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| Dataset Title: | North Atlantic Right Whale Habitat-based Marine Mammal Density Models for the U.S. Atlantic: Latest Versions 
|
| Institution: | Duke University Marine Geospatial Ecology Laboratory (Dataset ID: ECMM_North_Atlantic_right_whale) |
| Information: | Summary
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| ISO 19115
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Attributes {
time {
String _CoordinateAxisType "Time";
Float64 actual_range 1.3898304e+9, 1.418688e+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 "34382|3021|1507|726|256|168|99|71|41|33|25|19|19|17|13|86|4|8|11|9|9|12|16|7|2|8|8|4|5|7|4|7|10|5|5|4|4|5|2|2|0|1|1|0|3|2|1|5|3|2|1|2|3|1|4|1|2|0|1|0|0|1|4|0|1|2|0|0|1|2|0|0|2|0|2|1|2|0|2|1|0|0|0|0|0|1|2|3|0|0|0|0|1|0|1|0|1|1|1|2|1|1|0|0|0|0|0|0|1|1|0|0|2|0|0|0|1|0|0|0|0|1|1|0|0|0|1|0|0|0|1|1|1|1|0|0|2|0|0|1|0|0|0|0|0|1|0|1|0|0|2|0|0|0|0|0|0|1|0|0|0|0|0|1|1|0|1|1|0|0|0|0|1|0|0|1|0|0|1|0|0|0|0|0|0|0|0|0|1|0|0|1|0|0|1|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|1|0|0|0|0|0|1|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|1|";
Float64 STATISTICS_HISTOMAX 4.4778757991764;
Int32 STATISTICS_HISTOMIN 0;
Int32 STATISTICS_HISTONUMBINS 256;
Float64 STATISTICS_MAXIMUM 4.4778757991764;
Float64 STATISTICS_MEAN 0.012525098353568;
Int32 STATISTICS_MEDIAN 0;
Int32 STATISTICS_MINIMUM 0;
Int32 STATISTICS_MODE 0;
Int32 STATISTICS_SKIPFACTORX 1;
Int32 STATISTICS_SKIPFACTORY 1;
Float64 STATISTICS_STDDEV 0.10591613557291;
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 "30574|1705|1141|1064|903|834|673|610|410|281|208|214|179|152|120|86|82|63|68|69|63|43|32|36|32|31|33|28|21|31|24|18|27|29|19|24|23|8|23|14|25|13|13|14|16|18|11|22|13|14|13|18|8|16|8|7|8|6|14|12|5|8|10|72|6|6|6|6|5|8|5|11|6|4|9|5|7|5|10|10|2|4|5|7|3|9|5|2|7|3|4|3|2|6|3|4|6|3|8|3|9|5|5|5|5|4|3|4|4|6|4|2|3|1|1|1|5|5|5|2|4|1|2|5|1|1|1|2|2|1|4|3|3|0|2|1|3|3|0|1|2|1|4|1|3|2|1|2|3|2|0|1|0|0|1|1|1|0|0|1|0|0|1|1|2|1|3|1|1|1|1|1|0|0|0|0|3|0|1|0|1|0|0|0|1|0|1|1|0|1|2|0|0|0|0|2|0|0|3|1|1|2|1|0|0|0|0|0|0|2|1|0|0|0|0|0|0|0|0|1|0|0|0|0|0|1|0|0|0|1|0|0|0|0|0|1|0|0|0|0|0|0|0|1|0|1|0|0|1|0|0|0|0|0|0|1|";
Float64 STATISTICS_HISTOMAX 10.411260814322;
Int32 STATISTICS_HISTOMIN 0;
Int32 STATISTICS_HISTONUMBINS 256;
Float64 STATISTICS_MAXIMUM 10.411260814322;
Float64 STATISTICS_MEAN 0.12324350294976;
Int32 STATISTICS_MEDIAN 0;
Int32 STATISTICS_MINIMUM 0;
Int32 STATISTICS_MODE 0;
Int32 STATISTICS_SKIPFACTORX 1;
Int32 STATISTICS_SKIPFACTORY 1;
Float64 STATISTICS_STDDEV 0.51974365087431;
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 "3021|0|81|259|777|1664|1617|1143|982|1109|899|927|846|822|721|668|536|522|395|381|311|279|267|255|238|249|227|346|1229|1108|702|530|926|1388|2442|2545|3047|2698|1232|535|447|298|154|82|70|47|31|22|33|40|33|22|32|35|31|33|29|35|24|22|24|12|26|14|15|21|12|16|15|11|17|15|16|10|15|18|11|12|12|22|12|11|16|18|12|13|27|20|16|21|18|19|19|18|21|8|15|14|10|9|7|6|6|6|4|5|6|6|4|7|9|11|3|5|7|5|7|9|6|4|6|5|7|8|4|4|5|4|3|6|8|3|4|2|4|3|3|2|5|1|8|4|6|4|1|5|4|4|6|2|4|4|3|7|4|6|4|3|5|3|4|6|3|2|4|7|5|7|4|6|7|4|6|4|3|10|6|9|1|6|7|3|6|7|4|4|8|10|4|9|8|7|10|4|6|4|2|8|7|5|6|3|8|5|9|4|2|2|9|3|3|3|2|4|8|5|2|3|3|5|4|2|3|2|3|3|4|2|2|1|3|2|5|4|2|1|0|1|1|0|0|0|0|3|1|1|1|1|1|0|2|1|0|2|0|1|";
Float64 STATISTICS_HISTOMAX 34.15844279839;
Int32 STATISTICS_HISTOMIN 0;
Int32 STATISTICS_HISTONUMBINS 256;
Float64 STATISTICS_MAXIMUM 34.15844279839;
Float64 STATISTICS_MEAN 3.4445570294343;
Int32 STATISTICS_MEDIAN 0;
Int32 STATISTICS_MINIMUM 0;
Int32 STATISTICS_MODE 0;
Int32 STATISTICS_SKIPFACTORX 1;
Int32 STATISTICS_SKIPFACTORY 1;
Float64 STATISTICS_STDDEV 3.2505154876369;
