The dynamics of a quantitative trait in an age-structured population living in a variable environment

Extending eco-evolutionary theory with oligomorphic dynamics

Understanding the interplay between ecological processes and the evolutionary dynamics of quantitative traits in natural systems remains a major challenge. Two main theoretical frameworks are used to address this question, adaptive dynamics and quantitative genetics, both of which have strengths and limitations and are often used by distinct research communities to address different questions. In order to make progress, new theoretical developments are needed that integrate these approaches and strengthen the link to empirical data. Here, we discuss a novel theoretical framework that bridges the gap between quantitative genetics and adaptive dynamics approaches. 'Oligomorphic dynamics' can be used to analyse eco-evolutionary dynamics across different time scales and extends quantitative genetics theory to account for multimodal trait distributions, the dynamical nature of genetic variance, the potential for disruptive selection due to ecological feedbacks, and the non-normal or skewed trait distributions encountered in nature. Oligomorphic dynamics explicitly takes into account the effect of environmental feedback, such as frequency- and density-dependent selection, on the dynamics of multi-modal trait distributions and we argue it has the potential to facilitate a much tighter integration between eco-evolutionary theory and empirical data.

Adaption, neutrality and life-course diversity

Heterogeneity among individuals in fitness components is what selection acts upon. Evolutionary theories predict that selection in constant environments acts against such heterogeneity. But observations reveal substantial non-genetic and also non-environmental variability in phenotypes. Here, we examine whether there is a relationship between selection pressure and phenotypic variability by analysing structured population models based on data from a large and diverse set of species. Our findings suggest that non-genetic, non-environmental variation is in general neither truly neutral, selected for, nor selected against. We find much variations among species and populations within species, with mean patterns suggesting nearly neutral evolution of life-course variability. Populations that show greater diversity of life courses do not show, in general, increased or decreased population growth rates. Our analysis suggests we are only at the beginning of understanding the evolution and maintenance of non-genetic non-environmental variation.

The contribution of extra-pair paternity to the variation in lifetime and age-specific male reproductive success in a socially monogamous species

In socially monogamous species, extra-pair paternity (EPP) is predicted to increase variance in male reproductive success (RS) beyond that resulting from genetic monogamy, thus, increasing the "opportunity for selection" (maximum strength of selection that can act on traits). This prediction is challenging to investigate in wild populations because lifetime reproduction data are often incomplete. Moreover, age-specific variances in reproduction have been rarely quantified. We analyzed 21 years of near-complete social and genetic reproduction data from an insular population of Seychelles warblers (Acrocephalus sechellensis). We quantified EPP's contribution to lifetime and age-specific opportunities for selection in males. We compared the variance in male genetic RS vs social ("apparent") RS (RS_ap ) to assess if EPP increased the opportunity for selection over that resulting from genetic monogamy. Despite not causing a statistically significant excess (19%) of the former over the latter, EPP contributed substantially (27%) to the variance in lifetime RS, similarly to within-pair paternity (WPP, 39%) and to the positive WPP-EPP covariance (34%). Partitioning the opportunity for selection into age-specific (co)variance components, showed that EPP also provided a substantial contribution at most ages, varying with age. Therefore, despite possibly not playing the main role in shaping sexual selection in Seychelles warblers, EPP provided a substantial contribution to the lifetime and age-specific opportunity for selection, which can influence evolutionary processes in age-structured populations.

Cross-Latitude Behavioural Axis in an Adult Damselfly Calopteryx splendens (Harris, 1780)

Simple Summary

Animals adapt to the environment they live in. If the environment changes, animals usually adapt behaviourally as a first response. By studying behavioural profiles across long distances, we can detect environmental change reflected in shifts in behavioural profiles. This study examined variation in three behavioural axes: activity, courtship and boldness, and the association between these behaviours, i.e., behavioural syndromes, across three damselfly populations along a latitudinal gradient (i.e., climatic gradient). Our study organism was the temperate damselfly Calopteryx splendens. We predicted that behavioural expressions would gradually increase from southern to northern regions. This is because northern animals should compensate behaviourally for a brief and cold breeding season (i.e., time constraint). Activity was the only behaviour feature positively associated with latitudinal gradient. Courtship effort was highest in the central region, whereas boldness values were highest in the north but did not differ between central and south. In the southern region, an activity–boldness and a courtship—boldness syndrome were present, and in the northern region, only an activity–boldness syndrome was found. Our results confirm that environmental variability in biotic and abiotic factors across studied latitudes generates regional differences in behavioural profiles, which do not always follow latitudinal gradient.

Abstract

Behavioural variation is important for evolutionary and ecological processes, but can also be useful when predicting consequences of climate change and effects on species ranges. Latitudinal differences in behaviour have received relatively limited research interest when compared to morphological, life history and physiological traits. This study examined differences in expression of three behavioural axes: activity, courtship and boldness, and their correlations, along a European latitudinal gradient spanning ca. 1500 km. The study organism was the temperate damselfly Calopteryx splendens (Harris). We predicted that the expression of both behavioural traits and behavioural syndromes would be positively correlated to latitude, with the lowest values in the southern populations, followed by central and the highest in the north, because animals usually compensate behaviourally for increasing time constraints and declining environmental conditions. We found that behavioural expression varied along the latitudinal cline, although not always in the predicted direction. Activity was the only behaviour that followed our prediction and gradually increased northward. Whereas no south-to-north gradient was seen in any of the behavioural syndromes. The results, particularly for activity, suggest that climatic differences across latitudes change behavioural profiles. However, for other traits such as courtship and boldness, local factors might invoke stronger selection pressures, disrupting the predicted latitudinal pattern.

