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All organisms must simultaneously tolerate the environment and access limiting resources if they are to persist. Approaches to understanding abiotic filtering and competitive interactions have generally been developed independently. Consequently, integrating those factors to predict species abundances and community structure remains an unresolved challenge. We introduce a new synthetic framework that models both abiotic filtering and competition by using functional traits. First, our framework estimates species carrying capacities along abiotic gradients. Second, it estimates pairwise competitive interactions as a function of species trait differences. Applied to the study of a complex wetland community, our combined approach more than doubles the explained variance of species abundances compared to a model of abiotic tolerances alone. Trait-based integration of competitive interactions and abiotic filtering improves our ability to predict species abundances, bringing us closer to more accurate predictions of biodiversity structure in a changing world., (© 2022 The Authors. Ecology Letters published by John Wiley & Sons Ltd.)

It has long been anticipated that relating functional traits to species demography would be a cornerstone for achieving large-scale predictability of ecological systems. If such a relationship existed, species demography could be modeled only by measuring functional traits, transforming our ability to predict states and dynamics of species-rich communities with process-based community models. Here, we introduce a new method that links empirical functional traits with the demographic parameters of a process-based model by calibrating a transfer function through inverse modeling. As a case study, we parameterize a modified Lotka-Volterra model of a high-diversity mountain grassland with static plant community and functional trait data only. The calibrated trait-demography relationships are amenable to ecological interpretation, and lead to species abundances that fit well to the observed community structure. We conclude that our new method offers a general solution to bridge the divide between trait data and process-based models in species-rich ecosystems.

Livestock farmers rely on a high and stable grassland productivity for fodder production to sustain their livelihoods. Future drought events related to climate change, however, threaten grassland functionality in many regions across the globe. The introduction of sustainable grassland management could buffer these negative effects. According to the biodiversity-productivity hypothesis, productivity positively associates with local biodiversity. The biodiversity-insurance hypothesis states that higher biodiversity enhances the temporal stability of productivity. To date, these hypotheses have mostly been tested through experimental studies under restricted environmental conditions, hereby neglecting climatic variations at a landscape-scale. Here, we provide a landscape-scale assessment of the contribution of species richness, functional composition, temperature, and precipitation on grassland productivity. We found that the variation in grassland productivity during the growing season was best explained by functional trait composition. The community mean of plant preference for nutrients explained 24.8% of the variation in productivity and the community mean of specific leaf area explained 18.6%, while species richness explained only 2.4%. Temperature and precipitation explained an additional 22.1% of the variation in productivity. Our results indicate that functional trait composition is an important predictor of landscape-scale grassland productivity., Competing Interests: The authors declare no competing interests., (© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Describing how ecological interactions change over space and time and how they are shaped by environmental conditions is crucial to understand and predict ecosystem trajectories. However, it requires having an appropriate framework to measure network diversity locally, regionally and between samples (α-, γ- and β-diversity). Here, we propose a unifying framework that builds on Hill numbers and accounts both for the probabilistic nature of biotic interactions and the abundances of species or groups. We emphasise the importance of analysing network diversity across different species aggregation levels (e.g. from species to trophic groups) to get a better understanding of network structure. We illustrate our framework with a simulation experiment and an empirical analysis using a global food-web database. We discuss further usages of the framework and show how it responds to recent calls on comparing ecological networks and analysing their variation across environmental gradients and time., (© 2019 John Wiley & Sons Ltd/CNRS.)

The invasive fungus Cryphonectria parasitica, the causal agent of chestnut blight, is able to survive and sporulate on the bark of fresh dead Castanea sativa wood for at least 2 years. Here, we experimentally investigated the role of fresh dead wood in the epidemiology of chestnut blight, specifically in the spread of the hyperparasitic virus Cryphonectria hypovirus 1, which acts as biocontrol agent of C. parasitica. A total of 152 artificially initiated, virulent bark cankers in four chestnut stands were treated with virus-infected asexual spores originating either from sporulating dead wood or from a spore suspension. Molecular markers for both the virus and the fungal carrier were used to examine the spread of the applied biocontrol virus. Fourteen months after treatment, 42 to 76% of the conidial spray-treated cankers and 50 to 60% of the cankers exposed to a sporulating dead stem had been virus infected by the applied hypovirulent conidia in all four study sites. Virus infection reduced canker expansion and promoted canker healing (callusing). Thus, fresh chestnut dead wood may play an important role in supporting the successful spread of natural hypovirulence in chestnut forests. Further, combined with the application of virus-infected conidial suspensions, it may help promote the establishment of artificially released hypoviruses in chestnut stands to control chestnut blight.

