Modeling Adaptive and Nonadaptive Responses of Populations to Environmental Change

Phenotypic plasticity in the sailfin molly III: Geographic variation in reaction norms of growth and maturation to temperature and salinity

Phenotypic plasticity, the ability of a single genotype to produce different phenotypes under different environmental conditions, plays a profound role in several areas of evolutionary biology. One important role is as an adaptation to a variable environment. While plasticity is extremely well documented in response to many environmental factors, there is controversy over how much of that plasticity is adaptive. Evidence is also mixed over how often conspecific populations display qualitative differences in the nature of plasticity. We present data on the reaction norms of growth and maturation to variation in temperature and salinity in male and female sailfin mollies (Poecilia latipinna) from three locally adjacent populations from South Carolina (SC). We compare these reaction norms to those previously reported in locally adjacent populations from north Florida (NF). In general, patterns of plasticity in fish from SC were similar to those in fish from NF. The magnitude of plasticity differed; fish from SC displayed less plasticity than fish from NF. This was because SC fish grew faster and matured earlier at the lower temperatures and salinities compared to NF fish. This is a countergradient pattern of variation, in which SC fish grew faster and matured earlier in conditions that would otherwise slow growth and delay maturity. Among fish from both regions, males were much less plastic than females, especially for length at maturity. While there was no detectable heterogeneity among populations from NF, males from one of the SC populations, which is furthest from the other two, displayed a qualitatively different response in age at maturity to temperature variation than did males from the other two SC populations. The pattern of population variation in plasticity within and among regions suggests that gene flow, which diminishes with distance in sailfin mollies, plays a critical role in constraining divergence in norms of reaction.

Breeding and Selecting Corals Resilient to Global Warming

Selective breeding of resilient organisms is an emerging topic in marine conservation. It can help us predict how species will adapt in the future and how we can help restore struggling populations effectively in the present. Scleractinian corals represent a potential tractable model system given their widescale phenotypic plasticity across fitness-related traits and a reproductive life history based on mass synchronized spawning. Here, I explore the justification for breeding in corals, identify underutilized pathways of acclimation, and highlight avenues for quantitative targeted breeding from the coral host and symbiont perspective. Specifically, the facilitation of enhanced heat tolerance by targeted breeding of plasticity mechanisms is underutilized. Evidence from theoretical genetics identifies potential pitfalls, including inattention to physical and genetic characteristics of the receiving environment. Three criteria for breeding emerge from this synthesis: selection from warm, variable reefs that have survived disturbance. This information will be essential to protect what we have and restore what we can.

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.

Beyond simple adaptation: Incorporating other evolutionary processes and concepts into eco-evolutionary dynamics

Studies of eco-evolutionary dynamics have integrated evolution with ecological processes at multiple scales (populations, communities and ecosystems) and with multiple interspecific interactions (antagonistic, mutualistic and competitive). However, evolution has often been conceptualised as a simple process: short-term directional adaptation that increases population growth. Here we argue that diverse other evolutionary processes, well studied in population genetics and evolutionary ecology, should also be considered to explore the full spectrum of feedback between ecological and evolutionary processes. Relevant but underappreciated processes include (1) drift and mutation, (2) disruptive selection causing lineage diversification or speciation reversal and (3) evolution driven by relative fitness differences that may decrease population growth. Because eco-evolutionary dynamics have often been studied by population and community ecologists, it will be important to incorporate a variety of concepts in population genetics and evolutionary ecology to better understand and predict eco-evolutionary dynamics in nature.

Plastic responses to warmer climates: a semi-natural experiment on lizard populations

Facing warming environments, species can exhibit plastic or microevolutionary changes in their thermal physiology to adapt to novel climates. Here, using semi-natural mesocosms, we experimentally investigated over two successive years whether a 2°C-warmer climate produces selective and inter- and intragenerational plastic changes in the thermal traits (preferred temperature and dorsal coloration) of the lizard Zootoca vivipara. In a warmer climate, the dorsal darkness, dorsal contrast, and preferred temperature of adults plastically decreased and covariances between these traits were disrupted. While selection gradients were overall weak, selection gradients for darkness were slightly different between climates and in the opposite direction to plastic changes. Contrary to adults, male juveniles were darker in warmer climates either through plasticity or selection and this effect was strengthened by intergenerational plasticity when juveniles' mothers also experienced warmer climates. While the plastic changes in adult thermal traits alleviate the immediate overheating costs of warming, its opposite direction to selective gradients and to juveniles' phenotypic responses may slow down evolutionary shifts toward phenotypes that are better adapted to future climates. Our study demonstrates the importance of considering inter- and intragenerational plasticity along with selective processes to better understand adaptation and population dynamics in light of climate change.

Pesticide exposure affects DNA methylation patterns in natural populations of a mayfly

Chemical pollutants derived from agricultural activities represent a major threat to freshwater biota. Despite growing evidence involving epigenetic processes, such as DNA methylation, in response to pesticide contamination in agroecosystems, research on wild populations of non-model species remains scarce, particularly for endemic freshwater arthropods. Using the MethylRAD method, this study investigates whether exposure to pesticide contamination in natural populations of the endemic mayfly A. torrens produces genome wide changes in levels of DNA methylation. From a total of 1,377,147 MethylRAD markers produced from 285 specimens collected at 30 different study sites along the Limarí watershed of north-central Chile, six showed significant differential methylation between populations exposed and unexposed to pesticides. In all cases the effect of pesticides was positive, independent and stronger than the effects detected for other spatial and environmental factors. Only one candidate marker appeared correlated significantly with additional variables, nitrate and calcium levels, which also reflects the impact of agrichemicals and could additionally suggest, to a lower extent, antagonistic effects of mineral salts concentration for this specific marker. These results suggest that the effect of pesticide exposure on methylation levels is apparent at these six MethylRAD markers in A. torrens populations. Such data is challenging to obtain in natural populations and is, for the most part, lacking in ecotoxicological studies. Our study shows that DNA methylation processes are involved in the response to pesticide contamination in populations of the mayfly A. torrens in their natural habitat, and provides new evidence regarding the impact of pesticide contamination and agricultural activities on the endemic fauna of lotic ecosystems.

