An evolutionary tipping point in a changing environment

Evolution between two competing macrophyte populations along a resource gradient leads to collapse in a bistable lake ecosystem

While it is known that shallow lake ecosystems may experience abrupt shifts (ie tipping points) from a clear water state to a contrasting turbid alternative state as a result of eutrophication, the role of evolutionary processes and the impact of trait variation in this context remain largely unexplored. It is crucial to elucidate how eco-evolutionary feedbacks affect abrupt ecological transitions in shallow lakes and more in general in bistable ecosystems. These feedbacks can significantly alter the dynamics of aquatic plants competition, community structure, and species diversity, potentially affecting the existence of alternative states or either delay or expedite the thresholds at which these ecological shifts occur. In this paper, we explore the eco-evolutionary dynamics of submerged and floating macrophytes in a shallow lake ecosystem under asymmetric competition for nutrients and light along a gradient of nutrient diffusion. We use Adaptive Dynamics and a structured population model to analyze the evolution of the growth depth of the submerged and floating macrophytes populations, which influences their competitive ability for the two resources. We show how trait evolution can result in complex dynamics including evolutionary oscillations, extensive diversification and evolutionary suicide. Furthermore, we find that the co-evolution of the two competing populations plays a stabilizing role, but does not significantly alter the dynamics compared to when only one of the two populations is evolving. Overall, our study contributes to the understanding of the effects of evolution on the ecological dynamics of bistable ecosystems.

Transcriptomic reaction norms highlight metabolic depression as a divergence in phenotypic plasticity between oyster species under ocean acidification

Ocean acidification is occurring at a rate unprecedented for millions of years, forcing sessile organisms, such as oysters, to respond in the short term by relying on their phenotypic plasticity. But phenotypic plasticity has limits, tipping points, beyond which species will have to adapt or disappear. These limits could be related to the adaptation of species to different habitat variabilities. Here, we exposed juvenile pearl oysters, Pinctada margaritifera, to a broad pH range and determined the response at the gross physiological, lipidome and transcriptome levels. Thus, we identified its high tolerance with low pH tipping points at pH 7.3-6.8 below which most physiological parameters are impacted. We then compared the transcriptomic reaction norms of the tropical subtidal P. margaritifera with those of an intertidal temperate oyster, Crassostrea gigas, reusing data from a previous study. Despite showing similar tipping points to C. gigas, P. margaritifera exhibits strong mortality and depletion of energy reserves below these tipping points, which is not the case for C. gigas. This divergence relies mainly on the induction of metabolic depression, an adaptation to intertidal habitats in C. gigas but not P. margaritifera. Our method makes it possible to detect divergence in phenotypic plasticity, probably linked to the species' specific life-history strategies related to different habitats, which will determine the survival of species in the face of ongoing global changes. Such an approach is particularly relevant for studying the physiology of species in a world where physiological tipping points will increasingly be exceeded.

Impacts of limits to adaptation on population and community persistence in a changing environment

A key issue in predicting how ecosystems will respond to environmental change is understanding why populations and communities are able to live and reproduce in some parts of ecological and geographical space, but not in others. The limits to adaptation that cause ecological niches to vary in position and width across taxa and environmental contexts determine how communities and ecosystems emerge from selection on phenotypes and genomes. Ecological trade-offs mean that phenotypes can only be optimal in some environments unless these trade-offs can be reshaped through evolution. However, the amount and rate of evolution are limited by genetic architectures, developmental systems (including phenotypic plasticity) and the legacies of recent evolutionary history. Here, we summarize adaptive limits and their ecological consequences in time (evolutionary rescue) and space (species' range limits), relating theoretical predictions to empirical tests. We then highlight key avenues for future research in this area, from better connections between evolution and demography to analysing the genomic architecture of adaptation, the dynamics of plasticity and interactions between the biotic and abiotic environment. Progress on these questions will help us understand when and where evolution and phenotypic plasticity will allow species and communities to persist in the face of rapid environmental change.This article is part of the discussion meeting issue 'Bending the curve towards nature recovery: building on Georgina Mace's legacy for a biodiverse future'.