Investigating how trophic interactions influence the β-diversity of meta-communities is of paramount importance to understanding the processes shaping biodiversity distribution. Here, we apply a statistical method for inferring the strength of spatial dependencies between pairs of species groups. Using simulated community data generated from a multi-trophic model, we showed that this method can approximate biotic interactions in multi-trophic communities based on β-diversity patterns across groups. When applied to soil multi-trophic communities along an elevational gradient in the French Alps, we found that fungi make a major contribution to the structuring of β-diversity across trophic groups. We also demonstrated that there were strong spatial dependencies between groups known to interact specifically (e.g. plant-symbiotic fungi, bacteria-nematodes) and that the influence of environment was less important than previously reported in the literature. Our method paves the way for a better understanding and mapping of multi-trophic communities through space and time., (© 2018 John Wiley & Sons Ltd/CNRS.)

Reconstructing the processes that have shaped the emergence of biodiversity gradients is critical to understand the dynamics of diversification of life on Earth. Islands have traditionally been used as model systems to unravel the processes shaping biological diversity. MacArthur and Wilson's island biogeographic model predicts diversity to be based on dynamic interactions between colonization and extinction rates, while treating islands themselves as geologically static entities. The current spatial configuration of islands should influence meta-population dynamics, but long-term geological changes within archipelagos are also expected to have shaped island biodiversity, in part by driving diversification. Here, we compare two mechanistic models providing inferences on species richness at a biogeographic scale: a mechanistic spatial-temporal model of species diversification and a spatial meta-population model. While the meta-population model operates over a static landscape, the diversification model is driven by changes in the size and spatial configuration of islands through time. We compare the inferences of both models to floristic diversity patterns among land patches of the Indo-Australian Archipelago. Simulation results from the diversification model better matched observed diversity than a meta-population model constrained only by the contemporary landscape. The diversification model suggests that the dynamic re-positioning of islands promoting land disconnection and reconnection induced an accumulation of particularly high species diversity on Borneo, which is central within the island network. By contrast, the meta-population model predicts a higher diversity on the mainlands, which is less compatible with empirical data. Our analyses highlight that, by comparing models with contrasting assumptions, we can pinpoint the processes that are most compatible with extant biodiversity patterns., Competing Interests: We have no competing interests.

Rapid climatic changes and increasing human influence at high elevations around the world will have profound impacts on mountain biodiversity. However, forecasts from statistical models (e.g. species distribution models) rarely consider that plant community changes could substantially lag behind climatic changes, hindering our ability to make temporally realistic projections for the coming century. Indeed, the magnitudes of lags, and the relative importance of the different factors giving rise to them, remain poorly understood. We review evidence for three types of lag: "dispersal lags" affecting plant species' spread along elevational gradients, "establishment lags" following their arrival in recipient communities, and "extinction lags" of resident species. Variation in lags is explained by variation among species in physiological and demographic responses, by effects of altered biotic interactions, and by aspects of the physical environment. Of these, altered biotic interactions could contribute substantially to establishment and extinction lags, yet impacts of biotic interactions on range dynamics are poorly understood. We develop a mechanistic community model to illustrate how species turnover in future communities might lag behind simple expectations based on species' range shifts with unlimited dispersal. The model shows a combined contribution of altered biotic interactions and dispersal lags to plant community turnover along an elevational gradient following climate warming. Our review and simulation support the view that accounting for disequilibrium range dynamics will be essential for realistic forecasts of patterns of biodiversity under climate change, with implications for the conservation of mountain species and the ecosystem functions they provide., (© 2017 John Wiley & Sons Ltd.)

Grasslands deliver the resources for food production and are among the most biologically diverse ecosystems. These characteristics are often in conflict as increasing yield through fertilization can lead to biodiversity loss. Thus, the challenge in grassland management is to sustain both yield and diversity. Biodiversity-ecosystem functioning experiments typically reveal a positive relationship between manipulated species diversity and productivity. In contrast, observations of the effect of increasing productivity via fertilization suggest a negative association with biodiversity. Using a mathematical model simulating species co-existence along a resource gradient, we show that trade-offs and species pool structure (size and trait distribution) determines the shape of the productivity-diversity relationship. At a constant resource level, over-yielding drives a positive relationship between biodiversity and productivity. In contrast, along a resource gradient, the shape of the productivity-diversity relationship is determined by the distribution of species along trade-off axes and often resulted in a bell-shaped relationship. In accordance to this theoretical result, we then explain the general trend of plant biodiversity loss with fertilisation in the European flora, by showing empirical evidence that trait distribution of plant species pools throughout Europe is biased toward species preferring poorer soils.

