Form of an evolutionary tradeoff affects eco-evolutionary dynamics in a predator-prey system

Long-term studies provide unique insights into evolution

From experimental evolution in the laboratory to sustained measurements of natural selection in the wild, long-term studies have revolutionized our understanding of evolution. By directly investigating evolutionary dynamics in real time, these approaches have provided unparallelled insights into the complex interplay between evolutionary process and pattern. These approaches can reveal oscillations, stochastic fluctuations and systematic trends that unfold over extended periods, expose critical time lags between environmental shifts and population responses, and illuminate how subtle effects may accumulate into significant evolutionary patterns. Long-term studies can also reveal otherwise cryptic trends that unfold over extended periods, and offer the potential for serendipity: observing rare events that spur new evolutionary hypotheses and research directions. Despite the challenges of conducting long-term research, exacerbated by modern funding landscapes favouring short-term projects, the contributions of long-term studies to evolutionary biology are indispensable. This is particularly true in our rapidly changing, human-dominated world, where such studies offer a crucial window into how environmental changes and altered species interactions shape evolutionary trajectories. In this Review article, we showcase the groundbreaking discoveries of long-term evolutionary studies, underscoring their crucial role in advancing our understanding of the complex nature of evolution across multiple systems and timescales.

Trade-offs between defense and competitive traits in a planktonic predator-prey system

Predator-prey interactions are crucial components of populations and communities. Their dynamics depend on the covariation of traits of the interacting organisms, and there is increasing evidence that intraspecific trade-off relationships between defense and competitive traits are important drivers of trophic interactions. However, quantifying the relevant traits forming defense-competitiveness trade-offs and how these traits determine prey and predator fitness remains a major challenge. Here, we conducted feeding and growth experiments to assess multiple traits related to defense and competitiveness in six different strains of the green alga Chlamydomonas reinhardtii exposed to predation by the rotifer Brachionus calyciflorus. We found large differences in defense and competitive traits among prey strains and negative relationships between these traits for multiple trait combinations. Because we compared trait differences among strains whose ancestors evolved previously in controlled environments where selection favored either defense or competitiveness, these negative correlations suggest the presence of a trade-off between defense and competitiveness. These differences in traits and trade-offs translated into differences in prey and predator fitness, demonstrating the importance of intraspecific trade-offs in predicting the outcome of predator-prey interactions.

Community Trait Variation Drives Selection on Species Diversity Through Feedback With Predator Density

Identifying the processes underlying community assembly and dynamics remains a central goal in ecology. Although much research has been devoted to analyzing how environments affect species diversity, fewer studies have resolved the link between the fundamental process of ecological selection and species diversity. It has been suggested that identifying ecological selection by estimating changes in community-weighted variance (CWV) and mean (CWM) of functional traits may help to identify more general rules of community assembly. Here, we asked whether and how selection by predation and competition affect species diversity, and how this is determined by the initial CWV and CWM for traits governing species interactions, as in our case: Competitiveness and defense against a predator. We tracked experimental five-species phytoplankton communities in the presence and absence of a rotifer predator over time. We manipulated the initial community composition so that communities shared at least three of the five species but differed in CWV and CWM for defense against predation. We found that species diversity was highest with higher initial trait distributions and that temporal changes in diversity correlated with trait selection. The initial distributions determined the form of selection over time, with directional selection for defense and competitiveness, followed by reduced selection and an increase in niche availability when the initial trait distribution was low or high. For intermediate initial trait distributions, we observed directional selection in only one trait, followed by stabilizing selection. Differences and changes in selection for defense, competitiveness, and species diversity correlated with the changes in predator density over time. This suggests that the initial trait distribution determined species diversity through a feedback loop with changes in selection on traits and predator density. Overall, our study shows that identifying ecological selection on functional traits can provide a mechanistic understanding of community assembly.

Range of trait variation in prey determines evolutionary contributions to predator growth rates

Evolutionary and ecological dynamics can occur on similar timescales and thus influence each other. While it has been shown that the relative contribution of ecological and evolutionary change to population dynamics can vary, it still remains unknown what influences these differences. Here, we test whether prey populations with increased variation in their defence and competitiveness traits will have a stronger impact on evolution for predator growth rates. We controlled trait variation by pairing distinct clonal lineages of the green alga Chlamydomonas reinhardtii with known traits as prey with the rotifer Brachionus calyciforus as predator and compared those results with a mechanistic model matching the empirical system. We measured the impact of evolution (shift in prey clonal frequency) and ecology (shift in prey population density) for predator growth rate and its dependency on trait variation using an approach based on a 2-way ANOVA. Our experimental results indicated that higher trait variation, i.e., a greater distance in trait space, increased the relative contribution of prey evolution to predator growth rate over 3-4 predator generations, which was also observed in model simulations spanning longer time periods. In our model, we also observed clone-specific results, where a more competitive undefended prey resulted in a higher evolutionary contribution, independent of the trait distance. Our results suggest that trait combinations and total prey trait variation combine to influence the contribution of evolution to predator population dynamics, and that trait variation can be used to identify and better predict the role of eco-evolutionary dynamics in predator-prey systems.

