Combining sale records of landings and fishers knowledge for predicting metiers in a small-scale, multi-gear, multispecies fishery

TL;DR

This study develops a method combining fishers' knowledge and sales data to accurately predict fishing trip metiers in Mallorca's small-scale fishery, enhancing stock management and understanding of fishery dynamics.

Contribution

The paper introduces a novel approach that integrates expert knowledge with landings data to predict fishing trip metiers, improving data reliability for small-scale multispecies fisheries.

Findings

Successfully predicted metiers for over 162,000 trips from 2004-2015

Identified seasonal patterns and effort trends in different metiers

Effort, landings, and revenues declined over 12 years

Abstract

Stock management should be guided by assessment models that, among others, need to be fed by reliable data of catch and effort. However, precise data are difficult to obtain in heterogeneous fisheries. Specifically, small scale, multi gear, multispecies fisheries are dynamic systems where fishers may lively change fishing strategy conditioned by multiple drivers. Provided that some stocks can be shared by several metiers, a precise categorization of metiers should be the first step toward metier specific estimates of catch and effort, which in turn would allow a better understanding of the system dynamics. Here we propose an approach for predicting the metier of any given fishing trip from its landing records. This approach combines the knowledge of expert fishers with the existing sales register of landings in Mallorca. It successfully predicts metiers for all the 162815 small scale fishery fishing trips from Mallorca between 2004 and 2015. The largest effort is invested in the metiers Cuttlefish Fish and Spiny lobster, landings peak for Cuttlefish Fish and Dolphinfish and revenues for Spiny lobster and Dolphinfish. Metier predictions also allowed us to describe the temporal trends experienced by each metier and to characterize the species that are specific to each metier. Seasonal variability is by far more relevant than between year variability, which confirms that at least some fishers are adopting a rotation cycle of metiers along the year. Effort, landings and gross revenues decreased in the last 12 years. The approach proposed is also applicable to any other fishery for which the metier for a fishing trip sample is known, but relying on fishers expertise points more directly to fishers intention. Thus, metier predictions produced with the proposed approach are closer to the actual uses of fishers, providing better grounds for an improved management.