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Biologists have long sought to predict the distribution of species across landscapes to understand biodiversity patterns and dynamics. These efforts usually integrate ecological niche and dispersal dynamics, but evolution can also mediate these ecological dynamics. Species that disperse well and arrive early might adapt to local conditions, which creates an evolution-mediated priority effect that alters biodiversity patterns. Yet, dispersal is also a trait that can evolve and affect evolution-mediated priority effects. We developed an individual-based model where populations of competing species can adapt not only to local environments but also to different dispersal probabilities. We found that lower regional species diversity selects for populations with higher dispersal probabilities and stronger evolution-mediated priority effects. When all species evolved dispersal, they monopolized fewer patches and did so at the same rates. When only one of the species evolved dispersal, it evolved lower dispersal than highly dispersive species and monopolized habitats once freed from maladaptive gene flow. Overall, we demonstrate that dispersal evolution can shape evolution-mediated priority effects when provided with a greater ecological opportunity in species-poor communities. Dispersal- and evolution-mediated priority effects probably play greater roles in species-poor regions like the upper latitudes, isolated islands and in changing environments. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.

Urbanization is a persistent and widespread driver of global environmental change, potentially shaping evolutionary processes due to genetic drift and reduced gene flow in cities induced by habitat fragmentation and small population sizes. We tested this prediction for the eastern grey squirrel (Sciurus carolinensis), a common and conspicuous forest-dwelling rodent, by obtaining 44K SNPs using reduced representation sequencing (ddRAD) for 403 individuals sampled across the species' native range in eastern North America. We observed moderate levels of genetic diversity, low levels of inbreeding, and only a modest signal of isolation-by-distance. Clustering and migration analyses show that estimated levels of migration and genetic connectivity were higher than expected across cities and forested areas, specifically within the eastern portion of the species' range dominated by urbanization, and genetic connectivity was less than expected within the western range where the landscape is fragmented by agriculture. Landscape genetic methods revealed greater gene flow among individual squirrels in forested regions, which likely provide abundant food and shelter for squirrels. Although gene flow appears to be higher in areas with more tree cover, only slight discontinuities in gene flow suggest eastern grey squirrels have maintained connected populations across urban areas in all but the most heavily fragmented agricultural landscapes. Our results suggest urbanization shapes biological evolution in wildlife species depending strongly on the composition and habitability of the landscape matrix surrounding urban areas., (© 2023 John Wiley & Sons Ltd.)

Predicting if, when, and how populations can adapt to climate change constitutes one of the greatest challenges in science today. Here, we build from contributions to the special issue on evolutionary adaptation to climate change, a survey of its authors, and recent literature to explore the limits and opportunities for predicting adaptive responses to climate change. We outline what might be predictable now, in the future, and perhaps never even with our best efforts. More accurate predictions are expected for traits characterized by a well-understood mapping between genotypes and phenotypes and traits experiencing strong, direct selection due to climate change. A meta-analysis revealed an overall moderate trait heritability and evolvability in studies performed under future climate conditions but indicated no significant change between current and future climate conditions, suggesting neither more nor less genetic variation for adapting to future climates. Predicting population persistence and evolutionary rescue remains uncertain, especially for the many species without sufficient ecological data. Still, when polled, authors contributing to this special issue were relatively optimistic about our ability to predict future evolutionary responses to climate change. Predictions will improve as we expand efforts to understand diverse organisms, their ecology, and their adaptive potential. Advancements in functional genomic resources, especially their extension to non-model species and the union of evolutionary experiments and "omics," should also enhance predictions. Although predicting evolutionary responses to climate change remains challenging, even small advances will reduce the substantial uncertainties surrounding future evolutionary responses to climate change., Competing Interests: The authors declare no conflicts of interest. A.C., M.S., A.E., and C.T. are associate editors or special issue guest editors of Evolution Letters. Editorial processing of the manuscript was done independently of these editors., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEN).)

Rapid evolutionary adaptation could reduce the negative impacts of climate change if sufficient heritability of key traits exists under future climate conditions. Plastic responses to climate change could also reduce negative impacts. Understanding which populations are likely to respond via evolution or plasticity could therefore improve estimates of extinction risk. A large body of research suggests that the evolutionary and plastic potential of a population can be predicted by the degree of spatial and temporal climatic variation it experiences. However, we know little about the scale at which these relationships apply. Here, we test if spatial and temporal variation in temperature affects genetic variation and plasticity of fitness and a key thermal tolerance trait (critical thermal maximum; CT max ) at microgeographic scales using a metapopulation of Daphnia magna in freshwater rock pools. Specifically, we ask if (a) there is a microgeographic adaptation of CT max and fitness to differences in temperature among the pools, (b) pools with greater temporal temperature variation have more genetic variation or plasticity in CT max or fitness, and (c) increases in temperature affect the heritability of CT max and fitness. Although we observed genetic variation and plasticity in CT max and fitness, and differences in fitness among pools, we did not find support for the predicted relationships between temperature variation and genetic variation or plasticity. Furthermore, the genetic variation and plasticity we observed in CT max are unlikely sufficient to reduce the impacts of climate change. CT max plasticity was minimal and heritability was 72% lower when D. magna developed at the higher temperatures predicted under climate change. In contrast, the heritability of fitness increased by 53% under warmer temperatures, suggesting an increase in overall evolutionary potential unrelated to CT max under climate change. More research is needed to understand the evolutionary and plastic potential under climate change and how that potential will be altered in future climates., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Society for the Study of Evolution (SSE) and European Society for Evolutionary Biology (ESEN).)

