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Technical Documentation, State of the Ecosystem Report

57 Fishery Reliance and Social Vulnerability

Description: Fishing community commercial and recreational fishing reliance and social vulnerability

Found in: State of the Ecosystem - Gulf of Maine & Georges Bank (2018+), State of the Ecosystem - Mid-Atlantic (2018+)

Indicator category: Database pull with analysis

Contributor(s): Lisa L. Colburn, Changhua Weng

Data steward: Changhua Weng

Point of contact: Lisa L. Colburn

Public availability statement: The source data used to construct the commercial fishing engagement and reliance indices include confidential information and are not available publicly. However, the commercial fishing engagement and reliance indices are not confidential so are available to the public. All calculated indices can be found here.

57.1 Methods

57.1.1 Data sources

NOAA Fisheries’ Community Social Vulnerability Indicators (CSVIs) were developed using secondary data including social, demographic and fisheries variables. The social and demographic data were downloaded from the 2018 American Community Survey (ACS) 5-yr estimates Dataset at the U.S. Census American Community Survey (ACS) for coastal communities at the Census Designated Place (CDP) level, and in some cases the County Subdivision (MCD) level. Commercial fisheries data were pulled from the SOLE server located at Northeast Fisheries Science Center in Woods Hole, MA. The recreational fishing information is publicly accessible through the Marine Recreational Information Program (MRIP), and for this analysis was custom requested from NOAA Fisheries headquarters.

57.1.2 Data extraction

Commercial fisheries data was pulled from the NEFSC SOLE server in Woods Hole, MA.

SQL and SAS code for data extraction and processing steps can be found here.

57.1.3 Data analysis

The indicators were developed using the methodology described in Jacob et al. (2010), Jacob et al. (2013), Colburn and Jepson (2012) and M. Jepson and Colburn (2013). Indicators were constructed through principal component analysis with a single factor solution, and the following criteria had to have been met: a minimum variance explained of 45%; Kasier-Meyer Olkin measure of sampling adequacy above.500; factor loadings above.350; Bartlett’s test of sphericity significance above .05; and an Armor’s Theta reliability coefficient above .500. Factor scores for each community were ranked based on standard deviations into the following categories: High(>=1.00SD), MedHigh .500-.999 SD), Moderate (.000-.499 SD) and Low (<.000 SD).

57.1.4 Data processing

Data were formatted for inclusion in the ecodata R package using the R script found here.

catalog link https://noaa-edab.github.io/catalog/engagement.html

References

Colburn, Lisa L., and Michael Jepson. 2012. “Social Indicators of Gentrification Pressure in Fishing Communities: A Context for Social Impact Assessment.” Coastal Management 40 (3): 289–300. https://doi.org/10.1080/08920753.2012.677635.
Jacob, Steve, Priscilla Weeks, Benjamin G. Blount, and Michael Jepson. 2010. “Exploring fishing dependence in gulf coast communities.” Marine Policy 34 (6): 1307–14. https://doi.org/10.1016/j.marpol.2010.06.003.
Jacob, Steve, Priscilla Weeks, Ben Blount, and Michael Jepson. 2013. “Development and evaluation of social indicators of vulnerability and resiliency for fishing communities in the Gulf of Mexico.” Marine Policy 37 (1): 86–95. https://doi.org/10.1016/j.marpol.2012.04.014.
Jepson, M., and L. L. Colburn. 2013. “Development of Social Indicators of Fishing Community Vulnerability and Resilience in the U.S. Southeast and Northeast Regions.” https://spo.nmfs.noaa.gov/content/tech-memo/development-social-indicators-fishing-community-vulnerability-and-resilience-us.