ERDDAP > info > bcodmo_dataset_765477

Grid DAP Data	Sub- set	Table DAP Data	Make A Graph	W M S	Source Data Files	Acces- sible	Title	Sum- mary	ISO, Metadata	Back- ground Info	RSS	E mail	Institution	Dataset ID
		data	graph		files	public	Attributes of communities-at-sea, including the size of servicesheds and climate change risk exposure scores, determined from Vessel Trip Report (VTR) data for commercial fishing trips from 1996 to 2014		I   M	background			BCO-DMO	bcodmo_dataset_765477

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	The following methods are excerpted from Rogers et al. (in press): A trip was classified as belonging to a community if it shared the community's gear type and landing port, and the vessel either declared that port as its principal port or landed in that port at least 50% of its trips that year. Once aggregated into communities, trips were then weighted by a variable (\u201cfisherdays\u201d) indicating labor time expended on each trip: trip length (in days) multiplied by the number of crew on board. Fisherdays indicate how important an area at sea is to a community in terms of how much time they invest in that location. Given reported trip locations and fisherdays, we then created raster maps using a kernel density method. The resultant maps distribute fisherdays using different size kernels depending upon the fishery/gear-type/length. Nearshore fishing was processed using a smaller kernel (7.5 - 10 km) than offshore fishing (10 - 15 km). We used the area defined by a 90% volume contour (i.e., an area which encompasses 90% of fisherdays) to define the customary fishing grounds or servicesheds for a community. To compare the relative historical importance of particular species to a community-at-sea, landings data were compiled from vessel trip reports and summed over the available years of data for each community. Price information was extracted from NOAA Fisheries, Fisheries Statistics Division ([https://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html](\\"https://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html\\")). We used the average price per lb by species, adjusted for inflation (real 2014 prices in US$), over the period for which we had community-level data. State- level prices were used when available, and otherwise regional prices were used. We assessed a community's exposure to risk based on their historical dependence on species and spatial fishing patterns. A community was more exposed to risk if the species from which it historically earned the most revenue were projected to lose habitat in the locations where the community has traditionally fished. Specifically, risk exposure scores for communities were calculated as: [](\\"https://datadocs.bco- dmo.org/docs/CC_Fishery_Adaptations/data_docs/765477/communityAttributesRisk_Formula.png\\") where S\u209b,\ua700 is the mean projected change in habitat suitability for species s across the serviceshed of community c, and pRev\u209b,\ua700 is the proportion of historical revenues from fishing that the community has derived from species s. Positive risk exposure scores indicated expanding opportunities for communities based on their historical fishing revenue portfolios and projected changes to species habitat at sea, while negative values indicated shrinking opportunities and increased exposure to negative impacts of climate change. The R file, \"Servicesheds.rData\" (see\u00a0\"Supplemental Documents\" below) is\u00a0a spatial polygon dataframe (SPDF) giving 90% volume contours of fisher-days at sea for 98 communities-at-sea. The polygons outline the at-sea \"servicesheds\" or customary fishing grounds of communities. We use \"serviceshed\"\u00a0to describe the area from which a community has historically received ecosystem services, specifically fish in this case. The file is intended to be read by the program \"R\",\u00a0with data stored in the SPDF object \"Servicesheds\".
