Disentangling the socio-ecological drivers behind illegal fishing in a small-scale fishery managed by a TURF system

TL;DR

This study investigates how socio-economic factors influence illegal fishing in Chilean small-scale fisheries managed by TURF systems, using Bayesian analysis to identify key drivers affecting resource sustainability.

Contribution

It introduces a Bayesian-Belief Network approach to analyze multiple socio-economic and environmental drivers impacting illegal fishing in small-scale TURF-managed fisheries.

Findings

No direct link between enforcement level and resource status.

Alternative economic activities significantly influence illegal fishing.

Bayesian-Belief Network effectively models complex socio-ecological interactions.

Abstract

A substantial increase in illegal extraction of the benthic resources in central Chile is likely driven by an interplay of numerous socio-economic local factors that threatens the success of the fisheries management areas (MA) system. To assess this problem, the exploitation state of a commercially important benthic resource (i.e., keyhole limpet) in the MAs was related with socio-economic drivers of the small-scale fisheries. The potential drivers of illegal extraction included rebound effect of fishing effort displacement by MAs, level of enforcement, distance to surveillance authorities, wave exposure and land-based access to the MA, and alternative economic activities in the fishing village. The exploitation state of limpets was assessed by the proportion of the catch that is below the minimum legal size, with high proportions indicating a poor state, and by the relative median size of limpets fished within the MAs in comparison with neighbouring OA areas, with larger relative sizes in the MA indicating a good state. A Bayesian-Belief Network approach was adopted to assess the effects of potential drivers of illegal fishing on the status of the benthic resource in the MAs. Results evidenced the absence of a direct link between the level of enforcement and the status of the resource, with other socio-economic (e.g., alternative economic activities in the village) and context variables (e.g., fishing effort or distance to surveillance authorities) playing important roles. Scenario analysis explored variables that are susceptible to be managed, evidencing that BBN is a powerful approach to explore the role of multiple external drivers, and their impact on marine resources, in complex small-scale fisheries.