Dispersal evolution and eco-evolutionary dynamics in antagonistic species interactions.

Dispersal evolution modifies diverse spatial processes, such as range expansions or biological invasions of single species, but we are currently lacking a realistic vision for metacommunities. Focusing on antagonistic species interactions, we review existing theory of dispersal evolution between natural enemies, and explain how this might be relevant for classic themes in host-parasite evolutionary ecology, namely virulence evolution or local adaptation. Specifically, we highlight the importance of considering the simultaneous (co)evolution of dispersal and interaction traits. Linking such multi-trait evolution with reciprocal demographic and epidemiological feedbacks might change basic predictions about coevolutionary processes and spatial dynamics of interacting species. Future challenges concern the integration of system-specific disease ecology or spatial modifiers, such as spatial network structure or environmental heterogeneity.

Eco-evolution from deep time to contemporary dynamics: The role of timescales and rate modulators.

Eco-evolutionary dynamics, or eco-evolution for short, are often thought to involve rapid demography (ecology) and equally rapid heritable phenotypic changes (evolution) leading to novel, emergent system behaviours. We argue that this focus on contemporary dynamics is too narrow: Eco-evolution should be extended, first, beyond pure demography to include all environmental dimensions and, second, to include slow eco-evolution which unfolds over thousands or millions of years. This extension allows us to conceptualise biological systems as occupying a two-dimensional time space along axes that capture the speed of ecology and evolution. Using Hutchinson's analogy: Time is the 'theatre' in which ecology and evolution are two interacting 'players'. Eco-evolutionary systems are therefore dynamic: We identify modulators of ecological and evolutionary rates, like temperature or sensitivity to mutation, which can change the speed of ecology and evolution, and hence impact eco-evolution. Environmental change may synchronise the speed of ecology and evolution via these rate modulators, increasing the occurrence of eco-evolution and emergent system behaviours. This represents substantial challenges for prediction, especially in the context of global change. Our perspective attempts to integrate ecology and evolution across disciplines, from gene-regulatory networks to geomorphology and across timescales, from today to deep time.

A stabilizing eco-evolutionary feedback loop in the wild.

There is increasing evidence that evolutionary and ecological processes can operate on the same timescale1,2 (i.e., contemporary time). As such, evolution can be sufficiently rapid to affect ecological processes such as predation or competition. Thus, evolution can influence population, community, and ecosystem-level dynamics. Indeed, studies have now shown that evolutionary dynamics can alter community structure3,4,5,6 and ecosystem function.7,8,9,10 In turn, shifts in ecological dynamics driven by evolution might feed back to affect the evolutionary trajectory of individual species.11 This feedback loop, where evolutionary and ecological changes reciprocally affect one another, is a central tenet of eco-evolutionary dynamics.1,12 However, most work on such dynamics in natural populations has focused on one-way causal associations between ecology and evolution.13 Hence, direct empirical evidence for eco-evolutionary feedback is rare and limited to laboratory or mesocosm experiments.13,14,15,16 Here, we show in the wild that eco-evolutionary dynamics in a plant-feeding arthropod community involve a negative feedback loop. Specifically, adaptation in cryptic coloration in a stick-insect species mediates bird predation, with local maladaptation increasing predation. In turn, the abundance of arthropods is reduced by predation. Here, we experimentally manipulate arthropod abundance to show that these changes at the community level feed back to affect the stick-insect evolution. Specifically, low-arthropod abundance increases the strength of selection on crypsis, increasing local adaptation of stick insects in a negative feedback loop. Our results suggest that eco-evolutionary feedbacks are able to stabilize complex systems by preventing consistent directional change and therefore increasing resilience.

Landscape Structure Affects Metapopulation-Scale Tipping Points.