Evolutionary Adaptation in Heterogeneous and Changing Environments

Organisms that are adapting to long-term environmental change almost always deal with multiple environments and trade-offs that affect their optimal phenotypic strategy. Here, we combine the idea of repeated variation or heterogeneity, like seasonal shifts, with long-term directional dynamics. Using the framework of fitness sets, we determine the dynamics of the optimal phenotype in two competing environments encountered with different frequencies, one of which changes with time. When such an optimal strategy is selected for in simulations of evolving populations, we observe rich behavior that is qualitatively different from and more complex than adaptation to long-term change in a single environment. The probability of survival and the critical rate of environmental change above which populations go extinct depend crucially on the relative frequency of the two environments and the strength and asymmetry of their selection pressures. We identify a critical frequency for the stationary environment, above which populations can escape the pressure to constantly evolve by adapting to the stationary optimum. In the neighborhood of this critical frequency, we also find the counter-intuitive possibility of a lower bound on the rate of environmental change, below which populations go extinct, and above which a process of evolutionary rescue is possible.

Intra-specific diversity and adaptation modify regime shifts dynamics under environmental change

Environmental changes are a growing concern, as they exert pressures on ecosystems. In some cases, such changes lead to shifts in ecosystem structure. However, species can adapt to changes through evolution, and it is unclear how evolution interacts with regime shifts, which restricts ecosystem management strategies. Here, we used a model of prey population with evolution and intra-specific trait diversity, and simulated regime shifts through changes in predation pressure. We then explored interactions between evolution, diversity, and shifts in population density. Evolution induced delayed or early regime shifts, and altered the recovery of populations. Such changes depended on the relative speed of evolution and change of predation pressure, as well as on the initial state of the population. Evolution also influenced population resilience, which was important when considering strong environmental variability. For instance, storms can spontaneously increase mortality and induce shifts. Furthermore, environmental variability induced even higher mortality if the phenotypic diversity of populations is large. Some phenotypes were more vulnerable to environmental changes, and such increases in mortality favor shifts to decreases in density. Thus, population management needs to consider diversity, evolution, and environmental change altogether to better anticipate regime shifts on eco-evolutionary time scales. Here, evolution and diversity showed complex interactions with population shift dynamics. Investigating the influence of higher diversity levels, such as diversity at a community level, should be another step towards anticipating changes in ecosystems and communities.

Sharp habitat shifts, evolutionary tipping points and rescue: Quantifying the perilous path of a specialist species towards a refugium in a changing environment

Specialist species thriving under specific environmental conditions in narrow geographic ranges are widely recognized as heavily threatened by climate deregulation. Many might rely on both their potential to adapt and to disperse towards a refugium to avoid extinction. It is thus crucial to understand the influence of environmental conditions on the unfolding process of adaptation. Here, I study the eco-evolutionary dynamics of a sexually reproducing specialist species in a two-patch quantitative genetic model with moving optima. Thanks to a separation of ecological and evolutionary time scales and the phase-line study of the selection gradient, I derive the critical environmental speed for persistence, which reflects how the existence of a refugium impacts extinction patterns and how it relates to the cost of dispersal. Moreover, the analysis provides key insights about the dynamics that arise on the path towards this refugium. I show that after an initial increase of population size, there exists a critical environmental speed above which the species crosses a tipping point, resulting into an abrupt habitat switch. In addition, when selection for local adaptation is strong, this habitat switch passes through an evolutionary "death valley", leading to a phenomenon related to evolutionary rescue, which can promote extinction for lower environmental speeds than the critical one.

Demographic feedbacks during evolutionary rescue can slow or speed adaptive evolution

Populations declining toward extinction can persist via genetic adaptation in a process called evolutionary rescue. Predicting evolutionary rescue has applications ranging from conservation biology to medicine, but requires understanding and integrating the multiple effects of a stressful environmental change on population processes. Here we derive a simple expression for how generation time, a key determinant of the rate of evolution, varies with population size during evolutionary rescue. Change in generation time is quantitatively predicted by comparing how intraspecific competition and the source of maladaptation each affect the rates of births and deaths in the population. Depending on the difference between two parameters quantifying these effects, the model predicts that populations may experience substantial changes in their rate of adaptation in both positive and negative directions, or adapt consistently despite severe stress. These predictions were then tested by comparison to the results of individual-based simulations of evolutionary rescue, which validated that the tolerable rate of environmental change varied considerably as described by analytical results. We discuss how these results inform efforts to understand wildlife disease and adaptation to climate change, evolution in managed populations and treatment resistance in pathogens.

