Fernandez, C. and Cotter, J. and Burt, L. and Paxton, C. and Buckland, S. and Pan, J.-X (2004) Are stock assessment methods too complicated? A critical review central on North Sea demersal stocks. Fish and Fisheries, 5 (3). pp. 235-254. ISSN 1467-2979Full text not available from this repository.
This critical review argues that several methods for the estimation and prediction of numbers-at-age, fishing mortality coefficients F, and recruitment for a stock of fish are too hard to explain to customers (the fishing industry, managers, etc.) and do not pay enough attention to weaknesses in the supporting data, assumptions and theory. The review is linked to North Sea demersal stocks. First, weaknesses in the various types of data used in North Sea assessments are summarized, i.e. total landings, discards, commercial and research vessel abundance indices, age-length keys and natural mortality (M). A list of features that an ideal assessment should have is put forward as a basis for comparing different methods. The importance of independence and weighting when combining different types of data in an assessment is stressed. Assessment methods considered are Virtual Population Analysis, ad hoc tuning, extended survivors analysis (XSA), year-class curves, catch-at-age modelling, and state-space models fitted by Kalman filter or Bayesian methods. Year-class curves (not to be confused with ‘catch-curves’) are the favoured method because of their applicability to data sets separately, their visual appeal, simple statistical basis, minimal assumptions, the availability of confidence limits, and the ease with which estimates can be combined from different data sets after separate analyses. They do not estimate absolute stock numbers or F but neither do other methods unless M is accurately known, as is seldom true.
|Journal or Publication Title:||Fish and Fisheries|
|Subjects:||Q Science > QA Mathematics|
|Deposited By:||Mrs Yaling Zhang|
|Deposited On:||12 Jun 2008 16:19|
|Last Modified:||01 Feb 2016 01:08|
Actions (login required)