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Climate warming is altering life cycles of ectotherms by advancing phenology and decreasing generation times. Theoretical models provide powerful tools to investigate these effects of climate warming on consumer–resource population dynamics. Yet, existing theory primarily considers organisms with simplified life histories in constant temperature environments, making it difficult to predict how warming will affect organisms with complex life cycles in seasonal environments. We develop a size-structured consumer–resource model with seasonal temperature dependence, parameterized for a freshwater insect consuming zooplankton. We simulate how climate warming in a seasonal environment could alter a key life-history trait of the consumer, number of generations per year, mediating responses of consumer–resource population sizes and consumer persistence. We find that, with warming, consumer population sizes increase through multiple mechanisms. First, warming decreases generation times by increasing rates of resource ingestion and growth and/or lengthening the growing season. Second, these life-history changes shorten the juvenile stage, increasing the number of emerging adults and population-level reproduction. Unstructured models with similar assumptions found that warming destabilized consumer–resource dynamics. By contrast, our size-structured model predicts stability and consumer persistence. Our study suggests that, in seasonal environments experiencing climate warming, life-history changes that lead to shorter generation times could delay population extinctions.

Predicting how food webs will respond to global environmental change is difficult because of the complex interplay between the abiotic forcing and biotic interactions. Mechanistic models of species interactions in seasonal environments can help understand the effects of global change in different ecosystems. Seasonally ice-covered lakes are warming faster than many other ecosystems and undergoing pronounced food web changes, making the need to forecast those changes especially urgent. Using a seasonally forced food web model with a generalist zooplankton grazer and competing cold-adapted winter and warm-adapted summer phytoplankton, we show that with declining ice cover, the food web moves through different dynamic regimes, from annual to biennial cycles, with decreasing and then disappearing winter phytoplankton blooms and a shift of maximum biomass to summer season. Interestingly, when predator-prey interactions were not included, a declining ice cover did not cause regime shifts, suggesting that both are needed for regime transitions. A cluster analysis of long-term data from Lake Baikal, Siberia, supports the model results, revealing a change from regularly occurring winter blooms of endemic diatoms to less frequent winter bloom years with decreasing ice cover. Together, the results show that even gradual environmental change, such as declining ice cover duration, may cause discontinuous or abrupt transitions between dynamic regimes in food webs.

To understand how functional traits shape ecological communities it is necessary to understand both how traits across the community affect its functioning and how eco-evolutionary dynamics within the community change the traits over time. Of particular interest are so-called evolutionarily stable communities (ESCs), since these are the end points of eco-evolutionary dynamics and can persist over long time scales. One theoretical framework that has successfully been used for assembling ESCs is adaptive dynamics. However, this framework cannot account for intraspecific variation— neither locally nor across structured populations. On the other hand, in moment-based approaches, intraspecific variation is accommodated, but community assembly has been neglected. This is unfortunate as some questions regarding for example local adaptation vis-a-vis diversification into multiple species requires both facets. In this paper we develop a general theoretical framework that bridges the gap between these two approaches. We showcase how ESCs can be assembled using the framework, and illustrate various aspects of the framework using two simple models of resource competition. We believe this unifying framework could be of great use to address questions regarding the role of functional traits in communities where population structure, intraspecific variation, and eco-evolutionary dynamics are all important.

The spread of an enteric pathogen in the human gut depends on many interacting factors, including pathogen exposure, diet, host gut environment, and host microbiota, but how these factors jointly influence infection outcomes remains poorly characterized. Here we develop a model of host-mediated resource competition between mutualistic and pathogenic taxa in the gut that aims to explain why similar hosts, exposed to the same pathogen, can have such different infection outcomes. Our model successfully reproduces several empirically observed phenomena related to transitions between healthy and infected states, including (1) the nonlinear relationship between pathogen inoculum size and infection persistence, (2) the elevated risk of chronic infection during or after treatment with broad-spectrum antibiotics, (3) the resolution of gut dysbiosis with fecal microbiota transplants, and (4) the potential protection from infection conferred by probiotics. We then use the model to explore how host-mediated interventions-namely, shifts in the supply rates of electron donors (e.g., dietary fiber) and respiratory electron acceptors (e.g., oxygen)-can potentially be used to direct gut community assembly. Our study demonstrates how resource competition and ecological feedbacks between the host and the gut microbiota can be critical determinants of human health outcomes. We identify several testable model predictions ready for experimental validation.

Ongoing climate change is shifting species distributions and increasing extinction risks globally. It is generally thought that large population sizes and short generation times of marine phytoplankton may allow them to adapt rapidly to global change, including warming, thus limiting losses of biodiversity and ecosystem function. Here, we show that a marine diatom survives high, previously lethal, temperatures after adapting to above-optimal temperatures under nitrogen (N)-replete conditions. N limitation, however, precludes thermal adaptation, leaving the diatom vulnerable to high temperatures. A trade-off between high-temperature tolerance and increased N requirements may explain why N limitation inhibited adaptation. Because oceanic N limitation is common and likely to intensify in the future, the assumption that phytoplankton will readily adapt to rising temperatures may need to be reevaluated.

International audience

Environments change, for both natural and anthropogenic reasons, which can threaten species persistence. Evolutionary adaptation is a potentially powerful mechanism to allow species to persist in these changing environments. To determine the conditions under which adaptation will prevent extinction (evolutionary rescue), classic quantitative genetics models have assumed a constantly changing environment. They predict that species traits will track a moving environmental optimum with a lag that approaches a constant. If fitness is negative at this lag, the species will go extinct. There have been many elaborations of these models incorporating increased genetic realism. Here, we review and explore the consequences of four ecological complications: non-quadratic fitness functions, interacting density- and trait-dependence, species interactions and fundamental limits to adaptation. We show that non-quadratic fitness functions can result in evolutionary tipping points and existential crises, as can the interaction between density- and trait-dependent mortality. We then review the literature on how interspecific interactions affect adaptation and persistence. Finally, we suggest an alternative theoretical framework that considers bounded environmental change and fundamental limits to adaptation. A research programme that combines theory and experiments and integrates across organizational scales will be needed to predict whether adaptation will prevent species extinction in changing environments. This article is part of the theme issue ‘Integrative research perspectives on marine conservation’.