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	Attributes of communities-at-sea, including the size of servicesheds and climate change risk exposure scores PIs: Lauren Rogers & Malin Pinsky Version date: 22-April-2019
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	2019-04-22T19:43:43Z
attribute	NC_GLOBAL	date_modified	String	2019-05-21T20:06:35Z
attribute	NC_GLOBAL	defaultDataQuery	String	&time<now
attribute	NC_GLOBAL	doi	String	10.1575/1912/bco-dmo.765477.1
attribute	NC_GLOBAL	Easternmost_Easting	double	-69.253
attribute	NC_GLOBAL	geospatial_lat_max	double	43.927
attribute	NC_GLOBAL	geospatial_lat_min	double	34.718
attribute	NC_GLOBAL	geospatial_lat_units	String	degrees_north
attribute	NC_GLOBAL	geospatial_lon_max	double	-69.253
attribute	NC_GLOBAL	geospatial_lon_min	double	-76.693
attribute	NC_GLOBAL	geospatial_lon_units	String	degrees_east
attribute	NC_GLOBAL	infoUrl	String	https://www.bco-dmo.org/dataset/765477
attribute	NC_GLOBAL	institution	String	BCO-DMO
attribute	NC_GLOBAL	keywords	String	area, bco, bco-dmo, biological, chemical, community, data, dataset, dmo, erddap, exposure, fleetsize, gear, management, oceanography, office, port, PortLat, PortLon, preliminary, risk, RiskExposure, shed, ShedArea, state, trips, years
attribute	NC_GLOBAL	license	String	https://www.bco-dmo.org/dataset/765477/license
attribute	NC_GLOBAL	metadata_source	String	https://www.bco-dmo.org/api/dataset/765477
attribute	NC_GLOBAL	Northernmost_Northing	double	43.927
attribute	NC_GLOBAL	param_mapping	String	{'765477': {'PortLon': 'flag - longitude', 'PortLat': 'flag - latitude'}}
attribute	NC_GLOBAL	parameter_source	String	https://www.bco-dmo.org/mapserver/dataset/765477/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	Stanford University
attribute	NC_GLOBAL	people_1_person_name	String	Lauren Rogers
attribute	NC_GLOBAL	people_1_person_nid	String	765425
attribute	NC_GLOBAL	people_1_role	String	Principal Investigator
attribute	NC_GLOBAL	people_1_role_type	String	originator
attribute	NC_GLOBAL	people_2_affiliation	String	Stanford University
attribute	NC_GLOBAL	people_2_person_name	String	Robert Griffin
attribute	NC_GLOBAL	people_2_person_nid	String	768380
attribute	NC_GLOBAL	people_2_role	String	Co-Principal Investigator
attribute	NC_GLOBAL	people_2_role_type	String	originator
attribute	NC_GLOBAL	people_3_affiliation	String	Rutgers University
attribute	NC_GLOBAL	people_3_person_name	String	Kevin St. Martin
attribute	NC_GLOBAL	people_3_person_nid	String	559961
attribute	NC_GLOBAL	people_3_role	String	Co-Principal Investigator
attribute	NC_GLOBAL	people_3_role_type	String	originator
attribute	NC_GLOBAL	people_4_affiliation	String	Princeton University
attribute	NC_GLOBAL	people_4_person_name	String	Emma Fuller
attribute	NC_GLOBAL	people_4_person_nid	String	748888
attribute	NC_GLOBAL	people_4_role	String	Scientist
attribute	NC_GLOBAL	people_4_role_type	String	originator
attribute	NC_GLOBAL	people_5_affiliation	String	Rutgers University
attribute	NC_GLOBAL	people_5_person_name	String	Talia Young
attribute	NC_GLOBAL	people_5_person_nid	String	752628
attribute	NC_GLOBAL	people_5_role	String	Scientist
attribute	NC_GLOBAL	people_5_role_type	String	originator
attribute	NC_GLOBAL	people_6_affiliation	String	National Oceanic and Atmospheric Administration - Alaska Fisheries Science Center
attribute	NC_GLOBAL	people_6_affiliation_acronym	String	NOAA-AFSC
attribute	NC_GLOBAL	people_6_person_name	String	Lauren Rogers
attribute	NC_GLOBAL	people_6_person_nid	String	765425
attribute	NC_GLOBAL	people_6_role	String	Contact
attribute	NC_GLOBAL	people_6_role_type	String	related
attribute	NC_GLOBAL	people_7_affiliation	String	Woods Hole Oceanographic Institution
attribute	NC_GLOBAL	people_7_affiliation_acronym	String	WHOI BCO-DMO
attribute	NC_GLOBAL	people_7_person_name	String	Shannon Rauch
attribute	NC_GLOBAL	people_7_person_nid	String	51498
attribute	NC_GLOBAL	people_7_role	String	BCO-DMO Data Manager
attribute	NC_GLOBAL	people_7_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	34.718
attribute	NC_GLOBAL	standard_name_vocabulary	String	CF Standard Name Table v55
attribute	NC_GLOBAL	summary	String	Communities-at-sea are peer-groups of vessels which share a gear type and are associated with a particular port (e.g., vessels from New Bedford, MA that use gillnets). For vessels using trawl gear, small and large trawlers are considered separate communities according to vessel length (<> 65 feet). We used Vessel Trip Report (VTR) data for commercial fishing trips from 1996 to 2014, as reported by vessel captains, to determine the at-sea \servicesheds\ or customary fishing grounds of communities.
