Accessing BCO-DMO data
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BCO-DMO ERDDAP
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| Dataset Title: | [Projected species probability of occupancy and abundance under ocean warming] - Predicted probability of occupancy and abundance under a doubling of carbon dioxide using simulations from GFDL CM2.6 (Adaptations of fish and fishing communities to rapid climate change) 
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| Institution: | BCO-DMO (Dataset ID: bcodmo_dataset_753188) |
| Information: | Summary
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| ISO 19115
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Attributes {
s {
spp {
String bcodmo_name "taxon";
String description "species scientific name";
String long_name "SPP";
String units "unitless";
}
longitude {
String _CoordinateAxisType "Lon";
Float64 _FillValue NaN;
Float64 actual_range -75.75, -65.75;
String axis "X";
String bcodmo_name "latitude";
Float64 colorBarMaximum 180.0;
Float64 colorBarMinimum -180.0;
String description "longitude of grid cell";
String ioos_category "Location";
String long_name "Longitude";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LATX/";
String source_name "lon_deg";
String standard_name "longitude";
String units "degrees_east";
}
latitude {
String _CoordinateAxisType "Lat";
Float64 _FillValue NaN;
Float64 actual_range 35.25, 44.25;
String axis "Y";
String bcodmo_name "longitude";
Float64 colorBarMaximum 90.0;
Float64 colorBarMinimum -90.0;
String description "latitude of grid cell";
String ioos_category "Location";
String long_name "Latitude";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P09/current/LONX/";
String source_name "lat_deg";
String standard_name "latitude";
String units "degrees_north";
}
scen {
String bcodmo_name "time_elapsed";
String description "year from GFDL simulation. CO2 increases 1% per year over 80 years, doubling from initial levels at year 70 (see Saba et al. 2016 for details)";
String long_name "Scen";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/";
String units "unitless";
}
btemp {
Float32 _FillValue NaN;
Float32 actual_range 1.264, 22.847;
String bcodmo_name "temperature";
String description "predicted bottom temperature from GFDL simulation";
String long_name "Btemp";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
String units "degrees Celsius";
}
stemp {
Float32 _FillValue NaN;
Float32 actual_range 1.157, 21.303;
String bcodmo_name "temperature";
String description "predicted surface temperature from GFDL simulation";
String long_name "Stemp";
String nerc_identifier "https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/";
String units "degrees Celsius";
}
preds1 {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 0.984;
String bcodmo_name "unknown";
String description "predicted probability of occurrence (0-1)";
String long_name "Preds1";
String units "dimensionless";
}
preds {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 353.278;
String bcodmo_name "biomass";
String description "predicted biomass";
String long_name "Preds";
String units "kilograms (kg)";
}
se_fit {
Float32 _FillValue NaN;
Float32 actual_range 0.054, 0.187;
String bcodmo_name "biomass";
String description "standard error of prediction for probability of occurrence";
String long_name "Se Fit";
String units "kilograms (kg)";
}
preds1_upr {
Float32 _FillValue NaN;
Float32 actual_range 0.001, 0.988;
String bcodmo_name "unknown";
String description "upper bound of predicted probability of occurrence (fit + 2SE)";
String long_name "Preds1 Upr";
String units "dimensionless";
}
preds1_lwr {
Float32 _FillValue NaN;
Float32 actual_range 0.0, 0.977;
String bcodmo_name "unknown";
String description "lower bound of predicted probability of occurrence (fit -2SE)";
String long_name "Preds1 Lwr";
String units "dimensionless";
}
}
NC_GLOBAL {
String access_formats ".htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson";
String acquisition_description
"To evaluate how future warming may affect species overlap, we examined
projections of ocean temperature from experimental runs of CM2.6\\u2014a high-
resolution global climate model developed by the National Oceanographic and
Atmospheric Administration\\u2019s Geophysical Fluid Dynamics Laboratory. The
climate model simulates an annual 1% increase in atmospheric CO2 over the
course of 80-years, reaching a doubling of CO2 by year 70. Under the
IPCC\\u2019s RCP 8.5 emissions scenario, CO2 is predicted to approximately
double by 2075 (van Vuuren et al., 2011). The CM2.6 model projects temperature
as the change in temperature from the initial year, such that projections are
in relative units (\\u0394\\u00baC). We use \\u0394\\u00baC projections for
surface and bottom waters for the spring months of March, April and May. To
convert projected temperature change (\\u0394\\u00baC) to absolute temperatures
(\\u00baC), projected temperature changes were added to the long-term mean
climatology in each 0.25\\u00b0latitude x 0.25\\u00b0longitude grid cell. The
fitted species distribution models were then projected with the CM2.6 sea
bottom and sea surface temperatures for each simulated time step (t).
