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 data       graph  M    files  public Fin Whale Habitat-based Marine Mammal Density Models for the U.S. Atlantic: Latest Versions    ?   F   I   M   background (external link) RSS Subscribe
Duke University M...  ?
ECMM__Fin_whale

The Dataset's Variables and Attributes

Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL acknowledgement String 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).
attribute NC_GLOBAL cdm_data_type String Grid
attribute NC_GLOBAL contributor_name String 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
attribute NC_GLOBAL Conventions String ACDD-1.3, CF-1.11, COARDS
attribute NC_GLOBAL creator_email String 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).
attribute NC_GLOBAL creator_institution String Marine Geospatial Ecology Laboratory, Duke University, Durham, NC 27708, USA
attribute NC_GLOBAL creator_name String Jason J. Roberts
attribute NC_GLOBAL creator_type String person
attribute NC_GLOBAL creator_url String https://mgel.env.duke.edu/ (external link)
attribute NC_GLOBAL date_created String 2023-05-27
attribute NC_GLOBAL defaultGraphQuery String &.draw=surface&.vars=longitude|latitude|density&.colorBar=KT_dense|||0|5|&.bgColor=0xffccccff
attribute NC_GLOBAL Easternmost_Easting double -56.23721928665664
attribute NC_GLOBAL geospatial_bounds_crs String EPSG:4326
attribute NC_GLOBAL geospatial_lat_max double 47.701744867003754
attribute NC_GLOBAL geospatial_lat_min double 23.156215948215642
attribute NC_GLOBAL geospatial_lat_resolution double 0.04889547593384086
attribute NC_GLOBAL geospatial_lat_units String degrees_north
attribute NC_GLOBAL geospatial_lon_max double -56.23721928665664
attribute NC_GLOBAL geospatial_lon_min double -82.34740343532766
attribute NC_GLOBAL geospatial_lon_resolution double 0.048895475933840866
attribute NC_GLOBAL geospatial_lon_units String degrees_east
attribute NC_GLOBAL history String Version 1 (2013-05-10): Initial version. Version 2 (2014-03-01): Switched from four seasonal models to two. Reformulated density model using a Horvitz-Thompson estimator. Eliminated GAM for group size (consequence of above). Added group size as a candidate covariate in detection functions (benefit of above). Added survey ID as a candidate covariate in NOAA NARWSS detection functions. Took more care in selecting right-truncation distances. Fitted models with contemporaneous predictors, for comparison to climatological. Switched SST and SST fronts predictors from NOAA Pathfinder to GHRSST CMC0.2deg L4. Changed SST fronts algorithm to use Canny operator instead of Cayula-Cornillon. Switched winds predictors from SCOW to CCMP (SCOW only gives climatol. estimates.) Added DistToEddy predictors, based on Chelton et al. (2011) eddy database. Added cumulative VGPM predictors, summing productivity for 45, 90, and 180 days. Added North Atlantic Oscillation (NAO) predictor; included 3 and 6 month lags. Transformed predictors more carefully, to better minimize leverage of outliers. Implemented hybrid hierarchical- forward / exhaustive model selection procedure. Model selection procedure better avoids concurvity between predictors. Allowed GAMs to select between multiple formulations of dynamic predictors. Adjusted land mask to eliminate additional estuaries and hard-to-predict cells. Version 3 (2014-05-20): Fixed bug in temporal variability plots. Density models unchanged. Version 4 (2013-06-02): Added Reclassification of Ambiguous Sightings section, which was accidentally omitted. Density models unchanged. Version 5 (2014-09-02): Added surveys: NJ-DEP, Virginia Aquarium, NARWSS 2013, UNCW 2013. Extended study area up Scotian Shelf. Added SEAPODYM predictors. Switched to mgcv estimation of Tweedie p parameter (family=tw()). Version 6 (2014-10-18): Switched to a single season model. Added Palka (2006) survey-specific g(0) estimates. Updated distance to eddy predictors using Chelton et al.'s 2014 database. Removed distance to eddy and wind speed predictors. Fixed missing pixels in several climatological predictors, which led to not all segments being utilized. Eliminated Cape Cod Bay subregion. Version 7 (2014-11-03): Fixed error in g(0) for NEFSC Abel-J Binocular Surveys: previously used 0.87; changed to correct value, 0.32, and refitted the model. Updated documentation. Version 8 (2014-11-10): Reconfigured detection hierarchy and adjusted NARWSS detection functions based on additional information from Tim Cole. Removed CumVGPM180 predictor. Updated documentation. Version 9 (2014-12-03): Fixed bug that applied the wrong detection function to segments NE_narwss_1999_widgeon_hapo dataset. Refitted model. Updated documentation. Version 9.1 (2015-02-02): Updated the documentation. No changes to the model. Version 9.2 (2015-05-14): Updated calculation of CVs. Switched density rasters to logarithmic breaks. No changes to the model. Version 9.3 (2015-09-26): Updated the documentation. No changes to the model. Version 9.4 (2016-04-21): Switched calculation of monthly 5% and 95% confidence interval rasters to the method