Predation drives complex eco-evolutionary dynamics in sexually selected traits

Predation plays a role in preventing the evolution of ever more complicated sexual displays, because such displays often increase an individual's predation risk. Sexual selection theory, however, omits a key feature of predation in modeling costs to sexually selected traits: Predation is density dependent. As a result of this density dependence, predator-prey dynamics should feed back into the evolution of sexual displays, which, in turn, feeds back into predator-prey dynamics. Here, we develop both population and quantitative genetic models of sexual selection that explicitly link the evolution of sexual displays with predator-prey dynamics. Our primary result is that predation can drive eco-evolutionary cycles in sexually selected traits. We also show that mechanistically modeling the cost to sexual displays as predation leads to novel outcomes such as the maintenance of polymorphism in sexual displays and alters ecological dynamics by muting prey cycles. These results suggest predation as a potential mechanism to maintain variation in sexual displays and underscore that short-term studies of sexual display evolution may not accurately predict long-run dynamics. Further, they demonstrate that a common verbal model (that predation limits sexual displays) with widespread empirical support can result in unappreciated, complex dynamics due to the density-dependent nature of predation.

The role of mathematical modelling in understanding prokaryotic predation

With increasing levels of antimicrobial resistance impacting both human and animal health, novel means of treating resistant infections are urgently needed. Bacteriophages and predatory bacteria such as Bdellovibrio bacteriovorus have been proposed as suitable candidates for this role. Microbes also play a key environmental role as producers or recyclers of nutrients such as carbon and nitrogen, and predators have the capacity to be keystone species within microbial communities. To date, many studies have looked at the mechanisms of action of prokaryotic predators, their safety in in vivo models and their role and effectiveness under specific conditions. Mathematical models however allow researchers to investigate a wider range of scenarios, including aspects of predation that would be difficult, expensive, or time-consuming to investigate experimentally. We review here a history of modelling in prokaryote predation, from simple Lotka-Volterra models, through increasing levels of complexity, including multiple prey and predator species, and environmental and spatial factors. We consider how models have helped address questions around the mechanisms of action of predators and have allowed researchers to make predictions of the dynamics of predator-prey systems. We examine what models can tell us about qualitative and quantitative commonalities or differences between bacterial predators and bacteriophage or protists. We also highlight how models can address real-world situations such as the likely effectiveness of predators in removing prey species and their potential effects in shaping ecosystems. Finally, we look at research questions that are still to be addressed where models could be of benefit.

Evolution of population dynamics following invasion by a non-native predator

Invasive predatory species are frequently observed to cause evolutionary responses in prey phenotypes, which in turn may lead to evolutionary shifts in the population dynamics of prey. Research has provided a link between rates of predation and the evolution of prey population growth in the lab, but studies from natural populations are rare. Here, we tested for evolutionary changes in population dynamics parameters of zooplankton Daphnia pulicaria following invasion by the predator Bythotrephes longimanus into Lake Kegonsa, Wisconsin, US. We used a resurrection ecological approach, whereby clones from pre- and post-invasive periods were hatched from eggs obtained in sediment cores and were used in a 3-month growth experiment. Based on these data, we estimated intrinsic population growth rates (r), the shape of density dependence (θ) and carrying capacities (K) using theta-logistic models. We found that post-invasion Daphnia maintained a higher r and K under these controlled, predation-free laboratory conditions. Evidence for changes in θ was weaker. Whereas previous experimental evolution studies of predator-prey interactions have demonstrated that genotypes that have evolved under predation have inferior competitive ability when the predator is absent, this was not the case for the Daphnia. Given that our study was conducted in a laboratory environment and the possibility for genotype-by-environment interactions, extrapolating these apparent counterintuitive results to the wild should be done with caution. However, barring such complications, we discuss how selection for reduced predator exposure, either temporally or spatially, may have led to the observed changes. This scenario suggests that complexities in ecological interactions represents a challenge when predicting the evolutionary responses of population dynamics to changes in predation pressure in natural systems.

Predator-Prey Evolution from an Eco-evolutionary Trade-off Model: The Role of Trait Differentiation

We develop a novel eco-evolutionary modelling framework and demonstrate its efficacy by simulating the evolution of trait distributions in predator and prey populations. The eco-evolutionary modelling framework assumes that population traits have beta distributions and defines canonical equations for the dynamics of each total population size, the population's average trait value, and a measure of the population's trait differentiation. The trait differentiation is included in the modelling framework as a phenotype analogue, Q, of Wright's fixation index [Formula: see text], which is inversely related to the sum of the beta distribution shape parameters. The canonical equations may be used as templates to describe the evolution of population trait distributions in many ecosystems that are subject to stabilising selection. The solutions of the "population model" are compared with those of a "phenotype model" that simulates the growth of each phenotype as it interacts with every other phenotype under the same trade-offs. The models assume no sources of new phenotypic variance, such as mutation or gene flow. We examine a predator-prey system in which each population trades off growth against mortality: the prey optimises devoting resources to growth or defence against predation; and the predator trades off increasing its attack rate against increased mortality. Computer solutions with stabilising selection reveal very close agreement between the phenotype and population model results, which both predict that evolution operates to stabilise an initially oscillatory system. The population model reduces the number of equations required to simulate the eco-evolutionary system by several orders of magnitude, without losing verisimilitude for the overarching population properties. The population model also allows insights into the properties of the system that are not available from the equivalent phenotype model.