Competition is a pervasive interaction known to structure ecological communities. The Lotka-Volterra (LV) model has been foundational for our understanding of competition, and trait-based LV models have been used to model community assembly and eco-evolutionary phenomena like diversification. The intrinsic growth rate function is determined by the underlying resource distribution and is a key determinant of the resulting diversity, traits and abundances of species. In these models, the width of the resource distribution relative to the width of the competition kernel has been identified as a key parameter that leads to diversification. However, studies have only investigated the impact of width at just a few discrete values, while also often assuming the intrinsic growth rate function to be unimodal. Thus, the impact of the underlying resource distribution's width and shape together remains incompletely explored, particularly for large, diverse communities. In this study, we vary its width continuously for two shapes (unimodal and bimodal) to explore its impact on community structure. When the resource distribution is very narrow in both the unimodal bimodal cases, competition is strong, leading to exclusion of all but the best-adapted species. Wider resource distributions allow stable coexistence, where the traits of the species depend on the shape of the resource distribution. Extremely wide resource distributions support a diverse community, where the strength of competition ultimately determines the diversity and traits of coexisting species, but their abundances reflect the underlying resource distribution. Further, competition acts to maximize the use of available resources among the competing species. For large communities, the shape of resource distribution becomes immaterial and the width determines the diversity. These results affirm and extend our understanding of limiting similarity.

Trait-based approaches focus on the functional traits that define how organisms interact with the environment and each other. They represent an efficient way to capture different aspects of diversity in ecological models, which is essential for understanding community structure and ecosystem functioning, both now and in the future. There is an extensive history of trait-based approaches in theoretical ecology, enriched by an expanding array of complementary frameworks. In this chapter, we give a pedagogical introduction to one such framework—adaptive dynamics—explaining how to both set up and analyse models and surveying a range of applications. Then we show how adaptive dynamics relates to other frameworks, including species sorting, ecological quantitative genetics, and moment methods, highlighting the differences and connections between them. We then consider how these basic theories can be extended to incorporate temporal and spatial heterogeneity and multiple traits. Finally, we outline some frontiers of trait-based theory, including connections with empirical systems, linking trait- and species-based approaches, and embedding trait-based approaches in Earth system models.

Biological diversity depends on the interplay between evolutionary diversification and ecological mechanisms allowing species to coexist. Current research increasingly integrates ecology and evolution over a range of timescales, but our common conceptual framework for understanding species coexistence requires better incorporation of evolutionary processes. Here, we focus on the idea of evolutionarily stable communities (ESCs), which are theoretical endpoints of evolution in a community context. We use ESCs as a unifying framework to highlight some important but under-appreciated theoretical results, and we review empirical research relevant to these theoretical predictions. We explain how, in addition to generating diversity, evolution can also limit diversity by reducing the effectiveness of coexistence mechanisms. The coevolving traits of competing species may either diverge or converge, depending on whether the number of species in the community is low (undersaturated) or high (oversaturated) relative to the ESC. Competition in oversaturated communities can lead to extinction or neutrally coexisting, ecologically equivalent species. It is critical to consider trait evolution when investigating fundamental ecological questions like the strength of different coexistence mechanisms, the feasibility of ecologically equivalent species, and the interpretation of different patterns of trait dispersion.

Rapid evolution in response to environmental change will likely be a driving force determining the distribution of species across the biosphere in coming decades. This is especially true of microorganisms, many of which may evolve in step with warming, including phytoplankton, the diverse photosynthetic microbes forming the foundation of most aquatic food webs. Here we tested the capacity of a globally important, model marine diatom Thalassiosira pseudonana, for rapid evolution in response to temperature. Selection at 16 and 31°C for 350 generations led to significant divergence in several temperature response traits, demonstrating local adaptation and the existence of trade-offs associated with adaptation to different temperatures. In contrast, competitive ability for nitrogen (commonly limiting in marine systems), measured after 450 generations of temperature selection, did not diverge in a systematic way between temperatures. This study shows how rapid thermal adaptation affects key temperature and nutrient traits and, thus, a population's long-term physiological, ecological, and biogeographic response to climate change.

The ubiquity of cooperative cross-feeding (a resource-exchange mutualism) raises two related questions: Why is cross-feeding favored over self-sufficiency, and how are cross-feeders protected from non-producing cheaters? The Black Queen Hypothesis suggests that if leaky resources are costly, then there should be selection for either gene loss or self-sufficiency, but selection against mutualistic inter-dependency. Localized interactions have been shown to protect mutualists against cheaters, though their effects in the presence of self-sufficient organisms are not well understood. Here we develop a stochastic spatial model to examine how spatial effects alter the predictions of the Black Queen Hypothesis. Microbes need two essential resources to reproduce, which they can produce themselves (at a cost) or take up from neighbors. Additionally, microbes need empty sites to give birth into. Under well mixed mean-field conditions, the cross-feeders will always be displaced by a non-producer and a self-sufficient microbe. However, localized interactions have two effects that favor production. First, a microbe that interacts with a small number of neighbors will not always receive the essential resources it needs; this effect slightly harms cross-feeders but greatly harms non-producers. Second, microbes tend to displace other microbes that produce resources they need; this effect also slightly harms cross-feeders but greatly harms non-producers. Our work therefore suggests localized interactions produce an accelerating cost of non-production. Thus, the right trade-off between the cost of producing resources and the cost of sometimes being resource-limited can favor mutualistic inter-dependence over both self-sufficiency and non-production.

