Can estimates of genetic effective population size contribute to fisheries stock assessments?

Ovenden, J. R.; Leigh, G. M.; Blower, D. C.; Jones, A. T.; Moore, A.; Bustamante, C.; Buckworth, R. C.; Bennett, M. B.; Dudgeon, C. L.

Abstract

Sustainable exploitation of fisheries populations is challenging to achieve when the size of the population prior to exploitation and the actual numbers removed over time and across fishing zones are not clearly known. Quantitative fisheries' modeling is able to address this problem, but accurate and reliable model outcomes depend on high quality input data. Much of this information is obtained through the operation of the fishery under consideration, but while this seems appropriate, biases may occur. For example, poorly quantified changes in fishing methods that increase catch rates can erroneously suggest that the overall population size is increasing. Hence, the incorporation of estimates of abundance derived from independent data sources is preferable. We review and evaluate a fisheries-independent method of indexing population size; inferring adult abundance from estimates of the genetic effective size of a population (N-e). Recent studies of elasmobranch species have shown correspondence between N-e and ecologically determined estimates of the population size (N). Simulation studies have flagged the possibility that the range of N-e/N ratios across species may be more restricted than previously thought, and also show that declines in N-e track declines in the abundance of model fisheries species. These key developments bring this new technology closer to implementation in fisheries science, particularly for data-poor fisheries or species of conservation interest. (C) 2016 The Fisheries Society of the British Isles

Más información

Título según WOS: ID WOS:000390339900003 Not found in local WOS DB
Título de la Revista: JOURNAL OF FISH BIOLOGY
Volumen: 89
Número: 6
Editorial: Wiley
Fecha de publicación: 2016
Página de inicio: 2505
Página final: 2518
DOI:

10.1111/jfb.13129

Notas: ISI