Interaction capacity as a potential driver of community diversity

How patterns in community diversity emerge is a long-standing question in ecology. Studies suggested that community diversity and interspecific interactions are interdependent. However, evidence from high-diversity ecological communities is lacking because of practical challenges in characterizing speciose communities and their interactions. Here, I analysed time-varying interaction networks that were reconstructed using 1197 species, DNA-based ecological time series taken from experimental rice plots and empirical dynamic modelling, and introduced 'interaction capacity', namely, the sum of interaction strength that a single species gives and receives, as a potential driver of community diversity. As community diversity increases, the number of interactions increases exponentially but the mean interaction capacity of a community becomes saturated, weakening interspecific interactions. These patterns are modelled with simple mathematical equations, based on which I propose the 'interaction capacity hypothesis': that interaction capacity and network connectance can be two fundamental properties that influence community diversity. Furthermore, I show that total DNA abundance and temperature influence interaction capacity and connectance nonlinearly, explaining a large proportion of diversity patterns observed in various systems. The interaction capacity hypothesis enables mechanistic explanations of community diversity. Therefore, analysing ecological community data from the viewpoint of interaction capacity would provide new insight into community diversity.

Inconsistent evolution and growth-survival tradeoffs in Gambusia affinis

Growth-survival tradeoffs may be a generalizable mechanism influencing trajectories of prey evolution. Here, we investigate evolutionary contributions to growth and survival in western mosquitofish (Gambusia affinis) from 10 populations from high- and low-predation ancestral environments. We assess (i) the degree to which evolutionary components of growth and survival are consistent or inconsistent across populations within ancestral predation environments, and (ii) whether growth and survival trade off at the population level. We measure growth and survival on groups of common-reared mosquitofish in pond mesocosms. We find that evolution of growth is consistent, with fish from low-predation ancestral environments showing higher growth, while the evolution of survival is inconsistent, with significant population-level divergence unrelated to ancestral predation environment. Such inconsistency prevents a growth-survival tradeoff across populations. Thus, the generalizability of contemporary evolution probably depends on local context of evolutionary tradeoffs, and a continued focus on singular selective agents (e.g. predators) without such local context will impede insights into generalizable evolutionary patterns.

Maintenance of Intraspecific Diversity in Response to Species Competition and Nutrient Fluctuations

Intraspecific diversity is a substantial part of biodiversity, yet little is known about its maintenance. Understanding mechanisms of intraspecific diversity shifts provides realistic detail about how phytoplankton communities evolve to new environmental conditions, a process especially important in times of climate change. Here, we aimed to identify factors that maintain genotype diversity and link the observed diversity change to measured phytoplankton morpho-functional traits Vmax and cell size of the species and genotypes. In an experimental setup, the two phytoplankton species Emiliania huxleyi and Chaetoceros affinis, each consisting of nine genotypes, were cultivated separately and together under different fluctuation and nutrient regimes. Their genotype composition was assessed after 49 and 91 days, and Shannon's diversity index was calculated on the genotype level. We found that a higher intraspecific diversity can be maintained in the presence of a competitor, provided it has a substantial proportion to total biovolume. Both fluctuation and nutrient regime showed species-specific effects and especially structured genotype sorting of C. affinis. While we could relate species sorting with the measured traits, genotype diversity shifts could only be partly explained. The observed context dependency of genotype maintenance suggests that the evolutionary potential could be better understood, if studied in more natural settings including fluctuations and competition.

The Importance of Eco-evolutionary Potential in the Anthropocene

Humans are dominant global drivers of ecological and evolutionary change, rearranging ecosystems and natural selection. In the present article, we show increasing evidence that human activity also plays a disproportionate role in shaping the eco-evolutionary potential of systems—the likelihood of ecological change generating evolutionary change and vice versa. We suggest that the net outcome of human influences on trait change, ecology, and the feedback loops that link them will often (but not always) be to increase eco-evolutionary potential, with important consequences for stability and resilience of populations, communities, and ecosystems. We also integrate existing ecological and evolutionary metrics to predict and manage the eco-evolutionary dynamics of human-affected systems. To support this framework, we use a simple eco–evo feedback model to show that factors affecting eco-evolutionary potential are major determinants of eco-evolutionary dynamics. Our framework suggests that proper management of anthropogenic effects requires a science of human effects on eco-evolutionary potential.

Cell-growth gene expression reveals a direct fitness cost of grazer-induced toxin production in red tide dinoflagellate prey

Induced prey defences against consumers are conspicuous in microbes, plants and animals. In toxigenic prey, a defence fitness cost should result in a trade-off between defence expression and individual growth. Yet, previous experimental work has failed to detect such induced defence cost in toxigenic phytoplankton. We measured a potential direct fitness cost of grazer-induced toxin production in a red tide dinoflagellate prey using relative gene expression (RGE) of a mitotic cyclin gene (cyc), a marker that correlates to cell growth. This approach disentangles the reduction in cell growth from the defence cost from the mortality by consumers. Treatments where the dinoflagellate Alexandrium catenella were exposed to copepod grazers significantly increased toxin production while decreasing RGE of cyc, indicating a defence-growth trade-off. The defence fitness cost represents a mean decrease of the cell growth rate of 32%. Simultaneously, we estimate that the traditional method to measure mortality loss by consumers is overestimated by 29%. The defence appears adaptive as the prey population persists in quasi steady state after the defence is induced. Our approach provides a novel framework to incorporate the fitness cost of defence in toxigenic prey-consumer interaction models.

