|Appears in Collections:||Aquaculture Journal Articles|
|Peer Review Status:||Refereed|
|Title:||Bayesian fitting of probabilistic maturation reaction norms to population-level data|
|Authors:||McAdam, Bruce James|
Marshall, C Tara
|Citation:||McAdam BJ & Marshall CT (2014) Bayesian fitting of probabilistic maturation reaction norms to population-level data, Fisheries Research, 159, pp. 105-113.|
|Abstract:||Probabilistic maturation reaction norms (PMRNs) are an important tool for studying fisheries-induced evolution and environmental effects on life history. To date there has been no way to fit a PMRN to population-level fisheries data; instead individual-level data must be used. This limits the stocks and time periods that can be studied.We introduce a Bayesian method for fitting PMRNs to population-level data. The method is verified against both an existing result and simulated data, and applied to historical Barents Sea cod data which combines observations of population-level variation in age, size and maturity status from Russia and Norway.The method shows a clear and rapid trend towards greater probability of maturation at smaller lengths in the Barents Sea cod.The new model fitting algorithm allows us to study historic changes in life history despite the lack of individual-level data seen in much long term data. Access to more data will aid the study of evolutionary hypotheses in a wide range of organisms.|
|Rights:||This item has been embargoed for a period. During the embargo please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study. Published in Fisheries Research by Elsevier; Elsevier believes that individual authors should be able to distribute their AAMs for their personal voluntary needs and interests, e.g. posting to their websites or their institution’s repository, e-mailing to colleagues.|
University of Aberdeen
|pmrn_paper_FOR_STORRE.pdf||485.85 kB||Adobe PDF||View/Open|
This item is protected by original copyright
Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.
If you believe that any material held in STORRE infringes copyright, please contact firstname.lastname@example.org providing details and we will remove the Work from public display in STORRE and investigate your claim.