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The field of eco‐evolutionary dynamics is developing rapidly, with a growing number of well‐designed experiments quantifying the impact of evolution on ecological processes and patterns, ranging from population demography to community composition and ecosystem functioning. The key challenge remains to transfer the insights of these proof‐of‐principle experiments to natural settings, where multiple species interact and the dynamics are far more complex than those studied in most experiments. Here, we discuss potential pitfalls of building a framework on eco‐evolutionary dynamics that is based on data on single species studied in isolation from interspecific interactions, which can lead to both under‐ and overestimation of the impact of evolution on ecological processes. Underestimation of evolution‐driven ecological changes could occur in a single‐species approach when the focal species is involved in co‐evolutionary dynamics, whereas overestimation might occur due to increased rates of evolution following ecological release of the focal species. In order to develop a multi‐species perspective on eco‐evolutionary dynamics, we discuss the need for a broad‐sense definition of “eco‐evolutionary feedbacks” that includes any reciprocal interaction between ecological and evolutionary processes, next to a narrow‐sense definition that refers to interactions that directly feed back on the interactor that evolves. We discuss the challenges and opportunities of using more natural settings in eco‐evolutionary studies by gradually adding complexity: (a) multiple interacting species within a guild, (b) food web interactions and (c) evolving metacommunities in multiple habitat patches in a landscape. A literature survey indicated that only a few studies on microbial systems so far developed a truly multi‐species approach in their analysis of eco‐evolutionary dynamics, and mostly so in artificially constructed communities. Finally, we provide a road map of methods to study eco‐evolutionary dynamics in more natural settings. Eco‐evolutionary studies involving multiple species are necessarily demanding and might require intensive collaboration among research teams, but are highly needed. A plain language summary is available for this article. Plain Language Summary

The evolution of herbicide resistance in crop weeds presents one of the greatest challenges to agriculture and the production of food. Herbicide resistance has been studied for more than 60 yr, in the large part by researchers seeking to design effective weed control programs. As an outcome of this work, various unique questions in plant adaptation have been addressed. Here, I collate recent research on the herbicide-resistant problem in light of key questions and themes in evolution and ecology. I highlight discoveries made on herbicide-resistant weeds in three broad areas – the genetic basis of adaptation, evolutionary constraints, experimental evolution – and similarly discuss questions left to be answered. I then develop how one would use herbicideresistance evolution as a model for studying eco-evolutionary dynamics within a community context. My overall goals are to highlight important findings in the weed science literature that are relevant to themes in plant adaptation and to stimulate the use of herbicide-resistant plants as models for addressing key questions within ecology and evolution.

Global change is altering biodiversity locally and globally and subsequently affecting the dynamics of communities and ecosystems. Biodiversity can be impacted both at the interspecific (i.e., species composition of communities) and at the intraspecific (evolutionary modification of phenotypic traits through selection or plasticity) levels. Changes in intraspecific diversity have been demonstrated to generate evolutionary feedbacks acting on ecological dynamics. Quantifying the role of intraspecific trait variation, global change and their interactions on ecological dynamics is of utmost importance. Here, we used the range‐expanding dragonfly Crocothemis erythraea as a model species to test the relative effects of intraspecific trait variation in larvae and thermal conditions on the dynamics of freshwater community and ecosystem functioning. Using experimental mesocosms, we manipulated intraspecific trait variation arising from genetic (G), early developmental environment (EE) and late developmental environment (EL) contributions in a full factorial design. We showed that intraspecific trait variation arising from genetic effects has the strongest consequences on community and ecosystem dynamics relative to trait variation driven by the thermal environment (EE and EL). Importantly, the ecological effects of trait variation due to genetic effects were partly modulated by thermal conditions (G × EL, and to a lesser extent G × EE interactions) and varied among ecological response variables. For instance, the strongest G × EL effects were observed on primary productivity and zooplankton dynamics. Trait variation driven by plasticity related to early or late developmental environments has an overall weak effect on ecological dynamics. Intraspecific trait variation induced by genetic effects can affect ecological dynamics (evo‐to‐eco dynamics) more strongly than variation induced by the developmental environment. However, they likely interact to modulate the structure of communities and the functioning of ecosystems, highlighting the strong context (environmental) dependency of evo‐to‐eco dynamics. This article decomposes for the first time the genetic (evolutionary) and plastic (environmental) contributions of intraspecific trait variation to community and ecosystem dynamics. It shows the major importance of evolution for ecological dynamics.

