Population Dynamic Consequences of Context-Dependent Trade-Offs across Life Histories

Variety is the spice of life: nongenetic variation in life histories influences population growth and evolvability

Individual vital rates, such as mortality and birth rates, are key determinants of lifetime reproductive success, and variability in these rates shapes population dynamics. Previous studies have found that this vital rate heterogeneity can influence demographic properties, including population growth rates. However, the explicit effects of the variation within and the covariance between vital rates that can also vary throughout the lifespan on population growth remain unknown. Here, we explore the analytical consequences of nongenetic heterogeneity on long-term population growth rates and rates of evolution by modifying traditional age-structured population projection matrices to incorporate variation among individual vital rates. The model allows vital rates to be permanent throughout life ("fixed condition") or to change over the lifespan ("dynamic condition"). We reduce the complexity associated with adding individual heterogeneity to age-structured models through a novel application of matrix collapsing ("phenotypic collapsing"), showing how to collapse in a manner that preserves the asymptotic and transient dynamics of the original matrix. The main conclusion is that nongenetic individual heterogeneity can strongly impact the long-term growth rate and rates of evolution. The magnitude and sign of this impact depend heavily on how the heterogeneity covaries across the lifespan of an organism. Our results emphasize that nongenetic variation cannot simply be viewed as random noise, but rather that it has consistent, predictable effects on fitness and evolvability.

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.

Population Dynamic Consequences of Context-Dependent Trade-Offs across Life Histories

AbstractTrade-offs are central to life history theory and play a role in driving life history diversity. They arise from a finite amount of resources that need to be allocated among different functions by an organism. Yet covariation of demographic rates among individuals frequently do not reflect allocation trade-offs because of variation in resource acquisition. The covariation of traits among individuals can thus vary with the environment and often increases in benign environments. Surprisingly, little is known about how such context-dependent expression of trade-offs among individuals affect population dynamics across species with different life histories. To study their influence on population stability, we develop an individual-based simulation where covariation in demographic rates varies with the environment. We use it to simulate population dynamics for various life histories across the slow-fast pace-of-life continuum. We found that the population dynamics of slower life histories are relatively more sensitive to changes in covariation, regardless of the trade-off considered. Additionally, we found that the impact on population stability depends on which trade-off is considered, with opposite effects of intraindividual and intergenerational trade-offs. Last, the expression of different trade-offs can feed back to influence generation time through selection acting on individual heterogeneity within cohorts, ultimately affecting population dynamics.

Are some species more sensitive to environmental change than others? It may all depend on the context

Research Highlight: Rademaker, M., van Leeuwen, A., & Smallegange, I. M. (2024). Why we cannot always expect life history strategies to directly inform on sensitivity to environmental change. Journal of Animal Ecology, https://doi.org/10.1111/1365-2656.14050. Ecological studies have long delved into how organisms allocate energy between reproduction and somatic maintenance to maximize fitness. This allocation gives rise to various life-history strategies, and these strategies have been shown to predict how populations respond to environmental change, allowing us to generalize potential responses to increasing human pressures. Such predictions have, however, been made for a limited set of terrestrial taxa and typically do not explore how individual differences in life-history responses to environmental change scale to affect population-level responses. Using novel data on diverse fish species, Rademaker et al. (2024) construct models that link individual-level trade-offs in energy allocation under environmental change to population-level life-history strategies. A key finding in their study is that short-lived species are not more sensitive to environmental change-unlike results of previous studies. This study represents a new generation of work that underscores the complexity of predicting population responses to environmental shifts and suggests a need for a broader understanding of individual-level mechanisms. The results of Rademaker et al. (2024) encourage further mechanistic life-history analyses across a wider range of species and populations to validate the exciting findings and explore their implications across diverse ecological contexts.