used to produce the year-round rasters. (We intended this to happen in version 9.2 but I did not implement it properly.) No changes to the other rasters or the model itself. Model files released as supplementary information to Roberts et al. (2016). Version 10 (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. Model released as part of a scheduled update to the U.S. Navy Marine Species Density Database (NMSDD). Version 11 (2018-04-22): Discovered that model verison 10 erroneously excluded ambiguous "fin or sei whale" sightings classified as fin whales. Refitted the model with them included. The functional form of the resulting model was essentially the same but deviance explained rose from 36% to 40%. Predicted density showed a similar spatiotemporal pattern but total abundance rose about 15%, reflecting the addtional sightings introduced into the model. Model released as part of a scheduled update to the U.S. Navy Marine Species Density Database (NMSDD). Version 12 (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 12.1 (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
attribute NC_GLOBAL id String ECMM_densityModel_Finwhale
attribute NC_GLOBAL infoUrl String https://seamap.env.duke.edu/models/Duke/EC/ (external link)
attribute NC_GLOBAL institution String Duke University Marine Geospatial Ecology Laboratory
attribute NC_GLOBAL key_words String Balaenoptera physalus,Density models, Line-transect surveys, Passive acoustic monitoring, Abundance estimation, Generalized additive models
attribute NC_GLOBAL keywords String 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
attribute NC_GLOBAL license String 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/).
attribute NC_GLOBAL metadata_link String https://seamap.env.duke.edu/models/Duke/EC/ (external link)
attribute NC_GLOBAL naming_authority String edu.duke.env.seamap
attribute NC_GLOBAL Northernmost_Northing double 47.701744867003754
attribute NC_GLOBAL product_version String 12.1
attribute NC_GLOBAL publisher_email String erd.data at noaa.gov
attribute NC_GLOBAL references String (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).
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL Southernmost_Northing double 23.156215948215642
attribute NC_GLOBAL species String Fin whale
attribute NC_GLOBAL standard_name_vocabulary String CF Standard Name Table v70
attribute NC_GLOBAL summary String 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 fin whale.
attribute NC_GLOBAL taxon_comment String observer reported identifications included Fin whale and Fin or sei whale.
attribute NC_GLOBAL taxon_lsid String urn:lsid:marinespecies.org:taxname:137091
attribute NC_GLOBAL taxon_name String Balaenoptera physalus
attribute NC_GLOBAL time_coverage_comment String 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.
attribute NC_GLOBAL time_coverage_duration String 1998-01-01 00:00:00,2020-12-31 00:00:00
attribute NC_GLOBAL time_coverage_end String 2009-12-16T00:00:00Z
attribute NC_GLOBAL time_coverage_start String 2009-01-16T00:00:00Z
attribute NC_GLOBAL title String Fin Whale Habitat-based Marine Mammal Density Models for the U.S. Atlantic: Latest Versions
attribute NC_GLOBAL Westernmost_Easting double -82.34740343532766
dimension time   double nValues=12, evenlySpaced=false, averageSpacing=30 days 8h 43m 38s
attribute time _CoordinateAxisType String Time
attribute time actual_range double 1.232064E9, 1.2609216E9
attribute time axis String T
attribute time climatology String climatology_bounds
attribute time ioos_category String Time
attribute time long_name String Time
attribute time standard_name String time
attribute time time_origin String 01-JAN-1970 00:00:00
attribute time units String seconds since 1970-01-01T00:00:00Z
dimension latitude   double nValues=503, evenlySpaced=true, averageSpacing=-0.04889547593384086
attribute latitude _CoordinateAxisType String Lat
attribute latitude actual_range double 23.156215948215642, 47.701744867003754
attribute latitude axis String Y
attribute latitude ioos_category String Location
attribute latitude long_name String Latitude
attribute latitude standard_name String latitude
attribute latitude units String degrees_north
dimension longitude   double nValues=535, evenlySpaced=true, averageSpacing=0.048895475933840866
attribute longitude _CoordinateAxisType String Lon
attribute longitude actual_range double -82.34740343532766, -56.23721928665664
attribute longitude axis String X
attribute longitude ioos_category String Location
attribute longitude long_name String Longitude
attribute longitude standard_name String longitude
attribute longitude units String degrees_east
variable a_5_percent   float time, latitude, longitude
attribute a_5_percent _FillValue float -3.4E38
attribute a_5_percent cell_methods String time: mean within years time time: mean over years
attribute a_5_percent colorBarMaximum double 100.0
attribute a_5_percent colorBarMinimum double 0.0
attribute a_5_percent description String The lower 90% confidence interval around the density estimates. These have the same unit as the density values.