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 "32646|1886|1682|1333|857|553|312|166|126|120|83|72|81|40|54|44|36|32|28|26|28|27|42|24|32|23|22|19|19|12|8|7|13|15|12|5|3|8|10|6|5|12|4|4|9|2|3|1|4|5|67|6|0|2|5|2|1|2|5|0|2|0|1|2|1|2|1|4|2|0|0|3|1|1|0|4|2|1|1|0|0|1|1|1|0|0|0|1|1|2|1|2|0|1|0|1|0|0|2|1|0|0|0|1|2|2|0|2|0|0|0|0|1|0|1|0|1|3|1|1|0|0|0|1|0|2|0|0|2|0|1|0|0|0|0|0|0|0|0|0|0|3|0|0|2|0|0|0|0|1|0|1|1|1|2|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|1|0|1|0|0|0|0|0|0|0|0|0|0|1|2|0|3|0|1|1|0|0|0|0|0|0|0|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|1|0|0|0|0|0|1|0|0|0|0|0|0|0|0|0|0|0|0|0|1|1|0|1|0|0|0|0|0|0|0|0|1|";
Float64 STATISTICS_HISTOMAX 6.6621240562909;
Float64 STATISTICS_HISTOMIN -1.7347234759768e-18;
Int32 STATISTICS_HISTONUMBINS 256;
Float64 STATISTICS_MAXIMUM 6.6621240562909;
Float64 STATISTICS_MEAN 0.03531205407423;
Int32 STATISTICS_MEDIAN 0;
Int32 STATISTICS_MINIMUM 0;
Int32 STATISTICS_MODE 0;
Int32 STATISTICS_SKIPFACTORX 1;
Int32 STATISTICS_SKIPFACTORY 1;
Float64 STATISTICS_STDDEV 0.19805742409774;
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 "30175|1686|1059|972|828|723|701|575|523|433|310|210|185|166|160|144|127|102|75|66|58|57|61|48|55|43|37|33|26|28|20|28|24|22|24|25|19|22|16|17|21|17|16|20|21|9|15|11|16|20|9|11|8|8|15|14|12|13|16|11|11|11|10|11|6|9|6|9|7|6|4|11|7|9|8|6|4|7|3|7|6|4|5|8|3|4|8|5|4|6|4|10|5|5|5|6|8|5|1|2|5|3|6|68|10|4|1|4|8|5|4|0|1|5|2|5|4|1|2|8|3|7|2|2|8|2|7|2|0|2|4|8|2|6|1|4|3|0|1|5|1|4|6|3|0|3|1|2|2|4|4|1|1|4|0|2|1|2|2|0|3|3|0|2|4|1|1|1|1|1|0|0|1|4|2|1|0|2|1|2|2|3|0|0|0|1|1|0|1|0|2|0|0|0|1|0|1|0|0|0|2|1|1|3|0|2|0|0|0|2|1|0|0|0|0|1|0|1|1|1|1|0|0|0|0|0|0|0|0|0|0|0|1|1|0|0|0|0|2|0|0|0|1|1|0|1|0|0|0|0|0|0|0|0|0|1|";
Float64 STATISTICS_HISTOMAX 2.140915708766;
Int32 STATISTICS_HISTOMIN 0;
Int32 STATISTICS_HISTONUMBINS 256;
Float64 STATISTICS_MAXIMUM 2.140915708766;
Float64 STATISTICS_MEAN 0.030193581803142;
Int32 STATISTICS_MEDIAN 0;
Int32 STATISTICS_MINIMUM 0;
Int32 STATISTICS_MODE 0;
Int32 STATISTICS_SKIPFACTORX 1;
Int32 STATISTICS_SKIPFACTORY 1;
Float64 STATISTICS_STDDEV 0.12392491112385;
String units "number of individual animals per 100 square km";
}
NC_GLOBAL {
String acknowledgement
"Above all, we thank the observers, scientists, engineers, pilots, captains, and crews who collected the cetacean and covariate observations that formed the core of this analysis; we hope you find this project a worthwhile outcome of your efforts. A special thanks to colleagues who shared valuable advice or assisted with data preparation: Sue Barco, Elizabeth Becker, Danielle Cholewiak, Ana Ca¤adas, Peter Corkeron, Erin W. Cummings, Megan Ferguson, Karin Forney, Beth Josephson, David L. Miller, Richard Pace, Robert Schick, Doug Sigourney, and Len Thomas. We are grateful to Matthieu Authier and 2 anonymous reviewers for thoughtful comments that improved this paper. Corrie Curtice was our project manager. We thank all of the following for providing acoustic data: Sofie M. Van Parijs, Joel Bell, Jacqueline Bort Thornton, Gary Buchanan, Russell A. Charif, Danielle Cholewiak, Christopher W. Clark, Peter Corkeron, Julien Delarue, Kathleen Dudzinski, Robert Dziak, Jason Gedamke, Leila Hatch, Samara Haver, John Hildebrand, Lynne Hodge, Holger Klinck, Bruce Martin, David K. Mellinger, Hilary MoorsMurphy, Sharon Nieukirk, Susan Parks, Andrew J. Read, Aaron N. Rice, Denise Risch, Howard Rosenbaum, Melissa Soldevilla, Joy E. Stanistreet, Erin Summers, Christopher Tremblay, Sean Todd, Ann Warde, and David Wiley. Acoustic analysis was performed by Julianne Wilder, Nicole Pegg, Taylor Broadhead, Margaret Daly, Molly Martin, Alyssa Scott, Sarah Weiss, and Daniel Woodrich. Funding for visual and acoustic surveys was provided by NOAA Fisheries, NOAA Ocean Acoustics Program; National Oceanic Partnership Program (NOPP); US Navy, Navy N45, US Fleet Forces Command, and Naval Facilities Engineering Systems Command Atlantic (NAVFAC); Bureau of Ocean and Energy Management; US Coast Guard; US Army Corps of Engineers; Fisheries and Oceans Canada/Oceans and Coastal Management/Species at Risk Management, and Strategic Program for Ecosystem-Based Research and Ad - vice funds; Georgia Department of Natural Resources; Maine Department of Marine Resources; Massachusetts Clean Energy Center; New Jersey Department