Integrating population genomics and biophysical models towards evolutionary-based fisheries management

Overfishing and rapid environmental shifts pose severe challenges to the resilience and viability of marine fish populations. To develop and implement measures that enhance species' adaptive potential to cope with those pressures while, at the same time, ensuring sustainable exploitation rates is part of the central goal of fisheries management. Here, we argue that a combination of biophysical modelling and population genomic assessments offer ideal management tools to define stocks, their physical connectivity and ultimately, their short-term adaptive potential. To date, biophysical modelling has often been confined to fisheries ecology whereas evolutionary hypotheses remain rarely considered. When identified, connectivity patterns are seldom explored to understand the evolution and distribution of adaptive genetic variation, a proxy for species' evolutionary potential. Here, we describe a framework that expands on the conventional seascape genetics approach by using biophysical modelling and population genomics. The goals are to identify connectivity patterns and selective pressures, as well as putative adaptive variants directly responding to the selective pressures and, ultimately, link both to define testable hypotheses over species response to shifting ecological conditions and overexploitation.