A novel analytical framework to quantify co-gradient and countergradient variation

Spatial covariance between genotypic and environmental influences on phenotypes (Cov_GE ) can result in the nonrandom distribution of genotypes across environmental gradients and is a potentially important factor driving local adaptation. However, a framework to quantify the magnitude and significance of Cov_GE has been lacking. We develop a novel quantitative/analytical approach to estimate and test the significance of Cov_GE from reciprocal transplant or common garden experiments, which we validate using simulated data. We demonstrate how power to detect Cov_GE changes over a range of experimental designs. We confirm an inverse relationship between gene-by-environment interactions (GxE) and Cov_GE , as predicted by first principles, but show how phenotypes can be influenced by both. The metric provides a way to measure how phenotypic plasticity covaries with genetic differentiation and highlights the importance of understanding the dual influences of Cov_GE and GxE on phenotypes in studies of local adaptation and species' responses to environmental change.

Genomic reaction norms inform predictions of plastic and adaptive responses to climate change

Genomic reaction norms represent the range of gene expression phenotypes (usually mRNA transcript levels) expressed by a genotype along an environmental gradient. Reaction norms derived from common‐garden experiments are powerful approaches for disentangling plastic and adaptive responses to environmental change in natural populations. By treating gene expression as a phenotype in itself, genomic reaction norms represent invaluable tools for exploring causal mechanisms underlying organismal responses to climate change across multiple levels of biodiversity.

Our goal is to provide the context, framework and motivation for applying genomic reaction norms to study the responses of natural populations to climate change.

Here, we describe the utility of integrating genomics with common‐garden‐gradient experiments under a reaction norm analytical framework to answer fundamental questions about phenotypic plasticity, local adaptation, their interaction (i.e. genetic variation in plasticity) and future adaptive potential.

An experimental and analytical framework for constructing and analysing genomic reaction norms is presented within the context of polygenic climate change responses of structured populations with gene flow. Intended for a broad eco‐evo readership, we first briefly review adaptation with gene flow and the importance of understanding the genomic basis and spatial scale of adaptation for conservation and management of structured populations under anthropogenic change. Then, within a high‐dimensional reaction norm framework, we illustrate how to distinguish plastic, differentially expressed (difference in reaction norm intercepts) and differentially plastic (difference in reaction norm slopes) genes, highlighting the areas of opportunity for applying these concepts.

We conclude by discussing how genomic reaction norms can be incorporated into a holistic framework to understand the eco‐evolutionary dynamics of climate change responses from molecules to ecosystems. We aim to inspire researchers to integrate gene expression measurements into common‐garden experimental designs to investigate the genomics of climate change responses as sequencing costs become increasingly accessible.

Building integral projection models with nonindependent vital rates

Population dynamics are functions of several demographic processes including survival, reproduction, somatic growth, and maturation. The rates or probabilities for these processes can vary by time, by location, and by individual. These processes can co-vary and interact to varying degrees, e.g., an animal can only reproduce when it is in a particular maturation state. Population dynamics models that treat the processes as independent may yield somewhat biased or imprecise parameter estimates, as well as predictions of population abundances or densities. However, commonly used integral projection models (IPMs) typically assume independence across these demographic processes. We examine several approaches for modelling between process dependence in IPMs and include cases where the processes co-vary as a function of time (temporal variation), co-vary within each individual (individual heterogeneity), and combinations of these (temporal variation and individual heterogeneity). We compare our methods to conventional IPMs, which treat vital rates independent, using simulations and a case study of Soay sheep (Ovis aries). In particular, our results indicate that correlation between vital rates can moderately affect variability of some population-level statistics. Therefore, including such dependent structures is generally advisable when fitting IPMs to ascertain whether or not such between vital rate dependencies exist, which in turn can have subsequent impact on population management or life-history evolution.

The role of phenotypic plasticity in the establishment of range margins

It has been argued that adaptive phenotypic plasticity may facilitate range expansions over spatially and temporally variable environments. However, plasticity may induce fitness costs. This may hinder the evolution of plasticity. Earlier modelling studies examined the role of plasticity during range expansions of populations with fixed genetic variance. However, genetic variance evolves in natural populations. This may critically alter model outcomes. We ask: how does the capacity for plasticity in populations with evolving genetic variance alter range margins that populations without the capacity for plasticity are expected to attain? We answered this question using computer simulations and analytical approximations. We found a critical plasticity cost above which the capacity for plasticity has no impact on the expected range of the population. Below the critical cost, by contrast, plasticity facilitates range expansion, extending the range in comparison to that expected for populations without plasticity. We further found that populations may evolve plasticity to buffer temporal environmental fluctuations, but only when the plasticity cost is below the critical cost. Thus, the cost of plasticity is a key factor involved in range expansions of populations with the potential to express plastic response in the adaptive trait. This article is part of the theme issue 'Species' ranges in the face of changing environments (part I)'.