Schrödinger's Range-Shifting Cat: How Skewed Temperature Dependence Impacts Persistence with Climate Change

AbstractThe majority of species display strongly asymmetric responses to climatic variables, yet most analytic models used to investigate how species will respond to climate change assume symmetric responses, with largely unknown consequences. Applying a known mapping of population dynamical equations onto corresponding well-studied problems from quantum mechanics, we extend analytical results to incorporate this asymmetry. We derive expressions in terms of parameters representing climate velocity, dispersal rate, maximum growth rate, niche width, high-frequency climate variability, and environmental performance curve skew for three key responses: (1) population persistence, (2) lag between range displacement and climate displacement, and (3) location of maximum population sensitivity. We find that asymmetry impacts these climate change responses, but surprisingly, under our model assumptions, the direction (i.e., warm skewed or cool skewed) of performance curve asymmetry does not strongly contribute to either persistence or lags. Conservation measures to support range-shifting populations may have most benefit near their environmental optimum or where the environmental dependence is shallow, irrespective of whether this is the leading or trailing edge. A metapopulation simulation corroborates our results. Our results shed fresh light on how key features of a species' environmental performance curve can impact its response to climate change.

Stochastic resonance in climate reddening increases the risk of cyclic ecosystem extinction via phase-tipping

Human activity is leading to changes in the mean and variability of climatic parameters in most locations around the world. The changing mean has received considerable attention from scientists and climate policy makers. However, recent work indicates that the changing variability, that is, the amplitude and the temporal autocorrelation of deviations from the mean, may have greater and more imminent impact on ecosystems. In this paper, we demonstrate that changes in climate variability alone could drive cyclic predator-prey ecosystems to extinction via so-called phase-tipping (P-tipping), a new type of instability that occurs only from certain phases of the predator-prey cycle. We construct a mathematical model of a variable climate and couple it to two self-oscillating paradigmatic predator-prey models. Most importantly, we combine realistic parameter values for the Canada lynx and snowshoe hare with actual climate data from the boreal forest. In this way, we demonstrate that critically important species in the boreal forest have increased likelihood of P-tipping to extinction under predicted changes in climate variability, and are most vulnerable during stages of the cycle when the predator population is near its maximum. Furthermore, our analysis reveals that stochastic resonance is the underlying mechanism for the increased likelihood of P-tipping to extinction.

Adaptation of a quantitative trait to a changing environment: New analytical insights on the asexual and infinitesimal sexual models

Predicting the adaptation of populations to a changing environment is crucial to assess the impact of human activities on biodiversity. Many theoretical studies have tackled this issue by modeling the evolution of quantitative traits subject to stabilizing selection around an optimal phenotype, whose value is shifted continuously through time. In this context, the population fate results from the equilibrium distribution of the trait, relative to the moving optimum. Such a distribution may vary with the shape of selection, the system of reproduction, the number of loci, the mutation kernel or their interactions. Here, we develop a methodology that provides quantitative measures of population maladaptation and potential of survival directly from the entire profile of the phenotypic distribution, without any a priori on its shape. We investigate two different systems of reproduction (asexual and infinitesimal sexual models of inheritance), with various forms of selection. In particular, we recover that fitness functions such that selection weakens away from the optimum lead to evolutionary tipping points, with an abrupt collapse of the population when the speed of environmental change is too high. Our unified framework allows deciphering the mechanisms that lead to this phenomenon. More generally, it allows discussing similarities and discrepancies between the two systems of reproduction, which are ultimately explained by different constraints on the evolution of the phenotypic variance. We demonstrate that the mean fitness in the population crucially depends on the shape of the selection function in the infinitesimal sexual model, in contrast with the asexual model. In the asexual model, we also investigate the effect of the mutation kernel and we show that kernels with higher kurtosis tend to reduce maladaptation and improve fitness, especially in fast changing environments.