AbstractEven when environments deteriorate gradually, ecosystems may shift abruptly from one state to another. Such catastrophic shifts are difficult to predict and sometimes to reverse (so-called hysteresis). While well studied in simplified contexts, we lack a general understanding of how catastrophic shifts spread in realistically spatially structured landscapes. For different types of landscape structures, including typical terrestrial modular and riverine dendritic networks, we here investigate landscape-scale stability in metapopulations whose patches can locally exhibit catastrophic shifts. We find that such metapopulations usually exhibit large-scale catastrophic shifts and hysteresis and that the properties of these shifts depend strongly on the metapopulation spatial structure and on the population dispersal rate: an intermediate dispersal rate, a low average degree, or a riverine spatial structure can largely reduce hysteresis size. Our study suggests that large-scale restoration is easier with spatially clustered restoration efforts and in populations characterized by an intermediate dispersal rate.

Predicting evolution in experimental range expansions of an aquatic model system.

Predicting range expansion dynamics is an important goal of both fundamental and applied research in conservation and global change biology. However, this is challenging if ecological and evolutionary processes occur on the same time scale. Using the freshwater ciliate Paramecium caudatum, we combined experimental evolution and mathematical modeling to assess the predictability of evolutionary change during range expansions. In the experiment, we followed ecological dynamics and trait evolution in independently replicated microcosm populations in range core and front treatments, where episodes of natural dispersal alternated with periods of population growth. These eco-evolutionary conditions were recreated in a predictive mathematical model, parametrized with dispersal and growth data of the 20 founder strains in the experiment. We found that short-term evolution was driven by selection for increased dispersal in the front treatment and general selection for higher growth rates in all treatments. There was a good quantitative match between predicted and observed trait changes. Phenotypic divergence was further mirrored by genetic divergence between range core and front treatments. In each treatment, we found the repeated fixation of the same cytochrome c oxidase I (COI) marker genotype, carried by strains that also were the most likely winners in our model. Long-term evolution in the experimental range front lines resulted in the emergence of a dispersal syndrome, namely a competition-colonization trade-off. Altogether, both model and experiment highlight the potential importance of dispersal evolution as a driver of range expansions. Thus, evolution at range fronts may follow predictable trajectories, at least for simple scenarios, and predicting these dynamics may be possible from knowledge of few key parameters.

Experimental evolution of dispersal: Unifying theory, experiments and natural systems.

Dispersal is a central life history trait that affects the ecological and evolutionary dynamics of populations and communities. The recent use of experimental evolution for the study of dispersal is a promising avenue for demonstrating valuable proofs of concept, bringing insight into alternative dispersal strategies and trade-offs, and testing the repeatability of evolutionary outcomes. Practical constraints restrict experimental evolution studies of dispersal to a set of typically small, short-lived organisms reared in artificial laboratory conditions. Here, we argue that despite these restrictions, inferences from these studies can reinforce links between theoretical predictions and empirical observations and advance our understanding of the eco-evolutionary consequences of dispersal. We illustrate how applying an integrative framework of theory, experimental evolution and natural systems can improve our understanding of dispersal evolution under more complex and realistic biological scenarios, such as the role of biotic interactions and complex dispersal syndromes.

Travelling with a parasite: the evolution of resistance and dispersal syndromes during experimental range expansion.

Rapid evolutionary change during range expansions can lead to diverging range core and front populations, with the emergence of dispersal syndromes (coupled responses in dispersal and life-history traits). Besides intraspecific effects, range expansions may be impacted by interspecific interactions such as parasitism. Yet, despite the potentially large impact of parasites imposing additional selective pressures on the host, their role on range expansions remains largely unexplored. Using microcosm populations of the ciliate Paramecium caudatum and its bacterial parasite Holospora undulata, we studied experimental range expansions under parasite presence or absence. We found that the interaction of range expansion and parasite treatments affected the evolution of host dispersal syndromes. Namely, front populations showed different associations of population growth parameters and swimming behaviours than core populations, indicating divergent evolution. Parasitism reshaped trait associations, with hosts evolved in the presence of the parasite exhibiting overall increased resistance and reduced dispersal. Nonetheless, when comparing infected range core and front populations, we found a positive association, suggesting joint evolution of resistance and dispersal at the front. We conclude that host-parasite interactions during range expansions can change evolutionary trajectories; this in turn may feedback on the ecological dynamics of the range expansion and parasite epidemics.

