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

Abstract

There has been much recent research interest in the existence of a major axis of life‐history variation along a fast–slow continuum within almost all major taxonomic groups. Eco‐evolutionary models of density‐dependent selection provide a general explanation for such observations of interspecific variation in the "pace of life." One issue, however, is that some large‐bodied long‐lived “slow” species (e.g., trees and large fish) often show an explosive “fast” type of reproduction with many small offspring, and species with “fast” adult life stages can have comparatively “slow” offspring life stages (e.g., mayflies). We attempt to explain such life‐history evolution using the same eco‐evolutionary modeling approach but with two life stages, separating adult reproductive strategies from offspring survival strategies. When the population dynamics in the two life stages are closely linked and affect each other, density‐dependent selection occurs in parallel on both reproduction and survival, producing the usual one‐dimensional fast–slow continuum (e.g., houseflies to blue whales). However, strong density dependence at either the adult reproduction or offspring survival life stage creates quasi‐independent population dynamics, allowing fast‐type reproduction alongside slow‐type survival (e.g., trees and large fish), or the perhaps rarer slow‐type reproduction alongside fast‐type survival (e.g., mayflies—short‐lived adults producing few long‐lived offspring). Therefore, most types of species life histories in nature can potentially be explained via the eco‐evolutionary consequences of density‐dependent selection given the possible separation of demographic effects at different life stages.

Variation in generation time reveals density regulation as an important driver of pace of life in a bird metapopulation

“…In contrast, when mean fitness was high and populations were expected to grow, all individuals, even the young ones, managed to reproduce. These results are consistent with classic density-dependent selection theory predicting that when populations are growing, individuals investing more in current reproduction are favoured, but when populations are close to or above their carrying capacity, the favoured individuals will be the ones that allocate more into traits enhancing survival and competitive ability (see Engen et al, 2013, Wright et al, 2020and Saether et al, 2016b, 2021 for empirical evidence).…”

“…This idea slowly lost favour and was replaced by density‐independent but age‐dependent variation in mortality as the favoured explanation for differences in the pace of life‐history strategies (Boyce, 1984; Stearns, 1976). More recently, age‐structured models of density‐dependent evolution have provided general predictions concerning the role of density dependence in determining the optimal life‐history strategies (Engen & Sæther, 2016; Lande et al, 2017; Wright et al, 2020). Despite early models of life‐history evolution, showing that density regulation should shape age‐dependent reproductive effort (Charlesworth & Leon, 1976; Michod, 1979), very few empirical studies have focused on clarifying the role of population dynamics in shaping spatial and temporal variation in generation times (Kentie et al, 2020; Nilsen et al, 2009).…”

Phenotypic evolution in stochastic environments: The contribution of frequency‐ and density‐dependent selection

“…This indicates that how as well as affect resource limitation can strongly influence the pattern of phenotypic evolution through density‐dependent selection in natural populations (Abrams 2019) and distribute species along a slow‐fast pace‐of‐life continuum (Wright et al. 2019, 2020).…”

Individual variation in dispersal, and its sources, shape the fate of pushed vs. pulled range expansions

“…They may also be correlated in syndromes at the within-and/or among-species level (Beckman et al, 2018;Guerra, 2011;Jacob et al, 2019;Ochocki et al, 2020;Ronce & Clobert, 2012), and these syndromes may shape and constrain the evolution of their constituent traits (Ronce & Clobert, 2012;Wright et al, 2019), including during range expansions (Ochocki et al, 2020;Urquhart & Williams, 2021). In addition, theoretical work even suggests that density fluctuations themselves are one of the root evolutionary drivers shaping the (co)variation of life history traits, and potentially their association with behaviours such as dispersal (Wright et al, 2019(Wright et al, , 2020. How the complexities of phenotypic structure and trait coevolution drive the net effect of population density on spread, influencing the dynamics of pushed vs pulled expansions and our ability to predict them, remain to be discovered.…”