Recent evolutionary history predicts population but not ecosystem‐level patterns

In the face of rapid anthropogenic environmental change, it is increasingly important to understand how ecological and evolutionary interactions affect the persistence of natural populations. Augmented gene flow has emerged as a potentially effective management strategy to counteract negative consequences of genetic drift and inbreeding depression in small and isolated populations. However, questions remain about the long‐term impacts of augmented gene flow and whether changes in individual and population fitness are reflected in ecosystem structure, potentiating eco‐evolutionary feedbacks. In this study, we used Trinidadian guppies (Poecilia reticulata) in experimental outdoor mesocosms to assess how populations with different recent evolutionary histories responded to a scenario of severe population size reduction followed by expansion in a high‐quality environment. We also investigated how variation in evolutionary history of the focal species affected ecosystem dynamics. We found that evolutionary history (i.e., gene flow vs. no gene flow) consistently predicted variation in individual growth. In addition, gene flow led to faster population growth in populations from one of the two drainages, but did not have measurable impacts on the ecosystem variables we measured: zooplankton density, algal growth, and decomposition rates. Our results suggest that benefits of gene flow may be long‐term and environment‐dependent. Although small in replication and duration, our study highlights the importance of eco‐evolutionary interactions in determining population persistence and sets the stage for future work in this area.     

Predicting patterns of long‐term adaptation and extinction with population genetics

Population genetics struggles to model extinction; standard models track the relative rather than absolute fitness of genotypes, while the exceptions describe only the short‐term transition from imminent doom to evolutionary rescue. But extinction can result from failure to adapt not only to catastrophes, but also to a backlog of environmental challenges. We model long‐term adaptation to long series of small challenges, where fitter populations reach higher population sizes. The population's long‐term fitness dynamic is well approximated by a simple stochastic Markov chain model. Long‐term persistence occurs when the rate of adaptation exceeds the rate of environmental deterioration for some genotypes. Long‐term persistence times are consistent with typical fossil species persistence times of several million years. Immediately preceding extinction, fitness declines rapidly, appearing as though a catastrophe disrupted a stably established population, even though gradual evolutionary processes are responsible. New populations go through an establishment phase where, despite being demographically viable, their extinction risk is elevated. Should the population survive long enough, extinction risk later becomes constant over time.     

Eco‐evolutionary feedbacks between private and public goods: evidence from toxic algal blooms

The importance of ‘eco‐evolutionary feedbacks’ in natural systems is currently unclear. Here, we advance a general hypothesis for a particular class of eco‐evolutionary feedbacks with potentially large, long‐lasting impacts in complex ecosystems. These eco‐evolutionary feedbacks involve traits that mediate important interactions with abiotic and biotic features of the environment and a self‐driven reversal of selection as the ecological impact of the trait varies between private (small scale) and public (large scale). Toxic algal blooms may involve such eco‐evolutionary feedbacks due to the emergence of public goods. We review evidence that toxin production by microalgae may yield ‘privatised’ benefits for individual cells or colonies under pre‐ and early‐bloom conditions; however, the large‐scale, ecosystem‐level effects of toxicity associated with bloom states yield benefits that are necessarily ‘public’. Theory predicts that the replacement of private with public goods may reverse selection for toxicity in the absence of higher level selection. Indeed, blooms often harbor significant genetic and functional diversity: bloom populations may undergo genetic differentiation over a scale of days, and even genetically similar lineages may vary widely in toxic potential. Intriguingly, these observations find parallels in terrestrial communities, suggesting that toxic blooms may serve as useful models for eco‐evolutionary dynamics in nature. Eco‐evolutionary feedbacks involving the emergence of a public good may shed new light on the potential for interactions between ecology and evolution to influence the structure and function of entire ecosystems.     

Quantifying the effects of migration and mutation on adaptation and demography in spatially heterogeneous environments

How do mutation and gene flow influence population persistence, niche expansion and local adaptation in spatially heterogeneous environments? In this article, we analyse a demographic and evolutionary model of adaptation to an environment containing two habitats in equal frequencies, and we bridge the gap between different theoretical frameworks. Qualitatively, our model yields four qualitative types of outcomes: (i) global extinction of the population, (ii) adaptation to one habitat only, but also adaptation to both habitats with, (iii) specialized phenotypes or (iv) with generalized phenotypes, and we determine the conditions under which each equilibrium is reached. We derive new analytical approximations for the local densities and the distributions of traits in each habitat under a migration–selection–mutation balance, compute the equilibrium values of the means, variances and asymmetries of the local distributions of phenotypes, and contrast the effects of migration and mutation on the evolutionary outcome. We then check our analytical results by solving our model numerically, and also assess their robustness in the presence of demographic stochasticity. Although increased migration results in a decrease in local adaptation, mutation in our model does not influence the values of the local mean traits. Yet, both migration and mutation can have dramatic effects on population size and even lead to metapopulation extinction when selection is strong. Niche expansion, the ability for the population to adapt to both habitats, can also be prevented by small migration rates and a reduced evolutionary potential characterized by rare mutation events of small effects; however, niche expansion is otherwise the most likely outcome. Although our results are derived under the assumption of clonal reproduction, we finally show and discuss the links between our model and previous quantitative genetics models.     

