Combining fishery data through integrated species distribution models

Abstract Species Distribution Models are pivotal for fisheries management. There has been an increasing number of fishery data sources available, making integration attractive way to improve model predictions. A wide range methods have applied integrate different datasets in disciplines. We focus on the use Integrated (ISDMs) due their capacity formally accommodate types and scale proportional gear efficiencies. ISDMs joint modelling information from parameter estimation by fitting shared environmental, temporal spatial effects. illustrate this method first using a simulated example, then apply it case study that combines coming fishery-independent trawl survey fishery-dependent trammel net observations Solea solea. explore sensitivity outputs several weightings commercial also compare integrated results with ensemble combine population trends study. obtain similar but discuss requires both response variables link functions be same across models. conclude discussing flexibility requirements datasets.