Does life history mediate discharge as a driver of multi-decadal changes in populations of freshwater fish?

Understanding how and why the size of populations varies is critical knowledge for conservation and management. While considerable work has explored how different demographic parameters affect population growth, less is known the drivers of variability in these parameters. Long-term time series tracking population size that are coupled with empirical data to examine the relative importance of different drivers are rare, especially in freshwater systems. Even rarer are studies that collect this information concurrently from multiple species with contrasting life history strategies in the same system to assess whether population size and the relative importance of drivers also vary. We studied changes in the abundance and size structure of four native freshwater fish species in the Murray River, southeastern Australia, over a continuous 19-yr period. Two species with traits typical of "equilibrium" species (Murray cod Maccullochella peelii and trout cod Maccullochella macquariensis) and two with traits of "periodic" species (golden perch Macquaria ambigua and silver perch Bidyanus bidyanus) were sampled annually and capture-mark-recapture modeling was used to ask (1) how did population size change during this period, (2) how were changes in population size related to variability in hydrology, and (3) how were changes in population size driven by different processes (local recruitment or migration events)? Populations of all four species varied throughout the study, and our results are consistent with the notion that local recruitment is an important driver of this variability for Murray cod and trout cod, whereas immigration is more important for the two other species. Increases in spring river discharge strongly influenced these responses for trout cod and golden perch. Our study provides fundamental insights into the population dynamics of these valued species, and how management strategies might differ based on their life histories. Management should focus on allowing connectivity for golden and silver perch, and on promoting local scale recruitment and survival for Murray cod and trout cod. More generally, our study highlights the importance of understanding the processes underpinning population persistence, how these processes may vary for different species, and ultimately how this knowledge can inform targeted management actions.

Quantifying the effect of genetic, environmental and individual demographic stochastic variability for population dynamics in Plantago lanceolata

Simple demographic events, the survival and reproduction of individuals, drive population dynamics. These demographic events are influenced by genetic and environmental parameters, and are the focus of many evolutionary and ecological investigations that aim to predict and understand population change. However, such a focus often neglects the stochastic events that individuals experience throughout their lives. These stochastic events also influence survival and reproduction and thereby evolutionary and ecological dynamics. Here, we illustrate the influence of such non-selective demographic variability on population dynamics using population projection models of an experimental population of Plantago lanceolata. Our analysis shows that the variability in survival and reproduction among individuals is largely due to demographic stochastic variation with only modest effects of differences in environment, genes, and their interaction. Common expectations of population growth, based on expected lifetime reproduction and generation time, can be misleading when demographic stochastic variation is large. Large demographic stochastic variation exhibited within genotypes can lower population growth and slow evolutionary adaptive dynamics. Our results accompany recent investigations that call for more focus on stochastic variation in fitness components, such as survival, reproduction, and functional traits, rather than dismissal of this variation as uninformative noise.

Slower environmental cycles maintain greater life-history variation within populations

Populations in nature are comprised of individual life histories, whose variation underpins ecological and evolutionary processes. Yet the forces of environmental selection that shape intrapopulation life-history variation are still not well-understood, and efforts have largely focused on random (stochastic) fluctuations of the environment. However, a ubiquitous mode of environmental fluctuation in nature is cyclical, whose periodicities can change independently of stochasticity. Here, we test theoretically based hypotheses for whether shortened ('Fast') or lengthened ('Slow') environmental cycles should generate higher intrapopulation variation of life history phenotypes. We show, through a combination of agent-based modelling and a multi-generational laboratory selection experiment using the tidepool copepod Tigriopus californicus, that slower environmental cycles maintain higher levels of intrapopulation variation. Surprisingly, the effect of environmental periodicity on variation was much stronger than that of stochasticity. Thus, our results show that periodicity is an important facet of fluctuating environments for life-history variation.

The Price equation and evolutionary epidemiology

The Price equation has found widespread application in many areas of evolutionary biology, including the evolutionary epidemiology of infectious diseases. In this paper, we illustrate the utility of this approach to modelling disease evolution by first deriving a version of Price's equation that can be applied in continuous time and to populations with overlapping generations. We then show how this version of Price's equation provides an alternative perspective on pathogen evolution by considering the epidemiological meaning of each of its terms. Finally, we extend these results to the case where population size is small and generates demographic stochasticity. We show that the particular partitioning of evolutionary change given by Price's equation is also a natural way to partition the evolutionary consequences of demographic stochasticity, and demonstrate how such stochasticity tends to weaken selection on birth rate (e.g. the transmission rate of an infectious disease) and enhance selection on mortality rate (e.g. factors, like virulence, that cause the end of an infection). In the long term, if there is a trade-off between virulence and transmission across parasite strains, the weaker selection on transmission and stronger selection on virulence that arises from demographic stochasticity will tend to drive the evolution of lower levels of virulence. This article is part of the theme issue 'Fifty years of the Price equation'.