The nonreducing iterative type I polyketide synthases (NR-PKSs) CoPKS1 and CoPKS4 of the webcap mushroom Cortinarius odorifer share 88 % identical amino acids. CoPKS1 almost exclusively produces a tricyclic octaketide product, atrochrysone carboxylic acid, whereas CoPKS4 shows simultaneous hepta- and octaketide synthase activity and also produces the bicyclic heptaketide 6-hydroxymusizin. To identify the region(s) controlling chain length, four chimeric enzyme variants were constructed and assayed for activity in Aspergillus niger as heterologous expression platform. We provide evidence that the β-ketoacyl synthase (KS) domain determines chain length in these mushroom NR-PKSs, even though their KS domains differ in only ten amino acids. A unique proline-rich linker connecting the acyl carrier protein with the thioesterase domain varies most between these two enzymes but is not involved in chain length control., (© 2022 The Authors. ChemBioChem published by Wiley-VCH GmbH.)

Research on the evolutionary ecology of urban areas reveals how human-induced evolutionary changes affect biodiversity and essential ecosystem services. In a rapidly urbanizing world imposing many selective pressures, a time-sensitive goal is to identify the emergent issues and research priorities that affect the ecology and evolution of species within cities. Here, we report the results of a horizon scan of research questions in urban evolutionary ecology submitted by 100 interdisciplinary scholars. We identified 30 top questions organized into six themes that highlight priorities for future research. These research questions will require methodological advances and interdisciplinary collaborations, with continued revision as the field of urban evolutionary ecology expands with the rapid growth of cities., Competing Interests: Declaration of interests No interests are declared., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Understanding drivers of metapopulation dynamics remains a critical challenge for ecology and conservation. In particular, the degree of synchrony in metapopulation dynamics determines how resilient a metapopulation is to a widespread disturbance. In this study, we used 21 years of egg mass count data across 64 nonpermanent freshwater ponds in Connecticut, USA to evaluate patterns of abundance and growth and to assess regional as well as local factors in shaping the population dynamics of wood frogs (Rana sylvatica = Lithobates sylvaticus). In particular, we asked whether a species known to undergo metapopulation dynamics exhibited spatial synchrony in abundances. With the exception of a single year when breeding took place during severe drought conditions, our analyses revealed no evidence of synchrony despite close proximity (mean minimum distance < 300 m) of breeding ponds across the 3213-ha study area. Instead, local, pond-scale conditions best predicted patterns of abundance and population growth rate. We found negative density dependence on population growth rate within ponds as well as evidence that larger neighboring pond populations had a negative effect on focal ponds. Beyond density, pond depth was a critical predictor; deeper ponds supported larger populations. Drought conditions and warm winters negatively affected populations. Overall, breeding ponds vary in critical ways that either support larger, more persistent populations or smaller populations that are not represented by breeding pairs in some years. The infrequency of spatial synchrony in this system is surprising and suggests greater resilience to stressors than would have been expected if dynamics were strongly synchronized. More generally, understanding the characteristics of systems that determine synchronous population dynamics will be critical to predicting which species are more or less resilient to widespread disturbances like land conversion or climate change., (© 2022 The Ecological Society of America.)

A major challenge in climate change biology is to explain why the impacts of climate change vary around the globe. Microclimates could explain some of this variation, but climate change biologists often overlook microclimates because they are difficult to map. Here, we map microclimates in a freshwater rock pool ecosystem and evaluate how accounting for microclimates alters predictions of climate change impacts on aquatic invertebrates. We demonstrate that average maximum temperature during the growing season can differ by 9.9-11.6°C among microclimates less than a meter apart and this microclimate variation might increase by 21% in the future if deeper pools warm less than shallower pools. Accounting for this microclimate variation significantly alters predictions of climate change impacts on aquatic invertebrates. Predictions that exclude microclimates predict low future occupancy (0.08-0.32) and persistence probabilities (2%-73%) for cold-adapted taxa, and therefore predict decreases in gamma richness and a substantial shift toward warm-adapted taxa in local communities (i.e., thermophilization). However, predictions incorporating microclimates suggest cool locations will remain suitable for cold-adapted taxa in the future, no change in gamma richness, and 825% less thermophilization. Our models also suggest that cool locations will become suitable for warm-adapted taxa and will therefore accumulate biodiversity in the future, which makes cool locations essential for biodiversity conservation. Simulated protection of the 10 coolest microclimates (9% of locations on the landscape) results in a 100% chance of conserving all focal taxa in the future. In contrast, protecting the 10 currently most biodiverse locations, a commonly employed conservation strategy, results in a 3% chance of conserving all focal taxa in the future. Our study suggests that we must account for microclimates if we hope to understand the future impacts of climate change and design effective conservation strategies to limit biodiversity loss., (© 2022 John Wiley & Sons Ltd.)

The Metabolic Theory of Ecology explains ecological variation spanning taxonomic organization, space, and time based on universal physiological relationships. The theory depends on two core parameters: the normalization constant, a mass-independent measure of metabolic rate expected to be invariant among similar species, and the scaling coefficient, a measure of metabolic change with body mass commonly assumed to follow the universal 3/4 scaling law. However, emerging evidence for adaptive microevolution of metabolic rates led us to hypothesize that metabolic rate might exhibit evolved variation among populations on microgeographic scales. To evaluate our hypothesis, we explored evidence for evolved variation in the scaling coefficient and normalization constant within a spotted salamander (Ambystoma maculatum) metapopulation in Connecticut, USA. We measured standard metabolic rate in common-garden raised spotted salamanders from 22 different populations and tested for the effects of six ecological variables suspected in advance to select for divergent physiology. We found that metabolic rate rose with body mass with a log-log slope of 0.97 that was statistically different from the expected 3/4 scaling law. Although we found no evidence for interpopulation variation in the scaling coefficient, we found evidence for interpopulation variation in the normalization constants among populations. Metabolic variation was best explained by differences in population density among ponds. Our results provide mixed support for Metabolic Theory of Ecology assumptions about parameter invariance and illustrate how fundamental physiological processes such as metabolic rate can evolve across microgeographic spatial scales., (© 2021 by the Ecological Society of America.)

