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Our understanding of how biotic interactions influence animal community assembly is largely restricted to local systems due to the difficulty of obtaining ecologically meaningful assemblage data across large spatial extents. Here, we used thousands of spatio‐phenologically high‐resolution assemblages across three distinct European regions together with a functional diversity approach to understand community assembly of dragonflies and damselflies (Odonata), an insect group characterized by a pronounced competitive reproductive biology. We found that adult dragonfly, but not damselfly, assemblages were consistently composed of species morphologically more different than expected by chance based on the traits that enhance their interspecific reproductive encounters. These results provide consistent evidence for the role of competition in the assembly of animal communities, which we interpret is most likely caused by the territorial reproductive biology of dragonflies. Support for competition varied both spatially and seasonally following theoretical expectations, as it was strongest in locations and seasonal moments with low thermal stress (i.e. warm conditions) and high niche packing. Our study illustrates how spatio‐temporal diversity patterns arise from variation in assembly processes. [ABSTRACT FROM AUTHOR]

Biotic interactions are widely recognised as the backbone of ecological communities, but how best to study them is a subject of intense debate, especially at macro‐ecological scales. While some researchers claim that biotic interactions need to be observed directly, others use proxies and statistical approaches to infer them. Despite this ambiguity, studying and predicting the influence of biotic interactions on biogeographic patterns is a thriving area of research with crucial implications for conservation. Three distinct approaches are currently being explored. The first approach involves empirical observation and measurement of biotic interactions' effects on species demography in laboratory or field settings. While these findings contribute to theory and to understanding species' demographies, they can be challenging to generalise on a larger scale. The second approach centers on inferring biotic associations from observed co‐occurrences in space and time. The goal is to distinguish the environmental and biotic effects on species distributions. The third approach constructs extensive potential interaction networks, known as metanetworks, by leveraging existing knowledge about species ecology and interactions. This approach analyses local realisations of these networks using occurrence data and allows understanding large distributions of multi‐taxa assemblages. In this piece, we appraise these three approaches, highlighting their respective strengths and limitations. Instead of seeing them as conflicting, we advocate for their integration to enhance our understanding and expand applications in the emerging field of interaction biogeography. This integration shows promise for ecosystem understanding and management in the Anthropocene era. [ABSTRACT FROM AUTHOR]

1. Assembly of plant communities has long been scrutinized through the lens of trait-based ecology. Studies generally analyse functional traits related to the vegetative growth, survival and resource acquisition and thus ignore how assembly rules may affect plants at other stages of their life cycle, particularly when seeds disperse, persist in soil and germinate. 2. Here, we analysed an extensive dataset of 16 traits for 167 species measured in-situ in 36 grasslands located along an elevation gradient and studied the impact of abiotic filtering, biotic interactions and dispersal on traits reflecting different trait categories: plant vegetative growth, germination, dispersal and seed morphology. For each community, we quantified community-weighted means (CWMs) and functional diversity (FD) for all traits and established their relationships to mean annual temperature. 3. The seed traits were weakly correlated with vegetative traits. Therefore, these traits constituted independent axes of plant phenotypical variation that could be affected differently by community assembly rules. Abiotic filtering impacted mostly vegetative traits and to a lesser extent seed germination and morphological traits. Increasing low-temperature stress in upland sites selected for shortstature, slow-growing and frost-tolerant species that produce small quantities of small seeds with high degree of dormancy, high temperature requirements for germination and low germination speed. 4. Biotic interactions, specifically competition in the lowlands and facilitation in uplands, also filtered some functional traits in the studied communities. The benign climate in lowlands seems to promote plant with competitive strategies that include fast growth and resource acquisition (vegetative growth traits) and early and fast germination (germination traits), whereas the effects of facilitation on the vegetative and germination traits were cancelled out by the strong abiotic filtering. 5. The changes in the main dispersal vector from zoochory to anemochory along the elevation gradient strongly affected the dispersal and the seed morphological trait structure of the communities. This may be explained by stronger vertical turbulence and moderate warm upwinds and low grazing intensity in the uplands that select for light and non-round shaped seeds with lower terminal velocity and endozoochorous potential. 6. Synthesis. We demonstrate that, in addition to vegetative traits, seed traits can substantially contribute to functional structuring of plant communities along environmental gradients. Thus, the ‘hard’ seed traits related to germination and dispersal are critical to detect multiple, complex community assembly rules. Consequently, such traits should be included in core lists of plant traits and, when applicable, be incorporated into the analysis of community assembly. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Among key future challenges are the integration of mechanistic modelling and multi‐trophic interactions. Main conclusions: Our conclusion is that the filtering framework still holds promise, but only if researchers successfully navigate major pitfalls, foster the integration of mechanistic modelling and multi‐trophic interactions and directly account for uncertainty in their conclusions. [ABSTRACT FROM AUTHOR]