Understanding Maladaptation by Uniting Ecological and Evolutionary Perspectives

Evolutionary biologists have long trained their sights on adaptation, focusing on the power of natural selection to produce relative fitness advantages while often ignoring changes in absolute fitness. Ecologists generally have taken a different tack, focusing on changes in abundance and ranges that reflect absolute fitness while often ignoring relative fitness. Uniting these perspectives, we articulate various causes of relative and absolute maladaptation and review numerous examples of their occurrence. This review indicates that maladaptation is reasonably common from both perspectives, yet often in contrasting ways. That is, maladaptation can appear strong from a relative fitness perspective, yet populations can be growing in abundance. Conversely, resident individuals can appear locally adapted (relative to nonresident individuals) yet be declining in abundance. Understanding and interpreting these disconnects between relative and absolute maladaptation, as well as the cases of agreement, is increasingly critical in the face of accelerating human-mediated environmental change. We therefore present a framework for studying maladaptation, focusing in particular on the relationship between absolute and relative fitness, thereby drawing together evolutionary and ecological perspectives. The unification of these ecological and evolutionary perspectives has the potential to bring together previously disjunct research areas while addressing key conceptual issues and specific practical problems.

Selection in two-sex stage-structured populations: Genetics, demography, and polymorphism

The outcome of natural selection depends on the demographic processes of birth, death, and development. Here, we derive conditions for protected polymorphism in a population characterized by age- or stage-dependent demography with two sexes. We do so using a novel two-sex matrix population model including basic Mendelian genetics (one locus, two alleles, random mating). Selection may operate on survival, growth, or fertility, any or all of which may differ between the sexes. The model can therefore incorporate genes with arbitrary pleiotropic and sex-specific effects. Conditions for protected polymorphism are expressed in terms of the eigenvalues of the linearization of the model at the homozygote boundary equilibria. We show that in the absence of sexual dimorphism, polymorphism requires heterozygote superiority in the genotypic population growth rate. In the presence of sexual dimorphism, however, heterozygote superiority is not required; an inferior heterozygote may invade, reducing the population growth rate and even leading to extinction (so-called evolutionary suicide). Our model makes no assumptions about separation of time scales between ecological and evolutionary processes, and can thus be used to project sex×stage×genotype dynamics of eco-evolutionary processes. Empirical evidence that sexual dimorphism affects extinction risk is growing, yet sex differences are often ignored in evolutionary demography and in eco-evolutionary models. Our analysis highlights the importance of sexual dimorphism and suggests mechanisms by which an allele can be favored by selection, yet drive a population to extinction, as a result of the structure and interdependence of sex- and stage-specific processes.

Demographic responses underlying eco-evolutionary dynamics as revealed with inverse modelling

Changes in population dynamics due to interacting evolutionary and ecological processes are the direct result of responses in vital rates, that is stage‐specific growth, survival and fecundity. Quantifying through which vital rates population fitness is affected, instead of focusing on population trends only, can give a more mechanistic understanding of eco‐evolutionary dynamics.

The aim of this study was to estimate the underlying demographic rates of aphid (Myzus persicae) populations. We analysed unpublished stage‐structure population dynamics data of a field experiment with caged and uncaged populations in which rapid evolutionary dynamics were observed, as well as unpublished results from an individual life table experiment performed in a glasshouse.

Using data on changes in population abundance and stage distributions over time, we estimated transition matrices with inverse modelling techniques, in a Bayesian framework. The model used to fit across all experimental treatments included density as well as clone‐specific caging effects. We additionally used individual life table data to inform the model on survival, growth and reproduction.

Results suggest that clones varied considerably in vital rates, and imply trade‐offs between reproduction and survival. Responses to densities also varied between clones. Negative density dependence was found in growth and reproduction, and the presence of predators and competitors further decreased these two vital rates, while survival estimates increased. Under uncaged conditions, population growth rates of the evolving populations were increased compared to the expectation based on the pure clones.

Our inverse modelling approach revealed how much vital rates contributed to the eco‐evolutionary dynamics. The decomposition analysis showed that variation in population growth rates in the evolving populations was to a large extent shaped by plant size. Yet, it also revealed an impact of evolutionary changes in clonal composition. Finally, we discuss that inverse modelling is a complex problem, as multiple combinations of individual rates can result in the same dynamics. We discuss assumptions and limitations, as well as opportunities, of this approach.

