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Regulatory T lymphocytes expressing the forkhead/winged helix transcription factor Foxp3 (Treg) play a vital role in the protection of the organism from autoimmune disease and other immunopathologies. The antigen specificity of Treg plays an important role in their in vivo activity. We therefore assessed the diversity of the T-cell receptors (TCRs) for antigen expressed by Treg newly developed in the thymus of autoimmune type 1 diabetes-prone NOD mice and compared it to the control mouse strain C57BL/6. Our results demonstrate that use of the TCRα and TCRβ variable (V) and joining (J) segments, length of the complementarity determining region (CDR) 3, and the diversity of the TCRα and TCRβ chains are comparable between NOD and C57BL/6 mice. Genetic defects affecting the diversity of the TCR expressed by newly developed Treg therefore do not appear to be involved in the etiology of type 1 diabetes in the NOD mouse.

While the theory of micro-evolution by natural selection assigns a crucial role to competition, its role in macroevolution is less clear. Phylogenetic evidence for a decelerating accumulation of lineages suggests a feedback of lineage diversity on diversification, i.e., ecological limits to diversification. However, does this feedback only occur between close relatives, or do distant relatives also influence their diversification? In other words: are there phylogenetic limits to these ecological limits? Islands form ideal systems to answer these questions, because their boundedness facilitates an overview of all potential competitors. The DAISIE (Dynamic Assembly of Island biota through Speciation Immigration and Extinction) framework allows for testing the presence of diversity-dependence on islands given phylogenetic data on colonization and branching times. The current inference models in DAISIE assume that this diversity-dependence only applies within a colonizing clade, which we term clade-specific (CS) diversity-dependence. Here we introduce a new DAISIE model that assumes that diversity-dependence applies to all species regardless of their ancestry, i.e. diversity-dependence applies both to species within the same clade and between different clades. We call this island-wide (IW) diversity-dependence. Here we present a method to compute a likelihood for this model and develop a statistical procedure based on likelihood ratio bootstrapping to compare it to the likelihood of the CS model in order to overcome biases known for standard model selection. We apply it to the diversification of Eleutherodactylus frogs on Hispaniola. Across the Greater Antilles archipelago, this radiation shows repeated patterns of diversification in ecotypes which are similar across clades. This could be suggestive of overlapping niche space and hence between-clade interactions, i.e. IW diversity-dependence. But it could also be suggestive of only within-clade interactions, because between-clade interactions would have blocked the same ecotype re-appearing. We find that the CS model fits the data much better than the IW model, indicating that different colonizations, while resulting in similar ecotypes, are sufficiently distinct to avoid interacting strongly. We argue that non-overlapping distributions between clades (both spatially and in terms of ecotypes) cannot be used as evidence of CS diversity-dependence, because this pattern may be a consequence of IW diversity-dependence. By contrast, by using phylogenetic data rather than distributional data our method does allow for inferring the phylogenetic limits to ecological limits to diversification. We discuss how our new IW model advances our understanding also in other ways, ranging from identifying priority effects to modelling the spread of an epidemic in island-like systems, such as schools or hospitals.

Dispersal is a key process for the dynamics and functioning of meta-communities and meta-ecosystems. Meta-ecosystem theory, however, does not fully integrate the possible effects of dispersal, largely assuming random diffusion of organisms and nutrients, contrasting with rising empirical evidence for intraspecific variability in dispersal strategies. Dispersal is often associated with a suite of phenotypic traits, forming dispersal syndromes. Since phenotypic variability is now acknowledged as a key factor mediating ecosystem dynamics, we argue that dispersal syndromes can link trait-based ecology and meta-ecosystem functioning together. We highlight that the dispersal of individuals can be associated with functional effect traits and can therefore alter trophic and nutrient-mediated interactions in ecosystems. We illustrate how the association between dispersal tendency and functional traits can modify the spatial heterogeneity of ecosystems.

The branching patterns of molecular phylogenies are generally assumed to contain information on rates of the underlying speciation and extinction processes. Simple birth–death models with constant, time-varying, or diversity-dependent rates have been invoked to explain these patterns. They have one assumption in common: all lineages have the same set of diversification rates at a given point in time. It seems likely, however, that there is variability in diversification rates across subclades in a phylogenetic tree. This has inspired the construction of models that allow multiple rate regimes across the phylogeny, with instantaneous shifts between these regimes. Several methods exist for calculating the likelihood of a phylogeny under a specified mapping of diversification regimes and for performing inference on the most likely diversification history that gave rise to a particular phylogenetic tree. Here, we show that the likelihood computation of these methods is not correct. We provide a new framework to compute the likelihood correctly and show, with simulations of a single shift, that the correct likelihood indeed leads to parameter estimates that are on average in much better agreement with the generating parameters than the incorrect likelihood. Moreover, we show that our corrected likelihood can be extended to multiple rate shifts in time-dependent and diversity-dependent models. We argue that identifying shifts in diversification rates is a nontrivial model selection exercise where one has to choose whether shifts in now-extinct lineages are taken into account or not. Hence, our framework also resolves the recent debate on such unobserved shifts. [Diversification; macroevolution; phylogeny; speciation]

International audience; Phylogenetic trees are types of networks that describe the temporal relationship between individuals, species, or other units that are subject to evolutionary diversification. Many phylogenetic trees are constructed from molecular data that is often only available for extant species, and hence they lack all or some of the branches that did not make it into the present. This feature makes inference on the diversification process challenging. For relatively simple diversification models, analytical or numerical methods to compute the likelihood exist, but these do not work for more realistic models in which the likelihood depends on properties of the missing lineages. In this article, we study a general class of species diversification models, and we provide an expectation-maximization framework in combination with a uniform sampling scheme to perform maximum likelihood estimation of the parameters of the diversification process.

