Spatial analysis of Bering Sea groundfish survey data using generalized additive models

Abstract

Generalized additive models represent a statistical method, analogous to regression, but without the assumptions of normality or linearity that relate a response variable (in this case, fish abundance) to location (latitude and longitude) and associated environmental variables (eg depth and bottom temperature). GAM provided reasonable fits to the spatial distribution of five flatfish species and was able to define a spatial "signature' for each species (preferred depth and temperature range). GAM also gave lower average abundance and abundance variability estimates for these five flatfish species than a stratified sampling procedure. -from Authors