Stage-Structured Evolutionary Demography: Linking Life Histories, Population Genetics, and Ecological Dynamics

Demographic processes and ecological interactions are central to understanding evolution and vice versa. We present a novel framework that combines basic Mendelian genetics with the powerful demographic approach of matrix population models. The ecological components of the model may be stage classified or age classified, linear or nonlinear, time invariant or time varying, and deterministic or stochastic. Genotypes may affect, in fully pleiotropic fashion, any mixture of demographic traits (viability, fertility, development) at any points in the life cycle. The dynamics of the stage × genotype structure of the population are given by a nonlinear population projection matrix. We show how to construct this matrix and use it to derive sufficient conditions for a protected genetic polymorphism for the case of linear, time-independent demography. These conditions demonstrate that genotype-specific population growth rates (λ) do not determine the outcome of selection. Except in restrictive special cases, heterozygote superiority in λ is neither necessary nor sufficient for a genetic polymorphism. As a consequence, the population growth rate does not always increase, and populations can be driven to extinction due to evolutionary suicide. We demonstrate the construction and analysis of the model using data on a color polymorphism in the common buzzard (Buteo buteo). The model exhibits a stable genetic polymorphism and declining growth rate, consistent with field data and previous models.

What have humans done for evolutionary biology? Contributions from genes to populations

Many fundamental concepts in evolutionary biology were discovered using non-human study systems. Humans are poorly suited to key study designs used to advance this field, and are subject to cultural, technological, and medical influences often considered to restrict the pertinence of human studies to other species and general contexts. Whether studies using current and recent human populations provide insights that have broader biological relevance in evolutionary biology is, therefore, frequently questioned. We first surveyed researchers in evolutionary biology and related fields on their opinions regarding whether studies on contemporary humans can advance evolutionary biology. Almost all 442 participants agreed that humans still evolve, but fewer agreed that this occurs through natural selection. Most agreed that human studies made valuable contributions to evolutionary biology, although those less exposed to human studies expressed more negative views. With a series of examples, we discuss strengths and limitations of evolutionary studies on contemporary humans. These show that human studies provide fundamental insights into evolutionary processes, improve understanding of the biology of many other species, and will make valuable contributions to evolutionary biology in the future.

Stochastic Evolutionary Demography under a Fluctuating Optimum Phenotype

Many natural populations exhibit temporal fluctuations in abundance that are consistent with external forcing by a randomly changing environment. As fitness emerges from an interaction between the phenotype and the environment, such demographic fluctuations probably include a substantial contribution from fluctuating phenotypic selection. We study the stochastic population dynamics of a population exposed to random (plus possibly directional) changes in the optimum phenotype for a quantitative trait that evolves in response to this moving optimum. We derive simple analytical predictions for the distribution of log population size over time both transiently and at stationarity under Gompertz density regulation. These predictions are well matched by population- and individual-based simulations. The log population size is approximately reverse gamma distributed, with a negative skew causing an excess of low relative to high population sizes, thus increasing extinction risk relative to a symmetric (e.g., normal) distribution with the same mean and variance. Our analysis reveals how the mean and variance of log population size change with the variance and autocorrelation of deviations of the evolving mean phenotype from the optimum. We apply our results to the analysis of evolutionary rescue in a stochastic environment and show that random fluctuations in the optimum can substantially increase extinction risk by both reducing the expected growth rate and increasing the variance of population size by several orders of magnitude.

Incorporating variability in simulations of seasonally forced phenology using integral projection models

Phenology models are becoming increasingly important tools to accurately predict how climate change will impact the life histories of organisms. We propose a class of integral projection phenology models derived from stochastic individual‐based models of insect development and demography. Our derivation, which is based on the rate summation concept, produces integral projection models that capture the effect of phenotypic rate variability on insect phenology, but which are typically more computationally frugal than equivalent individual‐based phenology models. We demonstrate our approach using a temperature‐dependent model of the demography of the mountain pine beetle (Dendroctonus ponderosae Hopkins), an insect that kills mature pine trees. This work illustrates how a wide range of stochastic phenology models can be reformulated as integral projection models. Due to their computational efficiency, these integral projection models are suitable for deployment in large‐scale simulations, such as studies of altered pest distributions under climate change.

Modeling Adaptive and Nonadaptive Responses of Populations to Environmental Change

Understanding how the natural world will be impacted by environmental change over the coming decades is one of the most pressing challenges facing humanity. Addressing this challenge is difficult because environmental change can generate both population-level plastic and evolutionary responses, with plastic responses being either adaptive or nonadaptive. We develop an approach that links quantitative genetic theory with data-driven structured models to allow prediction of population responses to environmental change via plasticity and adaptive evolution. After introducing general new theory, we construct a number of example models to demonstrate that evolutionary responses to environmental change over the short-term will be considerably slower than plastic responses and that the rate of adaptive evolution to a new environment depends on whether plastic responses are adaptive or nonadaptive. Parameterization of the models we develop requires information on genetic and phenotypic variation and demography that will not always be available, meaning that simpler models will often be required to predict responses to environmental change. We consequently develop a method to examine whether the full machinery of the evolutionarily explicit models we develop will be needed to predict responses to environmental change or whether simpler nonevolutionary models that are now widely constructed may be sufficient.