As ecology and evolution become ever more entwined, many areas of ecological theory are being re-examined. Eco-evolutionary analyses of classic coexistence mechanisms are yielding new insights into the structure and stability of communities. We examine fluctuation-dependent coexistence models, identifying communities that are both ecologically and evolutionarily stable. Members of these communities possess distinct environmental preferences, revealing widespread patterns of limiting similarity. This regularity leads to consistent changes in the structure of communities across fluctuation regimes. However, at high amplitudes, subtle differences in the form of fluctuations dramatically affect the collapse of communities. We also show that identical fluctuations can support multiple evolutionarily stable communities - a novel example of alternative stable states within eco-evolutionary systems. Consequently, the configuration of communities will depend on historical contingencies, including details of the adaptive process. Integrating evolution into the study of coexistence offers new insights, while enriching our understanding of ecology.

To persist in a changing world, populations must adapt. The ability to adapt is influenced by interactions with other species, such as predators. Recent experiments and theory suggest that selective pressures arising from predation may help prey adapt phenotypically to changing environments, but how this influences persistence remains unclear. In particular, it has not yet been shown whether predator-induced adaptation can outweigh predator-imposed reductions in population size, allowing prey to persist when they would otherwise go extinct. Here we examine if (and if so, how) predation can enhance the ability of prey to persist in a directionally changing environment. To do so, we extend a single-species quantitative-genetics framework that predicts rates of environmental change beyond which populations go extinct. While we assume predation decreases prey density, we find that predators can indeed help prey persist if they sufficiently increase prey adaptedness (decrease phenotypic lag). We show two ways this can occur: (1) the selective push, in which predators consume maladapted individuals and thus add selection that pushes the mean prey trait toward its optimum; and (2) the evolutionary hydra effect, when predation reduces prey density and thereby increases prey birthrate, allowing more selective events per unit time and effectively reducing generation time. We also discuss how our results apply more broadly to sources of mortality beyond predation.

Temperature and nutrients are fundamental, highly nonlinear drivers of biological processes, but we know little about how they interact to influence growth. This has hampered attempts to model population growth and competition in dynamic environments, which is critical in forecasting species distributions, as well as the diversity and productivity of communities. To address this, we propose a model of population growth that includes a new formulation of the temperature–nutrient interaction and test a novel prediction: that a species’ optimum temperature for growth, Topt, is a saturating function of nutrient concentration. We find strong support for this prediction in experiments with a marine diatom, Thalassiosira pseudonana: Topt decreases by 3–6 °C at low nitrogen and phosphorus concentrations. This interaction implies that species are more vulnerable to hot, low-nutrient conditions than previous models accounted for. Consequently the interaction dramatically alters species’ range limits in the ocean, projected based on current temperature and nitrate levels as well as those forecast for the future. Ranges are smaller not only than projections based on the individual variables, but also than those using a simpler model of temperature–nutrient interactions. Nutrient deprivation is therefore likely to exacerbate environmental warming's effects on communities.

Joost Vanoverbeke, Department of Biology, Katholieke Universiteit Leuven, Leuven, Belgium. Abstract: 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 co-occurrence 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 following disturbance can often adapt to novel local conditions sufficiently fast to prevent successful colonization by other pre-adapted 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 co-occurrence at the landscape level while still maintaining strong local niche differentiation. Our model 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. Our results also demonstrate how local adaptive evolution can shape cryptic eco-evolutionary dynamics and thus alter the regional mechanisms that determine biological diversity and resistance to disturbance.

The question of species coexistence has been central to ecology since its founding. Ever-present environmental variation may be one answer to that question. Previous models have demonstrated that species can exploit this variation to coexist with competitors by having different environmental responses (the storage effect). When traits governing species’ environmental response can evolve, however, coexistence is not assured. In this study, we use a continuous time, two-season model to determine the evolutionary outcome of competing species evolving in their seasonal performance trait. We extend the competitive exclusion principle to show that the storage effect can allow no more than N species to coexist on N discrete seasons with no relative nonlinearity. We find a broad region of parameter space where coexistence is evolutionarily stable. The size of this region depends on the period of fluctuations relative to the individual lifespan. Relatively long period fluctuations yield a large coexistence region, but as the period decreases, the region narrows and disappears asymptotically. Finally, we cast our adaptive dynamics technique in terms of Chesson’s concept of equalizing and stabilizing mechanisms to demonstrate that the breakdown in coexistence at short periods is due to loss of the stabilizing covariance between the environment and competition.

International audience; Contemporary niche theory is a powerful structuring framework in theoretical ecology. First developed in the context of resource competition, it has been extended to encompass other types of regulating factors such as shared predators, parasites or inhibitors. A central component of contemporary niche theory is a graphical approach popularized by Tilman that illustrates the different outcomes of competition along environmental gradients, like coexistence and competitive exclusion. These food web modules have been used to address species sorting in community ecology, as well as adaptation and coexistence on eco-evolutionary time scales in adaptive dynamics. Yet, the associated graphical approach has been underused so far in the evolutionary context. In this paper, we provide a rigorous approach to extend this graphical method to a continuum of interacting strategies, using the geometrical concept of the envelope. Not only does this approach provide community and eco-evolutionary bifurcation diagrams along environmental gradients, it also sheds light on the similarities and differences between those two perspectives. Adaptive dynamics naturally merges with this ecological framework, with a close correspondence between the classification of singular strategies and the geometrical properties of the envelope. Finally, this approach provides an integrative tool to study adaptation between levels of organization, from the individual to the ecosystem.

Temperature strongly affects phytoplankton growth rates, but its effect on communities and ecosystem processes is debated. Because phytoplankton are often limited by light, temperature should change community structure if it affects the traits that determine competition for light. Furthermore, the aggregate response of phytoplankton communities to temperature will depend on how changes in community structure scale up to bulk rates. Here, we synthesize experiments on 57 phytoplankton species to analyze how the growth-irradiance relationship changes with temperature. We find that light-limited growth, light-saturated growth, and the optimal irradiance for growth are all highly sensitive to temperature. Within a species, these traits are co-adapted to similar temperature optima, but light-limitation reduces a species' temperature optimum by ∼5°C, which may be an adaptation to how light and temperature covary with depth or reflect underlying physiological correlations. Importantly, the maximum achievable growth rate increases with temperature under light saturation, but not under strong light limitation. This implies that light limitation diminishes the temperature sensitivity of bulk phytoplankton growth, even though community structure will be temperature-sensitive. Using a database of primary production incubations, we show that this prediction is consistent with estimates of bulk phytoplankton growth across gradients of temperature and irradiance in the ocean. These results indicate that interactions between temperature and resource limitation will be fundamental for explaining how phytoplankton communities and biogeochemical processes vary across temperature gradients and respond to global change.

