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Estimating Age at First Maturity in Fish from Change-Points in Growth Rate

Robert D. Scott, Jukka Heikkonen, Estimating Age at First Maturity in Fish from Change-Points in Growth Rate. Marine Ecology-Progress Series 450, 147–157, 2012.

Abstract:

Recent studies have drawn attention to the potential for evolutionary changes in lifehistory
traits as a consequence of the size-selective process of fishing, and evidence of so-called
fisheries-induced evolution has been reported for a number of different species. Most studies of
fisheries-induced evolution have focused on changes in sexual maturation using the probabilistic
maturation reaction norm method, which requires specific information on the age at which maturation
occurs, often derived from macroscopic examination of the gonads. In the absence of sufficiently
detailed measurements of maturity it is necessary to derive estimates of the age at which
maturation occurs from alternative sources of information, for example, from length at age data.
We apply a relatively simple segmented regression model to length at age data for plaice Pleuronectes
platessa in the Irish Sea in order to identify the change-point between 2 specific growth
schedules that can be used as a proxy for age at first maturity in individual cohorts. We use a
Bayesian approach for model fitting and map the resulting distribution of change-points using
Gaussian mixture models to show that the age at which the change-point occurred in individual
cohorts of both male and female plaice in the Irish Sea has declined progressively over an 18 yr
period between 1988 and 2005.

BibTeX entry:

@ARTICLE{jScHe12a,
  title = {Estimating Age at First Maturity in Fish from Change-Points in Growth Rate},
  author = {Scott, Robert D. and Heikkonen, Jukka},
  journal = {Marine Ecology-Progress Series},
  volume = {450},
  publisher = {Inter research},
  pages = {147–157},
  year = {2012},
  keywords = {Plaice, maturation, segmented regression, reaction norm, genetic adaptation, phenotypic plasticity, Bayesian statistics},
}

Belongs to TUCS Research Unit(s): Algorithmics and Computational Intelligence Group (ACI)

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