Evolutionary and Plastic Phenotypic Change Can Be Just as Fast as Changes in Population Densities

AbstractEvolution and plasticity can drive population-level phenotypic change (e.g., changes in the mean phenotype) on timescales comparable to changes in population densities. However, it is unclear whether phenotypic change has the potential to be just as fast as changes in densities or whether comparable rates of change occur only when densities are changing slow enough for phenotypes to keep pace. Moreover, it is unclear whether this depends on the mode of adaptation. Using scaling theory and fast-slow dynamical systems theory, we develop a method for comparing maximum rates of density and phenotypic change estimated from population-level time-series data. We apply our method to 30 published empirical studies where changes in morphological traits are caused by evolution, plasticity, or an unknown combination. For every study, the maximum rate of phenotypic change was between 0.5 and 2.5 times faster than the maximum rate of change in density. Moreover, there were no systematic differences between systems with different modes of adaptation. Our results show that plasticity and evolution can drive phenotypic change just as fast as changes in densities. We discuss the implications of our results in terms of the strengths of feedbacks between population densities and traits.

Eco-evolutionary dynamics driven by fishing: From single species models to dynamic evolution within complex food webs

Evidence of contemporary evolution across ecological time scales stimulated research on the eco-evolutionary dynamics of natural populations. Aquatic systems provide a good setting to study eco-evolutionary dynamics owing to a wealth of long-term monitoring data and the detected trends in fish life-history traits across intensively harvested marine and freshwater systems. In the present study, we focus on modelling approaches to simulate eco-evolutionary dynamics of fishes and their ecosystems. Firstly, we review the development of modelling from single species to multispecies approaches. Secondly, we advance the current state-of-the-art methodology by implementing evolution of life-history traits of a top predator into the context of complex food web dynamics as described by the allometric trophic network (ATN) framework. The functioning of our newly developed eco-evolutionary ATNE framework is illustrated using a well-studied lake food web. Our simulations show how both natural selection arising from feeding interactions and size-selective fishing cause evolutionary changes in the top predator and how those feed back to its prey species and further cascade down to lower trophic levels. Finally, we discuss future directions, particularly the need to integrate genomic discoveries into eco-evolutionary projections.

Antagonistic species interaction drives selection for sex in a predator-prey system

The evolutionary maintenance of sexual reproduction has long challenged biologists as the majority of species reproduce sexually despite inherent costs. Providing a general explanation for the evolutionary success of sex has thus proven difficult and resulted in numerous hypotheses. A leading hypothesis suggests that antagonistic species interaction can generate conditions selecting for increased sex due to the production of rare or novel genotypes that are beneficial for rapid adaptation to recurrent environmental change brought on by antagonism. To test this ecology-based hypothesis, we conducted experimental evolution in a predator (rotifer)-prey (algal) system by using continuous cultures to track predator-prey dynamics and in situ rates of sex in the prey over time and within replicated experimental populations. Overall, we found that predator-mediated fluctuating selection for competitive versus defended prey resulted in higher rates of genetic mixing in the prey. More specifically, our results showed that fluctuating population sizes of predator and prey, coupled with a trade-off in the prey, drove the sort of recurrent environmental change that could provide a benefit to sex in the prey, despite inherent costs. We end with a discussion of potential population genetic mechanisms underlying increased selection for sex in this system, based on our application of a general theoretical framework for measuring the effects of sex over time, and interpreting how these effects can lead to inferences about the conditions selecting for or against sexual reproduction in a system with antagonistic species interaction.

The shape of a defense-growth trade-off governs seasonal trait dynamics in natural phytoplankton

Theory predicts that trade-offs, quantifying costs of functional trait adjustments, crucially affect community trait adaptation to altered environmental conditions, but empirical verification is scarce. We evaluated trait dynamics (antipredator defense, maximum growth rate, and phosphate affinity) of a lake phytoplankton community in a seasonally changing environment, using literature trait data and 21 years of species-resolved high-frequency biomass measurements. The trait data indicated a concave defense-growth trade-off, promoting fast-growing species with intermediate defense. With seasonally increasing grazing pressure, the community shifted toward higher defense levels at the cost of lower growth rates along the trade-off curve, while phosphate affinity explained some deviations from it. We discuss how low fitness differences of species, inferred from model simulations, in concert with stabilizing mechanisms, e.g., arising from further trait dimensions, may lead to the observed phytoplankton diversity. In conclusion, quantifying trade-offs is key for predictions of community trait adaptation and biodiversity under environmental change.

