A comparative analysis of fish stock assessment methods: Spatial-temporal versus VPA.

Abstract

This thesis presents research on an alternative spatial-temporal method of fish stock assessment. We develop a simulation model of spatial-temporal stock analysis and compare its assessment with the common VPA/SPA method. In recent years, fisheries biologists have depended mainly on age structured aggregated sequential population analysis (SPA)/virtual population analysis (VPA) for stock assessment purposes. The VPA method is an aggregate model that consolidates all spatial and within-season temporal stock dynamics into a single total stock estimate. The proposed spatial-temporal method produces historical estimates of population size and fishing mortality rate by age and year. In this thesis, the abundance states of age-aggregated stock components are tracked in space over the course of each season using computer simulation. Data about fish stock spatial-temporal migration dynamics are used to estimate stock abundance in space and time over the course of a fishing season. The spatial-temporal assessment method is applied to the herring stock of the Scotia Fundy region of Atlantic Canada. The dynamics of the herring spawning groups are described and the simulation model is developed for a given season. The results suggest that disaggregated spatial-temporal estimates provide more information for in-season management of herring spawning groups than the traditional aggregate VPA approach.