Unravelling processes between phenotypic plasticity and population dynamics in migratory birds

Populations can rapidly respond to environmental change via adaptive phenotypic plasticity, which can also modify interactions between individuals and their environment, affecting population dynamics. Bird migration is a highly plastic resource‐tracking tactic in seasonal environments. However, the link between the population dynamics of migratory birds and migration tactic plasticity is not well‐understood.

The quality of staging habitats affects individuals' migration timing and energy budgets in the course of migration and can consequently affect individuals' breeding and overwintering performance, and impact population dynamics. Given staging habitats being lost in many parts of the world, our goal is to investigate responses of individual migration tactics and population dynamics in the face of loss of staging habitat and to identify the key processes connecting them.

We started by constructing and analysing a general full‐annual‐cycle individual‐based model with a stylized migratory population to generate hypotheses on how changes in the size of staging habitat might drive changes in individual stopover duration and population dynamics. Next, through the interrogation of survey data, we tested these hypotheses by analysing population trends and stopover duration of migratory waterbirds experiencing the loss of staging habitat.

Our modelling exercise led to us posing the following hypotheses: the loss of staging habitat generates plasticity in migration tactics, with individuals remaining on the staging habitat for longer to obtain food due to a reduction in per capita food availability. The subsequent increasing population density on the staging habitat has knock‐on effects on population dynamics in the breeding and overwintering stage. Our empirical results were consistent with the modelling predictions.

Our results demonstrate how environmental change that impacts one energetically costly life‐history stage in migratory birds can have population dynamic impacts across the entire annual cycle via phenotypic plasticity.

Neutral and adaptive drivers of genomic change in introduced brook trout (Salvelinus fontinalis) populations revealed by pooled sequencing

Understanding the drivers of successful species invasions is important for conserving native biodiversity and for mitigating the economic impacts of introduced species. However, whole-genome resolution investigations of the underlying contributions of neutral and adaptive genetic variation in successful introductions are rare. Increased propagule pressure should result in greater neutral genetic variation, while environmental differences should elicit selective pressures on introduced populations, leading to adaptive differentiation. We investigated neutral and adaptive variation among nine introduced brook trout (Salvelinus fontinalis) populations using whole-genome pooled sequencing. The populations inhabit isolated alpine lakes in western Canada and descend from a common source, with an average of ~19 (range of 7-41) generations since introduction. We found some evidence of bottlenecks without recovery, no strong evidence of purifying selection, and little support that varying propagule pressure or differences in local environments shaped observed neutral genetic variation differences. Putative adaptive loci analysis revealed nonconvergent patterns of adaptive differentiation among lakes with minimal putatively adaptive loci (0.001%-0.15%) that did not correspond with tested environmental variables. Our results suggest that (i) introduction success is not always strongly influenced by genetic load; (ii) observed differentiation among introduced populations can be idiosyncratic, population-specific, or stochastic; and (iii) conservatively, in some introduced species, colonization barriers may be overcome by support through one aspect of propagule pressure or benign environmental conditions.

Life histories as mosaics: plastic and genetic components differ among traits that underpin life-history strategies

Life‐history phenotypes emerge from clusters of traits that are the product of genes and phenotypic plasticity. If the impact of the environment differs substantially between traits, then life histories might not evolve as a cohesive whole. We quantified the sensitivity of components of the life history to food availability, a key environmental difference in the habitat occupied by contrasting ecotypes, for 36 traits in fast‐ and slow‐reproducing Trinidadian guppies. Our dataset included six putatively independent origins of the slow‐reproducing, derived ecotype. Traits varied substantially in plastic and genetic control. Twelve traits were influenced only by food availability (body lengths, body weights), five only by genetic differentiation (interbirth intervals, offspring sizes), 10 by both (litter sizes, reproductive timing), and nine by neither (fat contents, reproductive allotment). Ecotype‐by‐food interactions were negligible. The response to low food was aligned with the genetic difference between high‐ and low‐food environments, suggesting that plasticity was adaptive. The heterogeneity among traits in environmental sensitivity and genetic differentiation reveals that the components of the life history may not evolve in concert. Ecotypes may instead represent mosaics of trait groups that differ in their rate of evolution.

Integrating developmental plasticity into eco-evolutionary population dynamics

There are increasing calls to incorporate developmental plasticity into the framework of eco-evolutionary dynamics. The current way is via genotype-specified reaction norms in which inheritance and phenotype expression are gene-based. I propose a developmental system perspective in which phenotypes are formed during individual development in a process comprising a complex set of interactions that involve genes, biochemistry, somatic state, and the (a)biotic environment, and where the developmental system is the unit of phenotype evolution. I explain how the two perspectives differ in assumptions and predictions, which can be contrasted using cue-and-response systems of anticipatory or mitigating developmental plasticity. This can lead to new ways of eco-evolutionary thinking, and deliver important explanations of how populations respond to environmental change through evolved developmental plasticity.

Predicting evolution over multiple generations in deteriorating environments using evolutionarily explicit Integral Projection Models

Human impacts on the natural world often generate environmental trends that can have detrimental effects on distributions of phenotypic traits. We do not have a good understanding of how deteriorating environments might impact evolutionary trajectories across multiple generations, even though effects of environmental trends are often significant in the statistical quantitative genetic analyses of phenotypic trait data that are used to estimate additive genetic (co)variances. These environmental trends capture reaction norms, where the same (average) genotype expresses different phenotypic trait values in different environments. Not incorporated into the predictive models typically parameterised from statistical analyses to predict evolution, such as the breeder's equation. We describe how these environmental effects can be incorporated into multi-generational, evolutionarily explicit, structured population models before exploring how these effects can influence evolutionary dynamics. The paper is primarily a description of the modelling approach, but we also show how incorporation into models of the types of environmental trends that human activity has generated can have considerable impacts on the evolutionary dynamics that are predicted.

