Improving assessment of Pandalus stocks using a seasonal, size-structured assessment model with environmental variables. Part I: Model description and application

Abstract

Pandalus species display the following features that make it difficult to apply traditional age-based stock assessment models: (i) difficulty of determining age in the absence of hard parts retained through the molt; (ii) sex change in which individuals mature first as males and then transform to females; and (iii) potentially strong influence of environmental conditions on recruitment population dynamics. In this context, we propose a seasonal, size-structured assessment model dedicated to stock assessment of hermaphroditic Pandalidae. The modeling framework incorporates a submodel for changes of length at sex transformation and functions to incorporate environmental effects on recruitment dynamics. The model can be directly fitted to length-structured data, overcoming the length to age conversion problem. The model has a seasonal time step that allows it to account for seasonal variations in biological processes and fishing patterns. The model provides stock assessment outputs, such as fishing mortality and stock biomass estimates, and sex-specific abundance-at-length. The model is applied to the exploited shrimp stock of Pandalus borealis in the Gulf of Maine as an example of its utility. The model proposed in this study is flexible and generic and can be applied to many other exploited stocks.