Understanding how genetic variation is maintained in a metapopulation is a longstanding problem in evolutionary biology. Historical resurveys of polymorphisms have offered efficient insights about evolutionary mechanisms, but are often conducted on single, large populations, neglecting the more comprehensive view afforded by considering all populations in a metapopulation. Here, we resurveyed a metapopulation of spotted salamanders ( Ambystoma maculatum ) to understand the evolutionary drivers of frequency variation in an egg mass colour polymorphism. We found that this metapopulation was demographically, phenotypically and environmentally stable over the last three decades. However, further analysis revealed evidence for two modes of evolution in this metapopulation-genetic drift and balancing selection. Although we cannot identify the balancing mechanism from these data, our findings present a clear view of contemporary evolution in colour morph frequency and demonstrate the importance of metapopulation-scale studies for capturing a broad range of evolutionary dynamics.

A growing body of theory predicts that evolution of an early-arriving species in a new environment can produce a competitive advantage against later arriving species, therefore altering community assembly (i.e. the community monopolization hypothesis). Applications of the community monopolization hypothesis are increasing. However, experimental tests of the hypothesis are rare. Here, we provide a rare experimental demonstration of the community monopolization hypothesis using two archaeal species. We first expose one species to low- and high-temperature environments for 135 days. Populations in the high-temperature treatment evolved a 20% higher median performance when grown at high temperature. We then demonstrate that early arrival and adaptation reduce the abundance of a late-arriving species in the high-temperature environment by 63% relative to when both species arrive simultaneously and neither species is adapted to high temperature. These results are consistent with the community monopolization hypothesis and suggest that adaptation can reduce competitive dominance to alter community assembly. Hence, community monopolization might be much more common in nature than previously assumed. Our results strongly support the idea that patterns of biodiversity might often stem from a race between local adaptation and colonization of pre-adapted species.

A predator's functional response determines predator-prey interactions by describing the relationship between the number of prey available and the number eaten. Its shape and parameters fundamentally govern the dynamic equilibrium of predator-prey interactions and their joint abundances. Yet, estimates of these key parameters generally assume stasis in space and time and ignore the potential for local adaptation to alter feeding responses and the stability of trophic dynamics. Here, we evaluate if functional responses diverge among populations of spotted salamander ( Ambystoma maculatum ) larvae that face antagonistic selection on feeding strategies based on their own risk of predation. Common garden experiments revealed that spotted salamander from ponds with varying predation risks differed in their functional responses, suggesting an evolutionary response. Applying mechanistic equations, we discovered that the combined changes in attack rates, handling times and shape of the functional response enhanced feeding rate in environments with high densities of gape-limited predators. We suggest how these parameter changes could alter community equilibria and other emergent properties of food webs. Community ecologists might often need to consider how local evolution at fine scales alters key relationships in ways that alter local diversity patterns, food web dynamics, resource gradients and community responses to disturbance.

The virus causing COVID-19 has spread rapidly worldwide and threatens millions of lives. It remains unknown, as of April 2020, whether summer weather will reduce its spread, thereby alleviating strains on hospitals and providing time for vaccine development. Early insights from laboratory studies and research on related viruses predicted that COVID-19 would decline with higher temperatures, humidity, and ultraviolet (UV) light. Using current, fine-scaled weather data and global reports of infections, we develop a model that explains 36% of the variation in maximum COVID-19 growth rates based on weather and demography (17%) and country-specific effects (19%). UV light is most strongly associated with lower COVID-19 growth. Projections suggest that, without intervention, COVID-19 will decrease temporarily during summer, rebound by autumn, and peak next winter. Validation based on data from May and June 2020 confirms the generality of the climate signal detected. However, uncertainty remains high, and the probability of weekly doubling rates remains >20% throughout summer in the absence of social interventions. Consequently, aggressive interventions will likely be needed despite seasonal trends., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

Cities are uniquely complex systems regulated by interactions and feedbacks between nature and human society. Characteristics of human society-including culture, economics, technology and politics-underlie social patterns and activity, creating a heterogeneous environment that can influence and be influenced by both ecological and evolutionary processes. Increasing research on urban ecology and evolutionary biology has coincided with growing interest in eco-evolutionary dynamics, which encompasses the interactions and reciprocal feedbacks between evolution and ecology. Research on both urban evolutionary biology and eco-evolutionary dynamics frequently focuses on contemporary evolution of species that have potentially substantial ecological-and even social-significance. Still, little work fully integrates urban evolutionary biology and eco-evolutionary dynamics, and rarely do researchers in either of these fields fully consider the role of human social patterns and processes. Because cities are fundamentally regulated by human activities, are inherently interconnected and are frequently undergoing social and economic transformation, they represent an opportunity for ecologists and evolutionary biologists to study urban "socio-eco-evolutionary dynamics." Through this new framework, we encourage researchers of urban ecology and evolution to fully integrate human social drivers and feedbacks to increase understanding and conservation of ecosystems, their functions and their contributions to people within and outside cities., Competing Interests: None declared., (© 2020 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd.)