Estimation of breeding probability can make monitoring data more revealing: a case study of amphibians

Monitoring programs serve to detect trends in the distribution and abundance of species. To do so, monitoring programs often use static state variables. Dynamic state variables that describe population dynamics might be more valuable because they allow for a mechanistic understanding of the processes that lead to population trends. We fit multistate occupancy models to data from a country-wide multispecies amphibian occupancy monitoring program and estimated occupancy and breeding probabilities. If breeding probabilities are determinants of occupancy dynamics, then they may serve in monitoring programs as state variables that describe dynamic processes. The results showed that breeding probabilities were low and that a large proportion of the populations had to be considered to be non-breeding populations (i.e., populations where adults are present but no breeding occurs). For some species, the majority of populations were non-breeding populations. We found that non-breeding populations have lower persistence probabilities than populations where breeding occurs. Breeding probabilities may thus explain trends in occupancy but they might also explain other ecological phenomena, such as the success of invasive species, which had high breeding probabilities. Signs of breeding, i.e., the presence of eggs and larvae, were often hard to detect. Importantly, non-breeding populations also had low detection probabilities, perhaps because they had lower abundances. We suggest that monitoring programs should invest more in the detection of life history stages indicative of breeding, and also into the detection of non-breeding populations. We conclude that breeding probability should be used as a state variable in monitoring programs because it can lead to deeper insights into the processes driving occupancy dynamics.

Demystifying individual heterogeneity

Among-individual variation in vital rates, such as mortality and birth rates, exists in nearly all populations. Recent studies suggest that this individual heterogeneity produces substantial life-history and fitness differences among individuals, which in turn scale up to influence population dynamics. However, our ability to understand the consequences of individual heterogeneity is limited by inconsistencies across conceptual frameworks in the field. Studies of individual heterogeneity remain filled with contradicting and ambiguous terminology that introduces risks of misunderstandings, conflicting models and unreliable conclusions. Here, we synthesise the existing literature into a single and comparatively straightforward framework with explicit terminology and definitions. This work introduces a distinction between potential vital rates and realised vital rates to develop a coherent framework that maps directly onto mathematical models of individual heterogeneity. We suggest the terms "fixed condition" and "dynamic condition" be used to distinguish potential vital rates that are permanent from those that can change throughout an individual's life. To illustrate, we connect the framework to quantitative genetics models and to common classes of statistical models used to infer individual heterogeneity. We also develop a population projection matrix model that provides an example of how our definitions are translated into precise quantitative terms.

Extended phenotypes: buffers or amplifiers of climate change?

Historic approaches to understanding biological responses to climate change have viewed climate as something external that happens to organisms. Organisms, however, at least partially influence their own climate experience by moving within local mosaics of microclimates. Such behaviors are increasingly being incorporated into models of species distributions and climate sensitivity. Less attention has focused on how organisms alter microclimates via extended phenotypes: phenotypes that extend beyond the organismal surface, including structures that are induced or built. We argue that predicting the consequences of climate change for organismal performance and fitness will depend on understanding the expression and consequences of extended phenotypes, the microclimatic niches they generate, and the power of plasticity and evolution to shape those niches.

The ecological causes and consequences of hard and soft selection

Interactions between natural selection and population dynamics are central to both evolutionary-ecology and biological responses to anthropogenic change. Natural selection is often thought to incur a demographic cost that, at least temporarily, reduces population growth. However, hard and soft selection clarify that the influence of natural selection on population dynamics depends on ecological context. Under hard selection, an individual's fitness is independent of the population's phenotypic composition, and substantial population declines can occur when phenotypes are mismatched with the environment. In contrast, under soft selection, an individual's fitness is influenced by its phenotype relative to other interacting conspecifics. Soft selection generally influences which, but not how many, individuals survive and reproduce, resulting in little effect on population growth. Despite these important differences, the distinction between hard and soft selection is rarely considered in ecology. Here, we review and synthesize literature on hard and soft selection, explore their ecological causes and implications and highlight their conservation relevance to climate change, inbreeding depression, outbreeding depression and harvest. Overall, these concepts emphasise that natural selection and evolution may often have negligible or counterintuitive effects on population growth-underappreciated outcomes that have major implications in a rapidly changing world.

Towards a more precise - and accurate - view of eco-evolution

Over the past 15 years, the number of papers focused on 'eco-evo dynamics' has increased exponentially (Figure 1). This pattern suggests the rapid growth of a new, integrative discipline. We argue this overstates the case. First, the terms 'eco-evo dynamics' and 'eco-evo interactions' are used too imprecisely. As a result, many studies that claim to describe eco-evo dynamics are actually describing basic ecological or evolutionary processes. Second, these terms are often used as if the study of how ecological and evolutionary processes are intertwined is novel when, in fact, it is not. The result is confusion over what the term 'eco-evolution' and its derivatives describe. We advocate a more precise definition of eco-evolution that is more useful in efforts to understand and characterise the diversity of ecological and evolutionary processes and that focuses attention on the subset of those processes that occur only when ecological and evolutionary timescales are comparable. [Figure: see text].