Dispersal is a central biological process tightly integrated into life-histories, morphology, physiology and behaviour. Such associations, or syndromes, are anticipated to impact the eco-evolutionary dynamics of spatially structured populations, and cascade into ecosystem processes. As for dispersal on its own, these syndromes are likely neither fixed nor random, but conditional on the experienced environment. We experimentally studied how dispersal propensity varies with individuals' phenotype and local environmental harshness using 15 species ranging from protists to vertebrates. We reveal a general phenotypic dispersal syndrome across studied species, with dispersers being larger, more active and having a marked locomotion-oriented morphology and a strengthening of the link between dispersal and some phenotypic traits with environmental harshness. Our proof-of-concept metacommunity model further reveals cascading effects of context-dependent syndromes on the local and regional organisation of functional diversity. Our study opens new avenues to advance our understanding of the functioning of spatially structured populations, communities and ecosystems.

While the theory of micro-evolution by natural selection assigns a crucial role to competition, its role in macroevolution is less clear. Phylogenetic evidence for a decelerating accumulation of lineages suggests a feedback of lineage diversity on diversification. However, does this feedback only occur between close relatives, or do distant relatives also influence each other’s diversification? In other words: are there phylogenetic limits to this diversity-dependence? Islands form ideal systems to answer these questions because their boundedness facilitates an overview of all potential competitors. The DAISIE (Dynamic Assembly of Island biota through Speciation Immigration and Extinction) framework allows for testing the presence of diversity-dependence on islands given phylogenetic data on colonization and branching times. The current inference models in DAISIE assume that this diversity-dependence only applies within a colonizing clade, i.e., all mainland species can colonize and diversify independently from one another. We term this clade-specific (CS) diversity-dependence. Here we introduce a new DAISIE model that assumes that diversity-dependence applies to all island species of a taxonomic group regardless of their mainland ancestry, i.e., diversity-dependence applies both to species within the same clade and between different clades established by different mainland species. We call this island-wide (IW) diversity-dependence. We present a method to compute a likelihood for this model given phylogenetic data on colonization and branching events and use likelihood ratio bootstrapping to compare it to the likelihood of the CS model in order to overcome biases known for standard model selection. We apply it to the diversification of Eleutherodactylus frogs on Hispaniola. Across the Greater Antilles archipelago, this radiation shows repeated patterns of diversification in ecotypes that are similar across clades. This could be suggestive of overlapping niche space and hence between-clade interactions, i.e., IW diversity-dependence. But it could also be suggestive of only within-clade interactions because between-clade interactions would have blocked the same ecotype from re-appearing. We find that the CS model fits the data much better than the IW model, indicating that different colonizations while resulting in similar ecotypes, are sufficiently distinct to avoid interacting strongly. We argue that non-overlapping distributions between clades (both spatially and in terms of ecotypes) cannot be used as evidence of CS diversity-dependence, because this pattern may be a consequence of IW diversity-dependence. By contrast, by using phylogenetic data rather than distributional data our method does allow for inferring the phylogenetic limits to diversity-dependent diversification. We discuss possibilities for future extensions and applications of our modelling approach. [Adaptive radiation; birth-death model; Caribbean; diversity-dependence; Eleutherodactylus; island biogeography.]

During the past decade, the characterization of microbial community in soil of contaminated sites was primarily done by high-throughput short-read amplicon sequencing. However, due to the similarity of 16S rRNA and ITS genes amplicon sequences, the short-read approach often limits the microbial composition analysis at the species level. Here, we simultaneously performed full-length and short-read amplicon sequencing to clarify the community composition and ecological status of different microbial taxa in contaminated soil from a high-resolution perspective. We found that (1) full-length 16S rRNA gene sequencing gave better resolution for bacterial identification at all levels, while there were no significant differences between the two sequencing platforms for fungal identification in some samples. (2) Abundant taxa were vital for microbial co-occurrences network constructed by both full-length and short-read sequencing data, and abundant fungal species such as Mortierella alpine, Fusarium solani, Mrakia frigida, and Chaetomium homopilatum served as the keystone species. (3) Heavy metal correlated with the microbial community significantly, and bacterial community and its abundant taxa were assembled by deterministic process, while the other taxa were dominated by stochastic process. These findings contribute to the understanding of the ecological mechanisms and microbial interactions in site soil ecosystems and demonstrate that full-length sequencing has the potential to provide more details of microbial community.

International audience; Changes in temperature affect consumer-resource interactions which underpin the functioning of ecosystems. However, existing studies report contrasting predictions regarding the impacts of warming on biological rates and community dynamics. To improve prediction accuracy and comparability, we develop a framework that combines two approaches: sensitivity analysis and aggregate parameters. The former determines which biological parameters impact the community most strongly. The use of aggregate parameters (i.e., maximal energetic efficiency, ρ, and interaction strength, κ), that combine multiple biological parameters, increases explanatory power and reduces the complexity of theoretical analyses. We illustrate the framework using empirically-derived thermal dependence curves of biological rates and applying it to consumer-resource biomass ratio and community stability. Based on our analyses, we present four predictions: 1) resource growth rate regulates biomass distributions at mild temperatures, 2) interaction strength alone determines the thermal boundaries of the community, 3) warming destabilises dynamics at low and mild temperatures only, 4) interactions strength must decrease faster than maximal energetic efficiency for warming to stabilise dynamics. We argue that directly measuring the aggregate parameters should increase the accuracy of predictions on warming impacts on food webs and promote cross-system comparisons.