attribute a_5_percent ioos_category String Statistics
attribute a_5_percent LAYER_TYPE String athematic
attribute a_5_percent long_name String lower 90 percent confidence interval of density estimates
attribute a_5_percent standard_name String 5_percent
attribute a_5_percent STATISTICS_HISTOBINVALUES String 19594|7217|2060|1013|830|602|870|813|699|697|684|631|765|743|671|671|693|751|770|703|656|587|507|480|395|383|387|296|292|271|276|247|236|218|201|208|172|165|151|128|131|119|126|120|117|105|106|100|95|89|88|82|95|87|70|67|69|70|58|54|52|40|41|49|20|34|34|22|31|32|33|26|23|27|30|23|16|23|19|24|35|16|18|22|21|18|13|24|17|6|7|20|15|13|12|7|15|15|15|12|13|9|9|11|6|7|13|13|11|13|5|9|12|5|10|5|7|9|6|5|10|3|10|6|4|14|3|3|7|7|4|2|5|4|5|4|1|4|5|5|5|7|2|5|5|2|1|4|2|4|2|2|0|0|1|1|2|3|2|3|1|4|3|3|1|1|4|1|0|5|3|2|1|3|2|1|2|1|0|0|1|1|1|3|1|2|0|1|0|0|1|1|0|1|1|2|1|1|1|0|0|0|0|1|0|2|0|2|1|1|1|1|0|1|0|1|1|1|2|0|1|0|1|0|0|0|1|1|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|1|
attribute a_5_percent STATISTICS_HISTOMAX double 2.1122351391385
attribute a_5_percent STATISTICS_HISTOMIN double 3.6599819789457E-9
attribute a_5_percent STATISTICS_HISTONUMBINS int 256
attribute a_5_percent STATISTICS_MAXIMUM double 2.1122351391385
attribute a_5_percent STATISTICS_MEAN double 0.086486362052674
attribute a_5_percent STATISTICS_MEDIAN int 0
attribute a_5_percent STATISTICS_MINIMUM double 3.659981978319E-9
attribute a_5_percent STATISTICS_MODE int 0
attribute a_5_percent STATISTICS_SKIPFACTORX int 1
attribute a_5_percent STATISTICS_SKIPFACTORY int 1
attribute a_5_percent STATISTICS_STDDEV double 0.157515953065
attribute a_5_percent units String number of individual animals per 100 square km
variable a_95_percent   float time, latitude, longitude
attribute a_95_percent _FillValue float -3.4E38
attribute a_95_percent cell_methods String time: mean within years time time: mean over years
attribute a_95_percent colorBarMaximum double 100.0
attribute a_95_percent colorBarMinimum double 0.0
attribute a_95_percent description String The upper 90% confidence interval around the density estimates. These have the same unit as the density values.
