Fish capture as a stochastic process

• Published in: ICES Journal of Marine Science
• Main Author: Sampson, David B.
• Format: Text
• Language: English
• Published: Oxford University Press 1988
• Subjects: Articles; Southern Ocean
• Online Access: http://icesjms.oxfordjournals.org/cgi/content/short/45/1/39; https://doi.org/10.1093/icesjms/45.1.39

Catch and effort data are an important source of information about the status of exploited fish stocks. Many fisheries assessment procedures are based on the catch equation, a simple deterministic model for the accumulation of catch with time spent fishing (effort). But the catches which accrue for a given amount of fishing are often extremely variable. This paper attempts to develop a theoretical framework within which this variability may be analysed. Methods from the theory of stochastic processes are adapted and four stochastic models of the catch process are developed. 1) The simple catch process describes the catch of animals from a closed population by a fishing operation which removes animals one at a time. Equations for the expected cumulative catch and variance, the expected catch increments and variance, and the autocovariance and autocorrelation functions are derived. 2) The simple catch process with migration is an extension of the simple catch process which allows for immigration and emigration. 3) The generalized catch process extends the simple catch process for fishing operations which remove animals in groups. 4) The simple catch process with handling time explicitly includes a constant handling time for each animal caught. Statistical methods for the analysis of these theoretical processes are not fully developed in this paper, but various problems associated with the analysis of real data series are illustrated by means of catch data from the Southern Ocean pelagic whaling industry.