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.

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.

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.

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.

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.

Seasonality and competition select for variable germination behavior in perennials.

The occurrence of within-population variation in germination behavior and associated traits such as seed size has long fascinated evolutionary ecologists. In annuals, unpredictable environments are known to select for bet-hedging strategies causing variation in dormancy duration and germination strategies. Variation in germination timing and associated traits is also commonly observed in perennials and often tracks gradients of environmental predictability. Although bet-hedging is thought to occur less frequently in long-lived organisms, these observations suggest a role of bet-hedging strategies in perennials occupying unpredictable environments. We use complementary analytical and evolutionary simulation models of within-individual variation in germination behavior in seasonal environments to show how bet-hedging interacts with fluctuating selection, life-history traits, and competitive asymmetries among germination strategies. We reveal substantial scope for bet-hedging to produce variation in germination behavior in long-lived plants, when "false starts" to the growing season results in either competitive advantages or increased mortality risk for alternative germination strategies. Additionally, we find that lowering adult survival may, in contrast to classic bet-hedging theory, result in less spreading of germination by decreasing density-dependent competition. These models extend insights from bet-hedging theory to perennials and explore how competitive communities may be affected by ongoing changes in climate and seasonality patterns.

The diversification of the antimicrobial peptides from marine worms is driven by environmental conditions.

Antimicrobial peptides (AMPs) play a key role in the external immunity of animals, offering an interesting model for studying the influence of the environment on the diversification and evolution of immune effectors. Alvinellacin (ALV), arenicin (ARE) and polaricin (POL, a novel AMP identified here), characterized from three marine worms inhabiting contrasted habitats ('hot' vents, temperate and polar respectively), possess a well conserved BRICHOS domain in their precursor molecule despite a profound amino acid and structural diversification of the C-terminal part containing the core peptide. Data not only showed that ARE, ALV and POL display an optimal bactericidal activity against the bacteria typical of the habitat where each worm species lives but also that this killing efficacy is optimal under the thermochemical conditions encountered by their producers in their environment. Moreover, the correlation between species habitat and the cysteine contents of POL, ARE and ALV led us to investigate the importance of disulfide bridges in their biological efficacy as a function of abiotic pressures (pH and temperature). The construction of variants using non-proteinogenic residues instead of cysteines (α-aminobutyric acid variants) leading to AMPs devoid of disulfide bridges, provided evidence that the disulfide pattern of the three AMPs allows for a better bactericidal activity and suggests an adaptive way to sustain the fluctuations of the worm's environment. This work shows that the external immune effectors exemplified here by BRICHOS AMPs are evolving under strong diversifying environmental pressures to be structurally shaped and more efficient/specific under the ecological niche of their producer.

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.

A large-scale dataset reveals taxonomic and functional specificities of wild bee communities in urban habitats of Western Europe.

Wild bees are declining, mainly due to the expansion of urban habitats that have led to land-use changes. Effects of urbanization on wild bee communities are still unclear, as shown by contrasting reports on their species and functional diversities in urban habitats. To address this current controversy, we built a large dataset, merging 16 surveys carried out in 3 countries of Western Europe during the past decades, and tested whether urbanization influences local wild bee taxonomic and functional community composition. These surveys encompassed a range of urbanization levels, that were quantified using two complementary metrics: the proportion of impervious surfaces and the human population density. Urban expansion, when measured as a proportion of impervious surfaces, but not as human population density, was significantly and negatively correlated with wild bee community species richness. Taxonomic dissimilarity of the bee community was independent of both urbanization metrics. However, occurrence rates of functional traits revealed significant differences between lightly and highly urbanized communities, for both urbanization metrics. With higher human population density, probabilities of occurrence of above-ground nesters, generalist and small species increased. With higher soil sealing, probabilities of occurrence of above-ground nesters, generalists and social bees increased as well. Overall, these results, based on a large European dataset, suggest that urbanization can have negative impacts on wild bee diversity. They further identify some traits favored in urban environments, showing that several wild bee species can thrive in cities.