International audience; The 21st century has seen an acceleration of anthropogenic climate change and biodiversity loss, with both stressors deemed to affect ecosystem functioning. However, we know little about the interactive effects of both stressors and in particular about the interaction of increased climatic variability and biodiversity loss on ecosystem functioning. This should be remedied because larger climatic variability is one of the main features of climate change. Here, we demonstrated that temperature fluctuations led to changes in the importance of biodiversity for ecosystem functioning. We used microcosm communities of different phytoplankton species richness and exposed them to a constant, mild, and severe temperature-fluctuating environment. Wider temperature fluctuations led to steeper biodiversity–ecosystem functioning slopes, meaning that species loss had a stronger negative effect on ecosystem functioning in more fluctuating environments. For severe temperature fluctuations, the slope increased through time due to a decrease of the productivity of species-poor communities over time. We developed a theoretical competition model to better understand our experimental results and showed that larger differences in thermal tolerances across species led to steeper biodiversity–ecosystem functioning slopes. Species-rich communities maintained their ecosystem functioning with increased fluctuation as they contained species able to resist the thermally fluctuating environments, while this was on average not the case in species-poor communities. Our results highlight the importance of biodiversity for maintaining ecosystem functions and services in the context of increased climatic variability under climate change.

Regulatory T lymphocytes expressing the forkhead/winged helix transcription factor Foxp3 (Treg) play a vital role in the protection of the organism from autoimmune disease and other immunopathologies. The antigen-specificity of Treg plays an important role in their in vivo activity. We therefore assessed the diversity of the T cell receptors for antigen (TCR) expressed by Treg newly developed in the thymus of autoimmune type I diabetes-prone NOD mice and compared it to the control mouse strain C57BL/6. Our results demonstrate that usage of the TCRa and TCRb variable (V) and joining (J) segments, length of the complementarity determining region (CDR) 3, and the diversity of the TCRa and TCRb chains are comparable between NOD and C57BL/6 mice. Genetic defects affecting the diversity of the TCR expressed by newly developed Treg therefore do not appear to be involved in the etiology of type I diabetes in the NOD mouse.

International audience; Ensuring stable food supplies is a major challenge for the 21st century. There is consensus that increased food production is necessary, but not sufficient, to achieve food security, and that agriculture should also aim at stabilizing crop production over time. In this context, biodiversity-based approaches to food security are increasingly being supported based on the fact that biodiversity can increase and stabilize crop production. However, agricultural systems are often highly fragmented and our current understanding of how such fragmentation affects biodiversity and food production remains incomplete, thus limiting our capacity to manage agricultural landscapes for food security. We developed a spatially explicit model of crop dynamics to investigate how the fragmentation of natural habitats for agricultural conversion impacts food production and food security, with a focus on animal-dependent crop production. Fragmentation produces a variety of spatial and biodiversity-mediated effects that affect both the mean and stability (temporal invariability) of animal-dependent crop production. Fragmentation has a dual effect on animal-dependent production. On the one hand, spatial aggregation of natural land decreases animal-dependent production by reducing the Landscape Pollination Potential, a metric that captures fragmentation and pollinator spillover effects within the agricultural landscape. But aggregation increases animal-dependent production by maintaining a higher pollinator diversity in larger fragments of natural habitat. The net effects of fragmentation on animal-dependent crop production depend on the land-use change pattern, the strength of the pollinator spillover to crop land and the animal pollination dependence of crops. Synthesis. Our study sheds new light in the food security debate by showing that high and stable crop production depends on biodiversity and the spatial fragmentation of agricultural landscapes, and by revealing the ecological mechanisms of food security in crop pollination systems. Management for food security should consider factors such as pollinators’ spillover, the amount and spatial aggregation of semi-natural habitat and the animal pollination dependence of crops. This information would be useful to design agricultural landscapes for high Landscape Pollination Potential. These results are highly relevant in the global change context, and given the worldwide trends in agriculture, which shifts towards more animal-dependent crop production.

Changes in temperature affect consumer-resource interactions, which underpin the functioning of ecosystems. However, existing studies report contrasting predictions regarding the impacts of warming on biological rates and community dynamics. To improve prediction accuracy and comparability, we develop an approach that combines sensitivity analysis and aggregate parameters. The former determines which biological parameters impact the community most strongly. The use of aggregate parameters (i.e., maximal energetic efficiency, ρ, and interaction strength, κ), that combine multiple biological parameters, increases explanatory power and reduces the complexity of theoretical analyses. We illustrate the approach using empirically-derived thermal dependence curves of biological rates and applying it to consumer-resource biomass ratio and community stability. Based on our analyses, we generate four predictions: 1) resource growth rate regulates biomass distributions at mild temperatures, 2) interaction strength alone determines the thermal boundaries of the community, 3) warming destabilises dynamics at low and mild temperatures only, 4) interactions strength must decrease faster than maximal energetic efficiency for warming to stabilise dynamics. We argue for the potential benefits of directly working with the aggregate parameters to increase the accuracy of predictions on warming impacts on food webs and promote cross-system comparisons.