Prey adaptation along a competition-defense tradeoff cryptically shifts trophic cascades from density- to trait-mediated

Trophic cascades have become a dominant paradigm in ecology, yet considerable debate remains about the relative strength of density- (consumptive) and trait-mediated (non-consumptive) effects in trophic cascades. This debate may, in part, be resolved by considering prey experience, which shapes prey traits (through genetic and plastic change) and influences prey survival (and therefore density). Here, we investigate the cascading role of prey experience through the addition of mosquitofish (Gambusia affinis) from predator-experienced or predator-naïve sources to mesocosms containing piscivorous largemouth bass (Micropterus salmoides), zooplankton, and phytoplankton. These two sources were positioned along a competition-defense tradeoff. Results show that predator-naïve mosquitofish suffered higher depredation rates, which drove a density-mediated cascade, whereas predator-experienced mosquitofish exhibited higher survival but fed less, which drove a trait-mediated cascade. Both cascades were similar in strength, leading to indistinguishable top-down effects on lower trophic levels. Therefore, the accumulation of prey experience with predators can cryptically shift cascade mechanisms from density- to trait-mediated.

Destabilizing evolutionary and eco-evolutionary feedbacks drive empirical eco-evolutionary cycles

We develop a method to identify how ecological, evolutionary, and eco-evolutionary feedbacks influence system stability. We apply our method to nine empirically parametrized eco-evolutionary models of exploiter-victim systems from the literature and identify which particular feedbacks cause some systems to converge to a steady state or to exhibit sustained oscillations. We find that ecological feedbacks involving the interactions between all species and evolutionary and eco-evolutionary feedbacks involving only the interactions between exploiter species (predators or pathogens) are typically stabilizing. In contrast, evolutionary and eco-evolutionary feedbacks involving the interactions between victim species (prey or hosts) are destabilizing more often than not. We also find that while eco-evolutionary feedbacks rarely altered system stability from what would be predicted from just ecological and evolutionary feedbacks, eco-evolutionary feedbacks have the potential to alter system stability at faster or slower speeds of evolution. As the number of empirical studies demonstrating eco-evolutionary feedbacks increases, we can continue to apply these methods to determine whether the patterns we observe are common in other empirical communities.

Enhanced inference of ecological networks by parameterizing ensembles of population dynamics models constrained with prior knowledge

Background

Accurate network models of species interaction could be used to predict population dynamics and be applied to manage real world ecosystems. Most relevant models are nonlinear, however, and data available from real world ecosystems are too noisy and sparsely sampled for common inference approaches. Here we improved the inference of generalized Lotka–Volterra (gLV) ecological networks by using a new optimization algorithm to constrain parameter signs with prior knowledge and a perturbation-based ensemble method.

Results

We applied the new inference to long-term species abundance data from the freshwater fish community in the Illinois River, United States. We constructed an ensemble of 668 gLV models that explained 79% of the data on average. The models indicated (at a 70% level of confidence) a strong positive interaction from emerald shiner (Notropis atherinoides) to channel catfish (Ictalurus punctatus), which we could validate using data from a nearby observation site, and predicted that the relative abundances of most fish species will continue to fluctuate temporally and concordantly in the near future. The network shows that the invasive silver carp (Hypophthalmichthys molitrix) has much stronger impacts on native predators than on prey, supporting the notion that the invader perturbs the native food chain by replacing the diets of predators.

Conclusions

Ensemble approaches constrained by prior knowledge can improve inference and produce networks from noisy and sparsely sampled time series data to fill knowledge gaps on real world ecosystems. Such network models could aid efforts to conserve ecosystems such as the Illinois River, which is threatened by the invasion of the silver carp.

Factors Affecting the Mixotrophic Flagellate Poterioochromonas malhamensis Grazing on Chlorella Cells

Grazing behaviour between protozoa and phytoplankton exists widely in planktonic ecosystems. Poterioochromonas malhamensis is a well-known and widespread mixotrophic flagellate, which is recognized to play an important role within marine and freshwater planktonic ecosystems and regarded as the greatest contamination threat for mass algal cultures of Chlorella. In this study, a comprehensive range of factors, including morphological characters, biochemical compositions, and specific growth rate of ten species or strains of Chlorella, were evaluated for their effect on the feeding ability of P. malhamensis, which was assessed by two parameters: the clearance rate of P. malhamensis on Chlorella spp. and the specific growth rate of P. malhamensis. The results showed that the clearance rate of P. malhamensis was negatively correlated with cell wall thickness and specific growth rate of Chlorella spp., while the specific growth rate of P. malhamensis was positively correlated with carbohydrate percentage and C/N ratio and negatively correlated with protein, lipid percentage, and nitrogen mass. In conclusion, the factors influencing feeding selectivity include not only the morphological character and chemical composition of Chlorella, but also its population dynamics. Our study provides useful insights into the key factors that affect the feeding selectivity of P. malhamensis and provides basic and constructive data to help in screening for grazing-resistant microalgae.

Maladapted Prey Subsidize Predators and Facilitate Range Expansion

Dispersal of prey from predator-free patches frequently supplies a trophic subsidy to predators by providing more prey than are produced locally. Prey arriving from predator-free patches might also have evolved weaker defenses against predators and thus enhance trophic subsidies by providing easily captured prey. Using local models assuming a linear or accelerating trade-off between defense and population growth rate, we demonstrate that immigration of undefended prey increased predator abundances and decreased defended prey through eco-evolutionary apparent competition. In individual-based models with spatial structure, explicit genetics, and gene flow along an environmental gradient, prey became maladapted to predators at the predator's range edge, and greater gene flow enhanced this maladaptation. The predator gained a subsidy from these easily captured prey, which enhanced its abundance, facilitated its persistence in marginal habitats, extended its range extent, and enhanced range shifts during environmental changes, such as climate change. Once the predator expanded, prey adapted to it and the advantage disappeared, resulting in an elastic predator range margin driven by eco-evolutionary dynamics. Overall, the results indicate a need to consider gene flow-induced maladaptation and species interactions as mutual forces that frequently determine ecological and evolutionary dynamics and patterns in nature.