Life history and the evolutionary loss of parental care

Parental care has been gained and lost evolutionarily multiple times. While many studies have focused on the origin of care, few have explored the evolutionary loss of care. Understanding the loss of parental care is important as the conditions that favour its loss will not necessarily be the opposite of those that favour the evolution of care. Evolutionary hysteresis (the case in which evolution depends on the history of a system) could create a situation in which it is relatively challenging to lose care once it has evolved. Here, using a mathematical approach, we explore the evolutionary loss of parental care in relation to basic life-history conditions. Our results suggest that parental care is most likely to be lost when egg and adult death rates are low, eggs mature quickly, and the level of care provided is high. We also predict evolutionary hysteresis with respect to egg maturation rate: as egg maturation rate decreases, it becomes increasingly more costly to lose care than to gain it. This suggests that once care is present, it will be particularly challenging for it to be lost if eggs develop slowly.

Writing Accessible Theory in Ecology and Evolution: Insights from Cognitive Load Theory

Theories underpin science. In biology, theories are often formalized in the form of mathematical models, which may render them inaccessible to those lacking mathematical training. In the present article, we consider how theories could be presented to better aid understanding. We provide concrete recommendations inspired by cognitive load theory, a branch of psychology that addresses impediments to knowledge acquisition. We classify these recommendations into two classes: those that increase the links between new and existing information and those that reduce unnecessary or irrelevant complexities. For each, we provide concrete examples to illustrate the scenarios in which they apply. By enhancing a reader's familiarity with the material, these recommendations lower the mental capacity required to learn new information. Our hope is that these recommendations can provide a pathway for theoreticians to increase the accessibility of their work and for empiricists to engage with theory, strengthening the feedback between theory and experimentation.

Evolution reverses the effect of network structure on metapopulation persistence

Global environmental change is challenging species with novel conditions, such that demographic and evolutionary trajectories of populations are often shaped by the exchange of organisms and alleles across landscapes. Current ecological theory predicts that random networks with dispersal shortcuts connecting distant sites can promote persistence when there is no capacity for evolution. Here, we show with an eco‐evolutionary model that dispersal shortcuts across environmental gradients instead hinder persistence for populations that can evolve because long‐distance migrants bring extreme trait values that are often maladaptive, short‐circuiting the adaptive response of populations to directional change. Our results demonstrate that incorporating evolution and environmental heterogeneity fundamentally alters theoretical predictions regarding persistence in ecological networks.

Models for Eco-Evolutionary Extinction Vortices under Balancing Selection

AbstractThe smaller a population is, the faster it loses genetic diversity as a result of genetic drift. Loss of genetic diversity can reduce population growth rate, making populations even smaller and more vulnerable to loss of genetic diversity. Ultimately, the population can be driven to extinction by this "eco-evolutionary extinction vortex." While there are already quantitative models for extinction vortices resulting from inbreeding depression and mutation accumulation, to date extinction vortices resulting from loss of genetic diversity at loci under various forms of balancing selection have been mainly described verbally. To understand better when such extinction vortices arise and to develop methods for detecting them, we propose quantitative eco-evolutionary models, both stochastic individual-based simulations and deterministic approximations, linking loss of genetic diversity and population decline. Using mathematical analysis and simulations, we identify parameter combinations that exhibit strong interactions between population size and genetic diversity and match our definition of an eco-evolutionary vortex (i.e., per capita population decline rates and per-locus fixation rates increase with decreasing population size and number of polymorphic loci). We further highlight cues that may be exhibited by such populations but find that classical early-warning signals are of limited use in detecting populations undergoing an eco-evolutionary extinction vortex.

