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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.

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.

1. 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.2. 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.3. 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.4. 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.

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.

Stochastic processes such as genetic drift may hinder adaptation, but the effect of such stochasticity on evolution via its effect on ecological dynamics is poorly understood. Here we evaluate patterns of adaptation in a population subject to variation in demographic stochasticity. We show that stochasticity can alter population dynamics and lead to evolutionary outcomes that are not predicted by classic eco-evolutionary modeling approaches. We also show, however, that these outcomes are governed by nonequilibrium evolutionary attractors— these are maxima in lifetime reproductive success when stochasticity keeps the ecological system away from the deterministic equilibrium. These NEEAs alter the path of evolution but are not visible through the equilibrium lens that underlies much evolutionary theory. Our results reveal that considering population processes during transient periods can greatly improve our understanding of the path and pace of evolution.

Anthropogenic habitat fragmentation is often implicated as driving the current global extinction crisis, particularly in freshwater ecosystems. The genetic signal of recent population isolation can be confounded by the complex spatial arrangement of dendritic river systems. Consequently, many populations may presently be managed separately based on an incorrect assumption that they have evolved in isolation. Integrating landscape genomics data with models of connectivity that account for landscape structure, we show that the cumulative effects of multiple in‐stream barriers have contributed to the recent decline of a freshwater fish from the Murray–Darling Basin, Australia. In addition, individual‐based eco‐evolutionary simulations further demonstrate that contemporary inferences about population isolation are consistent with the 160‐year time frame since construction of in‐stream barriers began in the region. Our findings suggest that the impact of very recent fragmentation may be often underestimated for freshwater biodiversity. We argue that proactive conservation measures to reconnect many riverine populations are urgently needed.

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.

Microbial ecosystems harbor an astonishing diversity that can persist for long times. To understand how such diversity is structured and maintained, ecological and evolutionary processes need to be integrated at similar timescales. Here, we study a model of resource competition that allows for evolution via de novo mutation, and focus on rapidly adapting asexual populations with large mutational inputs, as typical of many bacteria species. We characterize the adaptation and diversification of an initially maladapted population and show how the eco-evolutionary dynamics are shaped by the interaction between simultaneously emerging lineages–clonal interference. We find that in large populations, more intense clonal interference can foster diversification under sympatry, increasing the probability that phenotypically and genetically distinct clusters coexist. In smaller populations, the accumulation of deleterious and compensatory mutations can push further the diversification process and kick-start speciation. Our findings have implications beyond microbial populations, providing novel insights about the interplay between ecology and evolution in clonal populations.