Bayesian fitting of probabilistic maturation reaction norms to population-level data

Bruce J. McAdam*, C. Tara Marshall

*Corresponding author for this work

Research output: Contribution to journalArticle

1 Citation (Scopus)

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. (C) 2014 Elsevier B.V. All rights reserved.

Original languageEnglish
Pages (from-to)105-113
Number of pages9
JournalFisheries Research
Volume159
Early online date5 Jul 2014
DOIs
Publication statusPublished - Nov 2014

Keywords

  • Bayesian
  • fisheries-induced evolution
  • maturation
  • reaction norm
  • life-history traits
  • poecilia-reticulata
  • fish stocks
  • age
  • evolution
  • size
  • maturity
  • cod
  • plasticity
  • selection

Cite this

Bayesian fitting of probabilistic maturation reaction norms to population-level data. / McAdam, Bruce J.; Marshall, C. Tara.

In: Fisheries Research, Vol. 159, 11.2014, p. 105-113.

Research output: Contribution to journalArticle

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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. (C) 2014 Elsevier B.V. All rights reserved.",
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note = "Date of Acceptance: 14/05/2014 Acknowledgements Data were provided by N. Yaragina and S. Kraak. F. Neat and M. Heino commented on earlier versions of this manuscript. Funding support was provided by the European Community (Contract No. 022717 [SSP8]). This work received funding from the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) and their support is gratefully acknowledged. MASTS is funded by the Scottish Funding Council (grant reference HR09011) and contributing institutions. We are grateful to the editor and anonymous reviewer of this manuscript for their suggestions.",
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