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

Life history tradeoffs are one of the central tenets of evolutionary demography. Tradeoffs, 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 tradeoffs are ubiquitous, empirical studies have often failed to detect such negative covariances in wild populations. One way to improve the detection of tradeoffs is by accounting for the environmental context, as tradeoff 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 tradeoffs 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 tradeoffs. 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 tradeoffs 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 tradeoff expression in particular, and life history theory in general.