New Zealand Statistical Association 2024 Conference

Oxana Hart

Victoria University of Wellington

Using spatio-temporal models to investigate stock structure, seasonality and environment influences in the snapper population from the west coast of New Zealand

This is joint work with Arnaud Grüss, Nokuthaba Sibanda, Adam Langley, Matthew Pinkerton

Spatio-temporal modelling is a valuable geostatistical approach that is increasingly being used for fish populations, which accounts for both spatial and spatio-temporal autocorrelation/structure in the data at a very fine scale. As such, spatio-temporal models have the potential to account for a lot of the unmeasured variation in the data. Spatio-temporal models can also include environmental covariates to represent environmental influences on fish density and/or catchability covariates to account for confounding variables affecting fish catchability (detectability).

Our research investigates stock structure, seasonality, and environmental influences in the snapper population from the west coast of New Zealand, using spatio-temporal models fitted to commercial bottom trawl catch-per-unit-effort data collected between 2008 and 2022.

Spatio-temporal models provide us with indices of relative abundance and estimates of population range and boundaries for subregions of the west coast of New Zealand, and inform us about spatial patterns of median log-density and interannual variability along the well coast, as well as about “core” and “transition” areas for snapper in the study region. All this information allows us to better understand seasonality, potential seasonal migration and stock structure in the snapper population from the west coast of New Zealand.

Our modelling framework for snapper allows us to enhance understanding of snapper ecology and provides important information to assist snapper population assessments. Our research demonstrates the value of spatio-temporal models in ecological research and illustrates how geostatistical methods can be employed to address complex issues in marine science.