Ecological limits to evolutionary rescue

Environments change, for both natural and anthropogenic reasons, which can threaten species persistence. Evolutionary adaptation is a potentially powerful mechanism to allow species to persist in these changing environments. To determine the conditions under which adaptation will prevent extinction (evolutionary rescue), classic quantitative genetics models have assumed a constantly changing environment. They predict that species traits will track a moving environmental optimum with a lag that approaches a constant. If fitness is negative at this lag, the species will go extinct. There have been many elaborations of these models incorporating increased genetic realism. Here, we review and explore the consequences of four ecological complications: non-quadratic fitness functions, interacting density- and trait-dependence, species interactions and fundamental limits to adaptation. We show that non-quadratic fitness functions can result in evolutionary tipping points and existential crises, as can the interaction between density- and trait-dependent mortality. We then review the literature on how interspecific interactions affect adaptation and persistence. Finally, we suggest an alternative theoretical framework that considers bounded environmental change and fundamental limits to adaptation. A research programme that combines theory and experiments and integrates across organizational scales will be needed to predict whether adaptation will prevent species extinction in changing environments. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.

Cooperation can promote rescue or lead to evolutionary suicide during environmental change

The adaptation of populations to changing conditions may be affected by interactions between individuals. For example, when cooperative interactions increase fecundity, they may allow populations to maintain high densities and thus keep track of moving environmental optima. Simultaneously, changes in population density alter the marginal benefits of cooperative investments, creating a feedback loop between population dynamics and the evolution of cooperation. Here we model how the evolution of cooperation interacts with adaptation to changing environments. We hypothesize that environmental change lowers population size and thus promotes the evolution of cooperation, and that this, in turn, helps the population keep up with the moving optimum. However, we find that the evolution of cooperation can have qualitatively different effects, depending on which fitness component is reduced by the costs of cooperation. If the costs decrease fecundity, cooperation indeed speeds adaptation by increasing population density; if, in contrast, the costs decrease viability, cooperation may instead slow adaptation by lowering the effective population size, leading to evolutionary suicide. Thus, cooperation can either promote or-counterintuitively-hinder adaptation to a changing environment. Finally, we show that our model can also be generalized to other social interactions by discussing the evolution of competition during environmental change.

The conflict between adaptation and dispersal for maintaining biodiversity in changing environments

Dispersal and adaptation both allow species to persist in changing environments. Yet, we have limited understanding of how these processes interact to affect species persistence, especially in diverse communities where biotic interactions greatly complicate responses to environmental change. Here we use a stochastic metacommunity model to demonstrate how dispersal and adaptation to environmental change independently and interactively contribute to biodiversity maintenance. Dispersal provides spatial insurance, whereby species persist on the landscape by shifting their distributions to track favorable conditions. In contrast, adaptation allows species to persist by allowing for evolutionary rescue. But, when species both adapt and disperse, dispersal and adaptation do not combine positively to affect biodiversity maintenance, even if they do increase the persistence of individual species. This occurs because faster adapting species evolve to hold onto their initial ranges (i.e., monopolization effects), thus impeding slower adapting species from shifting their ranges and thereby causing extinctions. Importantly, these differences in adaptation speed emerge as the result of competition, which alters population sizes and colonization success. By demonstrating how dispersal and adaptation each independently and interactively contribute to the maintenance of biodiversity, we provide a framework that links the theories of spatial insurance, evolutionary rescue, and monopolization. This highlights the expectation that the maintenance of biodiversity in changing environments depends jointly on rates of dispersal and adaptation, and, critically, the interaction between these processes.

Evolutionary Hysteresis and Ratchets in the Evolution of Periodical Cicadas

It has been previously hypothesized that the perfectly synchronized mass emergence of periodical cicadas (Magicicada spp.) evolved as a result of a switch from size-based to age-based emergence. In the former case, cicada nymphs emerge immediately (at the first opportunity) on reaching maturity, whereas in the latter case, nymphs wait in order to emerge at a specific age. Here we use an individual-based model to simulate the cicada life cycle and to study the evolution of periodicity. We find that if age-based emergence evolves in a constant abiotic environment, it typically results in a population that is protoperiodic, and synchronous emergence of the whole population is not achieved. However, perfect periodicity and synchronous emergence can be attained, if the abiotic environment changes back and forth between favorable and unfavorable conditions (hysteresis). Furthermore, once age-based emergence evolves, generally it can only be invaded by other age-based emergence strategies with longer cycle lengths (evolutionary ratchet). Together, these mechanisms promote the evolution of long periodic life cycles and synchronous emergence in the Magicicada. We discuss how our results connect to previous theories and recent phylogenetic studies on Magicicada evolution.