Incorporating habitat preference into the stock assessment and management of blue marlin (Makaira nigricans) in the Pacific Ocean
Nan-Jay Su A , Chi-Lu Sun A D , André E. Punt B , Su-Zan Yeh A and Gerard DiNardo C
+ Author Affiliations
- Author Affiliations
A Institute of Oceanography, National Taiwan University, Taipei 10 617, Taiwan.
B School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA 98 195, USA.
C NOAA Fisheries, Pacific Islands Fisheries Science Center, Honolulu, HI 96 822, USA.
D Corresponding author. Email: chilu@ntu.edu.tw
Marine and Freshwater Research 63(7) 565-575 https://doi.org/10.1071/MF11244
Submitted: 4 November 11 Accepted: 1 May 2012 Published: 27 June 2012
Abstract
Stock assessments that include a spatial component or relate population dynamics to environmental conditions can be considered one way of implementing an ecosystem approach to fisheries. A spatially-structured population dynamics model that takes account of habitat preference is developed and then applied to Pacific blue marlin (Makaira nigricans), as they prefer certain habitats and migrate seasonally. The model is fitted to fishery catch-rate and size data, along with information on the relative density of the population over space derived from a habitat preference model fitted to oceanographic and biological variables. Results show that blue marlin are more abundant in tropical waters, and females account for most of the biomass. Assessments that allow for environmental factors, movement dynamics and sexual dimorphism indicate that this population is in an over-exploited state, with current spawning stock biomass below the level corresponding to maximum sustainable yield (SMSY) and current fishing mortality exceeding that needed to achieve MSY (FMSY). A risk analysis based on samples from a Bayesian posterior distribution suggests that the population will remain above SMSY after 20 years if exploitation rates are below the level corresponding to FMSY.
Additional keywords: environmental variation, movement dynamics, risk analysis, sexual dimorphism, spatially structured model.
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