The role of weather and density dependence on population dynamics of Alpine-dwelling red deer

The dynamics of red deer Cervus elaphus populations has been investigated across different environmental conditions, with the notable exception of the European Alps. Although the population dynamics of mountain-dwelling ungulates is typically influenced by the interaction between winter severity and density, the increase of temperatures and the reduction of snowpack occurring on the Alps since the 1980s may be expected to alter this pattern, especially in populations dwelling at medium - low elevations. Taking advantage of a 29-year time series of spring count data, we explored the role of weather stochasticity and density dependence on growth rate and vital rates (mortality and weaning success), and the density-dependent variation in body mass in a red deer population of the Italian Alps. The interaction between increasing values of density and snow depth exerted negative and positive effects on growth and mortality rates, respectively, while weaning success was negatively affected by increasing values of density, female-biased sex ratio and snow depth. Body mass of males and females of different age classes declined as population size increased. Our data support the role of winter severity and density dependence as key components of red deer population dynamics, and provide insight into the species' ecology on the European Alps. Despite the recent decline of snowpack on the Alpine Region, the negative impacts of winter severity and population abundance on growth rrate (possibly mediated by the density-dependent decline in body mass) confirms the importance of overwinter mortality in affecting the population dynamics of Alpine-dwelling red deer.

Bigger Is Fitter? Quantitative Genetic Decomposition of Selection Reveals an Adaptive Evolutionary Decline of Body Mass in a Wild Rodent Population

In natural populations, quantitative trait dynamics often do not appear to follow evolutionary predictions. Despite abundant examples of natural selection acting on heritable traits, conclusive evidence for contemporary adaptive evolution remains rare for wild vertebrate populations, and phenotypic stasis seems to be the norm. This so-called “stasis paradox” highlights our inability to predict evolutionary change, which is especially concerning within the context of rapid anthropogenic environmental change. While the causes underlying the stasis paradox are hotly debated, comprehensive attempts aiming at a resolution are lacking. Here, we apply a quantitative genetic framework to individual-based long-term data for a wild rodent population and show that despite a positive association between body mass and fitness, there has been a genetic change towards lower body mass. The latter represents an adaptive response to viability selection favouring juveniles growing up to become relatively small adults, i.e., with a low potential adult mass, which presumably complete their development earlier. This selection is particularly strong towards the end of the snow-free season, and it has intensified in recent years, coinciding which a change in snowfall patterns. Importantly, neither the negative evolutionary change, nor the selective pressures that drive it, are apparent on the phenotypic level, where they are masked by phenotypic plasticity and a non causal (i.e., non genetic) positive association between body mass and fitness, respectively. Estimating selection at the genetic level enabled us to uncover adaptive evolution in action and to identify the corresponding phenotypic selective pressure. We thereby demonstrate that natural populations can show a rapid and adaptive evolutionary response to a novel selective pressure, and that explicitly (quantitative) genetic models are able to provide us with an understanding of the causes and consequences of selection that is superior to purely phenotypic estimates of selection and evolutionary change.

A population of snow voles provides a rare example of contemporary adaptive evolution in the wild, but without a quantitative genetic perspective this genetic change, and the selective pressure that underlies it, would have gone undetected.

Biologists struggle to demonstrate adaptive evolution in wild populations: while they routinely observe natural selection on heritable traits, in only a handful of cases could they demonstrate an evolutionary response. Although various explanations for this paradox have been proposed, comprehensive empirical tests are lacking. Over the past years, we have therefore studied an alpine population of snow voles. Following all individuals throughout their lives, we found that body mass is heritable and that heavy voles have a higher fitness. Nevertheless, mean body mass did not increase. To resolve this, we disentangled the role of genes and the environment in shaping body mass. This revealed that the population did evolve, but that this was masked by environmental variation. Furthermore, although the genetic change was adaptive, it was opposite to our initial expectation: the population evolved to become lighter, not heavier. This was because although heavy voles have the highest fitness, their mass does not cause high fitness. Instead, it is the voles with the genes for being light that do best, especially when the first winter snow arrives early. This shows that populations can evolve rapidly, but that without a genetic perspective, this, and its underlying mechanism, may go undetected.

The evolution of labile traits in sex- and age-structured populations

Many quantitative traits are labile (e.g. somatic growth rate, reproductive timing and investment), varying over the life cycle as a result of behavioural adaptation, developmental processes and plastic responses to the environment. At the population level, selection can alter the distribution of such traits across age classes and among generations. Despite a growing body of theoretical research exploring the evolutionary dynamics of labile traits, a data‐driven framework for incorporating such traits into demographic models has not yet been developed.

Integral projection models (IPMs) are increasingly being used to understand the interplay between changes in labile characters, life histories and population dynamics. One limitation of the IPM approach is that it relies on phenotypic associations between parents and offspring traits to capture inheritance. However, it is well‐established that many different processes may drive these associations, and currently, no clear consensus has emerged on how to model micro‐evolutionary dynamics in an IPM framework.

We show how to embed quantitative genetic models of inheritance of labile traits into age‐structured, two‐sex models that resemble standard IPMs. Commonly used statistical tools such as GLMs and their mixed model counterparts can then be used for model parameterization. We illustrate the methodology through development of a simple model of egg‐laying date evolution, parameterized using data from a population of Great tits (Parus major).

We demonstrate how our framework can be used to project the joint dynamics of species' traits and population density. We then develop a simple extension of the age‐structured Price equation (ASPE) for two‐sex populations, and apply this to examine the age‐specific contributions of different processes to change in the mean phenotype and breeding value.