of Environmental Protection and the New Jersey Clean Energy Fund; New York State Department of Environmental Conservation; Virginia Coastal Zone Management Program; Conservation Law Foundation; National Ocean Protection Coalition; Natural Resources Defense Council; and Cornell University. Funding for the development of HYCOM has been provided by NOPP and the Office of Naval Research. Data assimilative products using HYCOM are funded by the US Navy. The 1/12 degree global HYCOM+NCODA Ocean Reanalysis was funded by the US Navy and the Modeling and Simulation Coordination Office. Computer time for HYCOM was made available by the DoD High Performance Computing Modernization Program. The output is publicly available
at https://hycom.org. This analysis was conducted using EU Copernicus Marine Service Information. CCMP vector wind analyses were produced by Remote Sensing Systems. Data are available at https://www.remss.com. This analysis was funded by NOAA Fisheries (Cooperative Agreement NA20NMF0080246) and the US Navy (Cooperative Agreement N62470-20-2-2011). The results and conclusions, as well as any views or opinions expressed herein, are those of the authors and do not necessarily reflect the views of NMFS, NOAA, or the Department of Commerce.";
String cdm_data_type "Grid";
String contributor_name "Jason J. Roberts, Tina M. Yack, Ei Fujioka, Patrick N. Halpin, Mark F. Baumgartner, Oliver Boisseau, Samuel Chavez-Rosales, Timothy V. N. Cole, Mark P. Cotter, Genevieve E. Davis, Robert A. DiGiovanni Jr., Laura C. Ganley, Lance P. Garrison, Caroline P. Good, Timothy A. Gowan, Katharine A. Jackson, Robert D. Kenney, Christin B. Khan, Amy R. Knowlton, Scott D. Kraus, Gwen G. Lockhart, Kate S. Lomac-MacNair, Charles A. Mayo, Brigid E. McKenna, William A. McLellan, Douglas P. Nowacek, Orfhlaith O?Brien, D. Ann Pabst, Debra L. Palka, Eric M. Patterson, Daniel E. Pendleton, Ester Quintana-Rizzo, Nicholas R. Record, Jessica V. Redfern, Meghan E. Rickard, Melanie White, Amy D. Whitt, Ann M. Zoidis";
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 "2024-03-20";
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 (2013-02-20): Draft model of spring season only, for NOAA internal meetings. Version 2 (2013-04-30): All four seasons modeled; many improvements implemented, too numerous to list. Version 3 (2013-05-08): Figures regenerated with improved label placement. No changes to models. Version 4 (2014-05-28): Shrunk spring and fall seasons to two months, expanded summer to five. 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 5 (2015-01-20): Added additional surveys from UNCW and Virginia Aquarium. Changed winter to four months (Dec-Mar), spring to two (Apr-May), and summer and fall to three (Jun-Aug and Sep-Nov). Version 5.1 (2015-01-20): Updated the documentation. No changes to the model. Version 5.2 (2015-03-06): Updated the documentation. No changes to the model. Version 5.3 (2015-04-06): Updated the documentation. No changes to the model. Version 5.4 (2015-05-14): Updated calculation of CVs. Switched density rasters to logarithmic breaks. No changes to the model. Version 5.5 (2015-10-12): Updated the documentation. No changes to the model. Version 5.6 (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 5.4 but I did not implement it properly.) Updated the monthly CV rasters to have value 0 where we assumed the species was absent, consistent with the year-round CV raster. No changes to the other (non-zero) CV values, the mean abundance rasters, or the model itself. Model files released as supplementary information to Roberts et al. (2016). Version 6 (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. Switched to a two-season spatial model and adjusted model subregions. Changed aerial g(0) estimates to be based on geographic region, group size, and presence of calves. Refitted detection functions and spatial models from scratch using new and reprocessed covariates. Version 7 (2017-09-30): Switched back to four