Historically, many biologists assumed that evolution and ecology acted independently because evolution occurred over distances too great to influence most ecological patterns. Today, evidence indicates that evolution can operate over a range of spatial scales, including fine spatial scales. Thus, evolutionary divergence across space might frequently interact with the mechanisms that also determine spatial ecological patterns. Here, we synthesize insights from 500 eco-evolutionary studies and develop a predictive framework that seeks to understand whether and when evolution amplifies, dampens, or creates ecological patterns. We demonstrate that local adaptation can alter everything from spatial variation in population abundances to ecosystem properties. We uncover 14 mechanisms that can mediate the outcome of evolution on spatial ecological patterns. Sometimes, evolution amplifies environmental variation, especially when selection enhances resource uptake or patch selection. The local evolution of foundation or keystone species can create ecological patterns where none existed originally. However, most often, we find that evolution dampens existing environmental gradients, because local adaptation evens out fitness across environments and thus counteracts the variation in associated ecological patterns. Consequently, evolution generally smooths out the underlying heterogeneity in nature, making the world appear less ragged than it would be in the absence of evolution. We end by highlighting the future research needed to inform a fully integrated and predictive biology that accounts for eco-evolutionary interactions in both space and time., Competing Interests: The authors declare no competing interest.

Phenotypic plasticity can be an important adaptive response to climate change, particularly for dispersal-limited species. Temperature frequently alters developmental and phenotypic traits including morphology, behavior, and reproductive cycles. We often lack crucial information about if and how thermal conditions during development will interact with genetic responses and facilitate persistence or adaptation under climate change. Polymorphic species offer an ideal test for this, as alternative morphs often confer differential adaptive advantages. However, few studies have examined the effects of incubation temperature on color expression or development in polymorphic taxa. Here we test if developmental temperature mediates morph frequency in the polymorphic salamander Plethodon cinereus. Although previous research suggests geographic variation in morph proportions results from differential climate adaptation, it remains unknown if plasticity also contributes to this variation. We used a split-clutch common garden experiment to determine the effects of developmental temperature on the color and development of P. cinereus. Our results indicate developmental temperature affects coloration in P. cinereus, either via plasticity or differential mortality, with eggs incubated at warmer temperatures yielding a higher proportion of unstriped individuals than those from cooler temperatures. This temperature response may contribute to the spatial variation in morph frequencies in natural populations. Surprisingly, we found neither temperature nor egg size affected hatchling size. Our study provides important insights into the potential for climate-induced responses to preserve diversity in dispersal-limited species, like P. cinereus, and enable time for adaptive evolution.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; "CESTES". Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.

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.

Biodiversity in natural systems can be maintained either because niche differentiation among competitors facilitates stable coexistence or because equal fitness among neutral species allows for their long-term cooccurrence despite a slow drift toward extinction. Whereas the relative importance of these two ecological mechanisms has been well-studied in the absence of evolution, the role of local adaptive evolution in maintaining biological diversity through these processes is less clear. Here we study the contribution of local adaptive evolution to coexistence in a landscape of interconnected patches subject to disturbance. Under these conditions, early colonists to empty patches may adapt to local conditions sufficiently fast to prevent successful colonization by other preadapted species. Over the long term, the iteration of these local-scale priority effects results in niche convergence of species at the regional scale even though species tend to monopolize local patches. Thus, the dynamics evolve from stable coexistence through niche differentiation to neutral cooccurrence at the landscape level while still maintaining strong local niche segregation. Our results show that neutrality can emerge at the regional scale from local, niche-based adaptive evolution, potentially resolving why ecologists often observe neutral distribution patterns at the landscape level despite strong niche divergence among local communities., Competing Interests: The authors declare no conflict of interest.

Competing Interests: The author declares no conflict of interest.

Species' distributions will respond to climate change based on the relationship between local demographic processes and climate and how this relationship varies based on range position. A rarely tested demographic prediction is that populations at the extremes of a species' climate envelope (e.g., populations in areas with the highest mean annual temperature) will be most sensitive to local shifts in climate (i.e., warming). We tested this prediction using a dynamic species distribution model linking demographic rates to variation in temperature and precipitation for wood frogs (Lithobates sylvaticus) in North America. Using long-term monitoring data from 746 populations in 27 study areas, we determined how climatic variation affected population growth rates and how these relationships varied with respect to long-term climate. Some models supported the predicted pattern, with negative effects of extreme summer temperatures in hotter areas and positive effects on recruitment for summer water availability in drier areas. We also found evidence of interacting temperature and precipitation influencing population size, such as extreme heat having less of a negative effect in wetter areas. Other results were contrary to predictions, such as positive effects of summer water availability in wetter parts of the range and positive responses to winter warming especially in milder areas. In general, we found wood frogs were more sensitive to changes in temperature or temperature interacting with precipitation than to changes in precipitation alone. Our results suggest that sensitivity to changes in climate cannot be predicted simply by knowing locations within the species' climate envelope. Many climate processes did not affect population growth rates in the predicted direction based on range position. Processes such as species-interactions, local adaptation, and interactions with the physical landscape likely affect the responses we observed. Our work highlights the need to measure demographic responses to changing climate., (Published 2017. This article is a U.S. Government work and is in the public domain in the USA.)