The data‐driven framework we outline here has the potential to facilitate greater insight into the nature of selection and its consequences in settings where focal traits vary over the lifetime through ontogeny, behavioural adaptation and phenotypic plasticity, as well as providing a potential bridge between theoretical and empirical studies of labile trait variation.

Differential plasticity of size and mass to environmental change in a hibernating mammal

Morphological changes following changes in species' distribution and phenology have been suggested to be the third universal response to global environmental change. Although structural size and body mass result from different genetic, physiological, and ecological mechanisms, they are used interchangeably in studies evaluating population responses to environmental change. Using a 22-year (1991-2013) dataset including 1768 individuals, we investigated the coupled dynamics of size and mass in a hibernating mammal, the Alpine marmot (Marmota marmota), in response to local environmental conditions. We (i) quantified temporal trends in both traits, (ii) determined the environmental drivers of trait dynamics, and (iii) identified the life-history processes underlying the observed changes. Both phenotypic traits were followed through life: we focused on the initial trait value (juvenile size and mass) and later-life development (annual change in size [Δsize] and mass [Δmass]). First, we demonstrated contrasting dynamics between size and mass over the study period. Juvenile size and subsequent Δsize showed significant declines, whereas juvenile mass and subsequent Δmass remained constant. As a consequence of smaller size associated with a similar mass, individuals were in better condition in recent years. Second, size and mass showed different sensitivities to environmental variables. Both traits benefited from early access to resources in spring, whereas Δmass, particularly in early life, also responded to summer and winter conditions. Third, the interannual variation in both traits was caused by changes in early life development. Our study supports the importance of considering the differences between size and mass responses to the environment when evaluating the mechanisms underlying population dynamics. The current practice of focusing on only one trait in population modeling can lead to misleading conclusions when evaluating species' resilience to contemporary climate change.

Global change, life-history complexity and the potential for evolutionary rescue

Most organisms have complex life cycles, and in marine taxa, larval life‐history stages tend to be more sensitive to environmental stress than adult (reproductive) life‐history stages. While there are several models of stage‐specific adaptation across the life history, the extent to which differential sensitivity to environmental stress (defined here as reductions in absolute fitness across the life history) affects the tempo of adaptive evolution to change remains unclear. We used a heuristic model to explore how commonly observed features associated with marine complex life histories alter a population's capacity to cope with environmental change. We found that increasing the complexity of the life history generally reduces the evolutionary potential of taxa to cope with environmental change. Our model also predicted that genetic correlations in stress tolerance between stages, levels of genetic variance in each stage, and the relative plasticity of different stages, all interact to affect the maximum rate of environmental change that will permit species persistence. Our results suggest that marine organisms with complex life cycles are particularly vulnerable to anthropogenic global change, but we lack empirical estimates of key parameters for most species.

Cryptic eco-evolutionary dynamics

Natural systems harbor complex interactions that are fundamental parts of ecology and evolution. These interactions challenge our inclinations and training to seek the simplest explanations of patterns in nature. Not least is the likelihood that some complex processes might be missed when their patterns look similar to predictions for simpler mechanisms. Along these lines, theory and empirical evidence increasingly suggest that environmental, ecological, phenotypic, and genetic processes can be tightly intertwined, resulting in complex and sometimes surprising eco-evolutionary dynamics. The goal of this review is to temper inclinations to unquestioningly seek the simplest explanations in ecology and evolution, by recognizing that some eco-evolutionary outcomes may appear very similar to purely ecological, purely evolutionary, or even null expectations, and thus be cryptic. We provide theoretical and empirical evidence for observational biases and mechanisms that might operate among the various links in eco-evolutionary feedbacks to produce cryptic patterns. Recognition that cryptic dynamics can be associated with outcomes like stability, resilience, recovery, or coexistence in a dynamically changing world provides added impetus for finding ways to study them.

Des différences, pourquoi? Transmission, maintenance and effects of phenotypic variance

Despite the observed distribution of variable individual phenotypes, survival and reproductive performance in wild populations, models of population dynamics often focus on mean demographic rates. Populations are constituted by individuals with different phenotypes and thus different performances. However, many models of population dynamics provide no understanding of the influence of this phenotypic variation on population dynamics. In this paper, we investigate how the relationships between demographic rates and phenotype distribution influence the transmission and the upholding of phenotypic variation, and population dynamics. We used integral projection models to measure associations between differences of phenotypic trait (size or mass) among individuals and demographic rates, growth and inheritance, and then quantify the influence of phenotypic variation on population dynamics. We build an analytical and general model resulting from simplifications assuming small phenotypic variance. We illustrate our model with two case studies: a short- and a long-lived life history. Population growth rate r is determined by a Lotka style equation in which survival and fertility are averaged over a phenotypic distribution that changes with age. Here, we further decomposed r to show how much it is affected by shifts in phenotypic average as well as variance. We derived the elasticities of r to the first and second derivative of each demographic rate. In particular, we show that the nonlinearity of change in selective pressure with phenotype matters more to population dynamics than the strength of this selection. In other words, the variance of a given trait will be most important when the strength of selection increases (or decreases) nonlinearly with that trait. Inheritance shapes the distribution of newborn phenotypes. Even if newborns have a fixed average phenotype, the variance among newborns increases with phenotypic variance among mothers, strength of inheritance and developmental variation. We explain how the components of inheritance can influence phenotypic variance and thus the demographic rates and population dynamics. In particular, when mothers of different ages produce offspring of different mean phenotype, the inheritance function can have a large influence on both the mean and variance of the trait at different ages and thus on the population growth rate. We provide new tools to understand how phenotypic variation influences population dynamics and discuss in which life histories we expect this influence to be large. For instance, in our short-lived life history, individual variability has larger effect than in our long-lived life history. We conclude by indicating future directions of analysis.