International audience; Temperature and nutrients are two of the most important drivers of global change. Both can modify the elemental composition (i.e. stoichiometry) of primary producers and consumers. Yet their combined effect on the stoichiometry, dynamics, and stability of ecological communities remains largely unexplored. To fill this gap, we extended the Rosenzweig-MacArthur consumer-resource model by including thermal dependencies, nutrient dynamics, and stoichiometric constraints on both the primary producer and the consumer. We found that stoichiometric and nutrient conservation constraints dampen the paradox of enrichment and increased persistence at high nutrient levels. Nevertheless, stoichiometric constraints also reduced consumer persistence at extreme temperatures. Finally, we also found that stoichiometric constraints and nutrient dynamics can strongly influence biomass distribution across trophic levels by modulating consumer assimilation efficiency and resource growth rates along the environmental gradients. In the Rosenzweig-MacArthur model, consumer biomass exceeded resource biomass for most parameter values whereas, in the stoichiometric model, consumer biomass was strongly reduced and sometimes lower than resource biomass. Our findings highlight the importance of accounting for stoichiometric constraints as they can mediate the temperature and nutrient impact on the dynamics and functioning of ecological communities.

Molecular phylogenies have been increasingly recognized as an important source of information on species diversification. For many models of macroevolution, analytical likelihood formulas have been derived to infer macroevolutionary parameters from phylogenies. A few years ago, a general framework to numerically compute such likelihood formulas was proposed, which accommodates models that allow speciation and/or extinction rates to depend on diversity. This framework calculates the likelihood as the probability of the diversification process being consistent with the phylogeny from the root to the tips. However, while some readers found the framework presented in Etienne et al. (Proc R Soc Lond B Biol Sci 279(1732):1300–1309, 2012) convincing, others still questioned it (personal communication), despite numerical evidence that for special cases the framework yields the same (i.e., within double precision) numerical value for the likelihood as analytical formulas do that were independently derived for these special cases. Here we prove analytically that the likelihoods calculated in the new framework are correct for all special cases with known analytical likelihood formula. Our results thus add substantial mathematical support for the overall coherence of the general framework.

Quantifying stability properties of ecosystems is an important problem in ecology. A common approach is based on the recovery from pulse perturbations, and posits that the faster an ecosystem return to its pre-perturbation state, the more stable it is. Theoretical studies often collapse the recovery dynamics into a single quantity: the long-term rate of return, called asymptotic resilience. However, empirical studies typically measure the recovery dynamics at much shorter time scales. In this paper we explain why asymptotic resilience is rarely representative of the short-term recovery. First, we show that, in contrast to asymptotic resilience, short-term return rates depend on features of the perturbation, in particular on the way its intensity is distributed over species. We argue that empirically relevant predictions can be obtained by considering the median response over a set of perturbations, for which we provide explicit formulas. Next, we show that the recovery dynamics are controlled through time by different species: abundant species tend to govern the short-term recovery, while rare species often dominate the long-term recovery. This shift from abundant to rare species typically causes short-term return rates to be unrelated to asymptotic resilience. We illustrate that asymptotic resilience can be determined by rare species that have almost no effect on the observable part of the recovery dynamics. Finally, we discuss how these findings can help to better connect empirical observations and theoretical predictions.

Empirical knowledge of ecosystem stability and diversity-stability relationships is mostly based on the analysis of temporal variability of population and ecosystem properties. Variability, however, often depends on external factors that act as disturbances, making it difficult to compare its value across systems and relate it to other stability concepts. Here we show how variability, when viewed as a response to stochastic perturbations, can reveal inherent stability properties of ecological communities, with clear connections with other stability notions. This requires abandoning one-dimensional representations, in which a single variability measurement is taken as a proxy for how stable a system is, and instead consider the whole set of variability values associated to a given community, reflecting the whole set of perturbations that can generate variability. Against the vertiginous dimensionality of the perturbation set, we show that a generic variability-abundance pattern emerges from community assembly, which relates variability to the abundance of perturbed species. As a consequence, the response to stochastic immigration is governed by rare species while common species drive the response to environmental perturbations. In particular, the contrasting contributions of different species abundance classes can lead to opposite diversity-stability patterns, which can be understood from basic statistics of the abundance distribution. Our work shows that a multidimensional perspective on variability allows one to better appreciate the dynamical richness of ecological systems and the underlying meaning of their stability patterns.

International audience; Changes in land use generate trade-offs in the delivery of ecosystem services in agricultural landscapes. However, we know little about how the stability of ecosystem services responds to landscape composition, and what ecological mechanisms underlie these trade-offs. Here, we develop a model to investigate the dynamics of three ecosystem services in intensively managed agroecosystems, i.e., pollination-independent crop yield, crop pollination, and biodiversity. Our model reveals trade-offs and synergies imposed by landscape composition that affect not only the magnitude but also the stability of ecosystem service delivery. Trade-offs involving crop pollination are strongly affected by the degree to which crops depend on pollination and by their relative requirement for pollinator densities. We show conditions for crop production to increase with biodiversity and decreasing crop area, reconciling farmers' profitability and biodiversity conservation. Our results further suggest that, for pollination-dependent crops, management strategies that focus on maximizing yield will often overlook its stability. Given that agriculture has become more pollination-dependent over time, it is essential to understand the mechanisms driving these trade-offs to ensure food security.

