Coexistence of many species under a random competition-colonization trade-off.

The competition-colonization (CC) trade-off is a well-studied coexistence mechanism for metacommunities. In this setting, it is believed that the coexistence of all species requires their traits to satisfy restrictive conditions limiting their similarity. To investigate whether diverse metacommunities can assemble in a CC trade-off model, we study their assembly from a probabilistic perspective. From a pool of species with parameters (corresponding to traits) sampled at random, we compute the probability that any number of species coexist and characterize the set of species that emerges through assembly. Remarkably, almost exactly half of the species in a large pool typically coexist, with no saturation as the size of the pool grows, and with little dependence on the underlying distribution of traits. Through a mix of analytical results and simulations, we show that this unlimited niche packing emerges as assembly actively moves communities toward overdispersed configurations in niche space. Our findings also apply to a realistic assembly scenario where species invade one at a time from a fixed regional pool. When diversity arises de novo in the metacommunity, richness still grows without bound, but more slowly. Together, our results suggest that the CC trade-off can support the robust emergence of diverse communities, even when coexistence of the full species pool is exceedingly unlikely.

Assessing mutualistic metacommunity capacity by integrating spatial and interaction networks.

We develop a spatially realistic model of mutualistic metacommunities that exploits the joint structure of spatial and interaction networks. Assuming that all species have the same colonisation and extinction parameters, this model exhibits a sharp transition between stable non-null equilibrium states and a global extinction state. This behaviour allows defining a threshold on colonisation/extinction parameters for the long-term metacommunity persistence. This threshold, the 'metacommunity capacity', extends the metapopulation capacity concept and can be calculated from the spatial and interaction networks without needing to simulate the whole dynamics. In several applications we illustrate how the joint structure of the spatial and the interaction networks affects metacommunity capacity. It results that a weakly modular spatial network and a power-law degree distribution of the interaction network provide the most favourable configuration for the long-term persistence of a mutualistic metacommunity. Our model that encodes several explicit ecological assumptions should pave the way for a larger exploration of spatially realistic metacommunity models involving multiple interaction types.

Coevolution of species colonisation rates controls food-chain length in spatially structured food webs.

How the complexity of food webs depends on environmental variables is a long-standing ecological question. It is unclear though how food-chain length should vary with adaptive evolution of the constitutive species. Here we model the evolution of species colonisation rates and its consequences on occupancies and food-chain length in metacommunities. When colonisation rates can evolve, longer food-chains can persist. Extinction, perturbation and habitat loss all affect evolutionarily stable colonisation rates, but the strength of the competition-colonisation trade-off has a major role: weaker trade-offs yield longer chains. Although such eco-evo dynamics partly alleviates the spatial constraint on food-chain length, it is no magic bullet: the highest, most vulnerable, trophic levels are also those that least benefit from evolution. We provide qualitative predictions regarding how trait evolution affects the response of communities to disturbance and habitat loss. This highlights the importance of eco-evolutionary dynamics at metacommunity level in determining food-chain length.

Arthropod food webs predicted from body size ratios are improved by incorporating prey defensive properties.

Trophic interactions are often deduced from body size differences, assuming that predators prefer prey smaller than themselves because larger prey are more difficult to subdue. This has mainly been confirmed in aquatic ecosystems, but rarely in terrestrial ecosystems, especially in arthropods. Our goal was to validate whether body size ratios can predict trophic interactions in a terrestrial, plant-associated arthropod community and whether predator hunting strategy and prey taxonomy could explain additional variation. We conducted feeding trials with arthropods from marram grass in coastal dunes to test whether two individuals, of the same or different species, would predate each other. From the trial results, we constructed one of the most complete, empirically derived food webs for terrestrial arthropods associated with a single plant species. We contrasted this empirical food web with a theoretical web based on body size ratios, activity period, microhabitat, and expert knowledge. In our feeding trials, predator-prey interactions were indeed largely size-based. Moreover, the theoretical and empirically based food webs converged well for both predator and prey species. However, predator hunting strategy, and especially prey taxonomy improved predictions of predation. Well-defended taxa, such as hard-bodied beetles, were less frequently consumed than expected based on their body size. For instance, a beetle of average size (measuring 4 mm) is 38% less vulnerable than another average arthropod with the same length. Body size ratios predict trophic interactions among plant-associated arthropods fairly well. However, traits such as hunting strategy and anti-predator defences can explain why certain trophic interactions do not adhere to size-based rules. Feeding trials can generate insights into multiple traits underlying real-life trophic interactions among arthropods.