Exurban areas are expanding throughout the world, yet their effects on local biodiversity remain poorly understood. Wetlands, in particular, face ongoing and substantial threats from exurban development. We predicted that exurbanization would reduce the diversity of wetland amphibian and invertebrate communities and that more spatially aggregated residential development would leave more undisturbed natural land, thereby promoting greater local diversity. Using structural equation models, we tested a series of predictions about the direct and indirect pathways by which exurbanization extent, spatial pattern, and wetland characteristics might affect diversity patterns in 38 wetlands recorded during a growing season. We used redundancy, indicator species, and nested community analyses to evaluate how exurbanization affected species composition. In contrast to expectations, we found higher diversity in exurban wetlands. We also found that housing aggregation did not significantly affect diversity. Exurbanization affected biodiversity indirectly by increasing roads and development, which promoted permanent wetlands with less canopy cover and more aquatic vegetation. These pond characteristics supported greater diversity. However, exurbanization was associated with fewer temporary wetlands and fewer of the species that depend on these habitats. Moreover, the best indicator species for an exurban wetland was the ram's head snail, a common disease vector in disturbed ponds. Overall, results suggest that exurbanization is homogenizing wetlands into more permanent water bodies. These more permanent, exurban ponds support higher overall animal diversity, but exclude temporary wetland specialists. Conserving the full assemblage of wetland species in expanding exurban regions throughout the world will require protecting and creating temporary wetlands.

Climate change is altering life at multiple scales, from genes to ecosystems. Predicting the vulnerability of populations to climate change is crucial to mitigate negative impacts. We suggest that regional patterns of spatial and temporal climatic variation scaled to the traits of an organism can predict where and why populations are most vulnerable to climate change. Specifically, historical climatic variation affects the sensitivity and response capacity of populations to climate change by shaping traits and the genetic variation in those traits. Present and future climatic variation can affect both climate change exposure and population responses. We provide seven predictions for how climatic variation might affect the vulnerability of populations to climate change and suggest key directions for future research., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Synopsis: As climates change, biologists need to prioritize which species to understand, predict, and protect. One way is to identify key species that are both sensitive to climate change and that disproportionately affect communities and ecosystems. These "biotic multipliers" provide efficient targets for research and conservation. Here, we propose eight mechanistic hypotheses related to impact and sensitivity that suggest that top consumers might often act as biotic multipliers of climate change. For impact, top consumers often affect communities and ecosystems through strong top-down effects. For sensitivity, metabolic theory and data suggest that photosynthesis and respiration differ in temperature responses, potentially increasing the sensitivity of consumers relative to plants. Larger-bodied organisms are typically more thermally sensitive than smaller ones, suggesting how large top consumers might be more sensitive than their smaller prey. In addition, traits related to predation are more sensitive than defensive traits to temperature. Top consumers might also be more sensitive because they often lag behind prey in phenological responses. The combination of low population sizes and demographic traits of top consumers could make them more sensitive to disturbances like climate change, which could slow their recovery. As top consumers are positioned at the top of the food chain, many small effects can accumulate from other trophic levels to affect top consumers. Finally, top consumers also often disperse more frequently and farther than prey, potentially leading to greater sensitivity to climate-induced changes in ranges and subsequent impacts on invaded communities. Overall, we expect that large, ectothermic top consumers and mobile predators might frequently be biotic multipliers of climate change. However, this prediction depends on the particular features of species, habitats, and ecosystems. In specific cases, herbivores, plants, or pathogens might be more sensitive than top consumers or have greater community impacts. To predict biotic multipliers, we need to compare sensitivities and impacts across trophic groups in a broader range of ecosystems as well as perform experiments that uncouple proposed mechanisms. Overall, the biotic multiplier concept offers an alternative prioritization scheme for research and conservation that includes impacts on communities and ecosystems., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.)

Accurately predicting biological impacts of climate change is necessary to guide policy. However, the resolution of climate data could be affecting the accuracy of climate change impact assessments. Here, we review the spatial and temporal resolution of climate data used in impact assessments and demonstrate that these resolutions are often too coarse relative to biologically relevant scales. We then develop a framework that partitions climate into three important components: trend, variance, and autocorrelation. We apply this framework to map different global climate regimes and identify where coarse climate data is most and least likely to reduce the accuracy of impact assessments. We show that impact assessments for many large mammals and birds use climate data with a spatial resolution similar to the biologically relevant area encompassing population dynamics. Conversely, impact assessments for many small mammals, herpetofauna, and plants use climate data with a spatial resolution that is orders of magnitude larger than the area encompassing population dynamics. Most impact assessments also use climate data with a coarse temporal resolution. We suggest that climate data with a coarse spatial resolution is likely to reduce the accuracy of impact assessments the most in climates with high spatial trend and variance (e.g., much of western North and South America) and the least in climates with low spatial trend and variance (e.g., the Great Plains of the USA). Climate data with a coarse temporal resolution is likely to reduce the accuracy of impact assessments the most in the northern half of the northern hemisphere where temporal climatic variance is high. Our framework provides one way to identify where improving the resolution of climate data will have the largest impact on the accuracy of biological predictions under climate change., (© 2016 John Wiley & Sons Ltd.)

New biological models are incorporating the realistic processes underlying biological responses to climate change and other human-caused disturbances. However, these more realistic models require detailed information, which is lacking for most species on Earth. Current monitoring efforts mainly document changes in biodiversity, rather than collecting the mechanistic data needed to predict future changes. We describe and prioritize the biological information needed to inform more realistic projections of species' responses to climate change. We also highlight how trait-based approaches and adaptive modeling can leverage sparse data to make broader predictions. We outline a global effort to collect the data necessary to better understand, anticipate, and reduce the damaging effects of climate change on biodiversity., (Copyright © 2016, American Association for the Advancement of Science.)

