Detecting context dependence in the expression of life history trade‐offs

Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. Here, we present a hierarchical multivariate 'covariance reaction norm' model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general.

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Publication Details

Journal
Journal of Animal Ecology
Published
2024-09-02
DOI
https://doi.org/10.1111/1365-2656.14173
Citations
8
Primary Topic
Animal Behavior and Reproduction
Type
article
Field-Weighted Citation Impact
8.23

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article

Detecting context dependence in the expression of life history trade‐offs

Arpat Özgül, Julien G. A. Martin, Daniel H. Nussey, Dylan Z. Childs et al.
8 citations
Journal of Animal Ecology
Animal Behavior and Reproduction
8.23
article

Detecting context dependence in the expression of life history trade‐offs

Arpat Özgül, Julien G. A. Martin, Daniel H. Nussey, Dylan Z. Childs, Josephine M. Pemberton, Daniel T. Blumstein, Maria Paniw, Jordan S. Martin, Louis Bliard
article en
8 citations

Abstract

Life history trade-offs are one of the central tenets of evolutionary demography. Trade-offs, depicting negative covariances between individuals' life history traits, can arise from genetic constraints, or from a finite amount of resources that each individual has to allocate in a zero-sum game between somatic and reproductive functions. While theory predicts that trade-offs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. One way to improve the detection of trade-offs is by accounting for the environmental context, as trade-off expression may depend on environmental conditions. However, current methodologies usually search for fixed covariances between traits, thereby ignoring their context dependence. Here, we present a hierarchical multivariate 'covariance reaction norm' model, adapted from Martin (2023), to help detect context dependence in the expression of life-history trade-offs using demographic data. The method allows continuous variation in the phenotypic correlation between traits. We validate the model on simulated data for both intraindividual and intergenerational trade-offs. We then apply it to empirical datasets of yellow-bellied marmots (Marmota flaviventer) and Soay sheep (Ovis aries) as a proof-of-concept showing that new insights can be gained by applying our methodology, such as detecting trade-offs only in specific environments. We discuss its potential for application to many of the existing long-term demographic datasets and how it could improve our understanding of trade-off expression in particular, and life history theory in general.

Journal of Animal EcologyVol. 94(3)
University of Ottawa (CA), University of California, Los Angeles (US), University of Zurich (CH), Rocky Mountain Biological Laboratory (US), Estación Biológica de Doñana (ES), University of Sheffield (GB), University of Edinburgh (GB)
National Science Foundation, Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Natural Environment Research Council
Openalex Percentile: Top 3%
Animal Behavior and Reproduction
8.23
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