Equilibrium and surviving species in a large Lotka-Volterra system of differential equations.

Lotka-Volterra (LV) equations play a key role in the mathematical modeling of various ecological, biological and chemical systems. When the number of species (or, depending on the viewpoint, chemical components) becomes large, basic but fundamental questions such as computing the number of surviving species still lack theoretical answers. In this paper, we consider a large system of LV equations where the interactions between the various species are a realization of a random matrix. We provide conditions to have a unique equilibrium and present a heuristics to compute the number of surviving species. This heuristics combines arguments from Random Matrix Theory, mathematical optimization (LCP), and standard extreme value theory. Numerical simulations, together with an empirical study where the strength of interactions evolves with time, illustrate the accuracy and scope of the results.

Joint species distributions reveal the combined effects of host plants, abiotic factors and species competition as drivers of species abundances in fruit flies.

The relative importance of ecological factors and species interactions for shaping species distributions is still debated. The realised niches of eight sympatric tephritid fruit flies were inferred from field abundance data using joint species distribution modelling and network inference, on the whole community and separately on three host plant groups. These estimates were then confronted the fundamental niches of seven fly species estimated through laboratory-measured fitnesses on host plants. Species abundances depended on host plants, followed by climatic factors, with a dose of competition between species sharing host plants. The relative importance of these factors mildly changed among the three host plant groups. Despite overlapping fundamental niches, specialists and generalists had almost distinct realised niches, with possible competitive exclusion of generalists by specialists on Cucurbitaceae. They had different assembly rules: Specialists were mainly influenced by their adaptation to host plants, while generalist abundances varied regardless of their fundamental host use.

A methodological framework to analyse determinants of host-microbiota networks, with an application to the relationships between Daphnia magna's gut microbiota and bacterioplankton.

The past 30 years have seen both a surge of interest in assessing ecological interactions using tools borrowed from network theory and an explosion of data on the occurrence of microbial symbionts thanks to next-generation sequencing. Given that classic network methods cannot currently measure the respective effects of different environmental and biological drivers on network structure, we here present two methods to elucidate the determinants of bipartite interaction networks. The first method is based on classifications and compares communities within networks to the grouping of nodes by treatment or similar controlling groups. The second method assesses the link between multivariate explanatory variables and network structure using redundancy analyses after singular value decomposition. In both methods, the significance of effects can be gauged through two randomizations. Our methods were applied to experimental data on Daphnia magna and its interactions with gut microbiota and bacterioplankton. The whole network was affected by Daphnia's diet (algae and/or cyanobacteria) and sample type, but not by Daphnia genotype. At coarse grains, bacterioplankton and gut microbiota communities were different. At this scale, the structure of the gut microbiota-based network was not linked to any explanatory factors, while the bacterioplankton-based network was related to both Daphnia's diet and genotype. At finer grains, Daphnia's diet and genotype affected both microbial networks, but the effect of diet on gut microbiota network structure was mediated solely by differences in microbial richness. While no reciprocal effect between the microbial communities could be found, fine-grained analyses presented a more nuanced picture, with bacterioplankton likely affecting the composition of the gut microbiota. Our methods are widely applicable to bipartite networks, can elucidate both controlled and environmental effects in experimental setting using a large amount of sequencing data and can tease apart reciprocal effects of networks on one another. The twofold approach we propose has the advantage of being able to tease apart effects at different scales of network structure, thus allowing for detailed assessment of reciprocal effects of linked networks on one another. As such, our network methods can help ecologists understand huge datasets reporting microbial co-occurrences within different hosts.

Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition.

Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and consists mostly of repeated static analyses. Here we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability.

Metastasis and the evolution of dispersal.

Despite significant progress in oncology, metastasis remains the leading cause of mortality of cancer patients. Understanding the foundations of this phenomenon could help contain or even prevent it. As suggested by many ecologists and cancer biologists, metastasis could be considered through the lens of biological dispersal: the movement of cancer cells from their birth site (the primary tumour) to other habitats where they resume proliferation (metastatic sites). However, whether this model can consistently be applied to the emergence and dynamics of metastasis remains unclear. Here, we provide a broad review of various aspects of the evolution of dispersal in ecosystems. We investigate whether similar ecological and evolutionary principles can be applied to metastasis, and how these processes may shape the spatio-temporal dynamics of disseminating cancer cells. We further discuss complementary hypotheses and propose experimental approaches to test the relevance of the evolutionary ecology of dispersal in studying metastasis.

Worms' Antimicrobial Peptides.

