Human-environment feedback and the consistency of proenvironmental behavior.

Addressing global environmental crises such as anthropogenic climate change requires the consistent adoption of proenvironmental behavior by a large part of a population. Here, we develop a mathematical model of a simple behavior-environment feedback loop to ask how the individual assessment of the environmental state combines with social interactions to influence the consistent adoption of proenvironmental behavior, and how this feeds back to the perceived environmental state. In this stochastic individual-based model, individuals can switch between two behaviors, 'active' (or actively proenvironmental) and 'baseline', differing in their perceived cost (higher for the active behavior) and environmental impact (lower for the active behavior). We show that the deterministic dynamics and the stochastic fluctuations of the system can be approximated by ordinary differential equations and a Ornstein-Uhlenbeck type process. By definition, the proenvironmental behavior is adopted consistently when, at population stationary state, its frequency is high and random fluctuations in frequency are small. We find that the combination of social and environmental feedbacks can promote the spread of costly proenvironmental behavior when neither, operating in isolation, would. To be adopted consistently, strong social pressure for proenvironmental action is necessary but not sufficient-social interactions must occur on a faster timescale compared to individual assessment, and the difference in environmental impact must be small. This simple model suggests a scenario to achieve large reductions in environmental impact, which involves incrementally more active and potentially more costly behavior being consistently adopted under increasing social pressure for proenvironmentalism.

Auditory discrimination of natural soundscapes.

A previous modelling study reported that spectro-temporal cues perceptually relevant to humans provide enough information to accurately classify "natural soundscapes" recorded in four distinct temperate habitats of a biosphere reserve [Thoret, Varnet, Boubenec, Ferriere, Le Tourneau, Krause, and Lorenzi (2020). J. Acoust. Soc. Am. 147, 3260]. The goal of the present study was to assess this prediction for humans using 2 s samples taken from the same soundscape recordings. Thirty-one listeners were asked to discriminate these recordings based on differences in habitat, season, or period of the day using an oddity task. Listeners' performance was well above chance, demonstrating effective processing of these differences and suggesting a general high sensitivity for natural soundscape discrimination. This performance did not improve with training up to 10 h. Additional results obtained for habitat discrimination indicate that temporal cues play only a minor role; instead, listeners appear to base their decisions primarily on gross spectral cues related to biological sound sources and habitat acoustics. Convolutional neural networks were trained to perform a similar task using spectro-temporal cues extracted by an auditory model as input. The results are consistent with the idea that humans exclude the available temporal information when discriminating short samples of habitats, implying a form of a sub-optimality.

Eco-evolutionary responses of the microbial loop to surface ocean warming and consequences for primary production.

Predicting the response of ocean primary production to climate warming is a major challenge. One key control of primary production is the microbial loop driven by heterotrophic bacteria, yet how warming alters the microbial loop and its function is poorly understood. Here we develop an eco-evolutionary model to predict the physiological response and adaptation through selection of bacterial populations in the microbial loop and how this will impact ecosystem function such as primary production. We find that the ecophysiological response of primary production to warming is driven by a decrease in regenerated production which depends on nutrient availability. In nutrient-poor environments, the loss of regenerated production to warming is due to decreasing microbial loop activity. However, this ecophysiological response can be opposed or even reversed by bacterial adaptation through selection, especially in cold environments: heterotrophic bacteria with lower bacterial growth efficiency are selected, which strengthens the "link" behavior of the microbial loop, increasing both new and regenerated production. In cold and rich environments such as the Arctic Ocean, the effect of bacterial adaptation on primary production exceeds the ecophysiological response. Accounting for bacterial adaptation through selection is thus critically needed to improve models and projections of the ocean primary production in a warming world.

Coevolutionary transitions from antagonism to mutualism explained by the Co-Opted Antagonist Hypothesis.

There is now good evidence that many mutualisms evolved from antagonism; why or how, however, remains unclear. We advance the Co-Opted Antagonist (COA) Hypothesis as a general mechanism explaining evolutionary transitions from antagonism to mutualism. COA involves an eco-coevolutionary process whereby natural selection favors co-option of an antagonist to perform a beneficial function and the interacting species coevolve a suite of phenotypic traits that drive the interaction from antagonism to mutualism. To evaluate the COA hypothesis, we present a generalized eco-coevolutionary framework of evolutionary transitions from antagonism to mutualism and develop a data-based, fully ecologically-parameterized model of a small community in which a lepidopteran insect pollinates some of its larval host plant species. More generally, our theory helps to reconcile several major challenges concerning the mechanisms of mutualism evolution, such as how mutualisms evolve without extremely tight host fidelity (vertical transmission) and how ecological context influences evolutionary outcomes, and vice-versa.

