Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: Application to skipjack tuna

Abstract

A Spatial Ecosystem and Population Dynamic Model (SEAPODYM) is used in a data assimilation study aiming to estimate model parameters that describe dynamics of Pacific skipjack tuna population on ocean-based scale. The model based on advection–diffusion–reaction equations explicitly predicts spatial dynamics of large pelagic predators, while taking into account data on several mid-trophic level components, oceanic primary productivity and physical environment. In order to improve its quantitative ability, the model was parameterized through assimilation with commercial fisheries data, and optimization was carried out using maximum likelihood estimation approach. To address the optimization task we implemented an adjoint technique to obtain an exact, analytical evaluation of the likelihood gradient. We conducted a series of computer experiments in order to (i) determine model sensitivity with respect to variable parameters and, hence, investigate their observability; (ii) estimate observable parameters and their errors; and (iii) justify the reliability of the computed solution. Parameters describing recruitment, movement, habitat preferences, natural and fishing mortality of skipjack population were analysed and estimated. Results of the study suggest that SEAPODYM with achieved parameterization scheme can help to investigate the impact of fishing under various management scenarios, and also conduct forecasts of a given species stock and spatial dynamics in a context of environmental and climate changes.