Antimicrobial peptides (AMPs) are natural antibiotics produced by all living organisms. In metazoans, they act as host defense factors by eliminating microbial pathogens. But they also help to select the colonizing bacterial symbionts while coping with specific environmental challenges. Although many AMPs share common structural characteristics, for example having an overall size between 10-100 amino acids, a net positive charge, a γ-core motif, or a high content of cysteines, they greatly differ in coding sequences as a consequence of multiple parallel evolution in the face of pathogens. The majority of AMPs is specific of certain taxa or even typifying species. This is especially the case of annelids (ringed worms). Even in regions with extreme environmental conditions (polar, hydrothermal, abyssal, polluted, etc.), worms have colonized all habitats on Earth and dominated in biomass most of them while co-occurring with a large number and variety of bacteria. This review surveys the different structures and functions of AMPs that have been so far encountered in annelids and nematodes. It highlights the wide diversity of AMP primary structures and their originality that presumably mimics the highly diverse life styles and ecology of worms. From the unique system that represents marine annelids, we have studied the effect of abiotic pressures on the selection of AMPs and demonstrated the promising sources of antibiotics that they could constitute.

Plant Strategies along Resource Gradients.

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.

Host manipulation by cancer cells: Expectations, facts, and therapeutic implications.

Similar to parasites, cancer cells depend on their hosts for sustenance, proliferation and reproduction, exploiting the hosts for energy and resources, and thereby impairing their health and fitness. Because of this lifestyle similarity, it is predicted that cancer cells could, like numerous parasitic organisms, evolve the capacity to manipulate the phenotype of their hosts to increase their own fitness. We claim that the extent of this phenomenon and its therapeutic implications are, however, underappreciated. Here, we review and discuss what can be regarded as cases of host manipulation in the context of cancer development and progression. We elaborate on how acknowledging the applicability of these principles can offer novel therapeutic and preventive strategies. The manipulation of host phenotype by cancer cells is one more reason to adopt a Darwinian approach in cancer research.

The evolution of the competition-dispersal trade-off affects α- and ß-diversity in a heterogeneous metacommunity.

Difference in dispersal ability is a key driver of species coexistence in metacommunities. However, the available frameworks for interpreting species diversity patterns in natura often overlook trade-offs and evolutionary constraints associated with dispersal. Here, we build a metacommunity model accounting for dispersal evolution and a competition-dispersal trade-off. Depending on the distribution of carrying capacities among communities, species dispersal values are distributed either around a single strategy (evolutionarily stable strategy, ESS), or around distinct strategies (evolutionary branching, EB). We show that limited dispersal generates spatial aggregation of dispersal traits in ESS and EB scenarios, and that the competition-dispersal trade-off strengthens the pattern in the EB scenario. Importantly, individuals in larger (respectively (resp.) smaller) communities tend to harbour lower (resp. higher) dispersal, especially under the EB scenario. We explore how dispersal evolution affects species diversity patterns by comparing those from our model to the predictions of a neutral metacommunity model. The most marked difference is detected under EB, with distinctive values of both α- and ß-diversity (e.g. the dissimilarity in species composition between small and large communities was significantly larger than neutral predictions). We conclude that, from an empirical perspective, jointly assessing community carrying capacity with species dispersal strategies should improve our understanding of diversity patterns in metacommunities.

Geometrical envelopes: Extending graphical contemporary niche theory to communities and eco-evolutionary dynamics.

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.

Cancer and life-history traits: lessons from host-parasite interactions.

Despite important differences between infectious diseases and cancers, tumour development (neoplasia) can nonetheless be closely compared to infectious disease because of the similarity of their effects on the body. On this basis, we predict that many of the life-history (LH) responses observed in the context of host-parasite interactions should also be relevant in the context of cancer. Parasites are thought to affect LH traits of their hosts because of strong selective pressures like direct and indirect mortality effects favouring, for example, early maturation and reproduction. Cancer can similarly also affect LH traits by imposing direct costs and/or indirectly by triggering plastic adjustments and evolutionary responses. Here, we discuss how and why a LH focus is a potentially productive but under-exploited research direction for cancer research, by focusing our attention on similarities between infectious disease and cancer with respect to their effects on LH traits and their evolution. We raise the possibility that LH adjustments can occur in response to cancer via maternal/paternal effects and that these changes can be heritable to (adaptively) modify the LH traits of their offspring. We conclude that LH adjustments can potentially influence the transgenerational persistence of inherited oncogenic mutations in populations.

A neutral theory for interpreting correlations between species and genetic diversity in communities.