Merging dynamical and structural indicators to measure resilience in multispecies systems

Resilience is broadly understood as the ability of an ecological system to resist and recover from perturbations acting on species abundances and on the system's structure. However, one of the main problems in assessing resilience is to understand the extent to which measures of recovery and resistance provide complementary information about a system. While recovery from abundance perturbations has a strong tradition under the analysis of dynamical stability, it is unclear whether this same formalism can be used to measure resistance to structural perturbations (e.g. perturbations to model parameters). Here, we provide a framework grounded on dynamical and structural stability in Lotka-Volterra systems to link recovery from small perturbations on species abundances (i.e. dynamical indicators) with resistance to parameter perturbations of any magnitude (i.e. structural indicators). We use theoretical and experimental multispecies systems to show that the faster the recovery from abundance perturbations, the higher the resistance to parameter perturbations. We first use theoretical systems to show that the return rate along the slowest direction after a small random abundance perturbation (what we call full recovery) is negatively correlated with the largest random parameter perturbation that a system can withstand before losing any species (what we call full resistance). We also show that the return rate along the second fastest direction after a small random abundance perturbation (what we call partial recovery) is negatively correlated with the largest random parameter perturbation that a system can withstand before at most one species survives (what we call partial resistance). Then, we use a dataset of experimental microbial systems to confirm our theoretical expectations and to demonstrate that full and partial components of resilience are complementary. Our findings reveal that we can obtain the same level of information about resilience by measuring either a dynamical (i.e. recovery) or a structural (i.e. resistance) indicator. Irrespective of the chosen indicator (dynamical or structural), our results show that we can obtain additional information by separating the indicator into its full and partial components. We believe these results can motivate new theoretical approaches and empirical analyses to increase our understanding about risk in ecological systems.

Persistence and size of seasonal populations on a consumer-resource relationship depends on the allocation strategy toward life-history functions

The long-term ecological dynamics of a population inhabiting a seasonal environment is analyzed using a semi-discrete or impulsive system to represent the consumer-resource interaction. The resource corresponds to an incoming energy flow for consumers that is allocated to reproduction as well as to maintenance in each non-reproductive season. The energy invested in these life-history functions is used in reproductive events, determining the size of the offspring in each reproductive season. Two long-term dynamic patterns are found, resulting in either the persistence or the extinction of the population of consumers. In addition, our model indicates that only one energy allocation strategy provides an optimal combination between individual consumption and long-term population size. The current study contributes to the understanding of how the individual-level and the population-level are interrelated, exhibiting the importance of incorporating phenotypic traits in population dynamics.

Decrease in social cohesion in a colonial seabird under a perturbation regime

Social interactions, through influence on behavioural processes, can play an important role in populations’ resilience (i.e. ability to cope with perturbations). However little is known about the effects of perturbations on the strength of social cohesion in wild populations. Long-term associations between individuals may reflect the existence of social cohesion for seizing the evolutionary advantages of social living. We explore the existence of social cohesion and its dynamics under perturbations by analysing long-term social associations, in a colonial seabird, the Audouin’s gull Larus audouinii, living in a site experiencing a shift to a perturbed regime. Our goals were namely (1) to uncover the occurrence of long-term social ties (i.e. associations) between individuals and (2) to examine whether the perturbation regime affected this form of social cohesion. We analysed a dataset of more than 3500 individuals from 25 years of monitoring by means of contingency tables and within the Social Network Analysis framework. We showed that associations between individuals are not only due to philopatry or random gregariousness but that there are social ties between individuals over the years. Furthermore, social cohesion decreased under the perturbation regime. We sustain that perturbations may lead not only to changes in individuals’ behaviour and fitness but also to a change in populations’ social cohesion. The consequences of decreasing social cohesion are still not well understood, but they can be critical for the population dynamics of social species.

Consequences of Single-Locus and Tightly Linked Genomic Architectures for Evolutionary Responses to Environmental Change

Genetic and genomic architectures of traits under selection are key factors influencing evolutionary responses. Yet, knowledge of their impacts has been limited by a widespread assumption that most traits are controlled by unlinked polygenic architectures. Recent advances in genome sequencing and eco-evolutionary modeling are unlocking the potential for integrating genomic information into predictions of population responses to environmental change. Using eco-evolutionary simulations, we demonstrate that hypothetical single-locus control of a life history trait produces highly variable and unpredictable harvesting-induced evolution relative to the classically applied multilocus model. Single-locus control of complex traits is thought to be uncommon, yet blocks of linked genes, such as those associated with some types of structural genomic variation, have emerged as taxonomically widespread phenomena. Inheritance of linked architectures resembles that of single loci, thus enabling single-locus-like modeling of polygenic adaptation. Yet, the number of loci, their effect sizes, and the degree of linkage among them all occur along a continuum. We review how linked architectures are often associated, directly or indirectly, with traits expected to be under selection from anthropogenic stressors and are likely to play a large role in adaptation to environmental disturbance. We suggest using single-locus models to explore evolutionary extremes and uncertainties when the trait architecture is unknown, refining parameters as genomic information becomes available, and explicitly incorporating linkage among loci when possible. By overestimating the complexity (e.g., number of independent loci) of the genomic architecture of traits under selection, we risk underestimating the complexity (e.g., nonlinearity) of their evolutionary dynamics.

Phenotypic Plasticity for Desiccation Resistance, Climate Change, and Future Species Distributions: Will Plasticity Have Much Impact?

AbstractWhile species distribution models (SDMs) are widely used to predict the vulnerability of species to climate change, they do not explicitly indicate the extent to which plastic responses ameliorate climate change impacts. Here we use data on plastic responses of 32 species of Drosophila to desiccation stress to suggest that basal resistance, rather than adult hardening, is relatively more important in determining species differences in desiccation resistance and sensitivity to climate change. We go on to show, using the semimechanistic SDM CLIMEX, that the inclusion of plasticity has some impact on current species distributions and future vulnerability for widespread species but has little impact on the distribution of arguably more vulnerable tropically restricted species.