A multi-scale eco-evolutionary model of cooperation reveals how microbial adaptation influences soil decomposition.

The decomposition of soil organic matter (SOM) is a critical process in global terrestrial ecosystems. SOM decomposition is driven by micro-organisms that cooperate by secreting costly extracellular (exo-)enzymes. This raises a fundamental puzzle: the stability of microbial decomposition in spite of its evolutionary vulnerability to "cheaters"-mutant strains that reap the benefits of cooperation while paying a lower cost. Resolving this puzzle requires a multi-scale eco-evolutionary model that captures the spatio-temporal dynamics of molecule-molecule, molecule-cell, and cell-cell interactions. The analysis of such a model reveals local extinctions, microbial dispersal, and limited soil diffusivity as key factors of the evolutionary stability of microbial decomposition. At the scale of whole-ecosystem function, soil diffusivity influences the evolution of exo-enzyme production, which feeds back to the average SOM decomposition rate and stock. Microbial adaptive evolution may thus be an important factor in the response of soil carbon fluxes to global environmental change.

Interactions among interactions: The dynamical consequences of antagonism between mutualists.

Species often interact with multiple mutualistic partners that provide functionally different benefits and/or that interact with different life-history stages. These functionally different partners, however, may also interact directly with one another in other ways, indirectly altering net outcomes and persistence of the mutualistic system as a whole. We present a population dynamical model of a three-species system involving antagonism between species sharing a mutualist partner species with two explicit life stages. We find that, regardless of whether the antagonism is predatory or non-consumptive, persistence of the shared mutualist is possible only under a restrictive set of conditions. As the rate of antagonism between the species sharing the mutualist increases, indirect rather than direct interactions increasingly determine species' densities and sometimes result in complex, oscillatory dynamics for all species. Surprisingly, persistence of the mutualistic system is particularly dependent upon the degree to which each of the two mutualistic interactions is specialized. Our work investigates a novel mechanism by which changing ecological conditions can lead to extinction of mutualist partners and provides testable predictions regarding the interactive roles of mutualism and antagonism in net outcomes for species' densities.

Co-evolution of primitive methane-cycling ecosystems and early Earth's atmosphere and climate.

The history of the Earth has been marked by major ecological transitions, driven by metabolic innovation, that radically reshaped the composition of the oceans and atmosphere. The nature and magnitude of the earliest transitions, hundreds of million years before photosynthesis evolved, remain poorly understood. Using a novel ecosystem-planetary model, we find that pre-photosynthetic methane-cycling microbial ecosystems are much less productive than previously thought. In spite of their low productivity, the evolution of methanogenic metabolisms strongly modifies the atmospheric composition, leading to a warmer but less resilient climate. As the abiotic carbon cycle responds, further metabolic evolution (anaerobic methanotrophy) may feed back to the atmosphere and destabilize the climate, triggering a transient global glaciation. Although early metabolic evolution may cause strong climatic instability, a low CO:CH4 atmospheric ratio emerges as a robust signature of simple methane-cycling ecosystems on a globally reduced planet such as the late Hadean/early Archean Earth.

Characterizing amplitude and frequency modulation cues in natural soundscapes: A pilot study on four habitats of a biosphere reserve.

Natural soundscapes correspond to the acoustical patterns produced by biological and geophysical sound sources at different spatial and temporal scales for a given habitat. This pilot study aims to characterize the temporal-modulation information available to humans when perceiving variations in soundscapes within and across natural habitats. This is addressed by processing soundscapes from a previous study [Krause, Gage, and Joo. (2011). Landscape Ecol. 26, 1247] via models of human auditory processing extracting modulation at the output of cochlear filters. The soundscapes represent combinations of elevation, animal, and vegetation diversity in four habitats of the biosphere reserve in the Sequoia National Park (Sierra Nevada, USA). Bayesian statistical analysis and support vector machine classifiers indicate that: (i) amplitude-modulation (AM) and frequency-modulation (FM) spectra distinguish the soundscapes associated with each habitat; and (ii) for each habitat, diurnal and seasonal variations are associated with salient changes in AM and FM cues at rates between about 1 and 100 Hz in the low (<0.5 kHz) and high (>1-3 kHz) audio-frequency range. Support vector machine classifications further indicate that soundscape variations can be classified accurately based on these perceptually inspired representations.

