Simulating spatial dynamics to evaluate methods of deriving abundance indices for tropical tunas

Abstract

Relative abundance indices derived from nominal catch-per-unit-effort (CPUE) data are a principle source of information for the majority of stock assessments. A particular problem with formulating such abundance indices for pelagic species such as tuna is the interpretation of CPUE data from fleets that have changed distribution over time. In this research, spatial population dynamics are simulated to test the historical pattern of fishing effort as a basis for making inferences about relative abundance. A number of age-structured, spatially disaggregated population dynamics models are described for both Atlantic yellowfin tuna ( Thunnus albacares ) and bigeye tuna ( Thunnus obesus ) to account for uncertainty in spatial distribution and movement. These models are used to evaluate the reliability of standardization methods and a commonly applied model selection criterion, Akaike’s information criterion (AIC). The simulations demonstrate the pitfalls of aggregating CPUE data over spatial areas and highlight the need for data imputation. Simulations support simpler models than those selected using AIC for extracting reliable indices of relative abundance.