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    Comment on "Slow adaptation in the face of rapid warming leads to collapse of the Gulf of Maine cod fishery" (2016)
    American Association for the Advancement of Science (AAAS)
    Details
    Publication Date: 2016-04-23
    Description: Pershing et al (Science, 13 November 2015, p. 809) concluded that recent warming in the Gulf of Maine contributed to the collapse of Gulf of Maine cod. We argue that this conclusion is based on a flawed analysis of the population dynamics of this cod stock. We believe that understanding the potential role of climate change in the collapse of this stock requires more defensible analyses.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Swain, Douglas P -- Benoit, Hugues P -- Cox, Sean P -- Cadigan, Noel G -- New York, N.Y. -- Science. 2016 Apr 22;352(6284):423. doi: 10.1126/science.aad9346.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Fisheries and Oceans Canada, Gulf Fisheries Centre, Moncton, NB E1C 9B6, Canada. ; Fisheries and Oceans Canada, Gulf Fisheries Centre, Moncton, NB E1C 9B6, Canada. hugues.benoit@dfo-mpo.gc.ca. ; School of Resource and Environmental Management, Simon Fraser University, Burnaby, BC V5A 1S6, Canada. ; Centre for Fisheries Ecosystems Research, Marine Institute of Memorial University of Newfoundland, St. John's, NL A1C 5R3, Canada.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/27102474" target="_blank"〉PubMed〈/a〉
    Keywords: *Adaptation, Physiological ; Animals ; *Fisheries ; Gadus morhua/*physiology ; *Global Warming
    Print ISSN: 0036-8075
    Electronic ISSN: 1095-9203
    Topics: Biology , Chemistry and Pharmacology , Computer Science , Medicine , Natural Sciences in General , Physics
    Published by American Association for the Advancement of Science (AAAS)
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  • 2
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    Fitting a non-parametric stock-recruitment model in R that is useful for deriving MSY reference points and accounting for model uncertainty (2012)
    Oxford University Press
    Details
    Publication Date: 2012-12-12
    Description: Cadigan, N. G. 2013. Fitting a non-parametric stock–recruitment model in R that is useful for deriving MSY reference points and accounting for model uncertainty. – ICES Journal of Marine Science, 70:56–67. Modelling the relationship between parental stock size and subsequent recruitment of fish to a fishery is often required when deriving reference points, which are a fundamental component of fishery management. A non-parametric approach to estimate stock–recruitment relationships is illustrated using a simulated example and nine case studies. The approach preserves compensatory density dependence in which the recruitment rate monotonically decreases as stock size increases, which is a basic assumption of commonly used parametric stock–recruitment models. The implications of the non-parametric estimates on maximum sustainable yield (MSY) reference points are illustrated. The approach is used to provide non-parametric bootstrapped confidence intervals for reference points. The efficacy of the approach is investigated using simulations. The results demonstrate that the non-parametric approach can provide a more realistic estimation of the stock–recruitment relationship when informative data are available compared with common parametric models. Also, bootstrap confidence intervals for MSY reference points based on different parametric stock–recruitment models often do not overlap. The confidence intervals based on the non-parametric approach tend to be much wider, and reflect better uncertainty due to stock–recruit model choice.
    Print ISSN: 1054-3139
    Electronic ISSN: 1095-9289
    Topics: Biology , Geosciences , Physics
    Published by Oxford University Press
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