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The evolution of labile traits in sex‐ and age‐structured populations

1. Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of...

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Autores principales: Childs, Dylan Z., Sheldon, Ben C., Rees, Mark
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768649/
https://www.ncbi.nlm.nih.gov/pubmed/26899421
http://dx.doi.org/10.1111/1365-2656.12483
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author Childs, Dylan Z.
Sheldon, Ben C.
Rees, Mark
author_facet Childs, Dylan Z.
Sheldon, Ben C.
Rees, Mark
author_sort Childs, Dylan Z.
collection PubMed
description 1. Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data‐driven framework for incorporating such traits into demographic models has not yet been developed. 2. Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well‐established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro‐evolutionary dynamics in an IPM framework. 3. We show how to embed quantitative genetic models of inheritance of labile traits into age‐structured, two‐sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg‐laying date evolution, parameterized using data from a population of Great tits (Parus major). 4. We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age‐structured Price equation (ASPE) for two‐sex populations, and apply this to examine the age‐specific contributions of different processes to change in the mean phenotype and breeding value. 5. The data‐driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation.
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spelling pubmed-47686492016-03-09 The evolution of labile traits in sex‐ and age‐structured populations Childs, Dylan Z. Sheldon, Ben C. Rees, Mark J Anim Ecol British Ecological Society Special Feature: Demography Beyond the Population 1. Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data‐driven framework for incorporating such traits into demographic models has not yet been developed. 2. Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well‐established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro‐evolutionary dynamics in an IPM framework. 3. We show how to embed quantitative genetic models of inheritance of labile traits into age‐structured, two‐sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg‐laying date evolution, parameterized using data from a population of Great tits (Parus major). 4. We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age‐structured Price equation (ASPE) for two‐sex populations, and apply this to examine the age‐specific contributions of different processes to change in the mean phenotype and breeding value. 5. The data‐driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation. John Wiley and Sons Inc. 2016-02-22 2016-03 /pmc/articles/PMC4768649/ /pubmed/26899421 http://dx.doi.org/10.1111/1365-2656.12483 Text en © 2016 The Authors Journal of Animal Ecology published by John Wiley & Sons Ltd on behalf of British Ecological Society. This is an open access article under the terms of the Creative Commons Attribution (http://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle British Ecological Society Special Feature: Demography Beyond the Population
Childs, Dylan Z.
Sheldon, Ben C.
Rees, Mark
The evolution of labile traits in sex‐ and age‐structured populations
title The evolution of labile traits in sex‐ and age‐structured populations
title_full The evolution of labile traits in sex‐ and age‐structured populations
title_fullStr The evolution of labile traits in sex‐ and age‐structured populations
title_full_unstemmed The evolution of labile traits in sex‐ and age‐structured populations
title_short The evolution of labile traits in sex‐ and age‐structured populations
title_sort evolution of labile traits in sex‐ and age‐structured populations
topic British Ecological Society Special Feature: Demography Beyond the Population
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4768649/
https://www.ncbi.nlm.nih.gov/pubmed/26899421
http://dx.doi.org/10.1111/1365-2656.12483
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