Understanding the movement of species’ ranges is a classic ecological problem that takes on urgency in this era of global change. Historically treated as a purely ecological process, range expansion is now understood to involve eco-evolutionary feedbacks due to spatial genetic structure that emerges as populations spread.We synthesize empirical and theoretical work on the eco-evolutionary dynamics of range expansion, with emphasis on bridging directional, deterministic processes that favor evolved increases in dispersal and demographic traits with stochastic processes that lead to the random fixation of alleles and traits. We develop a framework for understanding the joint influence of these processes in changing the mean and variance of expansion speed and its underlying traits. Our synthesis of recent laboratory experiments supports the consistent role of evolution in accelerating expansion speed on average, and highlights unexpected diversity in how evolution can influence variability in speed: results not well predicted by current theory. We discuss and evaluate support for three classes of modifiers of eco-evolutionary range dynamics (landscape context, trait genetics, and biotic interactions), identify emerging themes, and suggest new directions for future work in a field that stands to increase in relevance as populations move in response to global change.

Theoretical models pertaining to feedbacks between ecological and evolutionary processes are prevalent in multiple biological fields. An integrative overview is currently lacking, due to little crosstalk between the fields and the use of different methodological approaches. Here, we review a wide range of models of eco‐evolutionary feedbacks and highlight their underlying assumptions. We discuss models where feedbacks occur both within and between hierarchical levels of ecosystems, including populations, communities and abiotic environments, and consider feedbacks across spatial scales. Identifying the commonalities among feedback models, and the underlying assumptions, helps us better understand the mechanistic basis of eco‐evolutionary feedbacks. Eco‐evolutionary feedbacks can be readily modelled by coupling demographic and evolutionary formalisms. We provide an overview of these approaches and suggest future integrative modelling avenues. Our overview highlights that eco‐evolutionary feedbacks have been incorporated in theoretical work for nearly a century. Yet, this work does not always include the notion of rapid evolution or concurrent ecological and evolutionary time scales. We show the importance of density‐ and frequency‐dependent selection for feedbacks, as well as the importance of dispersal as a central linking trait between ecology and evolution in a spatial context. A plain language summary is available for this article. Plain Language Summary

Global climate change (GCC) increasingly threatens biodiversity through the loss of species, and the transformation of entire ecosystems. Many species are challenged by the pace of GCC because they might not be able to respond fast enough to changing biotic and abiotic conditions. Species can respond either by shifting their range, or by persisting in their local habitat. If populations persist, they can tolerate climatic changes through phenotypic plasticity, or genetically adapt to changing conditions depending on their genetic variability and census population size to allow for de novo mutations. Otherwise, populations will experience demographic collapses and species may go extinct. Current approaches to predicting species responses to GCC begin to combine ecological and evolutionary information for species distribution modelling. Including an evolutionary dimension will substantially improve species distribution projections which have not accounted for key processes such as dispersal, adaptive genetic change, demography, or species interactions. However, eco‐evolutionary models require new data and methods for the estimation of a species' adaptive potential, which have so far only been available for a small number of model species. To represent global biodiversity, we need to devise large‐scale data collection strategies to define the ecology and evolutionary potential of a broad range of species, especially of keystone species of ecosystems. We also need standardized and replicable modelling approaches that integrate these new data to account for eco‐evolutionary processes when predicting the impact of GCC on species' survival. Here, we discuss different genomic approaches that can be used to investigate and predict species responses to GCC. This can serve as guidance for researchers looking for the appropriate experimental setup for their particular system. We furthermore highlight future directions for moving forward in the field and allocating available resources more effectively, to implement mitigation measures before species go extinct and ecosystems lose important functions.