Author Correction: Biotic soil-plant interaction processes explain most of hysteretic soil CO2 efflux response to temperature in cross-factorial mesocosm experiment.

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

Biotic soil-plant interaction processes explain most of hysteric soil CO2 efflux response to temperature in cross-factorial mesocosm experiment.

Ecosystem carbon flux partitioning is strongly influenced by poorly constrained soil CO2 efflux (Fsoil). Simple model applications (Arrhenius and Q10) do not account for observed diel hysteresis between Fsoil and soil temperature. How this hysteresis emerges and how it will respond to variation in vegetation or soil moisture remains unknown. We used an ecosystem-level experimental system to independently control potential abiotic and biotic drivers of the Fsoil-T hysteresis. We hypothesized a principally biological cause for the hysteresis. Alternatively, Fsoil hysteresis is primarily driven by thermal convection through the soil profile. We conducted experiments under normal, fluctuating diurnal soil temperatures and under conditions where we held soil temperature near constant. We found (i) significant and nearly equal amplitudes of hysteresis regardless of soil temperature regime, and (ii) the amplitude of hysteresis was most closely tied to baseline rates of Fsoil, which were mostly driven by photosynthetic rates. Together, these findings suggest a more biologically-driven mechanism associated with photosynthate transport in yielding the observed patterns of soil CO2 efflux being out of sync with soil temperature. These findings should be considered on future partitioning models of ecosystem respiration.

Local adaptation, dispersal evolution, and the spatial eco-evolutionary dynamics of invasion.

Local adaptation and dispersal evolution are key evolutionary processes shaping the invasion dynamics of populations colonizing new environments. Yet their interaction is largely unresolved. Using a single-species population model along a one-dimensional environmental gradient, we show how local competition and dispersal jointly shape the eco-evolutionary dynamics and speed of invasion. From a focal introduction site, the generic pattern predicted by our model features a temporal transition from wave-like to pulsed invasion. Each regime is driven primarily by local adaptation, while the transition is caused by eco-evolutionary feedbacks mediated by dispersal. The interaction range and cost of dispersal arise as key factors of the duration and speed of each phase. Our results demonstrate that spatial eco-evolutionary feedbacks along environmental gradients can drive strong temporal variation in the rate and structure of population spread, and must be considered to better understand and forecast invasion rates and range dynamics.

Clade diversification dynamics and the biotic and abiotic controls of speciation and extinction rates.

How ecological interactions, genetic processes, and environmental variability jointly shape the evolution of species diversity remains a challenging problem in biology. We developed an individual-based model of clade diversification to predict macroevolutionary dynamics when resource competition, genetic differentiation, and landscape fluctuations interact. Diversification begins with a phase of geographic adaptive radiation. Extinction rates rise sharply at the onset of the next phase. In this phase of niche self-structuring, speciation and extinction processes, albeit driven by biotic mechanisms (competition and hybridization), have essentially constant rates, determined primarily by the abiotic pace of landscape dynamics. The final phase of diversification begins when intense competition prevents dispersing individuals from establishing new populations. Species' ranges shrink, causing negative diversity-dependence of speciation rates. These results show how ecological and microevolutionary processes shape macroevolutionary dynamics and rates; they caution against the notion of ecological limits to diversity, and suggest new directions for the phylogenetic analysis of diversification.

The effect of competition and horizontal trait inheritance on invasion, fixation, and polymorphism.

Horizontal transfer (HT) of heritable information or 'traits' (carried by genetic elements, plasmids, endosymbionts, or culture) is widespread among living organisms. Yet current ecological and evolutionary theory addressing HT is scant. We present a modeling framework for the dynamics of two populations that compete for resources and horizontally exchange (transfer) an otherwise vertically inherited trait. Competition influences individual demographics, thereby affecting population size, which feeds back on the dynamics of transfer. This feedback is captured in a stochastic individual-based model, from which we derive a general model for the contact rate, with frequency-dependent (FD) and density-dependent (DD) rates as special cases. Taking a large-population limit on the stochastic individual-level model yields a deterministic Lotka-Volterra competition system with additional terms accounting for HT. The stability analysis of this system shows that HT can revert the direction of selection: HT can drive invasion of a deleterious trait, or prevent invasion of an advantageous trait. Due to HT, invasion does not necessarily imply fixation. Two trait values may coexist in a stable polymorphism even if their invasion fitnesses have opposite signs, or both are negative. Addressing the question of how the stochasticity of individual processes influences population fluctuations, we identify conditions on competition and mode of transfer (FD versus DD) under which the stochasticity of transfer events overwhelms demographic stochasticity. Assuming that one trait is initially rare, we derive invasion and fixation probabilities and time. In the case of costly plasmids, which are transfered unilaterally, invasion is always possible if the transfer rate is large enough; under DD and for intermediate values of the transfer rate, maintenance of the plasmid in a polymorphic population is possible. In conclusion, HT interacts with ecology (competition) in non-trivial ways. Our model provides a basis to model the influence of HT on evolutionary adaptation.