attribute	NC_GLOBAL	title	String	Attributes of communities-at-sea, including the size of servicesheds and climate change risk exposure scores, determined from Vessel Trip Report (VTR) data for commercial fishing trips from 1996 to 2014
attribute	NC_GLOBAL	version	String	1
attribute	NC_GLOBAL	Westernmost_Easting	double	-76.693
attribute	NC_GLOBAL	xml_source	String	osprey2erddap.update_xml() v1.3
variable	Community		String
attribute	Community	bcodmo_name	String	site
attribute	Community	description	String	Community-at-sea name, indicating port city and gear/vessel type
attribute	Community	long_name	String	Community
attribute	Community	units	String	unitless
variable	Port		String
attribute	Port	bcodmo_name	String	site
attribute	Port	description	String	Port city
attribute	Port	long_name	String	Port
attribute	Port	units	String	unitless
variable	State		String
attribute	State	bcodmo_name	String	site
attribute	State	description	String	State
attribute	State	long_name	String	State
attribute	State	units	String	unitless
variable	Gear		String
attribute	Gear	bcodmo_name	String	instrument
attribute	Gear	description	String	Type of fishing gear/vessel. Large Trawl indicates vessels longer than 65 feet using trawl gear. Small Trawl are vessels less than 65 feet using trawl gear.
attribute	Gear	long_name	String	Gear
attribute	Gear	units	String	unitless
variable	longitude		double
attribute	longitude	_CoordinateAxisType	String	Lon
attribute	longitude	_FillValue	double	NaN
attribute	longitude	actual_range	double	-76.693, -69.253
attribute	longitude	axis	String	X
attribute	longitude	bcodmo_name	String	longitude
attribute	longitude	description	String	Longitude of port city.
attribute	longitude	ioos_category	String	Location
attribute	longitude	long_name	String	Port Lon
attribute	longitude	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/LONX/
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	34.718, 43.927
attribute	latitude	axis	String	Y
attribute	latitude	bcodmo_name	String	latitude
attribute	latitude	description	String	Latitude of port city.
attribute	latitude	ioos_category	String	Location
attribute	latitude	long_name	String	Port Lat
attribute	latitude	nerc_identifier	String	https://vocab.nerc.ac.uk/collection/P09/current/LATX/
attribute	latitude	standard_name	String	latitude
attribute	latitude	units	String	degrees_north
variable	Fleetsize		byte
attribute	Fleetsize	_FillValue	byte	127
attribute	Fleetsize	actual_range	byte	3, 82
attribute	Fleetsize	bcodmo_name	String	unknown
attribute	Fleetsize	description	String	Average number of vessels in the community.
attribute	Fleetsize	long_name	String	Fleetsize
attribute	Fleetsize	units	String	number of vessels
variable	Trips		int
attribute	Trips	_FillValue	int	2147483647
attribute	Trips	actual_range	int	198, 50794
attribute	Trips	bcodmo_name	String	unknown
attribute	Trips	description	String	Total number of trips taken over the duration of the study.
attribute	Trips	long_name	String	Trips
attribute	Trips	units	String	number of trips
variable	Years		byte
attribute	Years	_FillValue	byte	127
attribute	Years	actual_range	byte	8, 18
attribute	Years	bcodmo_name	String	unknown
attribute	Years	description	String	Number of years the community was extant.
attribute	Years	long_name	String	Years
attribute	Years	units	String	number of years
variable	ShedArea		int
attribute	ShedArea	_FillValue	int	2147483647
attribute	ShedArea	actual_range	int	973, 62952
attribute	ShedArea	bcodmo_name	String	site_descrip
attribute	ShedArea	description	String	Area of the serviceshed, defined as the 90% volume contour of fisher days at sea.
attribute	ShedArea	long_name	String	Shed Area
attribute	ShedArea	units	String	square kilometers (sq km)
variable	RiskExposure		float
attribute	RiskExposure	_FillValue	float	NaN
attribute	RiskExposure	actual_range	float	-0.241, 0.112
attribute	RiskExposure	bcodmo_name	String	unknown
attribute	RiskExposure	description	String	Calculated risk exposure score based on projected changes in habitat suitability for harvested species. Negative values indicate increased exposure to risk.
attribute	RiskExposure	long_name	String	Risk Exposure
attribute	RiskExposure	units	String	unitless

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.