Life‐history evolution under fluctuating density‐dependent selection and the adaptive alignment of pace‐of‐life syndromes

Abstract

We present a novel perspective on life-history evolution that combines recent theoretical advances in fluctuating density-dependent selection with the notion of pace-of-life syndromes (POLSs) in behavioural ecology. These ideas posit phenotypic co-variation in life-history, physiological, morphological and behavioural traits as a continuum from the highly fecund, short-lived, bold, aggressive and highly dispersive 'fast' types at one end of the POLS to the less fecund, long-lived, cautious, shy, plastic and socially responsive 'slow' types at the other. We propose that such variation in life histories and the associated individual differences in behaviour can be explained through their eco-evolutionary dynamics with population density - a single and ubiquitous selective factor that is present in all biological systems. Contrasting regimes of environmental stochasticity are expected to affect population density in time and space and create differing patterns of fluctuating density-dependent selection, which generates variation in fast versus slow life histories within and among populations. We therefore predict that a major axis of phenotypic co-variation in life-history, physiological, morphological and behavioural traits (i.e. the POLS) should align with these stochastic fluctuations in the multivariate fitness landscape created by variation in density-dependent selection. Phenotypic plasticity and/or genetic (co-)variation oriented along this major POLS axis are thus expected to facilitate rapid and adaptively integrated changes in various aspects of life histories within and among populations and/or species. The fluctuating density-dependent selection POLS framework presented here therefore provides a series of clear testable predictions, the investigation of which should further our fundamental understanding of life-history evolution and thus our ability to predict natural population dynamics.

Contrasting patterns of density‐dependent selection at different life stages can create more than one fast–slow axis of life‐history variation

“…Indeed, there is a clear connection here between fast–slow life‐history variation among species and fast–slow “pace‐of‐life syndromes” (POLS) among individuals within populations. Wright et al () have recently argued that with stochastic environmental variation and thus under fluctuating density‐dependent selection, then the same Engen et al () model framework used here predicts that any fast–slow life‐history variation among species will be mirrored (i.e., along the same orientation of fast–slow multi‐trait axis) in fast versus slow life histories among individual in POLSs seen within each of these species or populations. Hence, our model raises the additional possibility of one than one axis of life‐history variation in POLSs within populations, if the population dynamics of the different life stages are sufficiently independent of each other.…”

“…Hence, fast‐selected life histories can be generated in populations limited by high levels of demographic stochasticity, for example in the form of random predation, where there is an individual probability of predation that is largely density‐independent and unpredictable and cannot be adaptively reduced further through the evolution of antipredator traits. The only difference is that such demographic stochasticity (via effects such as individual predation probabilities) will not have the same effects as environmental stochasticity (via such things as weather affecting whole populations) on variances in fitness that can lead to the evolution of additional bet‐hedging adaptations in life‐history strategies (see Wright et al, ). Likewise, any density‐dependent effects in models like this are perhaps usually imagined in terms of intraspecific competition for the resources needed to survive and reproduce.…”

“…We can therefore predict the role of any trait in driving density‐dependent life‐history evolution through its effects on the parameters describing density‐independent reproduction ( r 0 ) and density‐dependent effects on fitness ( γ ) estimated from natural populations (e.g., Sæther et al, ). In principle, these same effects can be investigated across multiple traits simultaneously using multivariate statistical analyses, such as structural equation modeling, at the species, population, and/or individual levels (Wright et al, ). Indeed, there is a clear connection here between fast–slow life‐history variation among species and fast–slow “pace‐of‐life syndromes” (POLS) among individuals within populations.…”

“…We hope that this will open up further opportunities for more structured explorations of life‐history evolution in more realistic ecological detail. For example, statistical analyses centered upon the demographic consequences of individual life‐history traits in terms of their contributions to density‐independent reproductive rates ( r 0 ) and density‐dependent effects on fitness ( γ ) (Sæther et al, ; Wright et al, ). In addition, we need more artificial density‐dependent selection experiments along the lines of Reznick et al () that manipulate natural sources of population limitation, whether they involve environmental and/or demographic stochasticity.…”

“…Understanding the eco‐evolutionary dynamics of life‐history evolution therefore requires an appreciation of the degree to which population densities are limited by environmental (or demographic) stochasticity versus the limiting effects of density dependence. The predictions concerning precisely which life‐history (and other physiological and behavioral) traits we expect to be implicated in any particular system thus depend upon the contributions of each trait to variation in density‐independent reproduction ( r 0 ) and density‐dependent reductions in fitness ( γ )—see Wright, Araya‐Aroy, Bolstad, and Dingemanse (). This is because selection will maximize Malthusian fitness given the trade‐off between these two parameters, which is what defines this revised and fully eco‐evolutionary version of density‐independent versus density‐dependent selection (Engen & Sæther, ).…”