Spatial patterns of biological diversity have been extensively studied in ecology and population genetics, because they reflect the forces acting on biodiversity. A growing number of studies have found that genetic (within-species) and species diversity can be correlated in space (the so-called species-gene diversity correlation [SGDC]), which suggests that they are controlled by nonindependent processes. Positive SGDCs are generally assumed to arise from parallel responses of genetic and species diversity to variation in site size and connectivity. However, this argument implicitly assumes a neutral model that has yet to be developed. Here, we build such a model to predict SGDC in a metacommunity. We describe how SGDC emerges from competition within sites and variation in connectivity and carrying capacity among sites. We then introduce the formerly ignored mutation process, which affects genetic but not species diversity. When mutation rate is low, our model confirms that variation in the number of migrants among sites creates positive SGDCs. However, when considering high mutation rates, interactions between mutation, migration, and competition can produce negative SGDCs. Neutral processes thus do not always contribute positively to SGDCs. Our approach provides empirical guidelines for interpreting these novel patterns in natura with respect to evolutionary and ecological forces shaping metacommunities.

Do animal personalities emerge?

The evolution of animal personalities is a topic of primary importance in behavioural ecology. An intriguing empirical fact is the consistency of animal responses to repeated stresses or threats. Wolf et al. propose an evolutionary model to explain the emergence of consistent personalities. They show that a population dimorphism for an exploration trait implies the existence of behavioural syndromes, such as decreased aggressiveness and the boldness of 'thorough explorers'. This finding helps explain how animal responses can be consistent, despite the seeming advantages of flexible responses. However, we contend that the emergence of a dimorphism depends critically on the intensity of the trade-off between exploration investment and first-year fecundity.

France needs a chief science adviser.

France is at a crossroads, facing environmental and social challenges that are profoundly altering its society. Yet, the French government keeps prioritizing short-term political gains over long-term evidence-based planning for major transitions that France, like most countries, will undergo over the next 20 years. There is an urgent need for France to implement long-term science-informed policy-making.

Impact of epizootics on mussel farms: Insights into microbiota composition of Mytilus species.

Outbreaks of marine mussel mortality on French farms could have different aetiologies. One of them implies Vibrio splendidus strains. Beyond the involvement of this pathogen, there is considerable evidence that diseases often result from interactions between several microbes and the host. In this study, we explored the bacterial communities associated with mussel species and the surrounding water collected from a mussel farm affected by mortalities. The microbiota of Mytilus edulis, Mytilus galloprovincialis and their hybrids displayed an abnormal abundance of Proteobacteria, in particular the genera Vibrio, Cobetia and Arcobacter. Despite the dysbiosis, the Mediterranean mussel showed a different microbiota profile with a higher richness and presence of the phylum Bacteroidetes. Bipartite network analyses at the level of bacteria families confirmed this finding and showed that the microbiomes of M. edulis and the hybrids tended to cluster together. In addition, injection of mussels with the virulent V. splendidus induced less mortality rate in M. galloprovincialis compared to the other Mytilus sp. suggesting a better resistance of the Mediterranean mussel to infection. Our findings point to a probable aetiology of pathobiome-mediated disease in mussels. To fully understand this phenomenon, more knowledge is needed on the roles of pathobiotic systems and their development during disease establishment.

Evolutionary ecology of dispersal in biodiverse spatially structured systems: what is old and what is new?

Dispersal is a well-recognized driver of ecological and evolutionary dynamics, and simultaneously an evolving trait. Dispersal evolution has traditionally been studied in single-species metapopulations so that it remains unclear how dispersal evolves in metacommunities and metafoodwebs, which are characterized by a multitude of species interactions. Since most natural systems are both species-rich and spatially structured, this knowledge gap should be bridged. Here, we discuss whether knowledge from dispersal evolutionary ecology established in single-species systems holds in metacommunities and metafoodwebs and we highlight generally valid and fundamental principles. Most biotic interactions form the backdrop to the ecological theatre for the evolutionary dispersal play because interactions mediate patterns of fitness expectations across space and time. While this allows for a simple transposition of certain known principles to a multispecies context, other drivers may require more complex transpositions, or might not be transferred. We discuss an important quantitative modulator of dispersal evolution-increased trait dimensionality of biodiverse meta-systems-and an additional driver: co-dispersal. We speculate that scale and selection pressure mismatches owing to co-dispersal, together with increased trait dimensionality, may lead to a slower and more 'diffuse' evolution in biodiverse meta-systems. Open questions and potential consequences in both ecological and evolutionary terms call for more investigation. This article is part of the theme issue 'Diversity-dependence of dispersal: interspecific interactions determine spatial dynamics'.