Modelling spatio-temporal preferences for albacore tuna

Abstract

This research looks at using a spatially explicit population modeling technique to predict the relative spatial distribution of albacore tuna Thunnus alalunga around New Zealand. Spatial Population Model (SPM) software implements preference processes to move a population around a spatial structure within the modeled area. The preference attributes that best reproduced the relative spatial and temporal distribution of longline fishery commercial catch rates were estimated as sea surface temperature as a logistic function and sea surface gradient (magnitude of front) as a logistic function. Albacore tuna were found to prefer areas with warmer temperatures, and areas with high seas surface gradient, which represents oceanic fronts. This study also investigated incorporating dependence structures between preference attributes using copulas. Future research in the area of spatially explicit population modeling is then suggested.