http://lod.bco-dmo.org/id/dataset/765477
eng; USA
utf8
dataset
Highest level of data collection, from a common set of sensors or instrumentation, usually within the same research project
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
2019-04-22
ISO 19115-2 Geographic Information - Metadata - Part 2: Extensions for Imagery and Gridded Data
ISO 19115-2:2009(E)
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
2019-04-22
publication
2019-04-22
revision
Marine Biological Laboratory/Woods Hole Oceanographic Institution Library (MBLWHOI DLA)
2019-05-22
publication
https://doi.org/10.1575/1912/bco-dmo.765477.1
Malin Pinsky
Rutgers University
principalInvestigator
Lauren Rogers
Stanford University
principalInvestigator
Robert Griffin
Stanford University
principalInvestigator
Kevin St. Martin
Rutgers University
principalInvestigator
Emma Fuller
Princeton University
principalInvestigator
Talia Young
Rutgers University
principalInvestigator
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
publisher
Cite this dataset as: Rogers, L., Griffin, R., Young, T., Fuller, E., St. Martin, K., Pinsky, M. (2019) 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. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2019-04-22 [if applicable, indicate subset used]. doi:10.1575/1912/bco-dmo.765477.1 [access date]
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 Dataset Description: <p>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 (&lt;&gt; 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.</p> Methods and Sampling: <p>The following methods are excerpted from Rogers et al. (in press):<br />
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.</p>
<p>Once aggregated into communities, trips were then weighted by a variable (“fisherdays”) 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.</p>
<p>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.</p>
<p>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 (<a href="https://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html" target="_blank">https://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html</a>). 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.</p>
<p>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:</p>
<p><a href="https://datadocs.bco-dmo.org/docs/CC_Fishery_Adaptations/data_docs/765477/communityAttributesRisk_Formula.png"><img alt="communityAttributesRisk_Formula.png" src="https://datadocs.bco-dmo.org/docs/CC_Fishery_Adaptations/data_docs/765477/communityAttributesRisk_Formula.png" style="height:25px; width:209px" /></a></p>
<p>where Sₛ,꜀ is the mean projected change in habitat suitability for species s across the serviceshed of community c, and pRevₛ,꜀ 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.</p>
<p>The R file, "Servicesheds.rData" (see&nbsp;"Supplemental Documents" below) is&nbsp;a 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"&nbsp;to 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",&nbsp;with data stored in the SPDF object "Servicesheds".</p>
Funding provided by NSF Division of Ocean Sciences (NSF OCE) Award Number: OCE-1426891 Award URL: https://www.nsf.gov/awardsearch/show-award?AWD_ID=1426891
completed
Malin Pinsky
Rutgers University
848-932-8242
14 College Farm Rd.
New Brunswick
NJ
08901
USA
malin.pinsky@rutgers.edu
pointOfContact
Lauren Rogers
Stanford University
206-526-4243
Alaska Fisheries Science Center 7600 Sand Point Way NE
Seattle
WA
98115
USA
lauren.rogers@noaa.gov
pointOfContact
Robert Griffin
Stanford University
rmgriff@stanford.edu
pointOfContact
Kevin St. Martin
Rutgers University
848-445-3634
Dept. of Geography, Rutgers University 54 Joyce Kilmer Dr.
Piscataway
NJ
08854
USA
kstmarti@rci.rutgers.edu
pointOfContact
Emma Fuller
Princeton University
206-618-7602
emma.cassel.fuller@gmail.com
pointOfContact
Talia Young
Rutgers University
848-228-2542
tyoung@marine.rutgers.edu
pointOfContact
asNeeded
Dataset Version: 1
Unknown
Community
Port
State
Gear
PortLon
PortLat
Fleetsize
Trips
Years
ShedArea
RiskExposure
theme
None, User defined
site
instrument
longitude
latitude
No BCO-DMO term
site description
featureType
BCO-DMO Standard Parameters
otherRestrictions
otherRestrictions
Access Constraints: none. Use Constraints: Please follow guidelines at: http://www.bco-dmo.org/terms-use Distribution liability: Under no circumstances shall BCO-DMO be liable for any direct, incidental, special, consequential, indirect, or punitive damages that result from the use of, or the inability to use, the materials in this data submission. If you are dissatisfied with any materials in this data submission your sole and exclusive remedy is to discontinue use.
