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

Louis Bliard*, Jordan S. Martin, Maria Paniw, Daniel T. Blumstein, Julien G. A. Martin, Josephine M. Pemberton, Daniel H. Nussey, Dylan Z. Childs, Arpat Ozgul

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract / Description of output

1. 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.
2. 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.
3. 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.
4. 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.
5. 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.
Original languageEnglish
Number of pages15
JournalJournal of Animal Ecology
Early online date2 Sept 2024
DOIs
Publication statusE-pub ahead of print - 2 Sept 2024

Keywords / Materials (for Non-textual outputs)

  • covariance reaction norm
  • demography
  • heterogeneity
  • life-history
  • mixed effects
  • multivariate model
  • phenotypic correlation
  • trade-off

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