Evaluation of a spatially sex‐specific assessment method incorporating a habitat preference model for blue marlin (

Authors: SU, NAN‐JAY1; SUN, CHI‐LU1; PUNT, ANDRE E.2; YEH, SU‐ZAN1; DINARDO, GERARD3

Source: Fisheries Oceanography, Volume 20, Number 5, 1 September 2011 , pp. 415-433(19)

Publisher: Wiley-Blackwell

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Abstract:

Abstract

Blue marlin, widely distributed throughout the Pacific Ocean, are sexually dimorphic, have certain preferred habitats, and migrate seasonally. These characteristics have been ignored in previous stock assessment models. A population dynamics model that includes spatial structure, and sex and age structure was therefore constructed and fitted to fisheries data for blue marlin, along with information on the relative density of the population over space derived from a habitat preference model that uses the oceanographic and biological variables sea‐surface temperature, mixed layer depth, sea‐surface height anomaly, and chlorophyll‐a concentration. Monte Carlo simulation was then used to examine the estimation performance of the stock assessment method. Estimates of management‐related quantities including current spawning stock biomass are substantially biased when the assessment method ignores seasonal movement and sexual dimorphism. We also found that (i) uncertainty about the relationship between catch rate and abundance influences estimation performance to a larger extent than uncertainty in catches, (ii) the outcomes of the assessment are sensitive to the values assumed for natural mortality and stock‐recruitment steepness, and (iii) the ratio of current spawning stock biomass to that at pre‐exploitation equilibrium appears to be the most robust among the quantities considered. We conclude that assessment methods for blue marlin in the Pacific Ocean need to take account of seasonal migration and sex structure to improve stock assessments.

Document Type: Research Article

DOI: http://dx.doi.org/10.1111/j.1365-2419.2011.00593.x

Affiliations: 1: Institute of Oceanography, National Taiwan University, Taipei 10617, Taiwan 2: School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98195, USA 3: NOAA Fisheries, Pacific Islands Fisheries Science Center, Honolulu, HI 96822, USA

Publication date: September 1, 2011

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