Soil microbial communities play a key role in ecosystem functioning but still little is known about the processes that determine their turnover (β‐diversity) along ecological gradients. Here, we characterize soil microbial β‐diversity at two spatial scales and at multiple phylogenetic grains to ask how archaeal, bacterial and fungal communities are shaped by abiotic processes and biotic interactions with plants. We characterized microbial and plant communities using DNA metabarcoding of soil samples distributed across and within eighteen plots along an elevation gradient in the French Alps. The recovered taxa were placed onto phylogenies to estimate microbial and plant β‐diversity at different phylogenetic grains (i.e. resolution). We then modeled microbial β‐diversities with respect to plant β‐diversities and environmental dissimilarities across plots (landscape scale) and with respect to plant β‐diversities and spatial distances within plots (plot scale). At the landscape scale, fungal and archaeal β‐diversities were mostly related to plant β‐diversity, while bacterial β‐diversities were mostly related to environmental dissimilarities. At the plot scale, we detected a modest covariation of bacterial and fungal β‐diversities with plant β‐diversity; as well as a distance–decay relationship that suggested the influence of ecological drift on microbial communities. In addition, the covariation between fungal and plant β‐diversity at the plot scale was highest at fine or intermediate phylogenetic grains hinting that biotic interactions between those clades depends on early‐evolved traits. Altogether, we show how multiple ecological processes determine soil microbial community assembly at different spatial scales and how the strength of these processes change among microbial clades. In addition, we emphasized the imprint of microbial and plant evolutionary history on today's microbial community structure. [ABSTRACT FROM AUTHOR]

Much effort has been devoted to better understanding the effects of environment and biodiversity on ecosystem functioning. However, few studies have moved beyond measuring biodiversity as species richness of a single group and/or focusing on a single ecosystem function. While there is a growing recognition that along environmental gradients, the compositional turnover of multiple trophic groups influences not only productivity but multiple ecosystem functions, we do not know yet which components of multi‐trophic β‐diversity influence which ecosystem functions.Here, we captured the biodiversity found in soils using environmental DNA to study total soil multi‐trophic β‐diversity (between all taxa regardless of their trophic group association), horizontal β‐diversities (β‐diversities within trophic groups) and vertical β‐diversity (β‐diversity across trophic groups) along a 1,000 m elevational gradient in the French Alps. Using path analyses, we quantified how these β‐diversity components mediate the effects of environmental turnover on the turnover of multiple ecosystem functions (i.e. productivity, N‐cycling, N‐leaching) and overall multifunctionality.While we found a strong direct effect of soil properties on the turnover of multiple ecosystem functions, we also found an indirect effect of climate and soil properties through multi‐trophic β‐diversity. More specifically, only total multi‐trophic β‐diversity and the horizontal β‐diversity of saprophytic fungi were strongly related to the turnover of multifunctionality and, to a lower extent, the turnover of productivity and N‐cycling. Our results suggest that decomposition processes and resulting nutrient availability are key to understand how ecosystem functions change along soil properties and climatic gradients in alpine ecosystems.By demonstrating how saprophytic fungi and their associated trophic groups can offset the direct responses of multiple ecosystem functions to environmental change, our study highlights the paramount importance of multi‐trophic diversity for better understanding ecosystem multifunctionality in a changing world. A free Plain Language Summary can be found within the Supporting Information of this article. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Abstract: Restoring resilient ecosystems in an era of rapid environmental change requires a flexible framework for selecting assemblages of species based on functional traits. However, current trait‐based models have been limited to algorithms that select species assemblages that only converge on specified average trait values, and could not accommodate the common desire among restoration ecologists to generate functionally diverse assemblages. We have solved this problem by applying a nonlinear optimization algorithm to solve for the species relative abundances that maximize Rao's quadratic entropy (Q) subject to other linear constraints. Rao's Q is a closed‐form algebraic expression of functional diversity that is maximized when the most abundant species are functionally dissimilar. Previous models have maximized species evenness subject to the linear constraints by maximizing the entropy function (H’). Maximizing Q alone produces an undesirable species abundance distribution because species that exhibit extreme trait values have the highest abundances. We demonstrate that the maximization of an objective function that additively combines Q and H’ produces a more even relative abundance distribution across the trait dimension. Some ecological restoration projects aim to restore communities that converge on one set of traits while diverging across another. The selectSpecies r function can derive assemblages for any size species pool that maximizes the diversity of any set of traits, while simultaneously converging on average values of any other set of traits. We demonstrate how the function works through examples using uniformly spaced trait distributions and data with a known structure. We also demonstrate the utility of the function using real trait data collected on dozens of species from three separate ecosystems: serpentine grasslands, ponderosa pine forests, and subtropical rainforests. The quantitative selection of species based on their functional traits for ecological restoration and experimentation must be both rigorous and accessible to practitioners. The selectSpecies function provides ecologists with an easy‐to‐use open‐source solution to objectively derive species assemblages based on their functional traits. [ABSTRACT FROM AUTHOR]

Abstract: 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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 characterized 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 data sets of repeated surveys. [ABSTRACT FROM AUTHOR]

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.)

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.

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.