Spatial heterogeneity of biomass turnover has contrasting effects on synchrony and stability in trophic metacommunities.

Spatial heterogeneity is a fundamental feature of ecosystems, and ecologists have identified it as a factor promoting the stability of population dynamics. In particular, differences in interaction strengths and resource supply between patches generate an asymmetry of biomass turnover with a fast and a slow patch coupled by a mobile predator. Here, we demonstrate that asymmetry leads to opposite stability patterns in metacommunities receiving localized perturbations depending on the characteristics of the perturbed patch. Perturbing prey in the fast patch synchronizes the dynamics of prey biomass between the two patches and destabilizes predator dynamics by increasing the predator's temporal variability. Conversely, perturbing prey in the slow patch decreases the synchrony of the prey's dynamics and stabilizes predator dynamics. Our results have implications for conservation ecology and suggest reinforcing protection policies in fast patches to dampen the effects of perturbations and promote the stability of population dynamics at the regional scale.

Abundant fungi dominate the complexity of microbial networks in soil of contaminated site: High-precision community analysis by full-length sequencing.

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.

The Phylogenetic Limits to Diversity-Dependent Diversification.

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.].

Dispersal syndromes in challenging environments: A cross-species experiment.

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.

IL-2 and IL-15 drive intrathymic development of distinct periphery-seeding CD4+Foxp3+ regulatory T lymphocytes.

Development of Foxp3-expressing regulatory T-lymphocytes (Treg) in the thymus is controlled by signals delivered in T-cell precursors via the TCR, co-stimulatory receptors, and cytokine receptors. In absence of IL-2, IL-15 or their receptors, fewer Treg apparently develop in the thymus. However, it was recently shown that a substantial part of thymic Treg are cells that had recirculated from the periphery back to the thymus, troubling interpretation of these results. We therefore reassessed the involvement of IL-2 and IL-15 in the development of Treg, taking into account Treg-recirculation. At the age of three weeks, when in wt and IL-15-deficient (but not in IL-2-deficient) mice substantial amounts of recirculating Treg are present in the thymus, we found similarly reduced proportions of newly developed Treg in absence of IL-2 or IL-15, and in absence of both cytokines even less Treg developed. In neonates, when practically no recirculating Treg were found in the thymus, the absence of IL-2 led to substantially more reduced Treg-development than deficiency in IL-15. IL-2 but not IL-15 modulated the CD25, GITR, OX40, and CD73-phenotypes of the thymus-egress-competent and periphery-seeding Treg-population. Interestingly, IL-2 and IL-15 also modulated the TCR-repertoire expressed by developing Treg. Upon transfer into Treg-less Foxp3sf mice, newly developed Treg from IL-2- (and to a much lesser extent IL-15-) deficient mice suppressed immunopathology less efficiently than wt Treg. Taken together, our results firmly establish important non-redundant quantitative and qualitative roles for IL-2 and, to a lesser extent, IL-15 in intrathymic Treg-development.

Dispersal syndromes can link intraspecific trait variability and meta-ecosystem functioning.

Dispersal mediates the flow of organisms in meta-communities and subsequently energy and material flows in meta-ecosystems. Individuals within species often vary in dispersal tendency depending on their phenotypic traits (i.e., dispersal syndromes), but the implications of dispersal syndromes for meta-ecosystems have been rarely studied. Using empirical examples on vertebrates, arthropods, and microbes, we highlight that key functional traits can be linked to dispersal. We argue that this coupling between dispersal and functional traits can have consequences for meta-ecosystem functioning, mediating flows of functional traits and thus the spatial heterogeneity of ecosystem functions. As dispersal syndromes may be genetically determined, the spatial heterogeneity of functional traits may be further carried over across generations and link meta-ecosystem functioning to evolutionary dynamics.

Stoichiometric constraints modulate temperature and nutrient effects on biomass distribution and community stability.

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.

Phytoplankton biodiversity is more important for ecosystem functioning in highly variable thermal environments.

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.

