BCO-DMO ERDDAP
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Row Type Variable Name Attribute Name Data Type Value
attribute NC_GLOBAL access_formats String .htmlTable,.csv,.json,.mat,.nc,.tsv,.esriCsv,.geoJson
attribute NC_GLOBAL acquisition_description String To evaluate how future warming may affect species overlap, we examined\nprojections of ocean temperature from experimental runs of CM2.6\\u2014a high-\nresolution global climate model developed by the National Oceanographic and\nAtmospheric Administration\\u2019s Geophysical Fluid Dynamics Laboratory. The\nclimate model simulates an annual 1% increase in atmospheric CO2 over the\ncourse of 80-years, reaching a doubling of CO2 by year 70. Under the\nIPCC\\u2019s RCP 8.5 emissions scenario, CO2 is predicted to approximately\ndouble by 2075 (van Vuuren et al., 2011). The CM2.6 model projects temperature\nas the change in temperature from the initial year, such that projections are\nin relative units (\\u0394\\u00baC). We use \\u0394\\u00baC projections for\nsurface and bottom waters for the spring months of March, April and May. To\nconvert projected temperature change (\\u0394\\u00baC) to absolute temperatures\n(\\u00baC), projected temperature changes were added to the long-term mean\nclimatology in each 0.25\\u00b0latitude x 0.25\\u00b0longitude grid cell. The\nfitted species distribution models were then projected with the CM2.6 sea\nbottom and sea surface temperatures for each simulated time step (t).\nProjections were made for each 0.25\\u00b0latitude x 0.25\\u00b0longitude grid\ncell j in the study region while holding species biomass constant at its\noverall mean and using the mean depth and substrate for each grid cell.\nProjections were also made with average biomass set equal to 50% and 150% of\nthe historical mean to explore the effect of abundance on projected species\noccupancy.
attribute NC_GLOBAL awards_0_award_nid String 559955
attribute NC_GLOBAL awards_0_award_number String OCE-1426891
attribute NC_GLOBAL awards_0_data_url String http://www.nsf.gov/awardsearch/showAward.do?AwardNumber=1426891 (external link)
attribute NC_GLOBAL awards_0_funder_name String NSF Division of Ocean Sciences
attribute NC_GLOBAL awards_0_funding_acronym String NSF OCE
attribute NC_GLOBAL awards_0_funding_source_nid String 355
attribute NC_GLOBAL awards_0_program_manager String Michael E. Sieracki
attribute NC_GLOBAL awards_0_program_manager_nid String 50446
attribute NC_GLOBAL cdm_data_type String Other
attribute NC_GLOBAL comment String Projected species probability of occupancy and abundance under ocean warming  \n  PI: Malin Pinsky \n  data version 1: 2019-03-05
attribute NC_GLOBAL Conventions String COARDS, CF-1.6, ACDD-1.3
attribute NC_GLOBAL creator_email String info at bco-dmo.org
attribute NC_GLOBAL creator_name String BCO-DMO
attribute NC_GLOBAL creator_type String institution
attribute NC_GLOBAL creator_url String https://www.bco-dmo.org/ (external link)
attribute NC_GLOBAL data_source String extract_data_as_tsv version 2.3  19 Dec 2019
attribute NC_GLOBAL date_created String 2019-01-18T06:10:54Z
attribute NC_GLOBAL date_modified String 2019-11-08T18:56:13Z
attribute NC_GLOBAL defaultDataQuery String &time<now
attribute NC_GLOBAL doi String 10.1575/1912/bco-dmo.753188.1
attribute NC_GLOBAL Easternmost_Easting double -65.75
attribute NC_GLOBAL geospatial_lat_max double 44.25
attribute NC_GLOBAL geospatial_lat_min double 35.25
attribute NC_GLOBAL geospatial_lat_units String degrees_north
attribute NC_GLOBAL geospatial_lon_max double -65.75
attribute NC_GLOBAL geospatial_lon_min double -75.75
attribute NC_GLOBAL geospatial_lon_units String degrees_east
attribute NC_GLOBAL infoUrl String https://www.bco-dmo.org/dataset/753188 (external link)
attribute NC_GLOBAL institution String BCO-DMO
attribute NC_GLOBAL keywords String 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
attribute NC_GLOBAL license String https://www.bco-dmo.org/dataset/753188/license (external link)
attribute NC_GLOBAL metadata_source String https://www.bco-dmo.org/api/dataset/753188 (external link)
attribute NC_GLOBAL Northernmost_Northing double 44.25
attribute NC_GLOBAL param_mapping String {'753188': {'lon_deg': 'flag - longitude', 'lat_deg': 'flag - latitude'}}
attribute NC_GLOBAL parameter_source String https://www.bco-dmo.org/mapserver/dataset/753188/parameters (external link)
attribute NC_GLOBAL people_0_affiliation String Rutgers University
attribute NC_GLOBAL people_0_person_name String Malin Pinsky
attribute NC_GLOBAL people_0_person_nid String 554708
attribute NC_GLOBAL people_0_role String Principal Investigator
attribute NC_GLOBAL people_0_role_type String originator
attribute NC_GLOBAL people_1_affiliation String Rutgers University
attribute NC_GLOBAL people_1_person_name String Rebecca Selden
attribute NC_GLOBAL people_1_person_nid String 753186
attribute NC_GLOBAL people_1_role String Contact
attribute NC_GLOBAL people_1_role_type String related
attribute NC_GLOBAL people_2_affiliation String Woods Hole Oceanographic Institution
attribute NC_GLOBAL people_2_affiliation_acronym String WHOI BCO-DMO
attribute NC_GLOBAL people_2_person_name String Amber York
attribute NC_GLOBAL people_2_person_nid String 643627
attribute NC_GLOBAL people_2_role String BCO-DMO Data Manager
attribute NC_GLOBAL people_2_role_type String related
attribute NC_GLOBAL project String CC Fishery Adaptations
attribute NC_GLOBAL projects_0_acronym String CC Fishery Adaptations
attribute NC_GLOBAL projects_0_description String Description from NSF award abstract:\nClimate 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.\nThe project will address three questions:\n1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes?\n2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and\n3) Which institutions create incentives that sustain or maximize the value of natural capital and comprehensive social wealth in the face of rapid climate change?\nAn 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.