Recent studies have supported a link between phylogenetic diversity and various ecological properties including ecosystem function. However, such studies typically assume that phylogenetic branches of equivalent length are more or less interchangeable. Here we suggest that there is a need to consider not only branch lengths but also their placement on the phylogeny. We demonstrate how two common indices of network centrality can be used to describe the evolutionary distinctiveness of network elements (nodes and branches) on a phylogeny. If phylogenetic diversity enhances ecosystem function via complementarity and the representation of functional diversity, we would predict a correlation between evolutionary distinctiveness of network elements and their contribution to ecosystem process. In contrast, if one or a few evolutionary innovations play key roles in ecosystem function, the relationship between evolutionary distinctiveness and functional contribution may be weak or absent. We illustrate how network elements associated with high functional contribution can be identified from regressions between phylogenetic diversity and productivity using a well-known empirical data set on plant productivity from the Cedar Creek Long-Term Ecological Research. We find no association between evolutionary distinctiveness and ecosystem functioning, but we are able to identify phylogenetic elements associated with species of known high functional contribution within the Fabaceae. Our perspective provides a useful guide in the search for ecological traits linking diversity and ecosystem function, and suggests a more nuanced consideration of phylogenetic diversity is required in the conservation and biodiversity-ecosystem-function literature., (© 2016 by the Ecological Society of America.)

Biologists are often confronted with high levels of unexplained variation when studying the processes that determine genetic and species diversity. Here, we argue that eco-evolutionary interactions might often play an important role during colonization and have longstanding effects on populations and communities. Adaptation following colonization can produce a strong positive feedback loop that promotes priority effects and context-dependent trajectories of population or species assembly. We establish how monopolization, and more generally evolution-mediated priority effects, influence ecological patterns at multiple scales of space, time, and biological organization. We then highlight the underappreciated implications for our understanding of population and landscape genetics, adaptive evolution, community diversity, biogeography, and conservation biology. We indicate multiple future directions for research, including extending theory beyond competition., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

Multiple theories predict the evolution of foraging rates in response to environmental variation in predation risk, intraspecific competition, time constraints, and temperature. We tested six hypotheses for the evolution of foraging rate in 24 spotted salamander (Ambystoma maculatum) populations from three latitudinally divergent sites using structural equation models derived from theory and applied to our system. We raised salamander larvae in a common-garden experiment and then assayed foraging rate under controlled conditions. Gape-limited predation risk from marbled salamanders solely explained foraging rate variation among populations at the southern site, which was dominated by this form of selection. However, at the middle and northern sites, populations evolved different foraging rates depending on their unique responses to local intraspecific density. The coupling of gape-limited predation risk from marbled salamanders and high intraspecific density at the middle site jointly contributed to selection for rapid foraging rate. At the northernmost site, intraspecific density alone explained 97% of the interpopulation variation in foraging rate. These results suggest that foraging rate has evolved multiple times in response to varying contributions from predation risk and intraspecific competition. Predation risk often varies along environmental gradients, and, thus, organisms might often shift evolutionary responses from minimizing predation risk to maximizing intraspecific competitive performance.

Current predictions of extinction risks from climate change vary widely depending on the specific assumptions and geographic and taxonomic focus of each study. I synthesized published studies in order to estimate a global mean extinction rate and determine which factors contribute the greatest uncertainty to climate change-induced extinction risks. Results suggest that extinction risks will accelerate with future global temperatures, threatening up to one in six species under current policies. Extinction risks were highest in South America, Australia, and New Zealand, and risks did not vary by taxonomic group. Realistic assumptions about extinction debt and dispersal capacity substantially increased extinction risks. We urgently need to adopt strategies that limit further climate change if we are to avoid an acceleration of global extinctions., (Copyright © 2015, American Association for the Advancement of Science.)

Dispersal has long been recognized as a mechanism that shapes many observed ecological and evolutionary processes. Thus, understanding the factors that promote its evolution remains a major goal in evolutionary ecology. Landscape connectivity may mediate the trade-off between the forces in favour of dispersal propensity (e.g. kin-competition, local extinction probability) and those against it (e.g. energetic or survival costs of dispersal). It remains, however, an open question how differing degrees of landscape connectivity may select for different dispersal strategies. We implemented an individual-based model to study the evolution of dispersal on landscapes that differed in the variance of connectivity across patches ranging from networks with all patches equally connected to highly heterogeneous networks. The parthenogenetic individuals dispersed based on a flexible logistic function of local abundance. Our results suggest, all else being equal, that landscapes differing in their connectivity patterns will select for different dispersal strategies and that these strategies confer a long-term fitness advantage to individuals at the regional scale. The strength of the selection will, however, vary across network types, being stronger on heterogeneous landscapes compared with the ones where all patches have equal connectivity. Our findings highlight how landscape connectivity can determine the evolution of dispersal strategies, which in turn affects how we think about important ecological dynamics such as metapopulation persistence and range expansion., (© 2015 The Author(s) Published by the Royal Society. All rights reserved.)

Local adaptation has been a major focus of evolutionary ecologists working across diverse systems for decades. However, little of this research has explored variation at microgeographic scales because it has often been assumed that high rates of gene flow will prevent adaptive divergence at fine spatial scales. Here, we establish a quantitative definition of microgeographic adaptation based on Wright's dispersal neighborhood that standardizes dispersal abilities, enabling this measure to be compared across species. We use this definition to evaluate growing evidence of evolutionary divergence at fine spatial scales. We identify the main mechanisms known to facilitate this adaptation and highlight illustrative examples of microgeographic evolution in nature. Collectively, this evidence requires that we revisit our understanding of the spatial scale of adaptation and consider how microgeographic adaptation and its driving mechanisms can fundamentally alter ecological and evolutionary dynamics in nature., (Copyright © 2014 Elsevier Ltd. All rights reserved.)