Adaptations of fish and fishing communities to rapid climate change
https://osprey.bco-dmo.org/project/559948
Adaptations of fish and fishing communities to rapid climate change
<p><em>Description from NSF award abstract:</em><br />
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.</p>
<p>The project will address three questions:<br />
1) How do the interacting impacts of fishing and climate change affect the persistence, abundance, and distribution of marine fishes?<br />
2) How do fishers and fishing communities adapt to species range shifts and related changes in abundance? and<br />
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?</p>
<p>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.</p>
CC Fishery Adaptations
largerWorkCitation
project
eng; USA
oceans
-76.693
-69.253
34.718
43.927
1996-01-01
2014-12-31
Northeast US Continental Shelf Large Marine Ecosystem
0
BCO-DMO catalogue of parameters from 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
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
http://lod.bco-dmo.org/id/dataset-parameter/765532.rdf
Name: Community
Units: unitless
Description: <p>Community-at-sea name, indicating port city and gear/vessel type</p>
http://lod.bco-dmo.org/id/dataset-parameter/765533.rdf
Name: Port
Units: unitless
Description: <p>Port city</p>
http://lod.bco-dmo.org/id/dataset-parameter/765534.rdf
Name: State
Units: unitless
Description: <p>State</p>
http://lod.bco-dmo.org/id/dataset-parameter/765535.rdf
Name: Gear
Units: unitless
Description: <p>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.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765536.rdf
Name: PortLon
Units: degrees East
Description: <p>Longitude of port city.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765537.rdf
Name: PortLat
Units: degrees North
Description: <p>Latitude of port city.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765538.rdf
Name: Fleetsize
Units: number of vessels
Description: <p>Average number of vessels in the community.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765539.rdf
Name: Trips
Units: number of trips
Description: <p>Total number of trips taken over the duration of the study.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765540.rdf
Name: Years
Units: number of years
Description: <p>Number of years the community was extant.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765541.rdf
Name: ShedArea
Units: square kilometers (sq km)
Description: <p>Area of the serviceshed, defined as the 90% volume contour of fisher days at sea.</p>
http://lod.bco-dmo.org/id/dataset-parameter/765542.rdf
Name: RiskExposure
Units: unitless
Description: <p>Calculated risk exposure score based on projected changes in habitat suitability for harvested species. Negative values indicate increased exposure to risk.</p>
GB/NERC/BODC > British Oceanographic Data Centre, Natural Environment Research Council, United Kingdom
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact
8325
https://darchive.mblwhoilibrary.org/bitstream/1912/24155/1/dataset-765477_attributes-communities-sea__v1.tsv
download
https://doi.org/10.1575/1912/bco-dmo.765477.1
download
onLine
dataset
<p>The following methods are excerpted from Rogers et al. (in press):<br />
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.</p>
<p>Once aggregated into communities, trips were then weighted by a variable (“fisherdays”) 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.</p>
<p>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.</p>
<p>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 (<a href="https://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html" target="_blank">https://www.st.nmfs.noaa.gov/st1/commercial/landings/annual_landings.html</a>). 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.</p>
<p>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:</p>
<p><a href="https://datadocs.bco-dmo.org/docs/CC_Fishery_Adaptations/data_docs/765477/communityAttributesRisk_Formula.png"><img alt="communityAttributesRisk_Formula.png" src="https://datadocs.bco-dmo.org/docs/CC_Fishery_Adaptations/data_docs/765477/communityAttributesRisk_Formula.png" style="height:25px; width:209px" /></a></p>
<p>where Sₛ,꜀ is the mean projected change in habitat suitability for species s across the serviceshed of community c, and pRevₛ,꜀ 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.</p>
<p>The R file, "Servicesheds.rData" (see&nbsp;"Supplemental Documents" below) is&nbsp;a 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"&nbsp;to 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",&nbsp;with data stored in the SPDF object "Servicesheds".</p>
Specified by the Principal Investigator(s)
<p>Data were processed using R version 3.4.4.</p>
Specified by the Principal Investigator(s)
asNeeded
7.x-1.1
Biological and Chemical Oceanography Data Management Office (BCO-DMO)
Unavailable
508-289-2009
WHOI MS#36
Woods Hole
MA
02543
USA
info@bco-dmo.org
http://www.bco-dmo.org
Monday - Friday 8:00am - 5:00pm
For questions regarding this resource, please contact BCO-DMO via the email address provided.
pointOfContact