ERDDAP > info > bcodmo_dataset_753188

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	FGDC, ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
		data	graph		files	public	[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)		F   I   M	background			BCO-DMO	bcodmo_dataset_753188

The Dataset's Variables and Attributes

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 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.
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
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 PI: Malin Pinsky 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/
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
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
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/753188
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
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: 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.
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/
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/
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/
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/
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/
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

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.