Evolution of thermal performance curves: A meta-analysis of selection experiments.

Temperatures are increasing due to global changes, putting biodiversity at risk. Organisms are faced with a limited set of options to cope with this situation: adapt, disperse or die. We here focus on the first possibility, more specifically, on evolutionary adaptations to temperature. Ectotherms are usually characterized by a hump-shaped relationship between fitness and temperature, a non-linear reaction norm that is referred to as thermal performance curve (TPC). To understand and predict impacts of global change, we need to know whether and how such TPCs evolve. Therefore, we performed a systematic literature search and a statistical meta-analysis focusing on experimental evolution and artificial selection studies. This focus allows us to directly quantify relative fitness responses to temperature selection by calculating fitness differences between TPCs from ancestral and derived populations after thermal selection. Out of 7561 publications screened, we found 47 studies corresponding to our search criteria representing taxa across the tree of life, from bacteria, to plants and vertebrates. We show that, independently of species identity, the studies we found report a positive response to temperature selection. Considering entire TPC shapes, adaptation to higher temperatures traded off with fitness at lower temperatures, leading to niche shifts. Effects were generally stronger in unicellular organisms. By contrast, we do not find statistical support for the often discussed "Hotter is better" hypothesis. While our meta-analysis provides evidence for adaptive potential of TPCs across organisms, it also highlights that more experimental work is needed, especially for under-represented taxa, such as plants and non-model systems.

Dispersal syndromes in challenging environments: A cross-species experiment.

Dispersal is a central biological process tightly integrated into life-histories, morphology, physiology and behaviour. Such associations, or syndromes, are anticipated to impact the eco-evolutionary dynamics of spatially structured populations, and cascade into ecosystem processes. As for dispersal on its own, these syndromes are likely neither fixed nor random, but conditional on the experienced environment. We experimentally studied how dispersal propensity varies with individuals' phenotype and local environmental harshness using 15 species ranging from protists to vertebrates. We reveal a general phenotypic dispersal syndrome across studied species, with dispersers being larger, more active and having a marked locomotion-oriented morphology and a strengthening of the link between dispersal and some phenotypic traits with environmental harshness. Our proof-of-concept metacommunity model further reveals cascading effects of context-dependent syndromes on the local and regional organisation of functional diversity. Our study opens new avenues to advance our understanding of the functioning of spatially structured populations, communities and ecosystems.

Genetic architecture of dispersal and local adaptation drives accelerating range expansions.

Contemporary evolution has the potential to significantly alter biotic responses to global change, including range expansion dynamics and biological invasions. Models predicting range dynamics often make highly simplifying assumptions about the genetic architecture underlying relevant traits. However, genetic architecture defines evolvability and higher-order evolutionary processes, which determine whether evolution will be able to keep up with environmental change or not. Therefore, we here study the impact of the genetic architecture of dispersal and local adaptation, two central traits of high relevance for range expansions, on the dynamics and predictability of invasion into an environmental gradient, such as temperature. In our theoretical model we assume that dispersal and local adaptation traits result from the products of two noninteracting gene-regulatory networks (GRNs). We compare our model to simpler quantitative genetics models and show that in the GRN model, range expansions are accelerating and less predictable. We further find that accelerating dynamics in the GRN model are primarily driven by an increase in the rate of local adaptation to novel habitats which results from greater sensitivity to mutation (decreased robustness) and increased gene expression. Our results highlight how processes at microscopic scales, here within genomes, can impact the predictions of large-scale, macroscopic phenomena, such as range expansions, by modulating the rate of evolution.

Scaling up our understanding of tipping points.