Theory of temperature-dependent consumer-resource interactions.

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 and (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.

The Repertoire of Newly Developing Regulatory T Cells in the Type 1 Diabetes-Prone NOD Mouse Is Very Diverse.

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 TCRß variable (V) and joining (J) segments, length of the complementarity determining region (CDR) 3, and the diversity of the TCRα and TCRß 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.

Detecting Lineage-Specific Shifts in Diversification: A Proper Likelihood Approach.

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].

Additional Analytical Support for a New Method to Compute the Likelihood of Diversification Models.

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.

The inherent multidimensionality of temporal variability: how common and rare species shape stability patterns.

Empirical knowledge of diversity-stability relationships is mostly based on the analysis of temporal variability. Variability, however, often depends on external factors that act as disturbances, which makes comparisons across systems difficult to interpret. Here, we show how variability can reveal inherent stability properties of ecological communities. This requires that we abandon 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 generated by all possible stochastic perturbations. Despite this complexity, in species-rich systems, a generic pattern emerges from community assembly, relating variability to the abundance of perturbed species. Strikingly, the contrasting contributions of different species abundance classes to variability, driven by different types of perturbations, can lead to opposite diversity-stability patterns. We conclude that a multidimensional perspective on variability helps reveal the dynamical richness of ecological systems and the underlying meaning of their stability patterns.

Trade-offs in the provisioning and stability of ecosystem services in agroecosystems.

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.

Habitat choice meets thermal specialization: Competition with specialists may drive suboptimal habitat preferences in generalists.

Limited dispersal is classically considered as a prerequisite for ecological specialization to evolve, such that generalists are expected to show greater dispersal propensity compared with specialists. However, when individuals choose habitats that maximize their performance instead of dispersing randomly, theory predicts dispersal with habitat choice to evolve in specialists, while generalists should disperse more randomly. We tested whether habitat choice is associated with thermal niche specialization using microcosms of the ciliate Tetrahymena thermophila, a species that performs active dispersal. We found that thermal specialists preferred optimal habitats as predicted by theory, a link that should make specialists more likely to track suitable conditions under environmental changes than expected under the random dispersal assumption. Surprisingly, generalists also performed habitat choice but with a preference for suboptimal habitats. Since this result challenges current theory, we developed a metapopulation model to understand under which circumstances such a preference for suboptimal habitats should evolve. We showed that competition between generalists and specialists may favor a preference for niche margins in generalists under environmental variability. Our results demonstrate that the behavioral dimension of dispersal-here, habitat choice-fundamentally alters our predictions of how dispersal evolve with niche specialization, making dispersal behaviors crucial for ecological forecasting facing environmental changes.

The relationship between the spatial scaling of biodiversity and ecosystem stability.

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.

Unifying dynamical and structural stability of equilibria.

We exhibit a fundamental relationship between measures of dynamical and structural stability of linear dynamical systems-e.g. linearized models in the vicinity of equilibria. We show that dynamical stability, quantified via the response to external perturbations (i.e. perturbation of dynamical variables), coincides with the minimal internal perturbation (i.e. perturbations of interactions between variables) able to render the system unstable. First, by reformulating a result of control theory, we explain that harmonic external perturbations reflect the spectral sensitivity of the Jacobian matrix at the equilibrium, with respect to constant changes of its coefficients. However, for this equivalence to hold, imaginary changes of the Jacobian's coefficients have to be allowed. The connection with dynamical stability is thus lost for real dynamical systems. We show that this issue can be avoided, thus recovering the fundamental link between dynamical and structural stability, by considering stochastic noise as external and internal perturbations. More precisely, we demonstrate that a linear system's response to white-noise perturbations directly reflects the intensity of internal white-noise disturbance that it can accommodate before becoming stochastically unstable.

Long-Distance Rescue and Slow Extinction Dynamics Govern Multiscale Metapopulations.

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.

Dispersal and metapopulation stability.

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.

A sampling formula for ecological communities with multiple dispersal syndromes.

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.