Recent studies have shown that accounting for intraspecific trait variation (ITV) may better address major questions in community ecology. However, a general picture of the relative extent of ITV compared to interspecific trait variation in plant communities is still missing. Here, we conducted a meta-analysis of the relative extent of ITV within and among plant communities worldwide, using a data set encompassing 629 communities (plots) and 36 functional traits. Overall, ITV accounted for 25% of the total trait variation within communities and 32% of the total trait variation among communities on average. The relative extent of ITV tended to be greater for whole-plant (e.g. plant height) vs. organ-level traits and for leaf chemical (e.g. leaf N and P concentration) vs. leaf morphological (e.g. leaf area and thickness) traits. The relative amount of ITV decreased with increasing species richness and spatial extent, but did not vary with plant growth form or climate. These results highlight global patterns in the relative importance of ITV in plant communities, providing practical guidelines for when researchers should include ITV in trait-based community and ecosystem studies., (© 2015 John Wiley & Sons Ltd/CNRS.)

The α, β, γ diversity decomposition methodology is commonly used to investigate changes in diversity over space or time but rarely conjointly. However, with the ever-increasing availability of large-scale biodiversity monitoring data, there is a need for a sound methodology capable of simultaneously accounting for spatial and temporal changes in diversity.Using the properties of Chao's index, we adapted Rao's framework of diversity decomposition between orthogonal dimensions to a multiplicative α, β, γ decomposition of functional or phylogenetic diversity over space and time, thereby combining their respective properties. We also developed guidelines for interpreting both temporal and spatial β-diversities and their interaction.We characterised the range of β-diversity estimates and their relationship to the nested decomposition of diversity. Using simulations, we empirically demonstrated that temporal and spatial β-diversities are independent from each other and from α and γ-diversities when the study design is balanced, but not otherwise. Furthermore, we showed that the interaction term between the temporal and the spatial β-diversities lacked such properties.We illustrated our methodology with a case study of the spatio-temporal dynamics of functional diversity in bird assemblages in four regions of France. Based on these data, our method makes it possible to discriminate between regions experiencing different diversity changes in time. Our methodology may therefore be valuable for comparing diversity changes over space and time using large-scale datasets of repeated surveys.

Climate and land cover changes are important drivers of the plant species distributions and diversity patterns in mountainous regions. Although the need for a multifaceted view of diversity based on taxonomic, functional and phylogenetic dimensions is now commonly recognized, there are no complete risk assessments concerning their expected changes. In this paper, we used a range of species distribution models in an ensemble-forecasting framework together with regional climate and land cover projections by 2080 to analyze the potential threat for more than 2,500 plant species at high resolution (2.5 km × 2.5 km) in the French Alps. We also decomposed taxonomic, functional and phylogenetic diversity facets into α and β components and analyzed their expected changes by 2080. Overall, plant species threats from climate and land cover changes in the French Alps were expected to vary depending on the species' preferred altitudinal vegetation zone, rarity, and conservation status. Indeed, rare species and species of conservation concern were the ones projected to experience less severe change, and also the ones being the most efficiently preserved by the current network of protected areas. Conversely, the three facets of plant diversity were also projected to experience drastic spatial re-shuffling by 2080. In general, the mean α-diversity of the three facets was projected to increase to the detriment of regional β-diversity, although the latter was projected to remain high at the montane-alpine transition zones. Our results show that, due to a high-altitude distribution, the current protection network is efficient for rare species, and species predicted to migrate upward. Although our modeling framework may not capture all possible mechanisms of species range shifts, our work illustrates that a comprehensive risk assessment on an entire floristic region combined with functional and phylogenetic information can help delimitate future scenarios of biodiversity and better design its protection.

Premise of Study: Plant functional traits are commonly used as proxies for plant responses to environmental challenges, yet few studies have explored how functional trait distributions differ across gradients of land-use change. By comparing trait distributions in intact forests with those across land-use change gradients, we can improve our understanding of the ways land-use change alters the diversity and functioning of plant communities., Methods: We examined how the variation and distribution of trait values for seven plant functional traits differ between reference natural forest and three types of land-use conversion (pasture, old-field, or "legacy" sites-regrowth following logging), landscape productivity (NPP) and vegetation strata (tree or non-tree "understory"), in a meta-analysis of studies from 15 landscapes across five continents., Key Results: Although trait variation often differed between land-uses within a landscape, these patterns were rarely consistent across landscapes. The variance and distribution of traits were more likely to differ consistently between natural forest and land-use conversion categories for understory (non-tree) plants than for trees. Landscape productivity did not significantly alter the difference in trait variance between natural forest and land-use conversion categories for any trait except dispersal., Conclusions: Our results suggest that even for traits well linked to plant environmental response strategies, broad classes of land-use change and landscape productivity are not generally useful indicators of the mechanisms driving compositional changes in human-modified forest systems.