Environmental variation mediates the evolution of anticipatory parental effects

Theory maintains that when future environment is predictable, parents should adjust the phenotype of their offspring to match the anticipated environment. The plausibility of positive anticipatory parental effects is hotly debated and the experimental evidence for the evolution of such effects is currently lacking. We experimentally investigated the evolution of anticipatory maternal effects in a range of environments that differ drastically in how predictable they are. Populations of the nematode Caenorhabditis remanei, adapted to 20°C, were exposed to a novel temperature (25°C) for 30 generations with either positive or zero correlation between parent and offspring environment. We found that populations evolving in novel environments that were predictable across generations evolved a positive anticipatory maternal effect, because they required maternal exposure to 25°C to achieve maximum reproduction in that temperature. In contrast, populations evolving under zero environmental correlation had lost this anticipatory maternal effect. Similar but weaker patterns were found if instead rate‐sensitive population growth was used as a fitness measure. These findings demonstrate that anticipatory parental effects evolve in response to environmental change so that ill‐fitting parental effects can be rapidly lost. Evolution of positive anticipatory parental effects can aid population viability in rapidly changing but predictable environments.

Predicting population responses to environmental change from individual-level mechanisms: towards a standardized mechanistic approach

Animal populations will mediate the response of global biodiversity to environmental changes. Population models are thus important tools for both understanding and predicting animal responses to uncertain future conditions. Most approaches, however, are correlative and ignore the individual-level mechanisms that give rise to population dynamics. Here, we assess several existing population modelling approaches and find limitations to both 'correlative' and 'mechanistic' models. We advocate the need for a standardized mechanistic approach for linking individual mechanisms (physiology, behaviour, and evolution) to population dynamics in spatially explicit landscapes. Such an approach is potentially more flexible and informative than current population models. Key to realizing this goal, however, is overcoming current data limitations, the development and testing of eco-evolutionary theory to represent interactions between individual mechanisms, and standardized multi-dimensional environmental change scenarios which incorporate multiple stressors. Such progress is essential in supporting environmental decisions in uncertain future conditions.

The active spread of adaptive variation for reef resilience

The speed at which species adapt depends partly on the rates of beneficial adaptation generation and how quickly they spread within and among populations. Natural rates of adaptation of corals may not be able to keep pace with climate warming. Several interventions have been proposed to fast-track thermal adaptation, including the intentional translocation of warm-adapted adults or their offspring (assisted gene flow, AGF) and the ex situ crossing of warm-adapted corals with conspecifics from cooler reefs (hybridization or selective breeding) and field deployment of those offspring. The introgression of temperature tolerance loci into the genomic background of cooler-environment corals aims to facilitate adaptation to warming while maintaining fitness under local conditions. Here we use research on selective sweeps and connectivity to understand the spread of adaptive variants as it applies to AGF on the Great Barrier Reef (GBR), focusing on the genus Acropora. Using larval biophysical dispersal modeling, we estimate levels of natural connectivity in warm-adapted northern corals. We then model the spread of adaptive variants from single and multiple reefs and assess if the natural and assisted spread of adaptive variants will occur fast enough to prepare receiving central and southern populations given current rates of warming. We also estimate fixation rates and spatial extent of fixation under multiple release scenarios to inform intervention design. Our results suggest that thermal tolerance is unlikely to spread beyond northern reefs to the central and southern GBR without intervention, and if it does, 30+ generations are needed for adaptive gene variants to reach fixation even under multiple release scenarios. We argue that if translocation, breeding, and reseeding risks are managed, AGF using multiple release reefs can be beneficial for the restoration of coral populations. These interventions should be considered in addition to conventional management and accompanied by strong mitigation of CO2 emissions.

The effects of individual nonheritable variation on fitness estimation and coexistence

Demographic theory and data have emphasized that nonheritable variation in individual frailty enables selection within cohorts, affecting the dynamics of a population while being invisible to its evolution. Here, we include the component of individual variation in longevity or viability which is nonheritable in simple bacterial growth models and explore its ecological and evolutionary impacts. First, we find that this variation produces consistent trends in longevity differences between bacterial genotypes when measured across stress gradients. Given that direct measurements of longevity are inevitably biased due to the presence of this variation and ongoing selection, we propose the use of the trend itself for obtaining more exact inferences of genotypic fitness. Second, we show how species or strain coexistence can be enabled by nonheritable variation in longevity or viability. These general conclusions are likely to extend beyond bacterial systems.

Adaptive responses of animals to climate change are most likely insufficient

Biological responses to climate change have been widely documented across taxa and regions, but it remains unclear whether species are maintaining a good match between phenotype and environment, i.e. whether observed trait changes are adaptive. Here we reviewed 10,090 abstracts and extracted data from 71 studies reported in 58 relevant publications, to assess quantitatively whether phenotypic trait changes associated with climate change are adaptive in animals. A meta-analysis focussing on birds, the taxon best represented in our dataset, suggests that global warming has not systematically affected morphological traits, but has advanced phenological traits. We demonstrate that these advances are adaptive for some species, but imperfect as evidenced by the observed consistent selection for earlier timing. Application of a theoretical model indicates that the evolutionary load imposed by incomplete adaptive responses to ongoing climate change may already be threatening the persistence of species.

It is unclear whether species’ responses to climate change tend to be adaptive or sufficient to keep up with climate change. Here, Radchuk et al. perform a meta-analysis showing that in birds phenology has advanced adaptively in some species, though not all the way to the new optima.

Why So Variable: Can Genetic Variance in Flowering Thresholds Be Maintained by Fluctuating Selection?

