Incorporating the spatial component of fisheries data into stock assessment models

TLDR: In this article, a three-dimensional visualization of the age-structure and fishery dependent and independent data associated with the sparid fish Pterogymnus laniarius on the Agulhas Bank, South Africa is presented.

Abstract: Fisheries-dependent and independent data have a strong spatial component. These data are also multi-dimensional, making them difficult to visualize and analyze, prompting the use of spatial analysis to facilitate an understanding of their relationships. One aspect of fisheries data that is often ignored is the distribution and abundance of a particular resource and the fishing patterns of its harvesting fisheries. In order to improve management advice, stock assessors need to incorporate the spatial component of these data into an existing assessment framework. This paper presents a three-dimensional visualization of the age-structure and fishery dependent and independent data associated with the sparid fish Pterogymnus laniarius on the Agulhas Bank, South Africa. A spatially-referenced spawner biomass per-recruit model is developed to illustrate the applicability of incorporating spatially referenced information in providing management advice. The model provided evidence that, even on a spatial scale, fishing mortality is significantly correlated to fishing effort. Areas of high levels of spawner biomass are noted, all of which corresponded to those geographic areas with a combination of low fishing effort and high adult biomass.