Fruit fly phylogeny imprints bacterial gut microbiota.

One promising avenue for reconciling the goals of crop production and ecosystem preservation consists in the manipulation of beneficial biotic interactions, such as between insects and microbes. Insect gut microbiota can affect host fitness by contributing to development, host immunity, nutrition, or behavior. However, the determinants of gut microbiota composition and structure, including host phylogeny and host ecology, remain poorly known. Here, we used a well-studied community of eight sympatric fruit fly species to test the contributions of fly phylogeny, fly specialization, and fly sampling environment on the composition and structure of bacterial gut microbiota. Comprising both specialists and generalists, these species belong to five genera from to two tribes of the Tephritidae family. For each fly species, one field and one laboratory samples were studied. Bacterial inventories to the genus level were produced using 16S metabarcoding with the Oxford Nanopore Technology. Sample bacterial compositions were analyzed with recent network-based clustering techniques. Whereas gut microbiota were dominated by the Enterobacteriaceae family in all samples, microbial profiles varied across samples, mainly in relation to fly identity and sampling environment. Alpha diversity varied across samples and was higher in the Dacinae tribe than in the Ceratitinae tribe. Network analyses allowed grouping samples according to their microbial profiles. The resulting groups were very congruent with fly phylogeny, with a significant modulation of sampling environment, and with a very low impact of fly specialization. Such a strong imprint of host phylogeny in sympatric fly species, some of which share much of their host plants, suggests important control of fruit flies on their gut microbiota through vertical transmission and/or intense filtering of environmental bacteria.

Mycobacterium tuberculosis genetic features associated with pulmonary tuberculosis severity.

OBJECTIVES: Mycobacterium tuberculosis (Mtb) infections result in a wide spectrum of clinical presentations but without proven Mtb genetic determinants. Herein, we hypothesized that the genetic features of Mtb clinical isolates, such as specific polymorphisms or microdiversity, may be linked to tuberculosis (TB) severity. METHODS: A total of 234 patients with pulmonary TB (including 193 drug-susceptible and 14 monoresistant cases diagnosed between 2017 and 2020 and 27 multidrug-resistant cases diagnosed between 2010 and 2020) were stratified according to TB disease severity, and Mtb genetic features were explored using whole genome sequencing, including heterologous single-nucleotide polymorphism (SNP), calling to explore microdiversity. Finally, we performed a structural equation modeling analysis to relate TB severity to Mtb genetic features. RESULTS: The clinical isolates from patients with mild TB carried mutations in genes associated with host-pathogen interaction, whereas those from patients with moderate/severe TB carried mutations associated with regulatory mechanisms. Genome-wide association study identified an SNP in the promoter of the gene coding for the virulence regulator espR, statistically associated with moderate/severe disease. Structural equation modeling and model comparisons indicated that TB severity was associated with the detection of Mtb microdiversity within clinical isolates and to the espR SNP. CONCLUSION: Taken together, these results provide a new insight to better understand TB pathophysiology and could provide a new prognosis tool for pulmonary TB severity.

Advancing biological invasion hypothesis testing using functional diversity indices.

Pioneering investigations on the effects of introduced populations on community structure, ecosystem functioning and services have focused on the effects of invaders on taxonomic diversity. However, taxonomic-based diversity metrics overlook the heterogeneity of species roles within and among communities. As the homogenizing effects of biological invasions on community and ecosystem processes can be subtle, they may require the use of functional diversity indices to be properly evidenced. Starting from the listing of major functional diversity indices, alongside the presentation of their strengths and limitations, we focus on studies pertaining to the effects of invasive species on native communities and recipient ecosystems using functional diversity indices. By doing so, we reveal that functional diversity of the recipient community may strongly vary at the onset of the invasion process, while it stabilizes at intermediate and high levels of invasion. As functional changes occurring during the lag phase of an invasion have been poorly investigated, we show that it is still unknown whether there are consistent changes in functional diversity metrics that could indicate the end of the lag phase. Thus, we recommend providing information on the invasion stage under consideration when computing functional diversity metrics. For the existing literature, it is also surprising that very few studies explored the functional difference between organisms from the recipient communities and invaders of the same trophic levels, or assessed the effects of non-native organism establishment into a non-analogue versus an analogue community. By providing valuable tools for obtaining in-depth diagnostics of community structure and functioning, functional diversity indices can be applied for timely implementation of restoration plans and improved conservation strategies. To conclude, our work provides a first synthetic guide for their use in hypothesis testing in invasion biology.