season model with new season and subregion definitions (relative to Roberts et al. 2015). Model released as part of a scheduled update to the U.S. Navy Marine Species Density Database (NMSDD). Version 8 (2019-03-26): Updated density predictions for Cape Cod Bay for January-May with estimates from Ganley et al. (2019). Adjusted subregion definitions and model formulations to eliminate edge effects. Otherwise this version is identical to version 7. Model released in collaboration with NOAA Fisheries following the April 2019 ALWTRT meeting. Version 9 (2020-05-06): This was a substantial update over version 8. We extended the aggregate database of surveys to extend up through early 2019 (vs. through 2016 in verison 8). The additional surveys contributed by collaborators included: NOAA NEFSC and SEFSC AMAPPS aerial and shipboard from 2016, 2017, and spring 2019; NEFSC pre-AMAPPS HB-07-09 cruise; NEFSC NARWSS for 2017 through spring 2019; southeast U.S. right whale EWS surveys from 2016/17, 2017/18, and 2018/19; VAMSC Navy surveys for 2016-2017; UNCW Navy surveys 2017; HDR Navy surveys for 2018; NYS-DEC/TetraTech NYBWM Years 1 and 2 surveys (2017-2018); New England Aquarium NLPSC 2011-2015 and MMS-WEA 2017-2018 aerial surveys. We shifted the start date of the model forward to 2003 (vs. 1998 in version 8), to make it more recent and to better equalize survey coverage between the north and south. We increased the spatial resolution to 5 km. At NOAA's request, we adjusted the study area to extend farther inshore in certain bays and estuaries, to facilitate better use of the model in NOAA's right whale take reduction decision support tool. We reformulated and refitted all detection functions and regional spatial models. We applied new availability bias corrections formulated using the Laake et al. (1997) estimator; the corrections accounted for survey altitude and speed, regional whale dive behavior, and, where possible, whale group size and composition. We summarized results into two eras, 2003-2009 and 2010-2018, reflecting the apparant major shift in right whale distributions around 2010. For comparison, we also summarized results in to a third era that spanned the entire period 2003-2018. We documented the overall model in a report to the U.S. Navy (Roberts et al. 2020) in summer 2020 and released it for public use in collaboration with NOAA Fisheries. The Navy Marine Species Density Database (NMSDD) was not updated at this time; the Navy will take delivery of the model in Feburary 2022 as scheduled. Version 10 (2020-10-13): This was a minor update to version 9, undertaken after NOAA NEFSC (B. Shank) reported implausibly high densities in spring months in the vicinity of Massachusetts Bay. To correct this problem we introduced additional survey data collected by NEFSC in spring of 2019, fixed a model term that caused an unrealistic extrapolation into Massachusetts Bay and refitted the \"Spring\" model in the \"North of Nantucket Shoals\" region. This fixed the problem in spring months around Massachusetts Bay, while leaving the rest of the Gulf of Maine region essentially the same as version 9. The additional data included additional effort and sightings in the \"Hatteras Island to Nantucket Shoals\" region, so we refitted that model as well, resulting in slightly higher predictions south of Nantucket. Predictions south of Hatteras Island are the same as version 9. For more details about this update, please see Section 3 of Roberts et al. (2021). Version 11 (2021-02-27): This was a minor update to version 10, undertaken in response to a request from the Massachusetts Division of Marine Fisheries that we reexamine the problem of how best to estimate abundance in Cape Cod Bay for the month of December. We prepared a new estimate based on all surveys conducted by the Center for Coastal Studies during the month of December from 2003-2020. The only predictions that changed during this update were for grid cells of Cape Cod