In theoretical studies, the most commonly used measure of ecological stability is resilience: ecosystems asymptotic rate of return to equilibrium after a pulse-perturbation $-$or shock. A complementary notion of growing popularity is reactivity: the strongest initial response to shocks. On the other hand, empirical stability is often quantified as the inverse of temporal variability, directly estimated on data, and reflecting ecosystems response to persistent and erratic environmental disturbances. It is unclear whether and how this empirical measure is related to resilience and reactivity. Here, we establish a connection by introducing two variability-based stability measures belonging to the theoretical realm of resilience and reactivity. We call them intrinsic, stochastic and deterministic invariability; respectively defined as the inverse of the strongest stationary response to white-noise and to single-frequency perturbations. We prove that they predict ecosystems worst response to broad classes of disturbances, including realistic models of environmental fluctuations. We show that they are intermediate measures between resilience and reactivity and that, although defined with respect to persistent perturbations, they can be related to the whole transient regime following a shock, making them more integrative notions than reactivity and resilience. We argue that invariability measures constitute a stepping stone, and discuss the challenges ahead to further unify theoretical and empirical approaches to stability., Comment: 35 pages, 7 figures, 2 tables

Changes in land use generate trade-offs in the delivery of ecosystem services in agricultural landscapes. However, we know little about how the stability of ecosystem services responds to landscape composition, and what ecological mechanisms underlie these trade-offs. Here, we develop a model to investigate the dynamics of three ecosystem services in intensively-managed agroecosystems, i.e. pollination-independent crop yield, crop pollination, and biodiversity. Our model reveals trade-offs and synergies imposed by landscape composition that affect not only the magnitude but also the stability of ecosystem service delivery. Trade-offs involving crop pollination are strongly affected by the degree to which crops depend on pollination and by their relative requirement for pollinator densities. We show conditions for crop production to increase with biodiversity and decreasing crop area, reconciling farmers’ profitability and biodiversity conservation. Our results further suggest that, for pollination-dependent crops, management strategies that focus on maximising yield will often overlook its stability. Given that agriculture has become more pollination-dependent over time, it is essential to understand the mechanisms driving these trade-offs to ensure food security.

International audience; Aim: Ecosystem stability and its link with biodiversity have mainly been studied at the local scale. Here we present a simple theoretical model to address the joint dependence of diversity and stability on spatial scale, from local to continental.Methods: The notion of stability we use is based on the temporal variability of an ecosystem-level property, such as primary productivity. In this way, our model integrates the well-known species-area relationship (SAR) with a recent proposal to quantify the spatial scaling of stability, called the invariability-area relationship (IAR). Results: We show that the link between the two relationships strongly depends on whether the temporal fluctuations of the ecosystem property of interest are more correlated within than between species. If fluctuations are correlated within species but not between them, then the IAR is strongly constrained by the SAR. If instead individual fluctuations are only correlated by spatial proximity, then the IAR is unrelated to the SAR. We apply these two correlation assumptions to explore the effects of species loss and habitat destruction on stability, and find a rich variety of multi-scale spatial dependencies, with marked differences between the two assumptions. Main conclusions: The dependence of ecosystem stability on biodiversity across spatial scales is governed by the spatial decay of correlations within and between species. Our work provides a point of reference for mechanistic models and data analyses. More generally, it illustrates the relevance of macroecology for ecosystem functioning and stability.

The development of neutral community theory has shown that the assumption of species neutrality, although implausible on the level of individual species, can lead to reasonable predictions on the community level. While Hubbell's neutral model and several of its variants have been analyzed in quite some detail, the comparison of theoretical predictions with empirical abundance data is often hindered by technical problems. Only for a few models the exact solution of the stationary abundance distribution is known and sufficiently simple to be applied to data. For other models approximate solutions have been proposed, but their accuracy is questionable. Here, we argue that many of these technical problems can be overcome by replacing the assumption of constant community size (the zero-sum constraint) by the assumption of independent species abundances. We present a general sampling formula for community abundance data under this assumption. We show that for the few models for which an exact solution with zero-sum constraint is known, our independent-species approach leads to very similar parameter estimates as the zero-sum models, for six frequently studied tropical forest community samples. We show that our general sampling formula can be easily confronted to a much wider range of data sets (very large data sets, relative abundance data, presence-absence data, and sets of multiple samples) for a large class of models, including non-neutral ones. We provide an R package, called SADISA (Species Abundance Distributions under the Independent Species Assumption), to facilitate the use of the sampling formula. This article is protected by copyright. All rights reserved.

aeres : ACL; International audience; In this article we propose a new framework for studying adaptive radiations in the context of diversity-dependent diversification. Diversity dependence causes diversification to decelerate at the end of an adaptive radiation but also plays a key role in the initial pulse of diversification. In particular, key innovations (which in our definition include novel traits as well as new environments) may cause decoupling of the diversity-dependent dynamics of the innovative clade from the diversity-dependent dynamics of its ancestral clade. We present a likelihood-based inference method to test for decoupling of diversity dependence using molecular phylogenies. The method, which can handle incomplete phylogenies, identifies when the decoupling took place and which diversification parameters are affected. We illustrate our approach by applying it to the molecular phylogeny of the North American clade of the legume tribe Psoraleeae (47 extant species, of which 4 are missing). Two diversification rate shifts were previously identified for this clade; our analysis shows that the first, positive shift can be associated with decoupling of two Pediomelum subgenera from the other Psoraleeae lineages, while we argue that the second, negative shift can be attributed to speciation being protracted. The latter explanation yields nonzero extinction rates, in contrast to previous findings. Our framework offers a new perspective on macroevolution: new environments and novel traits (ecological opportunity) and diversity dependence (ecological limits) cannot be considered separately.

International audience; The debate between niche-based and neutral community theories centers around the question of which forces shape predominantly ecological communities. Niche theory attributes a central role to niche differences between species, which generate a difference between the strength of intra- and interspecific interactions. Neutral theory attributes a central role to migration processes and demographic stochasticity. One possibility to bridge these two theories is to combine them in a common mathematical framework. Here we propose a mathematical model that integrates the two perspectives. From a niche-based perspective, our model can be interpreted as a Lotka-Volterra model with symmetric interactions in which we introduce immigration and demographic stochasticity. From a neutral perspective, it can be interpreted as Hubbell's local community model in which we introduce a difference between intra- and interspecific interactions. We investigate the stationary species abundance distribution and other community properties as functions of the interaction coefficient, the immigration rate and the strength of demographic stochasticity.