We use integral projection models (IPMs) and individual-based simulations to study the evolution of genetic variance in two monocarpic plant systems. Previous approaches combining IPMs with an adaptive dynamics-style invasion analysis predicted that genetic variability in the size threshold for flowering will not be maintained, which conflicts with empirical evidence. We ask whether this discrepancy can be resolved by making more realistic assumptions about the underlying genetic architecture, assuming a multilocus quantitative trait in an outcrossing diploid species. To do this, we embed the infinitesimal model of quantitative genetics into an IPM for a size-structured cosexual plant species. The resulting IPM describes the joint dynamics of individual size and breeding value of the evolving trait. We apply this general framework to the monocarpic perennials Oenothera glazioviana and Carlina vulgaris. The evolution of heritable variation in threshold size is explored in both individual-based models (IBMs) and IPMs, using a mutation rate modifier approach. In the Oenothera model, where the environment is constant, there is selection against producing genetically variable offspring. In the Carlina model, where the environment varies between years, genetically variable offspring provide a selective advantage, allowing the maintenance of genetic variability. The contrasting predictions of adaptive dynamics and quantitative genetics models for the same system suggest that fluctuating selection may be more effective at maintaining genetic variation than previously thought.

Remodeling Ancestral Phenotypic Plasticity in Local Adaptation: A New Framework to Explore the Role of Genetic Compensation in the Evolution of Homeostasis

Phenotypic plasticity is not universally adaptive. In certain cases, plasticity can result in phenotypic shifts that reduce fitness relative to the un-induced state. A common cause of such maladaptive plasticity is the co-option of ancestral developmental and physiological response systems to meet novel challenges. Because these systems evolved to meet specific challenges in an ancestral environment (e.g., localized and transient hypoxia), their co-option to meet a similar, but novel, stressor (e.g., reductions in ambient pO2 at high elevation) can lead to misdirected responses that reduce fitness. In such cases, natural selection should act to remodel phenotypic plasticity to suppress the expression of these maladaptive responses. Because these maladaptive responses reduce the fitness of colonizers in new environments, this remodeling of ancestral plasticity may be among the earliest steps in adaptive walks toward new local optima. Genetic compensation has been proposed as a general form of adaptive evolution that leads to the suppression of maladaptive plasticity to restore the ancestral trait value in the face of novel stimuli. Given their central role in the regulation of basic physiological functions, we argue that genetic compensation may often be achieved by modifications of homeostatic regulatory systems. We further suggest that genetic compensation to modify homeostatic systems can be achieved by two alternative strategies that differ in their mechanistic underpinnings; to our knowledge, these strategies have not been formally recognized by previous workers. We then consider how the mechanistic details of these alternative strategies may constrain their evolution. These considerations lead us to argue that genetic compensation is most likely to evolve by compensatory physiological changes that safeguard internal homeostatic conditions to prevent the expression of maladaptive portions of conserved reaction norms, rather than direct evolution of plasticity itself. Finally, we outline a simple experimental framework to test this hypothesis. Our goal is to stimulate research aimed at providing a deeper mechanistic understanding of whether and how phenotypic plasticity can be remodeled following environmental shifts that render ancestral responses maladaptive, an issue with increasing importance in our current era of rapid environmental change.

Trait-based predictions and responses from laboratory mite populations to harvesting in stochastic environments

Predictions on population responses to perturbations are often derived from trait-based approaches like integral projection models (IPMs), but are rarely tested. IPMs are constructed from functions that describe survival, growth and reproduction in relation to the traits of individuals and their environment. Although these functions comprise biologically non-informative statistical coefficients within standard IPMs, model parameters of the recently developed dynamic energy budget IPM (DEB-IPM) are life-history traits like "length at maturation" and "maximum reproduction rate". Testing predictions from mechanistic IPMs against empirical observations can therefore provide functional insights into the links between individual life history, the environment and population dynamics. Here, we compared the population dynamics of the bulb mite (Rhizoglyphus robini) predicted by a DEB-IPM with those observed in an experiment where populations experienced daily food rations that were either positively correlated over time (red noise), negatively (blue noise) or uncorrelated (white noise). We also selectively harvested large adults in half of these populations. The model failed to generate detailed predictions of population structure as juvenile numbers were overestimated; likely because juvenile-adult interference competition was underestimated. The model performed well at the population level as, for both harvested and unharvested populations, simulations matched the observed, long-term stochastic growth rate λ_s . We next generalised the model to investigate how stochastic change affects mite λ_s , which correlated well with the frequency f of experiencing periods of good environment, but, due to the relationship between f and noise colour ρ, did not correlate well with shifts in ρ. The sensitivity of λ_s to perturbations in life-history parameters depended on the type of stochastic change, as well as population growth. Our findings show that responses to differential mortality depend on individual life-history traits, environmental characteristics and population growth. As long-term climate change causes ever greater environmental fluctuations, trait-based approaches will be increasingly important in predicting population responses to change. We therefore conclude by illustrating what questions can be examined with mechanistic trait-based models like the DEB-IPM, the answers to which will advance our knowledge of the functional links between individual traits, the environment and population dynamics.