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

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

How Ecology and Landscape Dynamics Shape Phylogenetic Trees.

Whether biotic or abiotic factors are the dominant drivers of clade diversification is a long-standing question in evolutionary biology. The ubiquitous patterns of phylogenetic imbalance and branching slowdown have been taken as supporting the role of ecological niche filling and spatial heterogeneity in ecological features, and thus of biotic processes, in diversification. However, a proper theoretical assessment of the relative roles of biotic and abiotic factors in macroevolution requires models that integrate both types of factors, and such models have been lacking. In this study, we use an individual-based model to investigate the temporal patterns of diversification driven by ecological speciation in a stochastically fluctuating geographic landscape. The model generates phylogenies whose shape evolves as the clade ages. Stabilization of tree shape often occurs after ecological saturation, revealing species turnover caused by competition and demographic stochasticity. In the initial phase of diversification (allopatric radiation into an empty landscape), trees tend to be unbalanced and branching slows down. As diversification proceeds further due to landscape dynamics, balance and branching tempo may increase and become positive. Three main conclusions follow. First, the phylogenies of ecologically saturated clades do not always exhibit branching slowdown. Branching slowdown requires that competition be wide or heterogeneous across the landscape, or that the characteristics of landscape dynamics vary geographically. Conversely, branching acceleration is predicted under narrow competition or frequent local catastrophes. Second, ecological heterogeneity does not necessarily cause phylogenies to be unbalanced--short time in geographical isolation or frequent local catastrophes may lead to balanced trees despite spatial heterogeneity. Conversely, unbalanced trees can emerge without spatial heterogeneity, notably if competition is wide. Third, short isolation time causes a radically different and quite robust pattern of phylogenies that are balanced and yet exhibit branching slowdown. In conclusion, biotic factors have a strong and diverse influence on the shape of phylogenies of ecologically saturating clades and create the evolutionary template in which branching slowdown and tree imbalance may occur. However, the contingency of landscape dynamics and resource distribution can cause wide variation in branching tempo and tree balance. Finally, considerable variation in tree shape among simulation replicates calls for caution when interpreting variation in the shape of real phylogenies.

Stochastic dynamics of adaptive trait and neutral marker driven by eco-evolutionary feedbacks.

How the neutral diversity is affected by selection and adaptation is investigated in an eco-evolutionary framework. In our model, we study a finite population in continuous time, where each individual is characterized by a trait under selection and a completely linked neutral marker. Population dynamics are driven by births and deaths, mutations at birth, and competition between individuals. Trait values influence ecological processes (demographic events, competition), and competition generates selection on trait variation, thus closing the eco-evolutionary feedback loop. The demographic effects of the trait are also expected to influence the generation and maintenance of neutral variation. We consider a large population limit with rare mutation, under the assumption that the neutral marker mutates faster than the trait under selection. We prove the convergence of the stochastic individual-based process to a new measure-valued diffusive process with jumps that we call Substitution Fleming-Viot Process (SFVP). When restricted to the trait space this process is the Trait Substitution Sequence first introduced by Metz et al. (1996). During the invasion of a favorable mutation, a genetical bottleneck occurs and the marker associated with this favorable mutant is hitchhiked. By rigorously analysing the hitchhiking effect and how the neutral diversity is restored afterwards, we obtain the condition for a time-scale separation; under this condition, we show that the marker distribution is approximated by a Fleming-Viot distribution between two trait substitutions. We discuss the implications of the SFVP for our understanding of the dynamics of neutral variation under eco-evolutionary feedbacks and illustrate the main phenomena with simulations. Our results highlight the joint importance of mutations, ecological parameters, and trait values in the restoration of neutral diversity after a selective sweep.

Climate and atmosphere simulator for experiments on ecological systems in changing environments.

