Assessing attribute redundancy in the application of productivity-susceptibility analysis to data-limited fisheries

Abstract

Productivity-susceptibility analysis (PSA) is a widely used data-limited method to assess the relative vulnerability of species impacted by fisheries. Despite its widespread use, few authors have evaluated the impacts of attribute weightings and correlation of productivity attributes that may bias species' vulnerability scores. We evaluated the PSA methodology and performed sensitivity analyses to determine the impacts of correlation among productivity attributes used in the PSA, given that several of these attributes are strongly correlated. A PSA for species caught in the eastern Pacific Ocean tuna purse-seine fishery was used as an example to assess potential bias introduced by attribute weightings and correlation of productivity attributes on species' vulnerability scores. Redundancy was observed among three pairs of attributes. We demonstrated that manipulation of attribute weightings and removal of correlated attributes did not appreciably change any species' overall vulnerability status. Our results suggest that after removal of redundant attributes, PSAs can be conducted more rapidly with fewer data inputs than previous implementations, while retaining comparable vulnerability scores.