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

Author:

Bliard Louis1ORCID,Martin Jordan S.2ORCID,Paniw Maria13ORCID,Blumstein Daniel T.45ORCID,Martin Julien G. A.6ORCID,Pemberton Josephine M.7,Nussey Daniel H.7ORCID,Childs Dylan Z.8ORCID,Ozgul Arpat1ORCID

Affiliation:

1. Department of Evolutionary Biology and Environmental Studies Zurich University Zurich Switzerland

2. Institute of Evolutionary Medicine Zurich University Zurich Switzerland

3. Department of Conservation Biology Estación Biológica de Doñana (EBD‐CSIC) Seville Spain

4. Department of Ecology and Evolutionary Biology University of California Los Angeles California Los Angeles USA

5. The Rocky Mountain Biological Laboratory Crested Butte Colorado USA

6. Department of Biology University of Ottawa Ottawa Ontario Canada

7. Institute of Ecology and Evolution University of Edinburgh Edinburgh UK

8. Department of Animal and Plant Sciences University of Sheffield Sheffield UK

Abstract

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.

Funder

Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

National Science Foundation

Natural Environment Research Council

Publisher

Wiley

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