International audience; Plants present a variety of defensive strategies against herbivores, broadly classified into tolerance and resistance. Since resource availability can also limit plant growth, we expect plant allocation to resource acquisition and defense to vary along resource gradients. Yet, the conditions under which one defensive strategy is favored over the other are unclear. Here, we use an eco-evolutionary model to investigate plant adaptive allocation to resource acquisition, tolerance, and resistance along a resource gradient in a simple food web module inspired by plankton communities where plants compete for a single resource and are grazed on by a shared herbivore. We show that undefended, acquisition-specialist strategies dominate under low resource supplies. Conversely, high resource supplies, which lead to high herbivore abundance because of trophic transfers, result in either the dominance of very resistant strategies or coexistence between a completely resistant strategy and a fast-growing, tolerant one. We also explore the consequences of this adaptive allocation on species biomasses. Finally, we compare our predictions to a more traditional, density-independent optimization model. We show that density dependence mediated by resources and herbivores is the cause of the increase in plant resistance along the resource gradient, as the optimization model would instead have favored tolerance.

Mutualism, interspecific cooperation that yields reciprocal benefits, can promote species coexistence, enhancing biodiversity. As a specific form of mutualism, cross-feeding, where each of two mutualists produces a resource the other one needs, has been broadly studied. However, few theoretical studies have examined competition between cross-feeding mutualists and cheaters, who do not synthesize resources themselves. In this paper we study a model with two mutualists, a cheater, two micronutrients that are synthesized and exchanged by the mutualists, and one macronutrient that is only from external supply. We investigate the coexistence of the species in the framework of resource competition theory. In particular, we examine the effect of the mutualists’ synthesis rates on their coexistence. In the absence of cheaters, multiple stable states occur if the synthesis rates are high, and higher synthesis rates increase the possibility that mutualists coexist. However, when the cheater is present, higher synthesis rates promote invasion by the cheater: If the cheater is superior on all three resources, it will either persist with at most one mutualist or even trigger extinction of all three species; if the cheater is only superior on the macronutrient, both mutualists may still coexist with the cheater. Our results provide a framework for further study on more complex mutualistic networks and real microbial communities.

Mutualisms are ubiquitous, but models predict they should be susceptible to cheating. Resolving this paradox has become relevant to synthetic ecology: cooperative cross-feeding, a nutrient-exchange mutualism, has been proposed to stabilize microbial consortia. Previous attempts to understand how cross-feeders remain robust to non-producing cheaters have relied on complex behaviour (e.g. cheater punishment) or group selection. Using a stochastic spatial model, we demonstrate two novel mechanisms that can allow cross-feeders to outcompete cheaters, rather than just escape from them. Both mechanisms work through the spatial segregation of the resources, which prevents individual cheaters from acquiring the resources they need to reproduce. First, if microbe dispersal is low but resources are shared widely, then the cross-feeders self-organize into stable spatial patterns. Here the cross-feeders can build up where the resource they need is abundant, and send their resource to where their partner is, separating resources at regular intervals in space. Second, if dispersal is high but resource sharing is local, then random variation in population density creates small-scale variation in resource density, separating the resources from each other by chance. These results suggest that cross-feeding may be more robust than previously expected and offer strategies to engineer stable consortia.

Cooperative cross-feeding, a resource-exchange mutualism between microbes, is ubiquitous; however, models suggest it should be susceptible to cheating. Recent work suggested two novel mechanisms that could allow cross-feeders to exclude cheaters, even in the absence of tight coupling between cooperative organisms. The first is pattern formation, where cross-feeders form regular patterns so that their resources are separated and cheaters cannot obtain both. The second mechanism is neighbor uncertainty, where demographic stochasticity separates resources so cheaters cannot obtain both. Here we use a stochastic spatial model to test whether those mechanisms are evolutionarily stable, or whether they will collapse under gradual evolution towards reduced resource production. The answer depends on whether a microbe can make the resource for itself without sharing it. If it cannot (i.e. if producing more of a resource means sharing more of a resource), then both mechanisms continue to function. In this case, resource production directly benefits the individual, and cooperation is a byproduct. If microbes can make the resource without sharing it (i.e. if production is an altruistic trait), then neighbor uncertainty completely fails, and pattern formation is weakened. In this case, the costly trait has no direct benefit to the individual, and can only persist if cooperative organisms become associated with their partner. Thus, the novel mechanisms, which operate without tight associations, falter. These results have implications for synthetic ecology, as they suggest that how cross-feeding is engineered will impact its evolutionary stability.