Anthropogenic activities are increasingly affecting ecosystems across the globe. Meanwhile, empirical and theoretical evidence suggest that natural systems can exhibit abrupt collapses in response to incremental increases in the stressors, sometimes with dramatic ecological and economic consequences. These catastrophic shifts are faster and larger than expected from the changes in the stressors and happen once a tipping point is crossed. The primary mechanisms that drive ecosystem responses to perturbations lie in their architecture of relationships, i.e. how species interact with each other and with the physical environment and the spatial structure of the environment. Nonetheless, existing theoretical work on catastrophic shifts has so far largely focused on relatively simple systems that have either few species and/or no spatial structure. This work has laid a critical foundation for understanding how abrupt responses to incremental stressors are possible, but it remains difficult to predict (let alone manage) where or when they are most likely to occur in more complex real-world settings. Here, we discuss how scaling up our investigations of catastrophic shifts from simple to more complex-species rich and spatially structured-systems could contribute to expanding our understanding of how nature works and improve our ability to anticipate the effects of global change on ecological systems. This article is part of the theme issue 'Ecological complexity and the biosphere: the next 30 years'.

Spatial autocorrelation of local patch extinctions drives recovery dynamics in metacommunities.

Human activities put ecosystems under increasing pressure, often resulting in local extinctions. However, it is unclear how local extinctions affect regional processes, such as the distribution of diversity in space, especially if extinctions show spatial patterns, such as being clustered. Therefore, it is crucial to investigate extinctions and their consequences in a spatially explicit framework. Using highly controlled microcosm experiments and theoretical models, we ask here how the number and spatial autocorrelation of extinctions interactively affect metacommunity dynamics. We found that local patch extinctions increased local diversity (α-diversity) and inter-patch diversity (ß-diversity) by delaying the exclusion of inferior competitors. Importantly, recolonization dynamics depended more strongly on the spatial distribution than on the number of patch extinctions: clustered local patch extinctions resulted in slower recovery, lower α-diversity and higher ß-diversity. Our results highlight that the spatial distribution of perturbations should be taken into account when studying and managing spatially structured communities.

Selection on growth rate and local adaptation drive genomic adaptation during experimental range expansions in the protist Tetrahymena thermophila.

Populations that expand their range can undergo rapid evolutionary adaptation of life-history traits, dispersal behaviour and adaptation to the local environment. Such adaptation may be aided or hindered by sexual reproduction, depending on the context. However, few empirical and experimental studies have investigated the genetic basis of adaptive evolution during range expansions. Even less attention has been given to the question how sexual reproduction may modulate such adaptive evolution during range expansions. We here studied genomic adaptation during experimental range expansions of the protist Tetrahymena thermophila in landscapes with a uniform environment or a pH gradient. Specifically, we investigated two aspects of genomic adaptation during range expansion. First, we investigated adaptive genetic change in terms of the underlying numbers of allele frequency changes from standing genetic variation and de novo variants. We focused on how sexual reproduction may alter this adaptive genetic change. Second, we identified genes subject to selection caused by the expanding range itself, and directional selection due to the presence or absence of the pH gradient. We focused this analysis on alleles with large frequency changes that occurred in parallel in more than one population to identify the most likely candidate targets of selection. We found that sexual reproduction altered adaptive genetic change both in terms of de novo variants and standing genetic variation. However, sexual reproduction affected allele frequency changes in standing genetic variation only in the absence of long-distance gene flow. Adaptation to the range expansion affected genes involved in cell divisions and DNA repair, whereas adaptation to the pH gradient additionally affected genes involved in ion balance and oxidoreductase reactions. These genetic changes may result from selection on growth and adaptation to low pH. In the absence of gene flow, sexual reproduction may have aided genetic adaptation. Gene flow may have swamped expanding populations with maladapted alleles, thus reducing the extent of evolutionary adaptation during range expansion. Sexual reproduction also altered the genetic basis of adaptation in our evolving populations via de novo variants, possibly by purging deleterious mutations or by revealing fitness benefits of rare genetic variants.

Dispersal behaviour and riverine network connectivity shape the genetic diversity of freshwater amphipod metapopulations.

