Northernmost_Northing 47.701744867003754;
    String product_version "7.1";
    String publisher_email "erd.data@noaa.gov";
    String references "(1) Roberts, J., Best, B., Mannocci, L. et al. Habitat-based cetacean density models for the U.S. Atlantic and Gulf of Mexico. Sci Rep 6, 22615 (2016). https://doi.org/10.1038/srep22615; (2) Roberts, Jason J., Tina M. Yack, and Patrick N. Halpin. \"Marine mammal density models for the US Navy Atlantic Fleet Training and Testing (AFTT) study area for the Phase IV Navy Marine Species Density Database (NMSDD).\" Document version 1 (2023).";
    String sourceUrl "(local files)";
    Float64 Southernmost_Northing 23.156215948215642;
    String species "Pilot whales";
    String standard_name_vocabulary "CF Standard Name Table v70";
    String summary "In 2016, together with our collaborators, we published density models for 26 cetacean species and 3 guilds inhabiting U.S. waters of the western North Atlantic and northern Gulf of Mexico (Roberts et al. 2016). After publication, we began an update to the Atlantic (a.k.a. \"East Coast\") models that utilized the same methodology but incorporated additional survey data not available for use in models published in 2016. During 2017-2021, we released updated models for many of the East Coast taxa as additional data accumulated and new collaborators joined the project. Finally, in 2022, we released a comprehensive set of updated models covering all taxa. This model contains the 2022 update for pilot whales.";
    String taxon_comment "modeled as guild, observer reported identifications included Long-finned pilot whale, Short-finned pilot whale and Long-finned or Short-finned pilot whale.";
    String taxon_lsid "urn:lsid:marinespecies.org:taxname:137017";
    String taxon_name "Globicephala spp.";
    String time_coverage_comment "Days, months, and time associated with start, end, and duration are approximate. For datasets with multiple eras, only the most recent era is represented here.";
    String time_coverage_duration "1998-01-01 00:00:00,2019-12-31 00:00:00";
    String time_coverage_end "2008-12-31T12:00:00Z";
    String time_coverage_start "2008-12-31T12:00:00Z";
    String title "Pilot Whales Habitat-based Marine Mammal Density Models for the U.S. Atlantic: Latest Versions";
    Float64 Westernmost_Easting -82.34740343532766;
  }
}

 

Using griddap to Request Data and Graphs from Gridded Datasets

griddap lets you request a data subset, graph, or map from a gridded dataset (for example, sea surface temperature data from a satellite), via a specially formed URL. griddap uses the OPeNDAP (external link) Data Access Protocol (DAP) (external link) and its projection constraints (external link).

The URL specifies what you want: the dataset, a description of the graph or the subset of the data, and the file type for the response.

griddap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/griddap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/griddap/jplMURSST41.htmlTable?analysed_sst[(2002-06-01T09:00:00Z)][(-89.99):1000:(89.99)][(-179.99):1000:(180.0)]
Thus, the query is often a data variable name (e.g., analysed_sst), followed by [(start):stride:(stop)] (or a shorter variation of that) for each of the variable's dimensions (for example, [time][latitude][longitude]).

For details, see the griddap Documentation.


 
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