attribute a_95_percent ioos_category String Statistics
attribute a_95_percent LAYER_TYPE String athematic
attribute a_95_percent long_name String upper 90 percent confidence interval of density estimates
attribute a_95_percent standard_name String 95_percent
attribute a_95_percent STATISTICS_HISTOBINVALUES String 7282|12072|3509|3286|1835|1021|838|800|682|530|629|756|887|1003|857|1000|967|958|846|823|724|691|614|566|477|511|465|400|328|309|286|258|228|237|229|188|166|202|133|158|127|136|133|132|113|102|127|129|101|94|97|99|84|75|75|65|47|67|43|44|46|37|39|28|34|36|31|27|34|19|35|18|34|22|25|24|31|21|30|22|14|22|19|20|16|19|14|16|13|11|24|12|18|8|15|20|10|13|4|13|9|16|12|9|10|9|6|6|10|9|13|6|10|6|6|9|9|4|10|7|6|10|7|1|7|2|5|5|3|7|6|6|5|3|4|2|5|2|2|3|4|5|2|5|1|2|4|4|4|2|5|2|2|1|1|2|3|2|2|2|0|1|3|3|1|1|1|2|1|1|1|0|2|2|3|1|0|1|1|0|0|2|0|1|2|1|1|2|2|0|0|1|0|1|2|1|1|1|0|0|0|0|0|0|0|0|0|0|1|1|0|0|1|1|2|1|0|2|2|0|0|1|2|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|1|
attribute a_95_percent STATISTICS_HISTOMAX double 3.647533673061
attribute a_95_percent STATISTICS_HISTOMIN double 6.0808583246964E-7
attribute a_95_percent STATISTICS_HISTONUMBINS int 256
attribute a_95_percent STATISTICS_MAXIMUM double 3.647533673061
attribute a_95_percent STATISTICS_MEAN double 0.16572665703504
attribute a_95_percent STATISTICS_MEDIAN int 0
attribute a_95_percent STATISTICS_MINIMUM double 6.0808583246947E-7
attribute a_95_percent STATISTICS_MODE int 0
attribute a_95_percent STATISTICS_SKIPFACTORX int 1
attribute a_95_percent STATISTICS_SKIPFACTORY int 1
attribute a_95_percent STATISTICS_STDDEV double 0.26296591248048
attribute a_95_percent units String number of individual animals per 100 square km
variable cv   float time, latitude, longitude
attribute cv _FillValue float -3.4E38
attribute cv cell_methods String time: mean within years time time: mean over years
attribute cv description String The estimated coefficient of variation of the density estimates. These values are unitless and were computed as standard error divided by density.
attribute cv ioos_category String Physical Oceanography
attribute cv LAYER_TYPE String athematic
attribute cv long_name String estimated coefficient of variation of density estimates
attribute cv standard_name String cv
attribute cv STATISTICS_HISTOBINVALUES String 47|399|1681|2102|2208|1902|1375|1079|926|1027|739|789|774|767|818|755|490|369|583|592|776|615|499|579|627|562|496|526|548|606|663|910|917|1012|1198|1382|1799|2021|1935|1504|2388|1840|1091|1634|1085|1054|169|505|203|98|79|70|72|69|55|65|66|80|65|76|56|65|44|42|41|31|20|16|10|20|14|8|14|12|12|11|12|13|8|10|10|13|6|13|4|7|13|9|9|7|8|8|6|2|8|8|7|9|5|6|7|9|4|10|3|4|6|4|5|6|4|2|6|10|6|7|7|4|11|4|4|7|5|5|3|4|3|5|2|11|5|5|3|9|9|6|3|3|4|5|4|3|4|3|3|5|8|2|4|6|15|8|8|6|7|7|5|9|3|1|5|6|3|5|3|6|3|4|2|4|2|4|3|5|2|3|1|4|5|3|0|3|4|0|6|4|2|2|2|6|2|2|3|4|6|2|2|0|0|1|1|4|28|85|36|28|35|21|15|9|9|11|9|14|3|5|7|4|3|1|5|8|5|1|4|3|0|5|2|3|5|3|3|3|4|1|3|3|1|4|2|2|3|1|3|1|5|3|1|30|22|8|8|0|0|1|
attribute cv STATISTICS_HISTOMAX double 3.1930758057452
attribute cv STATISTICS_HISTOMIN double 0.10123158213956
attribute cv STATISTICS_HISTONUMBINS int 256
attribute cv STATISTICS_MAXIMUM double 3.1930758057452
attribute cv STATISTICS_MEAN double 0.4461684651312
attribute cv STATISTICS_MEDIAN int 0
attribute cv STATISTICS_MINIMUM double 0.10123158213956
attribute cv STATISTICS_MODE int 0
attribute cv STATISTICS_SKIPFACTORX int 1
attribute cv STATISTICS_SKIPFACTORY int 1
attribute cv STATISTICS_STDDEV double 0.32630132667829
attribute cv units String 1
variable density   float time, latitude, longitude
attribute density _FillValue float -3.4E38
attribute density cell_methods String time: mean within years time time: mean over years
attribute density colorBarMaximum double 100.0
attribute density colorBarMinimum double 0.0
attribute density description String 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.
