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.

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.

Aim: More than ever, ecologists seek to understand how species are distributed and have assembled into communities using the "filtering framework". This framework is based on the hypothesis that local assemblages result from a series of abiotic and biotic filters applied to regional species pools and that these filters leave predictable signals in observed diversity patterns. In theory, statistical comparisons of expected and observed patterns enable data-driven tests of assembly processes. However, so far this framework has fallen short in delivering generalizable conclusions, challenging whether (and how) diversity patterns can be used to characterize and understand underlying assembly processes better.Methods: By synthesizing the previously raised critiques and suggested solutions in a comprehensive way, we identify 10 pitfalls that can lead to flawed interpretations of α-diversity patterns, summarize solutions developed to circumvent these pitfalls and provide general guidelines. Results:We find that most issues arise from an overly simplistic view of potential processes that influence diversity patterns, which is often motivated by practical constraints on study design, focal scale and methodology. We outline solutions for each pitfall, such as methods spanning over spatial, environmental or phylogenetic scales, and suggest guidelines for best scientific practices in community ecology.

We argue that the traditional null model approach can only identify a single main process at a time and suggest to rather use a family of null models to disentangle intertwined assembly processes acting across spatial and evolutionary scales.

Summary 1.Assembly of grassland communities has long been scrutinized through the lens of functional diversity. Studies generally point to an overwhelming influence of climate on observed patterns of functional diversity, despite experimental evidence demonstrating the importance of biotic interactions. We postulate that this is because most observational studies neglect both scale dependencies of assembly processes and phenotypic variation between individuals. Here, we test for changes in the importance of abiotic filtering and biotic interactions along a stress gradient by explicitly accounting for different scales. In addition to quantifying intraspecific trait variability (ITV), we also vary the two components of spatial scale, including grain (i.e. community size) and extent (i.e. the geographical area that defines the species pool). 2.We sampled 20 grassland communities in ten sites distributed along a 975-m elevation gradient. At each site, we measured seven functional traits for a total of 2020 individuals at different spatial grains. We related community functional diversity metrics to the main environmental gradient of our study area, growing season length (GSL), and assessed the dependence of these relationships on spatial grain, spatial extent and ITV.3. At large spatial grain and extent, the imprint of environmental filtering on functional diversity became more important with increasing stress (i.e. functional diversity decreased with shorter GSL). At small spatial grain and extent, we found a convex relationship between functional diversity and GSL congruent with the hypothesis that competition is dominant at low-stress levels while facilitative interactions are dominant at high-stress levels (i.e. high functional diversity at both extremes of the stress gradient). Importantly, the effect of intraspecific variability on assembly rules was noticeable only at small spatial grain and extent.4. Synthesis. Our study reveals how the combination of abiotic stress and biotic interactions shapes the functional diversity of alpine grasslands at different spatial scales, and highlights the importance of phenotype variation between individuals for community assembly processes at fine spatial scale. Our results suggest that studies analysing trait-based assembly rules but ignoring ITV and focusing on a single spatial scale are likely to miss essential features of community diversity patterns.

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 2500 plant species at high resolution (2.5  2.5 km) in the French Alps. We also decomposed taxonomic, functional and phylogenetic diversity facets into a and b 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 a-diversity of the three facets was projected to increase to the detriment of regional b-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.

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.

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.