Eco‐evolutionary feedback promotes Red Queen dynamics and selects for sex in predator populations

Although numerous hypotheses exist to explain the overwhelming presence of sexual reproduction across the tree of life, we still cannot explain its prevalence when considering all inherent costs involved. The Red Queen hypothesis states that sex is maintained because it can create novel genotypes with a selective advantage. This occurs when the interactions between species induce frequent environmental change. Here, we investigate whether coevolution and eco‐evolutionary feedback dynamics in a predator‐prey system allows for indirect selection and maintenance of sexual reproduction in the predator. Combining models and chemostat experiments of a rotifer‐algae system we show a continuous feedback between population and trait change along with recurrent shifts from selection by predation and competition for a limited resource. We found that a high propensity for sex was indirectly selected and was maintained in rotifer populations within environments containing these eco‐evolutionary dynamics; whereas within environments under constant conditions, predators evolved rapidly to lower levels of sex. Thus, our results indicate that the influence of eco‐evolutionary feedback dynamics on the overall evolutionary change has been underestimated.     

The genomic signature of parallel adaptation from shared genetic variation

Parallel adaptation is common and may often occur from shared genetic variation, but the genomic consequences of this process remain poorly understood. We first use individual‐based simulations to demonstrate that comparisons between populations adapted in parallel to similar environments from shared variation reveal a characteristic genomic signature around a selected locus: a low‐divergence valley centred at the locus and flanked by twin peaks of high divergence. This signature is initiated by the hitchhiking of haplotype tracts differing between derived populations in the broader neighbourhood of the selected locus (driving the high‐divergence twin peaks) and shared haplotype tracts in the tight neighbourhood of the locus (driving the low‐divergence valley). This initial hitchhiking signature is reinforced over time because the selected locus acts as a barrier to gene flow from the source to the derived populations, thus promoting divergence by drift in its close neighbourhood. We next empirically confirm the peak‐valley‐peak signature by combining targeted and RAD sequence data at three candidate adaptation genes in multiple marine (source) and freshwater (derived) populations of threespine stickleback. Finally, we use a genome‐wide screen for the peak‐valley‐peak signature to discover additional genome regions involved in parallel marine‐freshwater divergence. Our findings offer a new explanation for heterogeneous genomic divergence and thus challenge the standard view that peaks in population divergence harbour divergently selected loci and that low‐divergence regions result from balancing selection or localized introgression. We anticipate that genome scans for peak‐valley‐peak divergence signatures will promote the discovery of adaptation genes in other organisms.     

Lack of adaptation from standing genetic variation despite the presence of putatively adaptive alleles in introduced sweet vernal grass (Anthoxanthum odoratum)

Population genetic theory predicts that the availability of appropriate standing genetic variation should facilitate rapid evolution when species are introduced to new environments. However, few tests of rapid evolution have been paired with empirical surveys for the presence of previously identified adaptive genetic variants in natural populations. In this study, we examined local adaptation to soil Al toxicity in the introduced range of sweet vernal grass (Anthoxanthum odoratum), and we genotyped populations for the presence of Al tolerance alleles previously identified at the long‐term ecological Park Grass Experiment (PGE, Harpenden, UK) in the species native range. We found that markers associated with Al tolerance at the PGE were present at appreciable frequency in introduced populations. Despite this, there was no strong evidence of local adaptation to soil Al toxicity among populations. Populations demonstrated significantly different intrinsic root growth rates in the absence of Al. This suggests that selection on correlated root growth traits may constrain the ability of populations to evolve significantly different root growth responses to Al. Our results demonstrate that genotype–phenotype associations may differ substantially between the native and introduced parts of a species range and that adaptive alleles from a native species range may not necessarily promote phenotypic differentiation in the introduced range.     

What can genetics tell us about population connectivity?

Genetic data are often used to assess ‘population connectivity’ because it is difficult to measure dispersal directly at large spatial scales. Genetic connectivity, however, depends primarily on the absolute number of dispersers among populations, whereas demographic connectivity depends on the relative contributions to population growth rates of dispersal vs. local recruitment (i.e. survival and reproduction of residents). Although many questions are best answered with data on genetic connectivity, genetic data alone provide little information on demographic connectivity. The importance of demographic connectivity is clear when the elimination of immigration results in a shift from stable or positive population growth to negative population growth. Otherwise, the amount of dispersal required for demographic connectivity depends on the context (e.g. conservation or harvest management), and even high dispersal rates may not indicate demographic interdependence. Therefore, it is risky to infer the importance of demographic connectivity without information on local demographic rates and how those rates vary over time. Genetic methods can provide insight on demographic connectivity when combined with these local demographic rates, data on movement behaviour, or estimates of reproductive success of immigrants and residents. We also consider the strengths and limitations of genetic measures of connectivity and discuss three concepts of genetic connectivity that depend upon the evolutionary criteria of interest: inbreeding connectivity, drift connectivity, and adaptive connectivity. To conclude, we describe alternative approaches for assessing population connectivity, highlighting the value of combining genetic data with capture‐mark‐recapture methods or other direct measures of movement to elucidate the complex role of dispersal in natural populations.