Phytoplankton are key players in the global carbon cycle, contributing about half of global primary productivity. Within the phytoplankton, functional groups (characterized by distinct traits) have impacts on other major biogeochemical cycles, such as nitrogen, phosphorus and silica. Changes in phytoplankton community structure, resulting from the unique environmental sensitivities of these groups, may significantly alter elemental cycling from local to global scales. We review key traits that distinguish major phytoplankton functional groups, how they affect biogeochemistry and how the links between community structure and biogeochemical cycles are modelled. Finally, we explore how global environmental change will affect phytoplankton communities, from the traits of individual species to the relative abundance of functional groups, and how that, in turn, may alter biogeochemical cycles. Synthesis. We can increase our mechanistic understanding of the links between the community structure of primary producers and biogeochemistry by focusing on traits determining functional group responses to the environment (response traits) and their biogeochemical functions (effect traits). Identifying trade-offs including allometric and phylogenetic constraints among traits will help parameterize predictive biogeochemical models, enhancing our ability to anticipate the consequences of global change. We can increase our mechanistic understanding of the links between the community structure of primary producers and biogeochemistry by focusing on traits at different organisational levels that determine the responses to the environment (response traits) and their biogeochemical functions (effect traits). Identifying trade-offs including allometric and phylogenetic constraints among traits will help parameterize predictive biogeochemical models, enhancing our ability to anticipate the consequences of global change. Fil: Litchman, Elena. Michigan State University; Estados Unidos Fil: de Tezanos Pinto, Paula. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina Fil: Edwards, Kyle F.. University of Hawaii at Manoa; Estados Unidos Fil: Klausmeier, Christopher A.. Michigan State University; Estados Unidos Fil: Kremer, Colin T.. University of Princeton; Estados Unidos. University of Yale; Estados Unidos Fil: Thomas, Mridul K.. Swiss Federal Institute of Aquatic Science and Technology; Suiza

Marine phytoplankton are a taxonomically and functionally diverse group of organisms that are key players in the most important biogeochemical cycles. Phytoplankton taxa show different resource utilization strategies (e.g. nutrient-uptake rates and cellular allocation) and traits. Therefore, acknowledging this diversity is crucial to understanding how elemental cycles operate, including the origin and dynamics of elemental ratios. In this paper, we focus on trait-based models as tools to study the role of phytoplankton diversity in the stoichiometric phenomenology observed in the laboratory and in the open ocean. We offer a compilation of known empirical results on stoichiometry and summarize how trait-based approaches have attempted to replicate these results. By contrasting the different ecological and evolutionary approaches available in the literature, we explore the strengths and limitations of the existing models. We thus try to identify existing gaps and challenges, and point to potential new directions that can be explored to fill these gaps. We aim to highlight the potential of including diversity explicitly in our modeling approaches, which can help us gain important knowledge about changes in local and global stoichiometric patterns.

Light-dependent growth of phytoplankton is a fundamental process in marine ecosystems, but we lack a comprehensive view of how light utilization traits vary across genotypes and species, and how this variation is structured by cell size, taxonomy, and environmental gradients. Here, we compile 308 growth-irradiance experiments performed on 119 species of marine phytoplankton from all major functional groups, and characterize growth-irradiance relationships in terms of the initial slope of the growth-irradiance curve (α), the optimal irradiance above which growth declines (Iopt), and the maximum growth rate (μmax). We find that α declines with increasing cell size, although cell size appears to be a weak constraint on this trait. There are significant differences across taxa in α and μmax, with dinoflagellates, raphidophytes, and diazotrophs having the lowest values for both traits, and Phaeocystis spp. and diatoms having relatively high values. Iopt does not vary among taxonomic groups, and all traits exhibit large variation within most groups. Open-ocean isolates tend to have higher α, lower Iopt, and lower μmax than coastal isolates, implying adaptation to low light and low productivity. The three traits are correlated across species such that α and Iopt are negatively related while μmax is positively correlated with both of these traits. There is some evidence that high α carries a cost of high N demand even when nitrogen (not light) is limiting. The results elucidate contrasting light-related ecological strategies across phytoplankton and should help improve the parameterization of major functional groups in biogeochemical models.

Rapid evolution in response to environmental change will likely be a driving force determining the distribution of species and the structure of communities across the biosphere in coming decades. This is especially true of microorganisms, many of which may be able to evolve in step with rising temperatures. An ecologically indispensable group of microorganisms with great potential for rapid thermal adaptation are the phytoplankton, the diverse photosynthetic microbes forming the foundation of most aquatic food webs. We tested the capacity of a globally important phytoplankton species, the marine diatomThalassiosira pseudonana, for rapid evolution in response to temperature. Evolution of replicate populations at 16 and 31°C for 350-450 generations led to significant divergence in several traits associated withT. pseudonana’s thermal reaction norm (TRN) for per-capita population growth, as well as in its competitive ability for nitrogen (commonly limiting in marine systems). Of particular interest were evolution of the optimum temperature for growth, the upper critical temperature, and the derivative of the TRN, an indicator of potential tradeoffs resulting from local adaptation to temperature. This study offers a broad examination of the evolution of the thermal reaction norm and how modes of TRN variation may govern a population’s long-term physiological, ecological, and biogeographic response to global climate change.

Populations can persist in directionally changing environments by evolving. Quantitative genetic theory aims to predict critical rates of environmental change beyond which populations go extinct. Here, we point out that all current predictions effectively assume the same specific fitness function. This function causes selection on the standing genetic variance of quantitative traits to become increasingly strong as mean trait values depart from their optima. Hence, there is no bound on the rate of evolution and persistence is determined by the critical rate of environmental change at which populations cease to grow. We then show that biologically reasonable changes to the underlying fitness function can impose a qualitatively different extinction threshold. In particular, inflection points caused by weakening selection create local extrema in the strength of selection and thus in the rate of evolution. These extrema can produce evolutionary tipping points, where long-run population growth rates drop from positive to negative values without ever crossing zero. Generic early-warning signs of tipping points are found to have little power to detect imminent extinction, and require hard-to-gather data. Furthermore, we show how evolutionary tipping points produce evolutionary hysteresis, creating extinction debts.

Spatial structure can decisively influence the way evolutionary processes unfold. Several methods have thus far been used to study evolution in spatial systems, including population genetics, quantitative genetics, momentclosure approximations, and individual-based models. Here we extend the study of spatial evolutionary dynamics to eco-evolutionary models based on reaction-diffusion equations and adaptive dynamics. Specifically, we derive expressions for the strength of directional and stabilizing/disruptive selection that apply in both continuous space and to metacommunities with symmetrical dispersal between patches. For directional selection on a quantitative trait, this yields a way to integrate local directional selection across space and determine whether the trait value will increase or decrease. The robustness of this prediction is validated against quantitative genetics. For stabilizing/disruptive selection, we show that spatial heterogeneity always contributes to disruptive selection and hence always promotes evolutionary branching. The expression for directional selection is numerically very effi- cient, and hence lends itself to simulation studies of evolutionary community assembly. We illustrate the application and utility of the expressions for this purpose with two examples of the evolution of resource utilization. Finally, we outline the domain of applicability of reaction-diffusion equations as a modeling framework and discuss their limitations.