International audience; The neutral theory of biodiversity and biogeography emphasizes the importance of dispersal and speciation to macro-ecological diversity patterns. While the influence of dispersal has been studied quite extensively, the effect of speciation has not received much attention, even though it was already claimed at an early stage of neutral theory development that the mode of speciation would leave a signature on metacommunity structure. Here, we derive analytical expressions for the distribution of abundances according to the neutral model with recruitment (i.e., dispersal and establishment) limitation and random fission speciation which seems to be a more realistic description of (allopatric) speciation than the point mutation mode of speciation mostly used in neutral models. We find that the two modes of speciation behave qualitatively differently except when recruitment is strongly limited. Fitting the model to six large tropical tree data sets, we show that it performs worse than the original neutral model with point mutation speciation but yields more realistic predictions for speciation rates, species longevities, and rare species. Interestingly, we find that the metacommunity abundance distribution under random fission is identical to the broken-stick abundance distribution and thus provides a dynamical explanation for this grand old lady of abundance distributions.

International audience; Entropy maximization (EM, also known as MaxEnt) is a general inference procedure that originated in statistical mechanics. It has been applied recently to predict ecological patterns, such as species abundance distributions and species-area relationships. It is well known in physics that the EM result strongly depends on how elementary configurations are described. Here we argue that the same issue is also of crucial importance for EM applications in ecology. To illustrate this, we focus on the EM prediction of species-level spatial abundance distributions. We show that the EM outcome depends on (1) the choice of configuration set, (2) the way constraints are imposed, and (3) the scale on which the EM procedure is applied. By varying these choices in the EM model, we obtain a large range of EM predictions. Interestingly, they correspond to spatial abundance distributions that have been derived previously from mechanistic models. We argue that the appropriate choice of the EM model assumptions is nontrivial and can be determined only by comparison with empirical data.

International audience; We propose a spatial version of the neutral community model on a network of interconnected patches. The dynamical equations for the abundances and higher order moments of the abundances are established. Due to the neutrality assumption these equations are autonomous, enabling an exact analysis of spatio-temporal dynamics. We compute local (i.e., inside a patch) and global (i.e., between patches) diversities, and illustrate our results with two examples: (1) a non-spatial community, for which we recover previous results, and (2) a model with a finite number of patches which are all connected to each other with equal migration intensity. We discuss the relevance of this model for experiments in microbial ecology.

International audience; Hubbell’s neutral model has become a major paradigm in ecology. Whereas the steady-state structure is well understood, results about the dynamical aspects of the model are scarce. Here we derive dynamical equations for the Simspon diversity index. Both mean and variance of the diversity are proven to satisfy stable linear system dynamics. We show that in the stationary limit we indeed recover previous results, and we supplement this with numerical simulations to validate the dynamical part of our analytical computations. These .ndings are especially relevant for experiments in microbial ecology, where the Simpson diversity index can be accurately measured as a function of time.

International audience; DNA reassociation kinetics, also known as Cot curves, were recently used by Gans and co-workers to estimate the number of bacterial species present in soil samples. By reanalysing the mathematical model we show that rather than the number of species, Simpson and Shannon diversity indices are encoded in the experimental data. Our main tool to establish this result are the so-called Renyi diversities, closely related to Hill numbers, illustrating the power of these concepts in interpreting ecological data. We argue that the huge diversity encountered in microbial ecology can be quantified more informatively by diversity indices than by number of species.

International audience; Rare long-distance dispersal is known to be critical for species dynamics, but how the interplay between short- and long-distance colonization influences regional persistence in a fragmented habitat remains poorly understood. We propose a metapopulation model that combines local colonization within habitat islands and long-distance colonization between islands. We study how regional occupancy dynamics are affected by the multiscale colonization process. We find that the island size distribution (ISD) is a key driver of the long-term occupancy dynamics. When the ISD is heterogeneous—that is, when the size of islands is variable—we show that extinction dynamics become very slow. We demonstrate that this behavior is unrelated to the well-known extinction debt near the critical extinction threshold. Hence, this finding questions the equivalence between extinction debt and critical transitions in the context of metapopulation collapse. Furthermore, we show that long-distance colonization can rescue small islands from extinction and sustain a steady regional occupancy. These results provide novel theoretical and practical insights into extinction dynamics and persistence in fragmented habitats and are thus relevant for the design of conservation strategies.

International audience; Over the past decade, the neutral theory of biodiversity has stirred up community assembly theory considerably by suggesting that stochasticity in the form of ecological drift is an important factor determining community composition and community turnover. The neutral theory assumes that all species within a community are functionally equivalent (the neutrality assumption), and therefore applies best to communities of trophically similar species. Evidently, trophically similar species may still differ in dispersal ability, and therefore may not be completely functionally equivalent. Here we present a new sampling formula that takes into account the partitioning of a community into two guilds that differ in immigration rate. We show that, using this sampling formula, we can accurately detect a subdivision into guilds from species abundance distributions, given ecological data about dispersal ability. We apply our sampling formula to tropical tree data from Barro Colorado Island, Panama. Tropical trees are divided depending on their dispersal mode, where biotically dispersed trees are grouped as one guild, and abiotically dispersed trees represent another guild. We find that breaking neutrality by adding guild structure to the neutral model significantly improves the fit to data and provides a better understanding of community assembly on BCI. Our findings are thus an important step towards an integration of neutral and niche theory.