How (co)evolution alters predator responses to increased mortality: extinction thresholds and hydra effects

Population responses to environmental change depend on both the ecological interactions between species and the evolutionary responses of all species. In this study, we explore how evolution in prey, predators, or both species affect the responses of predator populations to a sustained increase in mortality. We use an eco-evolutionary predator-prey model to explore how evolution alters the predator extinction threshold (defined as the minimum mortality rate that prevents population growth at low predator densities) and predator hydra effects (increased predator abundance in response to increased mortality). Our analysis identifies how evolutionary responses of prey and predators individually affect the predator extinction threshold and hydra effects, and how those effects are altered by interactions between the evolutionary responses. Based on our theoretical results, we predict that it is common in natural systems for evolutionary responses in one or both species to allow predators to persist at higher mortality rates than would be possible in the absence of evolution (i.e., evolution increases the predator mortality extinction threshold). We also predict that evolution-driven hydra effects occur in a minority of natural systems, but are not rare. We revisited published eco-evolutionary models and found that evolution causes hydra effects and increases the predator extinction threshold in many studies, but those effects have been overlooked. We discuss the implications of these results for species conservation, predicting population responses to environmental change, and the possibility of evolutionary rescue.

Eco-evolutionary feedbacks between prey densities and linkage disequilibrium in the predator maintain diversity

Diversity occurs at multiple scales. Within a single population, there is diversity in genotypes and phenotypes. At a larger scale, within ecological communities, there is diversity in species. A number of studies have investigated how diversity at these two scales influence each other through what has been termed eco-evolutionary feedbacks. Here we study a three-species ecological module called apparent competition, in which the predator is evolving in a trait that determines its interaction with two prey species. Unlike previous studies on apparent competition, which employed evolutionary frameworks with very simple genetics, we study an eco-evolutionary model in which the predator's trait is determined by two recombining diallelic loci, so that its mean and variance can evolve, as well as associations (linkage disequilibrium) between the loci. We ask how eco-evolutionary feedbacks with these two loci affect the coexistence of the prey species and the maintenance of polymorphisms within the predator species. We uncover a novel eco-evolutionary feedback between the prey densities and the linkage disequilibrium between the predator's loci. Through a stability analysis, we demonstrate how these feedbacks affect polymorphisms at both loci and, among others, may generate stable cycling.

Gradual plasticity alters population dynamics in variable environments: thermal acclimation in the green alga Chlamydomonas reinhartdii

Environmental variability is ubiquitous, but its effects on populations are not fully understood or predictable. Recent attention has focused on how rapid evolution can impact ecological dynamics via adaptive trait change. However, the impact of trait change arising from plastic responses has received less attention, and is often assumed to optimize performance and unfold on a separate, faster timescale than ecological dynamics. Challenging these assumptions, we propose that gradual plasticity is important for ecological dynamics, and present a study of the plastic responses of the freshwater green algae Chlamydomonas reinhardtii as it acclimates to temperature changes. First, we show that C. reinhardtii's gradual acclimation responses can both enhance and suppress its performance after a perturbation, depending on its prior thermal history. Second, we demonstrate that where conventional approaches fail to predict the population dynamics of C. reinhardtii exposed to temperature fluctuations, a new model of gradual acclimation succeeds. Finally, using high-resolution data, we show that phytoplankton in lake ecosystems can experience thermal variation sufficient to make acclimation relevant. These results challenge prevailing assumptions about plasticity's interactions with ecological dynamics. Amidst the current emphasis on rapid evolution, it is critical that we also develop predictive methods accounting for plasticity.

Trade-off shapes diversity in eco-evolutionary dynamics

We introduce an Interaction- and Trade-off-based Eco-Evolutionary Model (ITEEM), in which species are competing in a well-mixed system, and their evolution in interaction trait space is subject to a life-history trade-off between replication rate and competitive ability. We demonstrate that the shape of the trade-off has a fundamental impact on eco-evolutionary dynamics, as it imposes four phases of diversity, including a sharp phase transition. Despite its minimalism, ITEEM produces a remarkable range of patterns of eco-evolutionary dynamics that are observed in experimental and natural systems. Most notably we find self-organization towards structured communities with high and sustained diversity, in which competing species form interaction cycles similar to rock-paper-scissors games.

