2010
DOI: 10.1111/j.1600-0706.2009.17746.x
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Multiple growth-correlated life history traits estimated simultaneously in individuals

Abstract: We present a new methodology to estimate rates of energy acquisition, maintenance, reproductive investment and the onset of maturation (four-trait estimation) by fitting an energy allocation model to individual growth trajectories. The accuracy and precision of the method is evaluated on simulated growth trajectories. In the deterministic case, all life history parameters are well estimated with negligible bias over realistic parameter ranges. Adding environmental variability reduces precision, causes the main… Show more

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Cited by 17 publications
(34 citation statements)
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References 68 publications
(109 reference statements)
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“…Deriving life-history traits other than growth rate, e.g. reproductive investment, from an individual growth trajectory has only rarely been used in the literature on fisheries-induced evolution (Mollet et al 2010, Brunel et al 2013). Our methodological approach should be useful for more long-lived species because the back-constructed individual growth curve can more easily be estimated for such species than for the short-lived species we studied.…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Deriving life-history traits other than growth rate, e.g. reproductive investment, from an individual growth trajectory has only rarely been used in the literature on fisheries-induced evolution (Mollet et al 2010, Brunel et al 2013). Our methodological approach should be useful for more long-lived species because the back-constructed individual growth curve can more easily be estimated for such species than for the short-lived species we studied.…”
Section: Discussionmentioning
confidence: 99%
“…Back-calculation of length-at-age using growth marks contained in otoliths can offer a reliable method to obtain repeated measures of length-at-age over the lifespan of the same individual whenever there is a strong relationship between fish and otolith size (Pilling et al 2002, Swain et al 2007, Mollet et al 2010, Brunel et al 2013. We fitted the individual length-at-age data points extracted from the otoliths of S. scriba following the protocol by Al贸s et al (2010) to the bi-phasic growth model proposed by Lester et al (2004).…”
Section: Estimation Of Individual Life-history Traits Of Serranus Scribamentioning
confidence: 99%
“…With specific reference to estimating the onset of maturity, Rijnsdorp & Storbeck (1995) applied the segmented regression approach to back-calculated growth data from otolith measurements of North Sea plaice Pleuronectes platessa, and, more recently, Baulier & Heino (2008) investigated its application to growth patterns in Atlantic herring Clupea harengus, although neither 148 Scott & Heikkonen: Estimating age at first maturity in plaice study found the approach to be entirely satisfactory, recommending instead that a bio-energetic modelling approach may provide better estimates. Mollet et al (2010) extended the method to estimate multiple life-history parameters using the segmented regression approach to fit an energy allocation model to individual growth trajectories for female North Sea plaice. Their method provided estimates of the age of the onset of maturation that corresponded well with those obtained from direct observation.…”
Section: Resale or Republication Not Permitted Without Written Consenmentioning
confidence: 99%
“…Lester et al (2004) found the von Bertalanffy equation to be an appropriate model for post-maturity somatic growth but not appropriate for pre-maturation growth, and it is argued that multi-phase models may provide a more appropriate representation of growth in fishes (Dumas et al 2007, Quince et al 2008. These findings support the further investigation of alternative growth assumptions when investigating trends in maturation schedules, and the approach of Mollet et al (2010) has already begun this process through the incorporation of a bio-energetic approach to energy allocation.Bio-energetic considerations alone, however, may not be sufficient to fully explain the differences between the sexes or the trends observed over time. The sexual dimorphism in growth cannot be fully explained by differences between the sexes in reproductive investment and the onset of sexual maturity (Rijnsdorp & Ibelings 1989).…”
mentioning
confidence: 98%
“…It has been shown that past individual growth history influences maturation probability independently from age and size, with most recent growth condition (just before the age at which probability of maturing is calculated) being the most determinant factor (Morita & Fukuwaka 2006). Individual growth trajectories can be back-calculated from scale or otolith reading (Engelhard et al 2003, Baulier & Heino 2008, Mollet et al 2010), but again this information was not available.…”
Section: The Pmrn Approachmentioning
confidence: 99%