International audience; Ecological communities are structured by processes op-erating at multiple spatial scales, which results in an often dauntingcomplexity. Here we present a simple graphical theory to study theinteraction of two fundamental community processes: resource com-petition at the local scale and dispersal at the regional scale. Weconsider a metacommunity model with two habitat patches in whichconsumer species compete for a spatially distributed resource. Weintroduce a graphical construction of the equilibrium metacom-munity composition, analogous to traditional competition theory fortwo resources. As in the nonspatial case,the zero net growth isoclines(ZNGIs) play a central role in the analysis. We show that a consumerspecies’ ZNGI depends on its dispersal characteristics, and this de-pendence leads to a unification of various dispersal-based coexistencemechanisms. We illustrate this unification using four specific mech-anisms: species-specific dispersal rates, spatially asymmetric dispersal,resource-dependent dispersal, and competition between habitat spe-cialists and generalists.

International audience; Metapopulation dynamics are jointly regulated by local and spatial factors. These factors may affect the dynamics of local populations and of the entire metapopulation differently. Previous studies have shown that dispersal can stabilize local populations; however, as dispersal also tends to increase spatial synchrony, its net effect on metapopulation stability has been controversial. Here we present a simple metapopulation model to study how dispersal, in interaction with other spatial and local processes, affects the temporal variability of metapopulations in a stochastic environment. Our results show that in homogeneous metapopulations, the local stabilizing and spatial synchronizing effects of dispersal cancel each other out, such that dispersal has no effect on metapopulation variability. This result is robust to moderate heterogeneities in local and spatial parameters. When local and spatial dynamics exhibit high heterogeneities, however, dispersal can either stabilize or destabilize metapopulation dynamics through various mechanisms. Our findings have important theoretical and practical implications. We show that dispersal functions as a form of spatial intraspecific mutualism in metapopulation dynamics and that its effect on metapopulation stability is opposite to that of interspecific competition on local community stability. Our results also suggest that conservation corridors should be designed with appreciation of spatial heterogeneities in population dynamics in order to maximize metapopulation stability.

We compare two proposals for the dynamical entropy of quantum deterministic systems (CNT and AFL) by studying their extensions to classical stochastic systems. We show that the natural measurement procedure leads to a simple explicit expression for the stochastic dynamical entropy with a clear information-theoretical interpretation. Finally, we compare our construction with other recent proposals., 15 pages

This paper consists of two parts. First we set up a general scheme of local traps in a homogeneous deterministic quantum system. The current of particles caught by the trap is linked to the dynamical behaviour of the trap states. In this way, transport properties in a homogeneous system are related to spectral properties of a coherent dynamics. Next we apply the scheme to a system of Fermions in the one-particle approximation. We obtain in particular lower bounds for the dynamical entropy in terms of the current induced by the trap.

Ecological trade-offs between species are often invoked to explain species coexistence in ecological communities. However, few mathematical models have been proposed for which coexistence conditions can be characterized explicitly in terms of a trade-off. Here we present a model of a plant community which allows such a characterization. In the model plant species compete for sites where each site has a fixed stress condition. Species differ both in stress tolerance and competitive ability. Stress tolerance is quantified as the fraction of sites with stress conditions low enough to allow establishment. Competitive ability is quantified as the propensity to win the competition for empty sites. We derive the deterministic, discrete-time dynamical system for the species abundances. We prove the conditions under which plant species can coexist in a stable equilibrium. We show that the coexistence conditions can be characterized graphically, clearly illustrating the trade-off between stress tolerance and competitive ability. We compare our model with a recently proposed, continuous-time dynamical system for a tolerance-fecundity trade-off in plant communities, and we show that this model is a special case of the continuous-time version of our model., Comment: To be published in Journal of Mathematical Biology. 30 pages, 5 figures, 5 appendices

One of the central questions of metacommunity theory is how dispersal of organisms affects species diversity. Here we show that the diversity-dispersal relationship should not be studied in isolation of other abiotic and biotic flows in the metacommunity. We study a mechanistic metacommunity model in which consumer species compete for an abiotic or biotic resource. We consider both consumer species specialized to a habitat patch, and generalist species capable of using the resource throughout the metacommunity. We present analytical results for different limiting values of consumer dispersal and resource dispersal, and complement these results with simulations for intermediate dispersal values. Our analysis reveals generic patterns for the combined effects of consumer and resource dispersal on the metacommunity diversity of consumer species, and shows that hump-shaped relationships between local diversity and dispersal are not universal. Diversity-dispersal relationships can also be monotonically increasing or multimodal. Our work is a new step towards a general theory of metacommunity diversity integrating dispersal at multiple trophic levels., Main text: 15 pages, 4 figures. Supplement: 25 pages, 12 figures

International audience; Lalande et al. (Microb. Ecol. 66(3):647–658, 2013) introduced a promising approach to quantify microbial diversity from fingerprinting profiles. Their analysis is based on extrapolating the abundance of the phylotypes detectable in a fingerprint towards the rare phylotypes of the community. By considering a set of reconstructed communities, Lalande et al. obtained a range of estimates for phylotype richness, Shannon diversity and Simpson diversity. They reported narrow ranges indicating accurate estimation, especially for Shannon and Simpson diversities. Here, we show that a much larger set of reconstructed communities than the one considered by Lalande et al. is consistent with the fingerprint. We find that the estimates for phylotype richness and Shannon diversity vary over orders of magnitude, but that the estimates for Simpson diversity are restricted to a narrow range (around 10 %). We conclude that only Simpson diversity can be estimated accurately from fingerprints.