Not attackable or not crackable-How pre- and post-attack defenses with different competition costs affect prey coexistence and population dynamics

It is well-known that prey species often face trade-offs between defense against predation and competitiveness, enabling predator-mediated coexistence. However, we lack an understanding of how the large variety of different defense traits with different competition costs affects coexistence and population dynamics. Our study focusses on two general defense mechanisms, that is, pre-attack (e.g., camouflage) and post-attack defenses (e.g., weaponry) that act at different phases of the predator-prey interaction. We consider a food web model with one predator, two prey types and one resource. One prey type is undefended, while the other one is pre- or post-attack defended paying costs either by a higher half-saturation constant for resource uptake or a lower maximum growth rate. We show that post-attack defenses promote prey coexistence and stabilize the population dynamics more strongly than pre-attack defenses by interfering with the predator's functional response: Because the predator spends time handling "noncrackable" prey, the undefended prey is indirectly facilitated. A high half-saturation constant as defense costs promotes coexistence more and stabilizes the dynamics less than a low maximum growth rate. The former imposes high costs at low resource concentrations but allows for temporally high growth rates at predator-induced resource peaks preventing the extinction of the defended prey. We evaluate the effects of the different defense mechanisms and costs on coexistence under different enrichment levels in order to vary the importance of bottom-up and top-down control of the prey community.

Reversed predator-prey cycles are driven by the amplitude of prey oscillations

Ecoevolutionary feedbacks in predator-prey systems have been shown to qualitatively alter predator-prey dynamics. As a striking example, defense-offense coevolution can reverse predator-prey cycles, so predator peaks precede prey peaks rather than vice versa. However, this has only rarely been shown in either model studies or empirical systems. Here, we investigate whether this rarity is a fundamental feature of reversed cycles by exploring under which conditions they should be found. For this, we first identify potential conditions and parameter ranges most likely to result in reversed cycles by developing a new measure, the effective prey biomass, which combines prey biomass with prey and predator traits, and represents the prey biomass as perceived by the predator. We show that predator dynamics always follow the dynamics of the effective prey biomass with a classic ¼-phase lag. From this key insight, it follows that in reversed cycles (i.e., ¾-lag), the dynamics of the actual and the effective prey biomass must be in antiphase with each other, that is, the effective prey biomass must be highest when actual prey biomass is lowest, and vice versa. Based on this, we predict that reversed cycles should be found mainly when oscillations in actual prey biomass are small and thus have limited impact on the dynamics of the effective prey biomass, which are mainly driven by trait changes. We then confirm this prediction using numerical simulations of a coevolutionary predator-prey system, varying the amplitude of the oscillations in prey biomass: Reversed cycles are consistently associated with regions of parameter space leading to small-amplitude prey oscillations, offering a specific and highly testable prediction for conditions under which reversed cycles should occur in natural systems.

Evolutionary contribution to coexistence of competitors in microbial food webs

The theory of species coexistence is a key concept in ecology that has received much attention. The role of rapid evolution for determining species coexistence is still poorly understood although evolutionary change on ecological time-scales has the potential to change almost any ecological process. The influence of evolution on coexistence can be especially pronounced in microbial communities where organisms often have large population sizes and short generation times. Previous work on coexistence has assumed that traits involved in resource use and species interactions are constant or change very slowly in terms of ecological time-scales. However, recent work suggests that these traits can evolve rapidly. Nevertheless, the importance of rapid evolution to coexistence has not been tested experimentally. Here, we show how rapid evolution alters the frequency of two bacterial competitors over time when grown together with specialist consumers (bacteriophages), a generalist consumer (protozoan) and all in combination. We find that consumers facilitate coexistence in a manner consistent with classic ecological theory. However, through disentangling the relative contributions of ecology (changes in consumer abundance) and evolution (changes in traits mediating species interactions) on the frequency of the two competitors over time, we find differences between the consumer types and combinations. Overall, our results indicate that the influence of evolution on species coexistence strongly depends on the traits and species interactions considered.

Eco-evolutionary Feedbacks from Non-target Species Influence Harvest Yield and Sustainability

Evolution in harvested species has become a major concern for its potential to affect yield, sustainability, and recovery. However, the current singular focus on harvest-mediated evolution in target species overlooks the potential for evolution in non-target members of communities. Here we use an individual-based model to explore the scope and pattern of harvest-mediated evolution at non-target trophic levels and its potential feedbacks on abundance and yield of the harvested species. The model reveals an eco-evolutionary trophic cascade, in which harvest at top trophic levels drives evolution of greater defense or competitiveness at subsequently lower trophic levels, resulting in alternating feedbacks on the abundance and yield of the harvested species. The net abundance and yield effects of these feedbacks depends on the intensity of harvest and attributes of non-target species. Our results provide an impetus and framework to evaluate the role of non-target species evolution in determining fisheries yield and sustainability.

Eco-Evolutionary Dynamics of Ecological Stoichiometry in Plankton Communities

Nitrogen (N) and phosphorus (P) limit primary production in many aquatic ecosystems, with major implications for ecological interactions in plankton communities. Yet it remains unclear how evolution may affect the N∶P stoichiometry of phytoplankton-zooplankton interactions. Here, we address this issue by analyzing an eco-evolutionary model of phytoplankton-zooplankton interactions with explicit nitrogen and phosphorus dynamics. In our model, investment of phytoplankton in nitrogen versus phosphorus uptake is an evolving trait, and zooplankton display selectivity for phytoplankton with N∶P ratios matching their nutritional requirements. We use this model to explore implications of the contrasting N∶P requirements of copepods versus cladocerans. The model predicts that selective zooplankton strongly affect the N∶P ratio of phytoplankton, resulting in deviations from their optimum N∶P ratio. Specifically, selective grazing by nitrogen-demanding copepods favors dominance of phytoplankton with low N∶P ratios, whereas phosphorus-demanding cladocerans favor dominance of phytoplankton with high N∶P ratios. Interestingly, selective grazing by nutritionally balanced zooplankton leads to the occurrence of alternative stable states, where phytoplankton may evolve either low, optimum, or high N∶P ratios, depending on the initial conditions. These results offer a new perspective on commonly observed differences in N∶P stoichiometry between plankton of freshwater and those of marine ecosystems and indicate that selective grazing by zooplankton can have a major impact on the stoichiometric composition of phytoplankton.