The resources that organisms depend on often fluctuate over time, and a variety of common traits are thought to be adaptations to variable resource supply. To understand the trait structure of communities, it is necessary to understand the functional trade-offs that determine what trait combinations are possible and which species can persist and coexist in a given environment. We compare traits across phytoplankton species in order to test for proposed trade-offs between maximum growth rate, equilibrium competitive ability for phosphorus (P), and ability to store P. We find evidence for a three-way trade-off between these traits, and we use empirical trait covariation to parameterize a mechanistic model of competition under pulsed P supply. The model shows that different strategies are favored under different conditions of nutrient supply regime, productivity, and mortality. Furthermore, multiple strategies typically coexist, and the range of traits that persist in the model is similar to the range of traits found in real species. These results suggest that mechanistic models informed by empirical trait variation, in combination with data on the trait structure of natural communities, will play an important role in uncovering the mechanisms that underlie the diversity and structure of ecological communities.

Ecological communities exhibit regular shifts in structure along environmental gradients, but it has proved difficult to dissect the mechanisms by which environmental conditions determine the relative success of species. Functional traits may provide a link between environmental drivers and mechanisms of community membership, but this has not been well tested for phytoplankton, which dominate primary production in many aquatic ecosystems. Here we test whether functional traits of phytoplankton can explain how species respond to gradients of light and phosphorus across U.S. lakes. We find that traits related to light utilization and maximum growth rate can predict species' differential responses to the relative availability of these resources. These results show that laboratory-measured traits are predictive of species' performance under natural conditions, that functional traits provide a mechanistic foundation for community ecology, and that variation in community structure is predictable in spite of the complexity of ecological communities.

Syntrophic interactions, where species consume metabolites excreted by others, are common in microbial communities, and have uses in synthetic biology. Syntrophy is likely to arise when trade-offs favor an organism that specializes on particular metabolites, rather than all possible metabolites. Several trade-offs have been suggested; however, few models consider different trade-offs to test which are most consistent with observed patterns. Here, we develop a differential equation model to study competition between a syntrophic processing chain, where each microbe can perform one step in metabolizing an initial resource to a final state, and a metabolic generalist that can perform all metabolic functions. We also examine how competition affects the production of the final metabolic compound. We find that competitive outcomes can be predicted by a generalization of the R ⁎ -rule and relative nonlinearity. Therefore, the species that can persist at the lowest resource level is the competitive dominant in a constant environment, and species can coexist by partitioning variation in resources. We derive a simple rule for predicting production rates of the final metabolite, and show that competition may not maximize final metabolite production. We show that processing chains are inherently less efficient, because resources are lost during each step of the process. Our results also suggest which trade-offs are capable of explaining certain empirical observations. For example, processing chains appear to be more common in nutrient-rich environments; our model suggests that a specificity trade-off and an affinity-yield trade-off would not predict this, but a yield-maximum growth trade-off might.

Numerous studies show that increasing species richness leads to higher ecosystem productivity. This effect is often attributed to more efficient portioning of multiple resources in communities with higher numbers of competing species, indicating the role of resource supply and stoichiometry for biodiversity–ecosystem functioning relationships. Here, we merged theory on ecological stoichiometry with a framework of biodiversity–ecosystem functioning to understand how resource use transfers into primary production. We applied a structural equation model to define patterns of diversity–productivity relationships with respect to available resources. Meta-analysis was used to summarize the findings across ecosystem types ranging from aquatic ecosystems to grasslands and forests. As hypothesized, resource supply increased realized productivity and richness, but we found significant differences between ecosystems and study types. Increased richness was associated with increased productivity, although this effect was not seen in experiments. More even communities had lower productivity, indicating that biomass production is often maintained by a few dominant species, and reduced dominance generally reduced ecosystem productivity. This synthesis, which integrates observational and experimental studies in a variety of ecosystems and geographical regions, exposes common patterns and differences in biodiversity–functioning relationships, and increases the mechanistic understanding of changes in ecosystems productivity.

Rising ocean temperatures will alter the productivity and composition of marine phytoplankton communities, thereby affecting global biogeochemical cycles. Predicting the effects of future ocean warming on biogeochemical cycles depends critically on understanding how existing global temperature variation affects phytoplankton. Here we show that variation in phytoplankton temperature optima over 150 degrees of latitude is well explained by a gradient in mean ocean temperature. An eco-evolutionary model predicts a similar relationship, suggesting that this pattern is the result of evolutionary adaptation. Using mechanistic species distribution models, we find that rising temperatures this century will cause poleward shifts in species' thermal niches and a sharp decline in tropical phytoplankton diversity in the absence of an evolutionary response.

A fundamental yet elusive goal of ecology is to predict the structure of communities from the environmental conditions they experience. Trait-based approaches to terrestrial plant communities have shown that functional traits can help reveal the mechanisms underlying community assembly, but such approaches have not been tested on the microbes that dominate ecosystem processes in the ocean. Here, we test whether functional traits can explain community responses to seasonal environmental fluctuation, using a time series of the phytoplankton of the English Channel. We show that interspecific variation in response to major limiting resources, light and nitrate, can be well-predicted by lab-measured traits characterising light utilisation, nitrate utilisation and maximum growth rate. As these relationships were predicted a priori, using independently measured traits, our results show that functional traits provide a strong mechanistic foundation for understanding the structure and dynamics of ecological communities.

