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Predicting recruitment density dependence and intrinsic growth rate for all fishes worldwide using a data‐integrated life‐history model
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2019
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Source: Fish and Fisheries, 21(2), 237-251
[PDF-2.34 MB]
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Journal Title:Fish and Fisheries
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Description:Fisheries scientists use biological models to determine sustainable fishing rates and forecast future dynamics. These models require both life-history parameters (mortal - ity, maturity, growth) and stock-recruit parameters (juvenile production). However, there has been little research to simultaneously predict life-history and stock-recruit parameters. I develop the first data-integrated life-history model, which extends a simple model of evolutionary dynamics to field measurements of life-history pa - rameters as well as historical records of spawning output and subsequent recruit - ment. This evolutionary model predicts recruitment productivity (steepness) and variability (variance and autocorrelation in recruitment deviations) as well as mortal -
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Source:Fish and Fisheries, 21(2), 237-251
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DOI:
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ISSN:1467-2960;1467-2979;
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Rights Information:CC0 Public Domain
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Rights Statement:This article is a U.S. Government work and is in the public domain in the USA
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