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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]

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]

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]