Standardization of commercial catch data from multiple gears in mixed fisheries accounting for preferential sampling, catchability, and fishing effort

Commercial fisheries constitute a valuable source of high-resolution information that can aid in assessing stocks and establishing management schemes. Especially, multi-gear and multi-species fisheries can provide fine-scale insights in space and time with regards to the patterns in species distribution and abundance as well as to the comparative behavior of the fishing gears deployed. In this work we propose a Generalized Additive Modeling framework to standardize catch data collected through observer monitoring programs using a 2018–2021 dataset from the eastern Ionian (Mediterranean Sea, FAO GFCM GSA20) as a case study of data-poor mixed fisheries. Our framework extends the standardization procedures by accounting for preferential sampling, integrating effort from multiple gears and jointly modeling species. We show that such an integration leads to more robust estimations of abundance for both target and by-catch species as well as decreases inference uncertainty. Regarding single stocks, the identification of the independent effect of factors (e.g. spatial, temporal, fishing effort, gear, skipper effect) can aid in monitoring and management decisions; furthermore, an objective index of abundance is estimated that can be used to infer inter-annual trends from more extended time-series useful for stock assessments. Using standardized catch values, we have generated seasonal maps of species distribution and multiple-species persistence hotspots that are useful for designing spatiotemporal management restrictions and also informative of species ecology. We also address the effect of the technical (selectivity) and behavioral aspects of the fishing gears to inform gear-based management. Finally, we demonstrate how this broad inferential process can be condensed to form species assemblages (based on their shared responses on drivers of catch and abundance) as well as fishing gear assemblages (based on their catch profiles and the apparent heterogeneity between vessels deploying common gears) that can act as units of reference for management. Apart from an objective estimation of stock abundance in time and space, our standardization framework illustrates how ecological, technical and behavioral aspects of mixed fisheries can be collectively evaluated to inform stock assessment and management. • Commercial catch data have intrinsic biases regarding fishing effort and selectivity. • Data from multiple gears can provide broad spatio-temporal coverage. • Standardization of catch data from multiple gears provided integrated insights. • Catch standardization can be useful to design/evaluate management schemes.