Theory predicts that the distribution of genetic diversity in a landscape is strongly dependent on the connectivity of the metapopulation and the dispersal of individuals between patches. However, the influence of explicit spatial configurations such as dendritic landscapes on the genetic diversity of metapopulations is still understudied, and theoretical corroborations of empirical patterns are largely lacking. Here, we used microsatellite data and stochastic simulations of two metapopulations of freshwater amphipods in a 28,000 km2 riverine network to study the influence of spatial connectivity and dispersal strategies on the spatial distribution of their genetic diversity. We found a significant imprint of the effects of riverine network connectivity on the local and global genetic diversity of both amphipod species. Data from 95 sites showed that allelic richness significantly increased towards more central nodes of the network. This was also seen for observed heterozygosity, yet not for expected heterozygosity. Genetic differentiation increased with instream distance. In simulation models, depending on the mutational model assumed, upstream movement probability and dispersal rate, respectively, emerged as key factors explaining the empirically observed distribution of local genetic diversity and genetic differentiation. Surprisingly, the role of site-specific carrying capacities, for example by assuming a direct dependency of population size on local river size, was less clear cut: while our best fitting model scenario included this feature, over all simulations, scaling of carrying capacities did not increase data-model fit. This highlights the importance of dispersal behaviour along spatial networks in shaping population genetic diversity.

Parasitism and host dispersal plasticity in an aquatic model system.

Dispersal is a central determinant of spatial dynamics in communities and ecosystems, and various ecological factors can shape the evolution of constitutive and plastic dispersal behaviours. One important driver of dispersal plasticity is the biotic environment. Parasites, for example, influence the internal condition of infected hosts and define external patch quality. Thus, state-dependent dispersal may be determined by infection status and context-dependent dispersal by the abundance of infected hosts in the population. A prerequisite for such dispersal plasticity to evolve is a genetic basis on which natural selection can act. Using interconnected microcosms, we investigated dispersal in experimental populations of the freshwater protist Paramecium caudatum in response to the bacterial parasite Holospora undulata. For a collection of 20 natural host strains, we found substantial variation in constitutive dispersal and to a lesser degree in dispersal plasticity. First, infection tended to increase or decrease dispersal relative to uninfected controls, depending on strain identity, indicative of state-dependent dispersal plasticity. Infection additionally decreased host swimming speed compared to the uninfected counterparts. Second, for certain strains, there was a weak negative association between dispersal and infection prevalence, such that uninfected hosts dispersed less when infection was more frequent in the population, indicating context-dependent dispersal plasticity. Future experiments may test whether the observed differences in dispersal plasticity are sufficiently strong to be picked up by natural selection. The evolution of dispersal plasticity as a strategy to mitigate parasite effects spatially may have important implications for epidemiological dynamics.

An evolutionary trade-off between parasite virulence and dispersal at experimental invasion fronts.

Exploitative parasites are predicted to evolve in highly connected populations or in expanding epidemics. However, many parasites rely on host dispersal to reach new populations, potentially causing conflict between local transmission and global spread. We performed experimental range expansions in interconnected microcosms of the protozoan Paramecium caudatum, allowing natural dispersal of hosts infected with the bacterial parasite Holospora undulata. Parasites from range front treatments facilitated host dispersal and were less virulent, but also invested less in horizontal transmission than parasites from range cores. These differences were consistent with parameter estimates derived from an epidemiological model fitted on population-level time-series data. Our results illustrate how dispersal selection can have profound consequences for the evolution of parasite life history and virulence. Decrypting the eco-evolutionary processes that shape parasite 'dispersal syndromes' may be important for the management of spreading epidemics in changing environments, biological invasions or in other spatial non-equilibrium settings.

Generation and application of river network analogues for use in ecology and evolution.

Several key processes in freshwater ecology are governed by the connectivity inherent to dendritic river networks. These have extensively been analyzed from a geomorphological and hydrological viewpoint, yet structures classically used in ecological modeling have been poorly representative of the structure of real river basins, often failing to capture well-known scaling features of natural rivers. Pioneering work identified optimal channel networks (OCNs) as spanning trees reproducing all scaling features characteristic of natural stream networks worldwide. While OCNs have been used to create landscapes for studies on metapopulations, biodiversity, and epidemiology, their generation has not been generally accessible.Given the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we provide the R-package OCNet. Owing to the stochastic process generating OCNs, multiple network replicas spanning the same surface can be built; this allows performing computational experiments whose results are irrespective of the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three-dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the package provides functions that aggregate OCNs into an arbitrary number of nodes, calculate several descriptors of river networks, and draw relevant network features.We describe the main functionalities of the package and its integration with other R-packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species.In conclusion, OCNet provides a powerful tool to generate realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems and enhances our knowledge on spatial processes in freshwater ecology in general.