Conceptualizing ecosystem services using social-ecological networks.

Social-ecological networks (SENs) represent the complex relationships between ecological and social systems and are a useful tool for analyzing and managing ecosystem services. However, mainstreaming the application of SENs in ecosystem service research has been hindered by a lack of clarity about how to match research questions to ecosystem service conceptualizations in SEN (i.e., as nodes, links, attributes, or emergent properties). Building from different disciplines, we propose a typology to represent ecosystem service in SENs and identify opportunities and challenges of using SENs in ecosystem service research. Our typology provides guidance for this growing field to improve research design and increase the breadth of questions that can be addressed with SEN to understand human-nature interdependencies in a changing world.

A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities.

Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.

Investigation of Capitella spp. symbionts in the context of varying anthropic pressures: First occurrence of a transient advantageous epibiosis with the giant bacteria Thiomargarita sp. to survive seasonal increases of sulfides in sediments.

Capitella spp. is considered as an important ecological indicator of eutrophication due to its high densities in organic-rich, reduced, and sometimes polluted coastal ecosystems. We investigated whether such ability to cope with adverse ecological contexts might be a response to the microorganisms these worms are associated with. In populations from the French Atlantic coast (Roscoff, Brittany), we observed an epibiotic association covering the tegument of 20-30% specimens from an anthropized site while individuals from a reference, non-anthropized site were devoid of any visible epibionts. Using RNAseq, molecular and microscopic analyses, we described and compared the microbial communities associated with the epibiotic versus the non-epibiotic specimens at both locations. Interestingly, data showed that the epibiosis is characterized by sulfur-oxidizing bacteria among which the giant bacterium Thiomargarita sp., to date only described in deep sea habitats. Survey of Capitella combined with the geochemical analysis of their sediment revealed that epibiotic specimens are always found in muds with the highest concentration of sulfides, mostly during the summer. Concomitantly, tolerance tests demonstrated that the acquisition of epibionts increased survival against toxic level of sulfides. Overall, the present data highlight for the first time a peculiar plastic adaptation to seasonal variations of the habitat based on a transcient epibiosis allowing a coastal species to survive temporary harsher conditions.

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.

Diet and Genotype of an Aquatic Invertebrate Affect the Composition of Free-Living Microbial Communities.

In spite of the growing interest in the role of the gut microbiome (GM) in host physiology and health, the mechanisms governing its assembly and its effects on the environment are poorly understood. In this article, we show that the host genotype and the GM of Daphnia influence the community structure of the surrounding bacterioplankton (BPK). When Daphnia genotypes were placed in an identical environment, both the GM and BPK showed a genotype and diet-dependent taxonomic composition. Overall, the GM strongly differed from the BPK in taxonomic composition and was characterized by a lower α-diversity, suggesting a selective rejecting of bacteria from the regional species pool. In a microbiome transplant experiment, the assembly of both the GM and BPK was strongly affected by the host genotype and the inoculum to which germ-free Daphnia were exposed. The combination of these results suggests a strong interaction between the host genotype, its GM and free-living microbial communities. Currently, it is generally assumed that an animal's diet has a strong effect on the animal's GM, but only a negligible (if any) effect on the surrounding environment. However, our results indicate that the diet/microbiome inocula have a small effect on the gut community and a large effect on the community in the surrounding environment. This structuring genotype × microbiome × environment effect is an essential prerequisite that could indicate that microbiomes play an important role in eco-evolutionary processes.