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Identification and quantification of heteroscedasticity in stock–recruitment relationships

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Publication details

JournalCanadian Journal of Fisheries and Aquatic Sciences
DateE-pub ahead of print - 22 Apr 2015
DatePublished (current) - Aug 2015
Issue number8
Number of pages13
Pages (from-to)1259-1271
Early online date22/04/15
Original languageEnglish


Nonconstant variance (heteroscedasticity) in the stock–recruitment (S-R) relationship is proposed as an important factor in sustainable fisheries management, but its reliable estimation from noisy populations is problematic. We developed
methods for both frequentist and Bayesian approaches to test whether we can accurately estimate the degree of heteroscedasticity in 90 published S-R populations. We estimated the confidence interval for the heteroscedastic regression model via a parametric bootstrap approach and the credible interval for the Bayesian method via a Markov chain Monte Carlo sampling algorithm. We found strong evidence of negative heteroscedasticity in several stocks, regardless of the statistical paradigm, the details of density dependence, and the methods used to generate the original populations. This statistical framework, together with its associated freely available software, provides an efficient and reliable setting for assessing heteroscedasticity of the S-R relationship in fisheries

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