Two simple approaches to use of production models in fish stock assessment

Abstract

Catch and effort data are routinely collected for many fisheries and form an important, and often the only, source of data for fish stock assessment. For stock assessment, they are usually standardized to extract series of standardized cpues, into which production models are then fitted, to estimate population parameters and management quantities. This conventional approach to fish stock assessment cannot, in some cases, properly account for observational errors, i.e., those in observed catch and observed effort, and causes difficulties in making assumptions about the distributions of cpues and standardized cpues. In this paper, I develop both unconstrained and constrained production models for fish stock assessment to avoid or eliminate all these problems, through a simultaneous estimation of all parameters from observed catch and observed effort. The models are used to analyse a set of catch and effort data on the school shark Galeorhinus galeus (Linnaeus).