attribute density ioos_category String Statistics
attribute density LAYER_TYPE String athematic
attribute density long_name String estimated mean density per grid cell
attribute density standard_name String density
attribute density STATISTICS_HISTOBINVALUES String 13560|9766|3726|1607|1001|823|615|565|685|810|815|773|812|825|809|722|778|801|844|774|725|608|601|507|455|426|353|366|338|273|258|279|245|185|200|183|186|164|145|143|157|129|119|109|122|120|115|98|92|100|90|100|85|85|76|58|63|70|49|54|31|40|19|39|32|36|41|26|32|36|25|21|25|24|38|27|12|20|27|24|25|20|19|18|20|9|22|17|11|11|15|16|9|11|15|15|14|12|14|9|10|17|10|11|12|2|12|4|10|6|8|12|12|8|8|7|11|7|10|3|7|4|9|7|5|5|2|8|4|5|4|3|5|4|6|1|7|5|4|1|5|5|2|4|2|3|1|4|4|4|1|1|2|4|2|3|0|1|3|0|4|2|1|5|1|3|1|1|2|1|0|3|2|2|2|0|2|0|3|0|0|0|1|1|2|2|0|1|1|1|0|0|2|1|0|2|2|0|0|1|1|0|0|0|0|0|1|0|0|2|1|1|0|2|0|0|1|2|1|0|0|1|2|0|1|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|1|
attribute density STATISTICS_HISTOMAX double 2.7756888866425
attribute density STATISTICS_HISTOMIN double 4.7176087037727E-8
attribute density STATISTICS_HISTONUMBINS int 256
attribute density STATISTICS_MAXIMUM double 2.7756888866425
attribute density STATISTICS_MEAN String 1.#SNAN
attribute density STATISTICS_MEDIAN int 0
attribute density STATISTICS_MINIMUM double 4.717608703686E-8
attribute density STATISTICS_MODE int 0
attribute density STATISTICS_SKIPFACTORX int 1
attribute density STATISTICS_SKIPFACTORY int 1
attribute density STATISTICS_STDDEV String 1.#SNAN
attribute density units String number of individual animals per 100 square km
variable standard_error   float time, latitude, longitude
attribute standard_error _FillValue float -3.4E38
attribute standard_error cell_methods String time: mean within years time time: mean over years
attribute standard_error colorBarMaximum double 100.0
attribute standard_error colorBarMinimum double 0.0
attribute standard_error description String 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).
attribute standard_error ioos_category String Statistics
attribute standard_error LAYER_TYPE String athematic
attribute standard_error long_name String estimated standard error of density estimates
attribute standard_error standard_name String standard_error
attribute standard_error STATISTICS_HISTOBINVALUES String 3891|8975|5174|2659|1967|1964|1967|1225|973|875|790|939|813|915|914|930|1037|1007|914|923|910|766|746|696|616|571|516|494|466|404|342|338|291|282|263|251|214|204|197|161|201|163|144|124|116|119|118|116|116|96|72|84|66|70|59|65|63|67|49|55|51|49|57|55|42|39|38|43|25|34|35|20|19|29|22|31|28|23|17|21|16|18|16|20|14|19|18|26|14|12|28|17|18|15|16|17|10|12|12|9|11|15|15|19|5|7|8|8|8|8|11|8|14|7|7|2|7|4|8|7|8|10|5|6|5|3|7|4|4|9|7|1|5|3|1|4|2|3|6|5|6|7|1|4|2|3|0|2|1|1|0|2|1|1|3|2|1|1|1|0|3|3|0|3|1|0|1|1|0|2|1|1|0|2|1|2|2|0|0|0|2|0|1|0|0|1|1|1|1|0|0|2|0|1|1|0|0|1|0|1|0|0|0|0|0|1|0|1|0|0|1|0|1|0|0|0|2|2|3|0|0|2|1|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|1|
attribute standard_error STATISTICS_HISTOMAX double 0.46414044499397
attribute standard_error STATISTICS_HISTOMIN double 1.5063682212723E-7
attribute standard_error STATISTICS_HISTONUMBINS int 256
attribute standard_error STATISTICS_MAXIMUM double 0.46414044499397
attribute standard_error STATISTICS_MEAN String 1.#SNAN
attribute standard_error STATISTICS_MEDIAN int 0
attribute standard_error STATISTICS_MINIMUM double 1.5063682212713E-7
attribute standard_error STATISTICS_MODE int 0
attribute standard_error STATISTICS_SKIPFACTORX int 1
attribute standard_error STATISTICS_SKIPFACTORY int 1
attribute standard_error STATISTICS_STDDEV String 1.#SNAN
attribute standard_error units String number of individual animals per 100 square km

The information in the table above is also available in other file formats (.csv, .htmlTable, .itx, .json, .jsonlCSV1, .jsonlCSV, .jsonlKVP, .mat, .nc, .nccsv, .tsv, .xhtml) via a RESTful web service.


 
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