University Of Tasmania

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Understanding socio-ecological drivers of spatial allocation choice in a multi-species artisanal fishery: a Bayesian network modeling approach

journal contribution
posted on 2023-05-18, 17:03 authored by Naranjo-Madrigal, H, Elizabeth Van PuttenElizabeth Van Putten, Norman-Lopez, A
Effective management of artisanal fisheries requires understanding fishers, their behaviors, and the drivers that underpin their choices. Behavioral drivers are critical links in understanding the interactions between social and ecological systems and can help inform effective management approaches. A Bayesian Belief Network modeling approach was used to investigate a diverse range of qualitative and quantitative social and ecological drivers of spatial location choice in a multi-species artisanal dive fishery in Costa Rica. Empirical and observer data used to populate the BBN showed the influence of economic factors, environmental conditions as well as social interactions on the decision-making process of spatial location choice. Good governance scenarios represented by Responsible Fisheries Marine Areas Management were analyzed for both hookah and free diving methods to assess the effects of responsible fishing on the fishers and the fishery. Model based-scenario analysis suggests that management interventions should consider the fisher's potential behavioral responses in the context of environmental variability, dependence on cultural assets, and food security. The results show that there is a need to understand fisher's decisions based on broad socio-ecological system understanding and consider the environmental outcomes alongside food security and the cultural significance of different marine species to fishing communities.


Publication title

Marine Policy








Institute for Marine and Antarctic Studies


Pergamon Press

Place of publication

United Kingdom

Rights statement

Copyright 2015 Elsevier Ltd

Repository Status

  • Restricted

Socio-economic Objectives

Assessment and management of terrestrial ecosystems