Evolution in interacting species alters predator life-history traits, behaviour and morphology in experimental microbial communities.

Predator-prey interactions heavily influence the dynamics of many ecosystems. An increasing body of evidence suggests that rapid evolution and coevolution can alter these interactions, with important ecological implications, by acting on traits determining fitness, including reproduction, anti-predatory defence and foraging efficiency. However, most studies to date have focused only on evolution in the prey species, and the predator traits in (co)evolving systems remain poorly understood. Here, we investigated changes in predator traits after approximately 600 generations in a predator-prey (ciliate-bacteria) evolutionary experiment. Predators independently evolved on seven different prey species, allowing generalization of the predator's evolutionary response. We used highly resolved automated image analysis to quantify changes in predator life history, morphology and behaviour. Consistent with previous studies, we found that prey evolution impaired growth of the predator, although the effect depended on the prey species. By contrast, predator evolution did not cause a clear increase in predator growth when feeding on ancestral prey. However, predator evolution affected morphology and behaviour, increasing size, speed and directionality of movement, which have all been linked to higher prey search efficiency. These results show that in (co)evolving systems, predator adaptation can occur in traits relevant to foraging efficiency without translating into an increased ability of the predator to grow on the ancestral prey type.

Species multidimensional effects explain idiosyncratic responses of communities to environmental change.

Environmental change can alter species' abundances within communities consistently; for example, increasing all abundances by the same percentage, or more idiosyncratically. Here, we show how comparing effects of temperature on species grown in isolation and when grown together helps our understanding of how ecological communities more generally respond to environmental change. In particular, we find that the shape of the feasibility domain (the parameter space of carrying capacities compatible with positive species' abundances) helps to explain the composition of experimental microbial communities under changing environmental conditions. First, we introduce a measure to quantify the asymmetry of a community's feasibility domain using the column vectors of the corresponding interaction matrix. These column vectors describe the effects each species has on all other species in the community (hereafter referred to as species' multidimensional effects). We show that as the asymmetry of the feasibility domain increases the relationship between species' abundance when grown together and when grown in isolation weakens. We then show that microbial communities experiencing different temperature environments exhibit patterns consistent with this theory. Specifically, communities at warmer temperatures show relatively more asymmetry; thus, the idiosyncrasy of responses is higher compared with that in communities at cooler temperatures. These results suggest that while species' interactions are typically defined at the pairwise level, multispecies dynamics can be better understood by focusing on the effects of these interactions at the community level.

Gene swamping alters evolution during range expansions in the protist Tetrahymena thermophila.

At species' range edges, individuals often face novel environmental conditions that may limit range expansion until populations adapt. The potential to adapt depends on genetic variation upon which selection can act. However, populations at species' range edges are often genetically depauperate. One mechanism increasing genetic variation is reshuffling existing variation through sex. Sex, however, can potentially limit adaptation by breaking up existing beneficial allele combinations (recombination load). The gene swamping hypothesis predicts this is specifically the case when populations expand along an abiotic gradient and asymmetric dispersal leads to numerous maladapted dispersers from the range core swamping the range edge. We used the ciliate Tetrahymena thermophila as a model for testing the gene swamping hypothesis. We performed replicated range expansions in landscapes with or without a pH-gradient, while simultaneously manipulating the occurrence of gene flow and sexual versus asexual reproduction. We show that sex accelerated evolution of local adaptation in the absence of gene flow, but hindered it in the presence of gene flow. However, sex affected adaptation independently of the pH-gradient, indicating that both abiotic gradients and the biotic gradient in population density lead to gene swamping. Overall, our results show that gene swamping alters adaptation in life-history strategies.