AIM: Within fluvial and coastal ecosystems world‐wide, flows of water, wind and sediment generate a shifting landscape mosaic composed of bare substrate and pioneer and mature vegetation successional stages. Pioneer plant species that colonize these ecosystems at the land–water interface have developed specific traits in response to environmental constraints (response traits) and are able to modify habitat conditions by modulating geomorphic processes (effect traits). Changes in the geomorphic environment under the control of engineer plants often feed back to organism traits (feedback traits), and thereby ecosystem functioning, leading to eco‐evolutionary dynamics. Here we explain the joint foundations of fluvial and coastal ecosystems according to feedback between plants and the geomorphic environment. LOCATION: Dynamic fluvial and coastal ecosystems world‐wide. METHOD: Drawing from a pre‐existing model of ‘fluvial biogeomorphic succession’, we propose a conceptual framework showing that fluvial and coastal ‘biogeomorphic ecosystems’ are functionally similar due to eco‐evolutionary feedbacks between plants and geomorphology. RESULTS: The relationships between plant traits and their geomorphic environments within different fluvial and coastal biogeomorphic ecosystems are identified and classified within a framework of biogeomorphic functional similarity according to three criteria: (1) pioneer plants develop specific responses to the geomorphic environment; (2) engineer plants modulate the geomorphic environment; (3) geomorphic changes under biotic control within biogeomorphic ecosystems feed back to organisms. MAIN CONCLUSIONS: The conceptual framework of functional similarity proposed here will improve our capacity to analyse, compare, manage and restore fluvial and coastal biogeomorphic ecosystems world‐wide by using the same protocols based on the three criteria and four phases of the biogeomorphic succession model.

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

Marine sponges are hosts to large, diverse communities of microorganisms. These microbiomes are distinct among sponge species and from seawater bacterial communities, indicating a key role of host identity in shaping its resident microbial community. However, the factors governing intraspecific microbiome variability are underexplored and may shed light on the evolutionary and ecological relationships between host and microbiome. Here, we examined the influence of genetic variation and geographic location on the composition of the Ircinia campana microbiome. We developed new microsatellite markers to genotype I. campana from two locations in the Florida Keys, USA, and characterized their microbiomes using V4 16S rRNA amplicon sequencing. We show that microbial community composition and diversity is influenced by host genotype, with more genetically similar sponges hosting more similar microbial communities. We also found that although I. campana was not genetically differentiated between sites, microbiome composition differed by location. Our results demonstrate that both host genetics and geography influence the composition of the sponge microbiome. Host genotypic influence on microbiome composition may be due to stable vertical transmission of the microbial community from parent to offspring, making microbiomes more similar by descent. Alternatively, sponge genotypic variation may reflect variation in functional traits that influence the acquisition of environmental microbes. This study reveals drivers of microbiome variation within and among locations, and shows the importance of intraspecific variability in mediating eco‐evolutionary dynamics of host‐associated microbiomes. For the first time, the authors show that intraspecific genetic variation affects microbiome composition in a marine sponge (Ircinia campana), with positive correlations observed between genetic and microbiome similarity. This has significant implications for our understanding of the ecological and evolutionary relationships between host and microbiome in this important model system.

The long-running debate about the role of selection in maintaining genetic variation has been given new impetus by the discovery of hundreds of seasonally oscillating polymorphisms in wild Drosophila, possibly stabilized by an alternating summer-winter selection regime. Historically, there has been skepticism about the potential of temporal variation to balance polymorphism, because selection must be strong to have a meaningful stabilizing effect—unless dominance also varies over time (“reversal of dominance”). Here, we develop a simplified model of seasonally variable selection that simultaneously incorporates four different stabilizing mechanisms, including two genetic mechanisms (“cumulative overdominance” and reversal of dominance), as well as ecological “storage” (“protection from selection” and boom-bust demography). We use our model to compare the stabilizing effects of these mechanisms. Although reversal of dominance has by far the greatest stabilizing effect, we argue that the three other mechanisms could also stabilize polymorphism under plausible conditions, particularly when all three are present. With many loci subject to diminishing returns epistasis, reversal of dominance stabilizes many alleles of small effect. This makes the combination of the other three mechanisms, which are incapable of stabilizing small effect alleles, a better candidate for stabilizing the detectable frequency oscillations of large effect alleles.