Projections were made for each 0.25\\u00b0latitude x 0.25\\u00b0longitude grid
cell j in the study region while holding species biomass constant at its
overall mean and using the mean depth and substrate for each grid cell.
Projections were also made with average biomass set equal to 50% and 150% of
the historical mean to explore the effect of abundance on projected species
occupancy.";
String awards_0_award_nid "559955";
String awards_0_award_number "OCE-1426891";
String awards_0_data_url "http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1426891";
String awards_0_funder_name "NSF Division of Ocean Sciences";
String awards_0_funding_acronym "NSF OCE";
String awards_0_funding_source_nid "355";
String awards_0_program_manager "Michael E. Sieracki";
String awards_0_program_manager_nid "50446";
String cdm_data_type "Other";
String comment
"Projected species probability of occupancy and abundance under ocean warming
PI: Malin Pinsky
data version 1: 2019-03-05";
String Conventions "COARDS, CF-1.6, ACDD-1.3";
String creator_email "info@bco-dmo.org";
String creator_name "BCO-DMO";
String creator_type "institution";
String creator_url "https://www.bco-dmo.org/";
String data_source "extract_data_as_tsv version 2.3 19 Dec 2019";
String date_created "2019-01-18T06:10:54Z";
String date_modified "2019-11-08T18:56:13Z";
String defaultDataQuery "&time<now";
String doi "10.1575/1912/bco-dmo.753188.1";
Float64 Easternmost_Easting -65.75;
Float64 geospatial_lat_max 44.25;
Float64 geospatial_lat_min 35.25;
String geospatial_lat_units "degrees_north";
Float64 geospatial_lon_max -65.75;
Float64 geospatial_lon_min -75.75;
String geospatial_lon_units "degrees_east";
String history
"2024-11-23T17:14:25Z (local files)
2024-11-23T17:14:25Z https://erddap.bco-dmo.org/erddap/tabledap/bcodmo_dataset_753188.html";
String infoUrl "https://www.bco-dmo.org/dataset/753188";
String institution "BCO-DMO";
String keywords "bco, bco-dmo, biological, btemp, chemical, data, dataset, dmo, erddap, fit, latitude, longitude, lwr, management, oceanography, office, preds, preds1, preds1_lwr, preds1_upr, preliminary, scen, se_fit, spp, stemp, upr";
String license "https://www.bco-dmo.org/dataset/753188/license";
String metadata_source "https://www.bco-dmo.org/api/dataset/753188";
Float64 Northernmost_Northing 44.25;
String param_mapping "{'753188': {'lon_deg': 'flag - longitude', 'lat_deg': 'flag - latitude'}}";
String parameter_source "https://www.bco-dmo.org/mapserver/dataset/753188/parameters";
String people_0_affiliation "Rutgers University";
String people_0_person_name "Malin Pinsky";
String people_0_person_nid "554708";
String people_0_role "Principal Investigator";
String people_0_role_type "originator";
String people_1_affiliation "Rutgers University";
String people_1_person_name "Rebecca Selden";
String people_1_person_nid "753186";
String people_1_role "Contact";
String people_1_role_type "related";
String people_2_affiliation "Woods Hole Oceanographic Institution";
String people_2_affiliation_acronym "WHOI BCO-DMO";
String people_2_person_name "Amber York";
String people_2_person_nid "643627";
String people_2_role "BCO-DMO Data Manager";
String people_2_role_type "related";
String project "CC Fishery Adaptations";
String projects_0_acronym "CC Fishery Adaptations";
String projects_0_description
"Description from NSF award abstract:
Climate change presents a profound challenge to the sustainability of coastal systems. Most research has overlooked the important coupling between human responses to climate effects and the cumulative impacts of these responses on ecosystems. Fisheries are a prime example of this feedback: climate changes cause shifts in species distributions and abundances, and fisheries adapt to these shifts. However, changes in the location and intensity of fishing also have major ecosystem impacts. This project's goal is to understand how climate and fishing interact to affect the long-term sustainability of marine populations and the ecosystem services they support. In addition, the project will explore how to design fisheries management