attribute NC_GLOBAL projects_0_end_date String 2018-08
attribute NC_GLOBAL projects_0_geolocation String Northeast US Continental Shelf Large Marine Ecosystem
attribute NC_GLOBAL projects_0_name String Adaptations of fish and fishing communities to rapid climate change
attribute NC_GLOBAL projects_0_project_nid String 559948
attribute NC_GLOBAL projects_0_start_date String 2014-09
attribute NC_GLOBAL publisher_name String Biological and Chemical Oceanographic Data Management Office (BCO-DMO)
attribute NC_GLOBAL publisher_type String institution
attribute NC_GLOBAL sourceUrl String (local files)
attribute NC_GLOBAL Southernmost_Northing double 35.25
attribute NC_GLOBAL standard_name_vocabulary String CF Standard Name Table v55
attribute NC_GLOBAL summary String 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).
attribute NC_GLOBAL title String [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)
attribute NC_GLOBAL version String 1
attribute NC_GLOBAL Westernmost_Easting double -75.75
attribute NC_GLOBAL xml_source String osprey2erddap.update_xml() v1.3
variable spp String
attribute spp bcodmo_name String taxon
attribute spp description String species scientific name
attribute spp long_name String SPP
attribute spp units String unitless
variable longitude double
attribute longitude _CoordinateAxisType String Lon
attribute longitude _FillValue double NaN
attribute longitude actual_range double -75.75, -65.75
attribute longitude axis String X
attribute longitude bcodmo_name String latitude
attribute longitude colorBarMaximum double 180.0
attribute longitude colorBarMinimum double -180.0
attribute longitude description String longitude of grid cell
attribute longitude ioos_category String Location
attribute longitude long_name String Longitude
attribute longitude nerc_identifier String https://vocab.nerc.ac.uk/collection/P09/current/LATX/ (external link)
attribute longitude source_name String lon_deg
attribute longitude standard_name String longitude
attribute longitude units String degrees_east
variable latitude double
attribute latitude _CoordinateAxisType String Lat
attribute latitude _FillValue double NaN
attribute latitude actual_range double 35.25, 44.25
attribute latitude axis String Y
attribute latitude bcodmo_name String longitude
attribute latitude colorBarMaximum double 90.0
attribute latitude colorBarMinimum double -90.0
attribute latitude description String latitude of grid cell
attribute latitude ioos_category String Location
attribute latitude long_name String Latitude
attribute latitude nerc_identifier String https://vocab.nerc.ac.uk/collection/P09/current/LONX/ (external link)
attribute latitude source_name String lat_deg
attribute latitude standard_name String latitude
attribute latitude units String degrees_north
variable scen String
attribute scen bcodmo_name String time_elapsed
attribute scen description String 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)
attribute scen long_name String Scen
attribute scen nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/ELTMZZZZ/ (external link)
attribute scen units String unitless
variable btemp float
attribute btemp _FillValue float NaN
attribute btemp actual_range float 1.264, 22.847
attribute btemp bcodmo_name String temperature
attribute btemp description String predicted bottom temperature from GFDL simulation
attribute btemp long_name String Btemp
attribute btemp nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/ (external link)
attribute btemp units String degrees Celsius
variable stemp float
attribute stemp _FillValue float NaN
attribute stemp actual_range float 1.157, 21.303
attribute stemp bcodmo_name String temperature
attribute stemp description String predicted surface temperature from GFDL simulation
attribute stemp long_name String Stemp
attribute stemp nerc_identifier String https://vocab.nerc.ac.uk/collection/P01/current/TEMPP901/ (external link)
attribute stemp units String degrees Celsius
variable preds1 float
attribute preds1 _FillValue float NaN
attribute preds1 actual_range float 0.0, 0.984
attribute preds1 bcodmo_name String unknown
attribute preds1 description String predicted probability of occurrence (0-1)
attribute preds1 long_name String Preds1
attribute preds1 units String dimensionless
variable preds float
attribute preds _FillValue float NaN
attribute preds actual_range float 0.0, 353.278
attribute preds bcodmo_name String biomass
attribute preds description String predicted biomass
attribute preds long_name String Preds
attribute preds units String kilograms (kg)
variable se_fit float
attribute se_fit _FillValue float NaN
attribute se_fit actual_range float 0.054, 0.187
attribute se_fit bcodmo_name String biomass
attribute se_fit description String standard error of prediction for probability of occurrence
attribute se_fit long_name String Se Fit
attribute se_fit units String kilograms (kg)
variable preds1_upr float
attribute preds1_upr _FillValue float NaN
attribute preds1_upr actual_range float 0.001, 0.988
attribute preds1_upr bcodmo_name String unknown
attribute preds1_upr description String upper bound of predicted probability of occurrence (fit + 2SE)
attribute preds1_upr long_name String Preds1 Upr
attribute preds1_upr units String dimensionless
variable preds1_lwr float
attribute preds1_lwr _FillValue float NaN
attribute preds1_lwr actual_range float 0.0, 0.977
attribute preds1_lwr bcodmo_name String unknown
attribute preds1_lwr description String lower bound of predicted probability of occurrence (fit -2SE)
attribute preds1_lwr long_name String Preds1 Lwr
attribute preds1_lwr units String dimensionless

 
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