A recent theory of the vertical distribution of phytoplankton considers how interacting niche construction processes such as resource depletion, behavior, and population dynamics contribute to spatial heterogeneity in the aquatic environment. In poorly mixed water columns with opposing resource gradients of nutrients and light, theory predicts that a species should aggregate at a single depth. This depth of aggregation, or biomass maximum, should change through time due to depletion of available resources. In addition, the depth of the aggregation should be deeper under low amounts of nutrient loading and shallower under higher amounts of nutrient loading. Theory predicts total biomass to exhibit a saturating relationship with nutrient supply. A surface biomass maximum limited by light and a deep biomass maximum limited by nutrients or co-limited by nutrients and light is also predicted by theory. To test this theory, we used a motile phytoplankton species (Chlamydomonas reinhardtii) growing in cylindrical plankton towers. In our experiment, the resource environment was strongly modified by the movement, self-shading, nutrient uptake, and growth of the phytoplankton. Supporting predictions, we routinely observed a single biomass maximum at the surface throughout the course of the experiment and at equilibrium under higher nutrient loading. However, at equilibrium, low nutrient loading led to a non-distinct biomass maximum with the population distributed over most of the water column instead of the distinct subsurface peak predicted by theory. Also supporting predictions, total biomass across water columns was positively related to nutrient supply but saturating at high nutrient supply conditions. Further supporting predictions, we also found evidence of light limitation for a surface biomass maximum and nutrient limitation for the deep biomass when no surface maximum was present. In addition, the light level leaving the bottom of the water column declined through time as the phytoplankton grew and was negatively related to nutrient loading. Nutrients were strongly depleted where biomass was present by the end of the experiment. This experimental study shows that the vertical distribution of phytoplankton may be driven by intraspecific resource competition in space.

The presence of prey heterogeneity and weakly interacting prey species is frequently viewed as a stabilizer of predator-prey dynamics, countering the destabilizing effects of enrichment and reducing the amplitude of population cycles. However, prior model explorations have largely focused on long-term, dynamic attractors rather than transient dynamics. Recent theoretical work shows that the presence of prey that are defended from predation can have strongly divergent effects on dynamics depending on time scale: prey heterogeneity can counteract the destabilizing effects of enrichment on predator-prey dynamics at long time scales but strongly destabilize systems during transient phases by creating long periods of low predator/prey abundance and increasing extinction probability (an effect that is amplified with increasing enrichment). We tested these general predictions using a planktonic system composed of a zooplankton predator and multiple algal prey. We first parameterized a model of our system to generate predictions and tested these experimentally. Our results qualitatively supported several model predictions. During transient phases, presence of defended algal prey increased predator extinctions at low and high enrichment levels compared to systems with only a single edible prey. This destabilizing effect was moderated at higher dilution rates, as predicted by our model. When examining dynamics beyond initial oscillations, presence of the defended prey increased predator-prey temporal variability at high nutrient enrichment but had no effect at low nutrient levels. Our results highlight the importance of considering transient dynamics when assessing the role of stabilizing factors on the dynamics of food webs.

Nutrient utilization traits can be used to link the ecophysiology of phytoplankton to population dynamic models and the structure of communities across environmental gradients. Here we analyze a comprehensive literature compilation of four traits: maximum nutrient uptake rate; the half-saturation constant for nutrient uptake; the minimum subsistence quota, measured for nitrate and phosphate; and maximum growth rate. We also use these traits to analyze two composite traits, uptake affinity and scaled uptake affinity. All traits tend to increase with cell volume, except for scaled uptake affinity and maximum growth rate, which tend to decline with cell volume. Most scaling relationships are the same for freshwater and marine species, although important differences exist. Most traits differ on average between major taxa, but between-taxon variation is nearly always due to between-taxon variation in volume. There is some evidence for between-trait correlations that could constrain trait evolution, but these correlations are difficult to disentangle from correlation driven by cell volume. These results should enhance the parameterization of models that use size or taxonomic group to structure physiological variation in phytoplankton communities.

Trade-offs among functional traits are essential for explaining community structure and species coexistence. While two-way trade-offs have been investigated in many systems, higher-dimensional trade-offs remain largely hypothetical. Here we demonstrate a three-way trade-off between cell size and competitive abilities for nitrogen and phosphorus in marine and freshwater phytoplankton. At a given cell size, competitive abilities for N and P are negatively correlated, but as cell size increases, competitive ability decreases for both nutrients. The relative importance of the two trade-off axes appears to be environment dependent, suggesting different selective pressures: freshwater phytoplankton separate more along the N vs. P competition axis, and marine phytoplankton separate more along the nutrient competition vs. cell size axis. Our results demonstrate the multidimensional nature of key trade-offs among traits and suggest that such trade-offs may drive species interactions and structure ecological communities.

Our planet shows striking gradients in the species richness of plants and animals, from high biodiversity in the tropics to low biodiversity in polar and high-mountain regions. Recently, similar patterns have been described for some groups of microorganisms, but the large-scale biogeographical distribution of freshwater phytoplankton diversity is still largely unknown. We examined the species diversity of freshwater phytoplankton sampled from 540 lakes and reservoirs distributed across the continental United States and found strong latitudinal, longitudinal, and altitudinal gradients in phytoplankton biodiversity, demonstrating that microorganisms can show substantial geographic variation in biodiversity. Detailed analysis using structural equation models indicated that these large-scale biodiversity gradients in freshwater phytoplankton diversity were mainly driven by local environmental factors, although there were residual direct effects of latitude, longitude, and altitude as well. Specifically, we found that phytoplankton species richness was an increasing saturating function of lake chlorophyll a concentration, increased with lake surface area and possibly increased with water temperature, resembling effects of productivity, habitat area, and temperature on diversity patterns commonly observed for macroorganisms. In turn, these local environmental factors varied along latitudinal, longitudinal, and altitudinal gradients. These results imply that changes in land use or climate that affect these local environmental factors are likely to have major impacts on large-scale biodiversity patterns of freshwater phytoplankton.