Phenotypic plasticity and genetic adaptation are predicted to mitigate some of the negative biotic consequences of climate change. Here, we evaluate evidence for plastic and evolutionary responses to climate variation in amphibians and reptiles via a literature review and meta-analysis. We included studies that either document phenotypic changes through time or space. Plasticity had a clear and ubiquitous role in promoting phenotypic changes in response to climate variation. For adaptive evolution, we found no direct evidence for evolution of amphibians or reptiles in response to climate change over time. However, we found many studies that documented adaptive responses to climate along spatial gradients. Plasticity provided a mixture of adaptive and maladaptive responses to climate change, highlighting that plasticity frequently, but not always, could ameliorate climate change. Based on our review, we advocate for more experiments that survey genetic changes through time in response to climate change. Overall, plastic and genetic variation in amphibians and reptiles could buffer some of the formidable threats from climate change, but large uncertainties remain owing to limited data.

We need accurate predictions about how climate change will alter species distributions and abundances around the world. Most predictions assume simplistic dispersal scenarios and ignore biotic interactions. We argue for incorporating the complexities of dispersal and species interactions. Range expansions depend not just on mean dispersal, but also on the shape of the dispersal kernel and the population's growth rate. We show how models using species-specific dispersal can produce more accurate predictions than models applying all-or-nothing dispersal scenarios. Models that additionally include species interactions can generate distinct outcomes. For example, species interactions can slow climate tracking and produce more extinctions than models assuming no interactions. We conclude that (1) just knowing mean dispersal is insufficient to predict biotic responses to climate change, and (2) considering interspecific dispersal variation and species interactions jointly will be necessary to anticipate future changes to biological diversity. We advocate for collecting key information on interspecific dispersal differences and strong biotic interactions so that we can build the more robust predictive models that will be necessary to inform conservation efforts as climates continue to change., (© 2013 New York Academy of Sciences.)

Microgeographic adaptation occurs when populations evolve divergent fitness advantages across the spatial scales at which focal organisms regularly disperse. Although an increasing number of studies find evidence for microgeographic adaptation, the underlying causes often remain unknown. Adaptive divergence requires some combination of limited gene flow and strong divergent natural selection among populations. In this study, we estimated the relative influence of selection, gene flow, and the spatial arrangement of populations in shaping patterns of adaptive divergence in natural populations of the spotted salamander (Ambystoma maculatum). Within the study region, A. maculatum co-occur with the predatory marbled salamander (Ambystoma opacum) in some ponds, and past studies have established a link between predation risk and adaptive trait variation in A. maculatum. Using 14 microsatellite loci, we found a significant pattern of genetic divergence among A. maculatum populations corresponding to levels of A. opacum predation risk. Additionally, A. maculatum foraging rate was strongly associated with predation risk, genetic divergence, and the spatial relationship of ponds on the landscape. Our results indicate the sorting of adaptive genotypes by selection regime and strongly suggest that substantial selective barriers operate against gene flow. This outcome suggests that microgeographic adaptation in A. maculatum is possible because strong antagonistic selection quickly eliminates maladapted phenotypes despite ongoing and substantial immigration. Increasing evidence for microgeographic adaptation suggests a strong role for selective barriers in counteracting the homogenizing influence of gene flow., (© 2013 The Author(s). Evolution © 2013 The Society for the Study of Evolution.)

Ecological and evolutionary mechanisms are increasingly thought to shape local community dynamics. Here, I evaluate if the local adaptation of a meso-predator to an apex predator alters local food webs. The marbled salamander (Ambystoma opacum) is an apex predator that consumes both the spotted salamander (Ambystoma maculatum) and shared zooplankton prey. Common garden experiments reveal that spotted salamander populations which co-occur with marbled salamanders forage more intensely than those that face other predator species. These foraging differences, in turn, alter the diversity, abundance and composition of zooplankton communities in common garden experiments and natural ponds. Locally adapted spotted salamanders exacerbate prey biomass declines associated with apex predation, but dampen the top-down effects of apex predation on prey diversity. Countergradient selection on foraging explains why locally adapted spotted salamanders exacerbate prey biomass declines. The two salamander species prefer different prey species, which explains why adapted spotted salamanders buffer changes in prey composition owing to apex predation. Results suggest that local adaptation can strongly mediate effects from apex predation on local food webs. Community ecologists might often need to consider the evolutionary history of populations to understand local diversity patterns, food web dynamics, resource gradients and their responses to disturbance.

Evolutionary biologists typically predict future evolutionary responses to natural selection by analysing evolution on an adaptive landscape. Much theory assumes symmetric fitness surfaces even though many stabilizing selection gradients deviate from symmetry. Here we revisit Lande's adaptive landscape and introduce novel analytical theory that includes asymmetric selection. Asymmetric selection and the resulting skewed trait distributions bias equilibrium mean phenotypes away from fitness peaks, usually toward the flatter shoulder of the individual fitness surface. We apply this theory to explain a longstanding paradox in biology and medicine: the evolution of excessive defences against enemies. These so-called extraordinary defences can evolve in response to asymmetrical selection when marginal risks of insufficient defence exceed marginal costs of excessive defence. Eco-evolutionary feedbacks between population abundances and asymmetric selection further exaggerate these defences. Recognizing the effect of asymmetrical selection on evolutionary trajectories will improve the accuracy of predictions and suggest novel explanations for apparent sub-optimality.

