Catch per unit effort modelling for stock assessment: A summary of good practices

Abstract

Indices of abundance based on fishery catch-per-unit-effort (CPUE) are important components of many stock assessments, particularly when fishery-independent surveys are unavailable. Standardizing CPUE to develop indices that better reflect the relative abundance requires the analyst to make numerous decisions, which are influenced by factors that include the biology of the study species, the structure of the fishery of interest, the nature of the available data, and the objectives of the analysis such as how standardized data will be used in a subsequent assessment model. Alternative choices can substantially change the index, and hence stock assessment outcomes and management decisions. To guide decisions, we provide advice on good practices in 16 areas, focusing on decision points: fishery definitions, exploring and preparing data, misreporting, data aggregation, density and catchability covariates, environmental variables, combining CPUE and survey data, analysis tools, spatial considerations, setting up and predicting from the model, uncertainty estimation, error distributions, model diagnostics, model selection, multispecies targeting, and using CPUE in stock assessments. Often the most influential outcome of exploring and analysing catch and effort data is that analysts better understand the population and the fishery, thereby improving the stock assessment.