Integrating habitat features into spatio-temporal biomass dynamics models for a better understanding of stock productivity: a case study of sea scallop in the Bay of Fundy

Abstract

Abstract Recent efforts in ocean mapping of seafloor habitat have made data increasingly available. For bottom-dwelling and/or sessile species, there is often a strong relationship between population productivity and habitat, and stock assessment models are likely to be improved by the inclusion of habitat. Here, we extend a recently developed spatio-temporal biomass dynamics model to allow habitat to inform probabilities of non-zero tows and catchability. Simulation experiments demonstrate the ability of this new approach to reliably capture population trends over time and space, with the applicability of the method further demonstrated using data from the Canadian Maritimes Inshore Sea Scallop Fishery in the Bay of Fundy. This habitat-informed spatio-temporal biomass dynamics model better captures underlying processes, reduces uncertainty, thereby improving our understanding of stock status from which fisheries management decisions can be based.