The Theoretical Potential for Selection on Determinants of Fertility to Cause Aggregate Fertility Increases in Human Populations

While prior literature on the genetics of human fertility outcomes and attitudes has generally yielded significantly positive results in developed-country contexts, the implications of this dynamic for the potential for intergenerational increases in fertility are rarely raised. Here the prior literature on the subject is discussed in light of its implications for future changes due to selection, equations traditionally used in human demography are integrated into an evolutionary biological framework, and speculative calculations on the change in future fertility assuming already published numbers for parities and heritability are conducted. Limitations and overall conclusions are discussed.

Individual heterogeneity in life histories and eco-evolutionary dynamics

Individual heterogeneity in life history shapes eco-evolutionary processes, and unobserved heterogeneity can affect demographic outputs characterising life history and population dynamical properties. Demographic frameworks like matrix models or integral projection models represent powerful approaches to disentangle mechanisms linking individual life histories and population-level processes. Recent developments have provided important steps towards their application to study eco-evolutionary dynamics, but so far individual heterogeneity has largely been ignored. Here, we present a general demographic framework that incorporates individual heterogeneity in a flexible way, by separating static and dynamic traits (discrete or continuous). First, we apply the framework to derive the consequences of ignoring heterogeneity for a range of widely used demographic outputs. A general conclusion is that besides the long-term growth rate lambda, all parameters can be affected. Second, we discuss how the framework can help advance current demographic models of eco-evolutionary dynamics, by incorporating individual heterogeneity. For both applications numerical examples are provided, including an empirical example for pike. For instance, we demonstrate that predicted demographic responses to climate warming can be reversed by increased heritability. We discuss how applications of this demographic framework incorporating individual heterogeneity can help answer key biological questions that require a detailed understanding of eco-evolutionary dynamics.

The concept of fitness in fluctuating environments

Fitness is a central concept in evolutionary biology, but there is no unified definition. We review recent theoretical developments showing that including fluctuating environments and density dependence has important implications for how differences among phenotypes in their contributions to future generations should be quantified. The rate of phenotypic evolution will vary through time because of environmental stochasticity. Density dependence may produce fluctuating selection for large growth rates at low densities but for larger carrying capacities when population sizes are large. In general, including ecologically realistic assumptions when defining the concept of fitness is crucial for estimating the potential of evolutionary rescue of populations affected by environmental perturbations such as climate change.

Estimating phenotypic selection in age-structured populations by removing transient fluctuations

An extension of the selection differential in the Robertson-Price equation for the mean phenotype in an age-structured population is provided. Temporal changes in the mean phenotype caused by transient fluctuations in the age-distribution and variation in mean phenotype among age classes, which can mistakenly be interpreted as selection, will disappear if reproductive value weighting is applied. Changes in any weighted mean phenotype in an age-structured population may be decomposed into between- and within-age class components. Using reproductive value weighting the between-age class component becomes pure noise, generated by previous genetic drift or fluctuating selection. This component, which we call transient quasi-selection, can therefore be omitted when estimating age-specific selection on fecundity or viability within age classes. The final response can be computed at the time of selection, but can not be observed until lifetime reproduction is realized unless the heritability is one. The generality of these results is illustrated further by our derivation of the selection differential for the continuous time age-structured model with general age-dependent weights. A simple simulation example as well as estimation of selection components in a house sparrow population illustrates the applicability of the theory to analyze selection on the mean phenotype in fluctuating age-structured populations.

Generation time, net reproductive rate, and growth in stage-age-structured populations

Major insights into the relationship between life-history features and fitness have come from Lotka's proof that population growth rate is determined by the level (expected amount) of reproduction and the average timing of reproduction of an individual. But this classical result is limited to age-structured populations. Here we generalize this result to populations structured by stage and age by providing a new, unique measure of reproductive timing (Tc) that, along with net reproductive rate (R0), has a direct mathematical relationship to and approximates growth rate (r). We use simple examples to show how reproductive timing Tc and level R0 are shaped by stage dynamics (individual trait changes), selection on the trait, and parent-offspring phenotypic correlation. We also show how population structure can affect dispersion in reproduction among ages and stages. These macroscopic features of the life history determine population growth rate r and reveal a complex interplay of trait dynamics, timing, and level of reproduction. Our results contribute to a new framework of population and evolutionary dynamics in stage-and-age-structured populations.

