Disentangling the socio-ecological drivers behind illegal fishing in a small-scale fishery managed by a TURF system
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.
Code (0)
등록된 구현이 없습니다.
Tasks
ManagementMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
A framework for analyzing ecological trait-based models in multi-dimensional niche spaces
We develop an theoretical approach for predicting biodiversity in multi-dimensional niche spaces, arising due to ecological drivers such as competitive exclusion. The novelty of our approach relies on the fact that ecolo…
Investigating the importance of social vulnerability in opioid-related mortality across the United States
The opioid crisis remains a critical public health challenge in the United States. Despite national efforts to reduce opioid prescribing rates by nearly 45\% between 2011 and 2021, opioid overdose deaths more than triple…
Feature ImportanceBayesian Networks for Causal Analysis in Socioecological Systems
Causal and counterfactual reasoning are emerging directions in data science that allow us to reason about hypothetical scenarios. This is particularly useful in fields like environmental and ecological sciences, where in…
counterfactualCounterfactual ReasoningA Framework to Quantify Adaptation to Multiple Drivers
We develop an analytical framework to assess the adaptations in a coupled ecological-economic system and apply it to a bio-economic model. Our framework allows us to quantify the impact of multiple drivers on a coupled e…
The Ecological Fallacy in Annotation: Modelling Human Label Variation goes beyond Sociodemographics
Many NLP tasks exhibit human label variation, where different annotators give different labels to the same texts. This variation is known to depend, at least in part, on the sociodemographics of annotators. Recent resear…