and other institutions that are robust to climate-driven shifts in species distributions. The project focuses on fisheries for summer flounder and hake on the northeast U.S. continental shelf, which target some of the most rapidly shifting species in North America. By focusing on factors affecting the adaptation of fish, fisheries, fishing communities, and management institutions to the impacts of climate change, this project will have direct application to coastal sustainability. The project involves close collaboration with the National Oceanic and Atmospheric Administration, and researchers will conduct regular presentations for and maintain frequent dialogue with the Mid-Atlantic and New England Fisheries Management Councils in charge of the summer flounder and hake fisheries. To enhance undergraduate education, project participants will design a new online laboratory investigation to explore the impacts of climate change on fisheries, complete with visualization tools that allow students to explore inquiry-driven problems and that highlight the benefits of teaching with authentic data. This project is supported as part of the National Science Foundation's Coastal Science, Engineering, and Education for Sustainability program - Coastal SEES.
The project will address three questions:
1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes?
2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and
3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change?
An interdisciplinary team of scientists will use dynamic range and statistical models with four decades of geo-referenced data on fisheries catch and fish biogeography to determine how fish populations are affected by the cumulative impacts of fishing, climate, and changing species interactions. The group will then use comprehensive information on changes in fisher behavior to understand how fishers respond to changes in species distribution and abundance. Interviews will explore the social, regulatory, and economic factors that shape these strategies. Finally, a bioeconomic model for summer flounder and hake fisheries will examine how spatial distribution of regulatory authority, social feedbacks within human communities, and uncertainty affect society's ability to maintain natural and social capital.";
String projects_0_end_date "2018-08";
String projects_0_geolocation "Northeast US Continental Shelf Large Marine Ecosystem";
String projects_0_name "Adaptations of fish and fishing communities to rapid climate change";
String projects_0_project_nid "559948";
String projects_0_start_date "2014-09";
String publisher_name "Biological and Chemical Oceanographic Data Management Office (BCO-DMO)";
String publisher_type "institution";
String sourceUrl "(local files)";
Float64 Southernmost_Northing 35.25;
String standard_name_vocabulary "CF Standard Name Table v55";
String summary "Predicted probability of occupancy and abundance under a doubling of carbon dioxide using simulations from GFDL CM2.6. These data were published in Selden (2018).";
String title "[Projected species probability of occupancy and abundance under ocean warming] - Predicted probability of occupancy and abundance under a doubling of carbon dioxide using simulations from GFDL CM2.6 (Adaptations of fish and fishing communities to rapid climate change)";
String version "1";
Float64 Westernmost_Easting -75.75;
String xml_source "osprey2erddap.update_xml() v1.3";
}
}
Data Access Protocol (DAP) and its
selection 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.
Tabledap request URLs must be in the form
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/datasetID.fileType{?query}
For example,
https://coastwatch.pfeg.noaa.gov/erddap/tabledap/pmelTaoDySst.htmlTable?longitude,latitude,time,station,wmo_platform_code,T_25&time>=2015-05-23T12:00:00Z&time<=2015-05-31T12:00:00Z
Thus, the query is often a comma-separated list of desired variable names,
followed by a collection of
constraints (e.g., variable<value),
each preceded by '&' (which is interpreted as "AND").
For details, see the tabledap Documentation.