Volume 21, Issue 1 p. 120-131
ORIGINAL ARTICLE

Social ties explain catch portfolios of small-scale fishers in the Caribbean

Steven M. Alexander,

Corresponding Author

National Socio-Environmental Synthesis Center (SESYNC), Annapolis, Maryland

Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden

Environmental Change and Governance Group, Faculty of Environment, University of Waterloo, Waterloo, ON, Canada

Correspondence

Steven M. Alexander and Phillip P.A. Staniczenko, National Socio-Environmental Synthesis Center (SESYNC), Annapolis, MD.

Emails: s22alexa@uwaterloo.ca; pstaniczenko@brooklyn.cuny.edu

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Phillip P. A. Staniczenko,

Corresponding Author

National Socio-Environmental Synthesis Center (SESYNC), Annapolis, Maryland

Department of Biology, University of Maryland College Park, College Park, Maryland

Department of Biology, Brooklyn College, City University of New York, New York, New York

Correspondence

Steven M. Alexander and Phillip P.A. Staniczenko, National Socio-Environmental Synthesis Center (SESYNC), Annapolis, MD.

Emails: s22alexa@uwaterloo.ca; pstaniczenko@brooklyn.cuny.edu

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Örjan Bodin,

Stockholm Resilience Centre, Stockholm University, Stockholm, Sweden

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First published: 31 October 2019
Citations: 5
Steven M. Alexander and Phillip P. A. Staniczenko are joint first authors.

Abstract

Small-scale fisheries often involve weak management regimes with limited top-down enforcement of rules and minimal support from legal institutions, making them useful model systems for investigating the role of social influence in determining economic and environmental outcomes. In such regimes, interpersonal relationships are expected to have a strong effect on a fisher's catch portfolio, the set of fish species targeted by an individual fisher. Here, we test three competing hypotheses about social influence using belief propagation network models and show that a peer-to-peer information-sharing social network is key to explaining catch portfolios at a small-scale fishery in Jamaica. We find that experience dictates the direction of influence among fishers in the social network, with older fishers and information brokers having distinct roles in shaping catch patterns for large- and small-sized fish species, respectively. These findings highlight concrete opportunities for harnessing social networks in natural resource management. Our new approach to modelling social influence is applicable to many social–ecological systems with minimal legal and institutional support or those that rely heavily on bottom-up participatory processes.

DATA AVAILABILITY STATEMENT

All data needed to evaluate the conclusions in the paper are present in the paper and supporting information. Additional data related to this paper may be requested from the authors. Code to perform belief propagation network and total length analysis is available from https://github.com/pstaniczenko/SSF

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