Most climate change predictions omit species interactions and interspecific variation in dispersal. Here, we develop a model of multiple competing species along a warming climatic gradient that includes temperature-dependent competition, differences in niche breadth and interspecific differences in dispersal ability. Competition and dispersal differences decreased diversity and produced so-called 'no-analogue' communities, defined as a novel combination of species that does not currently co-occur. Climate change altered community richness the most when species had narrow niches, when mean community-wide dispersal rates were low and when species differed in dispersal abilities. With high interspecific dispersal variance, the best dispersers tracked climate change, out-competed slower dispersers and caused their extinction. Overall, competition slowed the advance of colonists into newly suitable habitats, creating lags in climate tracking. We predict that climate change will most threaten communities of species that have narrow niches (e.g. tropics), vary in dispersal (most communities) and compete strongly. Current forecasts probably underestimate climate change impacts on biodiversity by neglecting competition and dispersal differences.

We need to understand joint ecological and evolutionary responses to climate change to predict future threats to biological diversity. The 'evolving metacommunity' framework emphasizes that interactions between ecological and evolutionary mechanisms at both local and regional scales will drive community dynamics during climate change. Theory suggests that ecological and evolutionary dynamics often interact to produce outcomes different from those predicted based on either mechanism alone. We highlight two of these dynamics: (i) species interactions prevent adaptation of nonresident species to new niches and (ii) resident species adapt to changing climates and thereby prevent colonization by nonresident species. The rate of environmental change, level of genetic variation, source-sink structure, and dispersal rates mediate between these potential outcomes. Future models should evaluate multiple species, species interactions other than competition, and multiple traits. Future experiments should manipulate factors such as genetic variation and dispersal to determine their joint effects on responses to climate change. Currently, we know much more about how climates will change across the globe than about how species will respond to these changes despite the profound effects these changes will have on global biological diversity. Integrating evolving metacommunity perspectives into climate change biology should produce more accurate predictions about future changes to species distributions and extinction threats.

Given the potential for rapid and microgeographical adaptation, ecologists increasingly are exploring evolutionary explanations for community patterns. Biotic selection can generate local adaptations that alter species interactions. Although some gene flow might be necessary to fuel local adaptation, higher gene flow can homogenise traits across regions and generate local maladaptation. Herein, I estimate the contributions of local biotic selection, gene flow and spatially autocorrelated biotic selection to among-population divergence in traits involved in species interactions across 75 studies. Local biotic selection explained 6.9% of inter-population trait divergence, an indirect estimate of restricted gene flow explained 0.1%, and spatially autocorrelated selection explained 9.3%. Together, biotic selection explained 16% of the variance in population trait means. Most biotic selection regimes were spatially autocorrelated. Hence, most populations receive gene flow from populations facing similar selection, which could allow for local adaptation despite moderate gene flow. Gene flow constrained adaptation in studies conducted at finer spatial scales as expected, but this effect was often confounded with spatially autocorrelated selection. Results indicate that traits involved in species interactions might often evolve across landscapes, especially when biotic selection is spatially autocorrelated. The frequent evolution of species interactions suggests that evolutionary processes might often influence community ecology., (© 2011 Blackwell Publishing Ltd/CNRS.)

Most predictions about species responses to climate change ignore species interactions. Helland and colleagues (2011) test whether this assumption is valid by evaluating whether ice cover affects competition between brown trout [Salmo trutta (L.)] and Arctic charr [Salvelinus alpines (L.)]. They show that increasing ice cover correlates with lower trout biomass when Arctic charr co-occur, but not in charr's absence. In experiments, charr grew better in the cold, dark environments that typify ice-covered lakes. Decreasing ice cover with warmer winters could mean more trout and fewer charr. More generally, their results provide an excellent example, suggesting that species interactions can strongly modify responses to climate change., (© 2011 The Authors. Journal of Animal Ecology © 2011 British Ecological Society.)

Natural populations consist of phenotypically diverse individuals that exhibit variation in their demographic parameters and intra- and inter-specific interactions. Recent experimental work indicates that such variation can have significant ecological effects. However, ecological models typically disregard this variation and focus instead on trait means and total population density. Under what situations is this simplification appropriate? Why might intraspecific variation alter ecological dynamics? In this review we synthesize recent theory and identify six general mechanisms by which trait variation changes the outcome of ecological interactions. These mechanisms include several direct effects of trait variation per se and indirect effects arising from the role of genetic variation in trait evolution.

Two major approaches address the need to predict species distributions in response to environmental changes. Correlative models estimate parameters phenomenologically by relating current distributions to environmental conditions. By contrast, mechanistic models incorporate explicit relationships between environmental conditions and organismal performance, estimated independently of current distributions. Mechanistic approaches include models that translate environmental conditions into biologically relevant metrics (e.g. potential duration of activity), models that capture environmental sensitivities of survivorship and fecundity, and models that use energetics to link environmental conditions and demography. We compared how two correlative and three mechanistic models predicted the ranges of two species: a skipper butterfly (Atalopedes campestris) and a fence lizard (Sceloporus undulatus). Correlative and mechanistic models performed similarly in predicting current distributions, but mechanistic models predicted larger range shifts in response to climate change. Although mechanistic models theoretically should provide more accurate distribution predictions, there is much potential for improving their flexibility and performance.