A Bayesian model of fisheries discards with flexible structure and priors defined by experts

Abstract

Minimizing the probability of discards is an important step in mitigating environmental impacts of fishing activities and maximizing economic gains from fish stocks. Although several discard models have been recently developed, current approaches are still unable to robustly adjust to different circumstances (e.g. fishery target species, geographical location), and lack a closer interaction with stakeholders. Here, we present a novel approach consisting of a modular Bayesian model, which can incorporate any relevant explanatory variable, independently of data availability. The relationships between the variables and discard rates are initially delineated by stakeholders through surveys, and included to the model as priors. The priors are then used together with observed data for estimating posterior distributions of discard probability. We test this approach in two study areas at the Mediterranean Sea: the Ligurian and Tyrrhenian Seas in Italy, and the Greek part of the Aegean Sea. For each site, we evaluated the model for estimating discards from bottom trawl fishery associated with European minimum conservation reference size regulations, as well as discards caused by the low economic value of catches.