Climate warming and Bergmann's rule through time: is there any evidence?

Climate change is expected to induce many ecological and evolutionary changes. Among these is the hypothesis that climate warming will cause a reduction in body size. This hypothesis stems from Bergmann's rule, a trend whereby species exhibit a smaller body size in warmer climates, and larger body size under colder conditions in endotherms. The mechanisms behind this rule are still debated, and it is not clear whether Bergmann's rule can be extended to predict the effects of climate change through time. We reviewed the primary literature for evidence (i) of a decrease in body size in response to climate warming, (ii) that changing body size is an adaptive response and (iii) that these responses are evolutionary or plastic. We found weak evidence for changes in body size through time as predicted by Bergmann's rule. Only three studies investigated the adaptive nature of these size decreases. Of these, none reported evidence of selection for smaller size or of a genetic basis for the size change, suggesting that size decreases could be due to nonadaptive plasticity in response to changing environmental conditions. More studies are needed before firm conclusions can be drawn about the underlying causes of these changes in body size in response to a warming climate.

Moose body mass variation revisited: disentangling effects of environmental conditions and genetics

Large-scale geographical variation in phenotypic traits within species is often correlated to local environmental conditions and population density. Such phenotypic variation has recently been shown to also be influenced by genetic structuring of populations. In ungulates, large-scale geographical variation in phenotypic traits, such as body mass, has been related to environmental conditions and population density, but little is known about the genetic influences. Research on the genetic structure of moose suggests two distinct genetic lineages in Norway, structured along a north-south gradient. This corresponds with many environmental gradients, thus genetic structuring provides an additional factor affecting geographical phenotypic variation in Norwegian moose. We investigated if genetic structure explained geographical variation in body mass in Norwegian moose while accounting for environmental conditions, age and sex, and if it captured some of the variance in body mass that previously was attributed to environmental factors. Genetic structuring of moose was the most important variable in explaining the geographic variation in body mass within age and sex classes. Several environmental variables also had strong explanatory power, related to habitat diversity, environmental seasonality and winter harshness. The results suggest that environmental conditions, landscape characteristics, and genetic structure should be evaluated together when explaining large-scale patterns in phenotypic characters or life history traits. However, to better understand the role of genetic and environmental effects on phenotypic traits in moose, an extended individual-based study of variation in fitness-related characters is needed, preferably in an area of convergence between different genetic lineages.

Eco-evolutionary dynamics in response to selection on life-history

Understanding the consequences of environmental change on ecological and evolutionary dynamics is inherently problematic because of the complex interplay between them. Using invertebrates in microcosms, we characterise phenotypic, population and evolutionary dynamics before, during and after exposure to a novel environment and harvesting over 20 generations. We demonstrate an evolved change in life-history traits (the age- and size-at-maturity, and survival to maturity) in response to selection caused by environmental change (wild to laboratory) and to harvesting (juvenile or adult). Life-history evolution, which drives changes in population growth rate and thus population dynamics, includes an increase in age-to-maturity of 76% (from 12.5 to 22 days) in the unharvested populations as they adapt to the new environment. Evolutionary responses to harvesting are outweighed by the response to environmental change (∼ 1.4 vs. 4% change in age-at-maturity per generation). The adaptive response to environmental change converts a negative population growth trajectory into a positive one: an example of evolutionary rescue.

How evolving heterogeneity distributions of resource allocation strategies shape mortality patterns

It is well established that individuals age differently. Yet the nature of these inter-individual differences is still largely unknown. For humans, two main hypotheses have been recently formulated: individuals may experience differences in aging rate or aging timing. This issue is central because it directly influences predictions for human lifespan and provides strong insights into the biological determinants of aging. In this article, we propose a model which lets population heterogeneity emerge from an evolutionary algorithm. We find that whether individuals differ in (i) aging rate or (ii) timing leads to different emerging population heterogeneity. Yet, in both cases, the same mortality patterns are observed at the population level. These patterns qualitatively reproduce those of yeasts, flies, worms and humans. Such findings, supported by an extensive parameter exploration, suggest that mortality patterns across species and their potential shapes belong to a limited and robust set of possible curves. In addition, we use our model to shed light on the notion of subpopulations, link population heterogeneity with the experimental results of stress induction experiments and provide predictions about the expected mortality patterns. As biology is moving towards the study of the distribution of individual-based measures, the model and framework we propose here paves the way for evolutionary interpretations of empirical and experimental data linking the individual level to the population level.

Towards a general, population-level understanding of eco-evolutionary change

Most population-level studies of eco-evolutionary dynamics assume that evolutionary change occurs in response to ecological change and vice versa. However, a growing number of papers report simultaneous ecological and evolutionary change, suggesting that the eco-evolutionary consequences of environmental change for populations can only be fully understood through the simultaneous analysis of statistics used to describe both ecological and evolutionary dynamics. Here we argue that integral projection models (IPM), and matrix approximations of them, provide a powerful approach to integrate population ecology, life history theory, and evolution. We discuss key questions in population biology that can be examined using these models, the answers to which are essential for a general, population-level understanding of eco-evolutionary change.