Geographic variation in thermal sensitivity of early life traits in a widespread reptile

Taxa with large geographic distributions generally encompass diverse macroclimatic conditions, potentially requiring local adaptation and/or phenotypic plasticity to match their phenotypes to differing environments. These eco-evolutionary processes are of particular interest in organisms with traits that are directly affected by temperature, such as embryonic development in oviparous ectotherms. Here we examine the spatial distribution of fitness-related early life phenotypes across the range of a widespread vertebrate, the painted turtle (Chrysemys picta). We quantified embryonic and hatchling traits from seven locations (in Idaho, Minnesota, Oregon, Illinois, Nebraska, Kansas, and New Mexico) after incubating eggs under constant conditions across a series of environmentally relevant temperatures. Thermal reaction norms for incubation duration and hatchling mass varied among locations under this common-garden experiment, indicating genetic differentiation or pre-ovulatory maternal effects. However, latitude, a commonly used proxy for geographic variation, was not a strong predictor of these geographic differences. Our findings suggest that this macroclimatic proxy may be an unreliable surrogate for microclimatic conditions experienced locally in nests. Instead, complex interactions between abiotic and biotic factors likely drive among-population phenotypic variation in this system. Understanding spatial variation in key life-history traits provides an important perspective on adaptation to contemporary and future climatic conditions.

A comparison of stable and fluctuating resources with respect to evolutionary adaptation and life-history traits using individual-based modeling and machine learning

There are three non-mutually-exclusive key strategies evolved by gene pools to cope with fluctuating food resource availability, including evolutionary adaptation, phenotypic plasticity, and migration. We focus primarily on evolutionary adaptation and behavioral plasticity, which is a type of phenotypic plasticity, resulting in life-history changes as ways of dealing with fluctuations in food resource availability. Using EcoSim, a predator-prey individual-based model, we compare individuals with stable food resources with those in environments where there are fluctuating food resources in terms of adaptation through behavioral plasticity and evolution. The purpose of our study is to determine whether evolution and behavioral plasticity truly play a role in adapting to an environment with fluctuating food resources, as well as to determine whether there are specific gene divergences between gene pools in fluctuating food resource environments versus gene pools where food resources are relatively stable. An important result of our study is that individuals in environments that are unstable with respect to food resource availability exhibited significant differences in behaviors versus those in environments with stable food resources. Although behavioral plasticity facilitates a rapid response to unstable food conditions, our study revealed the evolution of perceptual traits such as vision range in reaction to fluctuating food resources, indicating the importance of evolution in adapting to unstable resource environments in the long run. Moreover, using decision trees, we found that there were significant behavioral gene divergences between individuals in environments with fluctuating food resources as opposed to individuals in environments with stable food resources.

Maladaptive phenotypic plasticity in cardiac muscle growth is suppressed in high-altitude deer mice

How often phenotypic plasticity acts to promote or inhibit adaptive evolution is an ongoing debate among biologists. Recent work suggests that adaptive phenotypic plasticity promotes evolutionary divergence, though several studies have also suggested that maladaptive plasticity can potentiate adaptation. The role of phenotypic plasticity, adaptive, or maladaptive, in evolutionary divergence remains controversial. We examined the role of plasticity in evolutionary divergence between two species of Peromyscus mice that differ in native elevations. We used cardiac mass as a model phenotype, since ancestral hypoxia-induced responses of the heart may be both adaptive and maladaptive at high-altitude. While left ventricle growth should enhance oxygen delivery to tissues, hypertrophy of the right ventricle can lead to heart failure and death. We compared left- and right-ventricle plasticity in response to hypoxia between captive-bred P. leucopus (representing the ancestral lowland condition) and P. maniculatus from high-altitude. We found that maladaptive ancestral plasticity in right ventricle hypertrophy is reduced in high-altitude deer mice. Analysis of the heart transcriptome suggests that changes in expression of inflammatory signaling genes, particularly interferon regulatory factors, contribute to the suppression of right ventricle hypertrophy. We found weak evidence that adaptive plasticity of left ventricle mass contributes to evolution. Our results suggest that selection to suppress ancestral maladaptive plasticity plays a role in adaptation.

An eco-evolutionary feedback loop between population dynamics and fighter expression affects the evolution of alternative reproductive tactics

Surprisingly, little is known about how eco‐evolutionary feedback loops affect trait dynamics within a single population. Polymorphisms of discrete alternative phenotypes present ideal test beds to investigate this, as the alternative phenotypes typically exhibit contrasting demographic rates mediated through frequency or density dependence, and are thus differentially affected by selection.

Alternative reproductive tactics (ARTs), like male fighters and sneakers, are an extreme form of discrete phenotype expression and occur across many taxa. Fighters possess weapons for male–male competition over access to mates, whereas sneakers are defenceless but adopt tactics like female‐mimicking. Because fighters in some species mortally injure conspecifics, this raises the question whether fighter expression can feed back to affect population size and structure, thereby altering the selection gradient and evolutionary dynamics of ART expression in an eco‐evolutionary feedback loop.

Here, we investigated how the eco‐evolutionary feedback loop between fighter expression and population size and structure affects the evolution and maintenance of ARTs. We introduced intraspecific killing by fighters in a two‐sex, two‐ART population model parameterized for the male dimorphic bulb mite (Rhizoglyphus robini) that includes life‐history differences between the ARTs and a mating‐probability matrix analogous to the classic hawk–dove game.

Using adaptive dynamics, we found that the intraspecific killing by fighters can extend the range of life‐history parameter values under which ARTs evolve, because fighters that kill other fighters decrease fighter fitness. This effect can be nullified when benefits from killing are incorporated, like increased reproduction through increased energy uptake.

The eco‐evolutionary feedback effects found here for a dimorphic trait likely also occur in other fitness‐related traits, such as behavioural syndromes, parental care and niche construction traits. Current theoretical advances to model eco‐evolutionary processes, and empirical steps towards unravelling the underlying drivers, pave the way for understanding how selection affects trait evolution in an eco‐evolutionary feedback loop.