Fluctuating interaction network and time-varying stability of a natural fish community

Ecological theory suggests that large-scale patterns such as community stability can be influenced by changes in interspecific interactions that arise from the behavioural and/or physiological responses of individual species varying over time. Although this theory has experimental support, evidence from natural ecosystems is lacking owing to the challenges of tracking rapid changes in interspecific interactions (known to occur on timescales much shorter than a generation time) and then identifying the effect of such changes on large-scale community dynamics. Here, using tools for analysing nonlinear time series and a 12-year-long dataset of fortnightly collected observations on a natural marine fish community in Maizuru Bay, Japan, we show that short-term changes in interaction networks influence overall community dynamics. Among the 15 dominant species, we identify 14 interspecific interactions to construct a dynamic interaction network. We show that the strengths, and even types, of interactions change with time; we also develop a time-varying stability measure based on local Lyapunov stability for attractor dynamics in non-equilibrium nonlinear systems. We use this dynamic stability measure to examine the link between the time-varying interaction network and community stability. We find seasonal patterns in dynamic stability for this fish community that broadly support expectations of current ecological theory. Specifically, the dominance of weak interactions and higher species diversity during summer months are associated with higher dynamic stability and smaller population fluctuations. We suggest that interspecific interactions, community network structure and community stability are dynamic properties, and that linking fluctuating interaction networks to community-level dynamic properties is key to understanding the maintenance of ecological communities in nature.

Experimental evidence that parasites drive eco-evolutionary feedbacks

Host resistance to parasites is a rapidly evolving trait that can influence how hosts modify ecosystems. Eco-evolutionary feedbacks may develop if the ecosystem effects of host resistance influence selection on subsequent host generations. In a mesocosm experiment, using a recently diverged (<100 generations) pair of lake and stream three-spined sticklebacks, we tested how experimental exposure to a common fish parasite (Gyrodactylus spp.) affects interactions between hosts and their ecosystems in two environmental conditions (low and high nutrients). In both environments, we found that stream sticklebacks were more resistant to Gyrodactylus and had different gene expression profiles than lake sticklebacks. This differential infection led to contrasting effects of sticklebacks on a broad range of ecosystem properties, including zooplankton community structure and nutrient cycling. These ecosystem modifications affected the survival, body condition, and gene expression profiles of a subsequent fish generation. In particular, lake juvenile fish suffered increased mortality in ecosystems previously modified by lake adults, whereas stream fish showed decreased body condition in stream fish-modified ecosystems. Parasites reinforced selection against lake juveniles in lake fish-modified ecosystems, but only under oligotrophic conditions. Overall, our results highlight the overlapping timescales and the interplay of host-parasite and host-ecosystem interactions. We provide experimental evidence that parasites influence host-mediated effects on ecosystems and, thereby, change the likelihood and strength of eco-evolutionary feedbacks.

Population and Evolutionary Dynamics based on Predator-Prey Relationships in a 3D Physical Simulation

Recent studies have reported that population dynamics and evolutionary dynamics, occurring at different time scales, can be affected by each other. Our purpose is to explore the interaction between population and evolutionary dynamics using an artificial life approach based on a 3D physically simulated environment in the context of predator-prey and morphology-behavior coevolution. The morphologies and behaviors of virtual prey creatures are evolved using a genetic algorithm based on the predation interactions between predators and prey. Both population sizes are also changed, depending on the fitness. We observe two types of cyclic behaviors, corresponding to short-term and long-term dynamics. The former can be interpreted as a simple population dynamics of Lotka-Volterra type. It is shown that the latter cycle is based on the interaction between the changes in the prey strategy against predators and the long-term change in both population sizes, resulting partly from a tradeoff between their defensive success and the cost of defense.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms.

Indirect evolutionary rescue: prey adapts, predator avoids extinction

Recent studies have increasingly recognized evolutionary rescue (adaptive evolution that prevents extinction following environmental change) as an important process in evolutionary biology and conservation science. Researchers have concentrated on single species living in isolation, but populations in nature exist within communities of interacting species, so evolutionary rescue should also be investigated in a multispecies context. We argue that the persistence or extinction of a focal species can be determined solely by evolutionary change in an interacting species. We demonstrate that prey adaptive evolution can prevent predator extinction in two-species predator–prey models, and we derive the conditions under which this indirect evolutionary interaction is essential to prevent extinction following environmental change. A nonevolving predator can be rescued from extinction by adaptive evolution of its prey due to a trade-off for the prey between defense against predation and population growth rate. As prey typically have larger populations and shorter generations than their predators, prey evolution can be rapid and have profound effects on predator population dynamics. We suggest that this process, which we term ‘indirect evolutionary rescue’, has the potential to be critically important to the ecological and evolutionary responses of populations and communities to dramatic environmental change.