Grand challenges in global change research and environmental science raise the need for replicated experiments on ecosystems subjected to controlled changes in multiple environmental factors. We designed and developed the Ecolab as a variable climate and atmosphere simulator for multifactor experimentation on natural or artificial ecosystems. The Ecolab integrates atmosphere conditioning technology optimized for accuracy and reliability. The centerpiece is a highly contained, 13-m(3) chamber to host communities of aquatic and terrestrial species and control climate (temperature, humidity, rainfall, irradiance) and atmosphere conditions (O2 and CO2 concentrations). Temperature in the atmosphere and in the water or soil column can be controlled independently of each other. All climatic and atmospheric variables can be programmed to follow dynamical trajectories and simulate gradual as well as step changes. We demonstrate the Ecolab's capacity to simulate a broad range of atmospheric and climatic conditions, their diurnal and seasonal variations, and to support the growth of a model terrestrial plant in two contrasting climate scenarios. The adaptability of the Ecolab design makes it possible to study interactions between variable climate-atmosphere factors and biotic disturbances. Developed as an open-access, multichamber platform, this equipment is available to the international scientific community for exploring interactions and feedbacks between ecological and climate systems.

Eco-evolutionary feedbacks, adaptive dynamics and evolutionary rescue theory.

Adaptive dynamics theory has been devised to account for feedbacks between ecological and evolutionary processes. Doing so opens new dimensions to and raises new challenges about evolutionary rescue. Adaptive dynamics theory predicts that successive trait substitutions driven by eco-evolutionary feedbacks can gradually erode population size or growth rate, thus potentially raising the extinction risk. Even a single trait substitution can suffice to degrade population viability drastically at once and cause 'evolutionary suicide'. In a changing environment, a population may track a viable evolutionary attractor that leads to evolutionary suicide, a phenomenon called 'evolutionary trapping'. Evolutionary trapping and suicide are commonly observed in adaptive dynamics models in which the smooth variation of traits causes catastrophic changes in ecological state. In the face of trapping and suicide, evolutionary rescue requires that the population overcome evolutionary threats generated by the adaptive process itself. Evolutionary repellors play an important role in determining how variation in environmental conditions correlates with the occurrence of evolutionary trapping and suicide, and what evolutionary pathways rescue may follow. In contrast with standard predictions of evolutionary rescue theory, low genetic variation may attenuate the threat of evolutionary suicide and small population sizes may facilitate escape from evolutionary traps.

Evolutionary rescue: an emerging focus at the intersection between ecology and evolution.

There is concern that the rate of environmental change is now exceeding the capacity of many populations to adapt. Mitigation of biodiversity loss requires science that integrates both ecological and evolutionary responses of populations and communities to rapid environmental change, and can identify the conditions that allow the recovery of declining populations. This special issue focuses on evolutionary rescue (ER), the idea that evolution might occur sufficiently fast to arrest population decline and allow population recovery before extinction ensues. ER emphasizes a shift to a perspective on evolutionary dynamics that focuses on short time-scales, genetic variants of large effects and absolute rather than relative fitness. The contributions in this issue reflect the state of field; the articles address the latest conceptual developments, and report novel theoretical and experimental results. The examples in this issue demonstrate that this burgeoning area of research can inform problems of direct practical concern, such as the conservation of biodiversity, adaptation to climate change and the emergence of infectious disease. The continued development of research on ER will be necessary if we are to understand the extent to which anthropogenic global change will reduce the Earth's biodiversity.

Eco-evolutionary community dynamics: covariation between diversity and invasibility across temperature gradients.

Understanding biodiversity gradients is a long-standing challenge, and progress requires theory unifying ecology and evolution. Here, we unify concepts related to the speed of evolution, the influence of species richness on diversification, and niche-based coexistence. We focus on the dynamics, through evolutionary time, of community invasibility and species richness across a broad thermal gradient. In our framework, the evolution of body size influences the ecological structure and dynamics of a trophic network, and organismal metabolism ties temperature to eco-evolutionary processes. The framework distinguishes ecological invasibility (governed by ecological interactions) from evolutionary invasibility (governed by local ecology and constraints imposed by small phenotypic effects of mutation). The model yields four primary predictions: (1) ecological invasibility declines through time and with increasing temperature; (2) average evolutionary invasibility across communities increases and then decreases through time as the richness-temperature gradient flattens; (3) in the early stages of diversification, richness and evolutionary invasibility both increase with increasing temperature; and (4) at equilibrium, richness does not vary with temperature, yet evolutionary invasibility decreases with increasing temperature. These predictions emerge from the "evolutionary-speed" hypothesis, which attempts to account for latitudinal species richness gradients by invoking faster biological rates in warmer, tropical regions. The model contrasts with predictions from other richness-gradient hypotheses, such as "niche conservatism" and "species energy." Empirically testing our model's predictions should help distinguish among these hypotheses.