Bay in the month of December. For more information about this, please see Section 4 of Roberts et al. (2021) and the Appendix of that report. Version 11.1 (2021-11-22): In this update, the density surfaces remain unchanged from version 11, but we have added uncertainty surfaces to go with them. Section 5 of Roberts et al. (2021) gives complete details of how uncertainty was derived. As discussed there, the density surfaces represent means for each month averaged over an era, either 2003-2009, 2010-2018, or 2003-2018. The uncertainty surfaces estimate how much density is likely to vary from the mean if a random year was selected from that era, accounting for the estimated statistical error in model parameter estimates and, when possible, the interannual variability in the model covariates over the era. The uncertainty surfaces include standard error (see Roberts et al. 2021 for the specific definition), the coefficient of variation, and the lower (5%) and upper (95%) limits of a 90% confidence interval. These are similar to what we provided with the model up through version 8, but now account for interannual variability. (Version 8 and prior only accounted for the estimated statistical error in model parameter estimates.) Version 12 (2022-02-14): This model is a major update over version 11. We incorporated additional surveys from all collaborators through 2020. (Due to data limitations, the last month predicted by the model is September 2020.) 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. Similar to verison 11.1, uncertainty outputs account for variance derived from uncertainty in model parameter estimates and from temporal variability. In all regions, this includes both seasonal and interannual variability, except in August and September north of the Great South Channel, where data limitations necessitated the use of climatological covariates, for which only seasonal variability is derivable. The model 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. Version 12.1 (2023-05-27): Completed the supplementary report documenting the details of this model. Corrected the 5 and 95 percent rasters so that they contain the value 0 where the taxon was asssumed absent, rather than NoData. Nothing else was changed. Version 12.2 (2024-03-20): Updated the supplementary report to reference the newly-released Roberts et al. (2024) publication that documents the 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
2024-10-06T22:26:20Z (local files)
2024-10-06T22:26:20Z https://coastwatch.pfeg.noaa.gov/erddap/griddap/ECMM_North_Atlantic_right_whale.das";
String id "ECMM_densityModel_NorthAtlanticrightwhale";
String infoUrl "https://seamap.env.duke.edu/models/Duke/EC/";
String institution "Duke University Marine Geospatial Ecology Laboratory";
String key_words "Eubalaena glacialis,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 "12.2";
String publisher_email "erd.data@noaa.gov";
String references "Roberts JJ, Yack TM, Fujioka E, Halpin PN and others (2024) North Atlantic right whale density surface model for the US Atlantic evaluated with passive acoustic monitoring. Mar Ecol Prog Ser 732:167-192. https://doi.org/10.3354/meps14547";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 23.156215948215642;
String species "North Atlantic right whale";
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 North Atlantic right whale.";
String taxon_lsid "urn:lsid:marinespecies.org:taxname:159023";
String taxon_name "Eubalaena glacialis";
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 "2010-01-01 00:00:00,2019-12-31 00:00:00";
String time_coverage_end "2014-12-16T00:00:00Z";
String time_coverage_start "2014-01-16T00:00:00Z";
String title "North Atlantic Right Whale Habitat-based Marine Mammal Density Models for the U.S. Atlantic: Latest Versions";
Float64 Westernmost_Easting -82.34740343532766;
}
}
Data Access Protocol (DAP) and its
projection constraints.
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.