Ecol. Lett. ISI Document Delivery No.: 132OA Times Cited: 0 Cited Reference Count: 46 de Mazancourt, Claire Isbell, Forest Larocque, Allen Berendse, Frank De Luca, Enrica Grace, James B. Haegeman, Bart Polley, H. Wayne Roscher, Christiane Schmid, Bernhard Tilman, David van Ruijven, Jasper Weigelt, Alexandra Wilsey, Brian J. Loreau, Michel Wiley-blackwell Hoboken; International audience; As biodiversity is declining at an unprecedented rate, an important current scientific challenge is to understand and predict the consequences of biodiversity loss. Here, we develop a theory that predicts the temporal variability of community biomass from the properties of individual component species in monoculture. Our theory shows that biodiversity stabilises ecosystems through three main mechanisms: (1) asynchrony in species’ responses to environmental fluctuations, (2) reduced demographic stochasticity due to overyielding in species mixtures and (3) reduced observation error (including spatial and sampling variability). Parameterised with empirical data from four long-term grassland biodiversity experiments, our prediction explained 22–75% of the observed variability, and captured much of the effect of species richness. Richness stabilised communities mainly by increasing community biomass and reducing the strength of demographic stochasticity. Our approach calls for a re-evaluation of the mechanisms explaining the effects of biodiversity on ecosystem stability.

Quantifying diversity is of central importance for the study of structure, function and evolution of microbial communities. The estimation of microbial diversity has received renewed attention with the advent of large-scale metagenomic studies. Here, we consider what the diversity observed in a sample tells us about the diversity of the community being sampled. First, we argue that one cannot reliably estimate the absolute and relative number of microbial species present in a community without making unsupported assumptions about species abundance distributions. The reason for this is that sample data do not contain information about the number of rare species in the tail of species abundance distributions. We illustrate the difficulty in comparing species richness estimates by applying Chao's estimator of species richness to a set of in silico communities: they are ranked incorrectly in the presence of large numbers of rare species. Next, we extend our analysis to a general family of diversity metrics ("Hill diversities"), and construct lower and upper estimates of diversity values consistent with the sample data. The theory generalizes Chao's estimator, which we retrieve as the lower estimate of species richness. We show that Shannon and Simpson diversity can be robustly estimated for the in silico communities. We analyze nine metagenomic data sets from a wide range of environments, and show that our findings are relevant for empirically-sampled communities. Hence, we recommend the use of Shannon and Simpson diversity rather than species richness in efforts to quantify and compare microbial diversity., Comment: To be published in The ISME Journal. Main text: 16 pages, 5 figures. Supplement: 16 pages, 4 figures

The branching times of molecular phylogenies allow us to infer speciation and extinction dynamics even when fossils are absent. Troublingly, phylogenetic approaches usually return estimates of zero extinction, conflicting with fossil evidence. Phylogenies and fossils do agree, however, that there are often limits to diversity. Here, we present a general approach to evaluate the likelihood of a phylogeny under a model that accommodates diversity-dependence and extinction. We find, by likelihood maximization, that extinction is estimated most precisely if the rate of increase in the number of lineages in the phylogeny saturates towards the present or first decreases and then increases. We demonstrate the utility and limits of our approach by applying it to the phylogenies for two cases where a fossil record exists (Cetacea and Cenozoic macroperforate planktonic foraminifera) and to three radiations lacking fossil evidence ( Dendroica , Plethodon and Heliconius ). We propose that the diversity-dependence model with extinction be used as the standard model for macro-evolutionary dynamics because of its biological realism and flexibility.

The mathematical structure of the two models is summarized in Table 1. The metacommunity composition inside a niche is given by Hubbell’s metacommunity distribution. The model of CP10 imposes the zero-sum constraint, whereas our model does not. Hence, the two models differ only in the sizes of the metacommunity niches. The absolute niche sizes (i.e. the number of individuals in a niche) are infinite in both models; the relative niche sizes (i.e. the fraction of individuals in a niche) are fixed in the model of CP10, and are randomly distributed in our model. This distribution tends to the fixed niche sizes of CP10’s model for high diversity, so that the two models coincide for highly diverse metacommunities. The local community is a sample from the metacommunity, that can be taken with or without dispersal limitation. For both models, the local community SAD inside a niche is given by the Ewens (without dispersal limitation; Ewens 1972) or the Etienne (with dispersal limitation; Etienne 2005) distribution. The models only differ in the niche sizes: fixed in the model of CP10, and randomly distributed in our model. Again, the latter distribution tends to the fixed niche sizes of CP10’s model when the diversity in the local community is high, so that the two models coincide for highly diverse communities.

Background The dual concepts of pan and core genomes have been widely adopted as means to assess the distribution of gene families within microbial species and genera. The core genome is the set of genes shared by a group of organisms; the pan genome is the set of all genes seen in any of these organisms. A variety of methods have provided drastically different estimates of the sizes of pan and core genomes from sequenced representatives of the same groups of bacteria. Results We use a combination of mathematical, statistical and computational methods to show that current predictions of pan and core genome sizes may have no correspondence to true values. Pan and core genome size estimates are problematic because they depend on the estimation of the occurrence of rare genes and genomes, respectively, which are difficult to estimate precisely because they are rare. Instead, we introduce and evaluate a robust metric - genomic fluidity - to categorize the gene-level similarity among groups of sequenced isolates. Genomic fluidity is a measure of the dissimilarity of genomes evaluated at the gene level. Conclusions The genomic fluidity of a population can be estimated accurately given a small number of sequenced genomes. Further, the genomic fluidity of groups of organisms can be compared robustly despite variation in algorithms used to identify genes and their homologs. As such, we recommend that genomic fluidity be used in place of pan and core genome size estimates when assessing gene diversity within genomes of a species or a group of closely related organisms.