When two species form a mutualistic association, the degree of control that each has over the interaction may be pivotal in determining the relative benefit each obtains. We incorporate the capacity for partner choice into a model of mutualism based on the exchange of goods and/or services, where one guild of mutualists plays the role of proposer (proposing a price at which the goods and/or services will be exchanged) and the other plays the role of responder (accepting or rejecting the deal). We show how the payoff structure in this scenario and other closely related ones correspond to the ultimatum and demand games of economics. In the model, there are both costs and benefits to a guild whose players have control over interactions. Control over interactions in the sense of being able to exercise partner choice can benefit a guild by selecting for mutualism in its partners, but is most effective in selecting against moderately exploitative partners, and so can give highly exploitative partners an advantage. This can generate dynamics similar to taxon cycles or those seen in models with competition-colonization tradeoffs, wherein increasingly more mutualistic partners (acting as superior competitors) are selected for up to a tipping point, at which highly exploitative strategies (akin to superior colonizers) gain an advantage. Control over interactions in the sense of being able to appropriate 'surplus' payoffs in each interaction, which is selected for within-guild and is equivalent to playing the role of responders, selects against high demands (and so for mutualism) in the guild with control. Combining the two mechanisms, a high degree of mutualism in both guilds and coexistence of more mutualistic and more exploitative strategies within each are both consistent with control over the interaction being highly skewed toward one side that does what is in its own short-term interests.

In addition to answering Hutchinson's question "Why are there so many species?", we need to understand why certain species are found only under certain environmental conditions and not others. Trait-based approaches are being increasingly used in ecology to do just that: explain and predict species distributions along environmental gradients. These approaches can be successful in understanding the diversity and community structure of phytoplankton. Among major traits shaping phytoplankton distributions are resource utilization traits, morphological traits (with size being probably the most influential), grazer resistance traits, and temperature responses. We review these trait-based approaches and give examples of how trait data can explain species distributions in both freshwater and marine systems. We also outline new directions in trait-based approaches applied to phytoplankton such as looking simultaneously at trait and phylogenetic structure of phytoplankton communities and using adaptive dynamics models to predict trait evolution. Fil: Litchman, Elena. Michigan State University; Estados Unidos Fil: de Tezanos Pinto, Paula. Michigan State University; Estados Unidos. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Ecología, Genética y Evolución de Buenos Aires. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Ecología, Genética y Evolución de Buenos Aires; Argentina Fil: Klausmeier, Christopher A.. Michigan State University; Estados Unidos Fil: Thomas, Mridul K.. Michigan State University; Estados Unidos Fil: Yoshiyama, Kohei. University Of Tokyo; Japón

Despite the recognition of the importance of seasonal forcing in nature, remarkably few studies have theoretically explored periodically forced community dynamics. Here we employ a novel approach called "successional state dynamics" (SSD) to model a seasonally forced predator-prey system. We first generated analytical predictions of the effects of altered seasonality on species persistence and the timing of community state transitions. We then parameterized the model using a zooplankton-phytoplankton system and tested quantitative predictions using controlled experiments. In the majority of cases, timing of zooplankton and algal population peaks matched model predictions. Decreases in growing-period length delayed algal blooms, consequently delaying peaks in zooplankton abundance. Predictions of increased probability of predator extinction at low growing-period lengths were also upheld experimentally. Our results highlight the utility of the SSD modeling approach as a framework for predicting the effects of altered seasonality on the structure and dynamics of multitrophic communities.

Diatoms are key players in the global carbon cycle and most aquatic ecosystems. Their cell sizes impact carbon sequestration and energy transfer to higher trophic levels. We report fundamental differences in size distributions of marine and freshwater diatoms, with marine diatoms significantly larger than freshwater species. An evolutionary game theoretical model with empirical allometries of growth and nutrient uptake shows that these differences can be explained by nitrogen versus phosphorus limitation, nutrient fluctuations and mixed layer depth differences. Constant and pulsed phosphorus supply select for small sizes, as does constant nitrogen supply. In contrast, intermediate frequency nitrogen pulses common in the ocean select for large sizes or the evolutionarily stable coexistence of large and small sizes. Size-dependent sinking interacts with mixed layer depth (MLD) to further modulate optimal sizes, with smaller sizes selected for by strong sinking and shallow MLD. In freshwaters, widespread phosphorus limitation, together with strong sinking and shallow MLD produce size distributions with smaller range, means and upper values, compared with the ocean. Shifting patterns of nutrient limitation and mixing may alter diatom size distributions, affecting global carbon cycle and the structure and functioning of aquatic ecosystems.

In this paper we study a mathematical model of two parallel food chains in a chemostat. Each food chain consists of a prey species $x$ and a predator species $y$. Two food chains are symmetric in the sense that the prey species are identical and so are the specialized predator species. We assume that both of the prey species in the parallel food chains share the same nutrient $R$. In this paper we show that as the input concentration $R^{(0)}$ of the nutrient varies, there are several possible outcomes: (1) all species go extinct; (2) only the two prey species survive; (3) all species coexist at equilibrium; (4) all species coexist in the form of oscillations. We analyze cases (1)-(3) rigorously; for case (4) we do extensive numerical studies to present all possible phenomena, which include limit cycles, heteroclinic cycles, and chaos.

Because phytoplankton live at the interface between the abiotic and the biotic compartments of ecosystems, they play an important role in coupling multiple nutrient cycles. The quantitative details of how these multiple nutrient cycles intersect is determined by phytoplankton stoichiometry. Here we review some classic work and recent advances on the determinants of phytoplankton stoichiometry and their role in determining ecosystem stoichiometry. First, we use a model of growth with flexible stoichiometry to reexamine Rhee and Goldman’s classic chemostat data. We also discuss a recent data compilation by Hall and colleagues that illustrates some limits to phytoplankton flexibility, and a model of physiological adaptation that can account for these results. Second, we use a model of resource allocation to determine the how the optimal nitrogen-to-phosphorus stoichiometry depends on the ecological conditions under which species grow and compete. Third, we discuss Redfield’s mechanism for the homeostasis of the oceans’ nitrogen-to-phosphorus stoichiometry and show its robustness to additional factors such as iron-limitation and temporal fluctuations. Finally, we suggest areas for future research.