Summary1. An international group of scientists has built an open internet data base of life-history traits of the Northwest European flora (the LEDA-Traitbase) that can be used as a data source for fundamental research on plant biodiversity and coexistence, macro-ecological patterns and plant functional responses. 2. The species-trait matrix comprises referenced information under the control of an editorial board, for ca. 3000 species of the Northwest European flora, combining existing information and additional measurements. The data base currently contains data on 26 plant traits that describe three key features of plant dynamics: persistence, regeneration and dispersal. The LEDA-Traitbase is freely available at www.leda-traitbase.org. 3. We present the structure of the data base and an overview of the trait information available. 4. Synthesis. The LEDA Traitbase is useful for large-scale analyses of functional responses of communities to environmental change, effects of community trait composition on ecosystem properties and patterns of rarity and invasiveness, as well as linkages between traits as expressions of fundamental trade-offs in plants.

Understanding how communities of living organisms assemble has been a central question in ecology since the early days of the discipline. Disentangling the different processes involved in community assembly is not only interesting in itself but also crucial for an understanding of how communities will behave under future environmental scenarios. The traditional concept of assembly rules reflects the notion that species do not co-occur randomly but are restricted in their co-occurrence by interspecific competition. This concept can be redefined in a more general framework where the co-occurrence of species is a product of chance, historical patterns of speciation and migration, dispersal, abiotic environmental factors, and biotic interactions, with none of these processes being mutually exclusive. Here we present a survey and meta-analyses of 59 papers that compare observed patterns in plant communities with null models simulating random patterns of species assembly. According to the type of data under study and the different methods that are applied to detect community assembly, we distinguish four main types of approach in the published literature: species co-occurrence, niche limitation, guild proportionality and limiting similarity. Results from our meta-analyses suggest that non-random co-occurrence of plant species is not a widespread phenomenon. However, whether this finding reflects the individualistic nature of plant communities or is caused by methodological shortcomings associated with the studies considered cannot be discerned from the available metadata. We advocate that more thorough surveys be conducted using a set of standardized methods to test for the existence of assembly rules in data sets spanning larger biological and geographical scales than have been considered until now. We underpin this general advice with guidelines that should be considered in future assembly rules research. This will enable us to draw more accurate and general conclusions about the non-random aspect of assembly in plant communities.

Abstract. Many studies have shown plant species' dispersal distances to be strongly related to life-history traits, but how well different traits can predict dispersal distances is not yet known. We used cross-validation techniques and a global data set (576 plant species) to measure the predictive power of simple plant traits to estimate species' maximum dispersal distances. Including dispersal syndrome (wind, animal, ant, ballistic, and no special syndrome), growth form (tree, shrub, herb), seed mass, seed release height, and terminal velocity in different combinations as explanatory variables we constructed models to explain variation in measured maximum dispersal distances and evaluated their power to predict maximum dispersal distances. Predictions are more accurate, but also limited to a particular set of species, if data on more specific traits, such as terminal velocity, are available. The best model (R 2 ¼ 0.60) included dispersal syndrome, growth form, and terminal velocity as fixed effects. Reasonable predictions of maximum dispersal distance (R 2 ¼ 0.53) are also possible when using only the simplest and most commonly measured traits; dispersal syndrome and growth form together with species taxonomy data. We provide a function (dispeRsal) to be run in the software package R. This enables researchers to estimate maximum dispersal distances with confidence intervals for plant species using measured traits as predictors. Easily obtainable trait data, such as dispersal syndrome (inferred from seed morphology) and growth form, enable predictions to be made for a large number of species.

Functional trait differences among species are increasingly used to infer the effects of biotic and abiotic processes on species coexistence. Commonly, the trait diversity observed within communities is compared to patterns simulated in randomly generated communities based on sampling within a region. The resulting patterns of trait convergence and divergence are assumed to reveal abiotic and biotic processes, respectively. However, biotic processes such as competition can produce both trait divergence and convergence, through either excluding similar species (niche differences, divergence) or excluding dissimilar species (weaker competitor exclusion, convergence). Hence, separating biotic and abiotic processes that can produce identical patterns of trait diversity, or even patterns that neutralize each other, is not feasible with previous methods. We propose an operational framework in which the functional trait dissimilarity within communities (FDcomm) is compared to the corresponding trait dissimilarity expected from the species pool (i.e., functional species pool diversity, FDpool). FDpool includes the set of potential species for a site delimited by the operating environmental and dispersal limitation filters. By applying these filters, the resulting pattern of trait diversity is consistent with biotic processes, i.e., trait divergence (FDcomm > FDpool) indicates niche differentiation, while trait convergence (FDcomm < FDpool) indicates weaker competitor exclusion. To illustrate this framework, with its potential application and constraints, we analyzed both simulated and field data. The functional species pool framework more consistently detected the simulated trait diversity patterns than previous approaches. In the field, using data from plant communities of typical Northern European habitats in Estonia, we found that both niche-based and weaker competitor exclusion influenced community assembly, depending on the traits and community considered. In both simulated and field data, we demonstrated that only by estimating the species pool of a site is it possible to differentiate the patterns of trait dissimilarity produced by operating biotic processes. The framework, which can be applied with both functional and phylogenetic diversity, enables a reinterpretation of community assembly processes. Solving the challenge of defining an appropriate reference species pool for a site can provide a better understanding of community assembly.

Summary 1.Dispersal is fundamental to ecological processes at all scales and levels of organization, but progress is limited by a lack of information about the general shape and form of plant dispersal kernels. We addressed this gap by synthesizing empirical data describing seed dispersal and fitting general dispersal kernels representing major plant types and dispersal modes. 2. A comprehensive literature search resulted in 107 papers describing 168 dispersal kernels for 144 vascular plant species. The data covered 63 families, all the continents except Antarctica, and the broad vegetation types of forest, grassland, shrubland and more open habitats (e.g. deserts). We classified kernels in terms of dispersal mode (ant, ballistic, rodent, vertebrates other than rodents, vehicle or wind), plant growth form (climber, graminoid, herb, shrub or tree), seed mass and plant height. 3. We fitted 11 widely used probability density functions to each of the 168 data sets to provide a statistical description of the dispersal kernel. The exponential power (ExP) and log-sech (LogS) functions performed best. Other 2-parameter functions varied in performance. For example, the lognormal and Weibull performed poorly, while the 2Dt and power law performed moderately well. Of the single-parameter functions, the Gaussian performed very poorly, while the exponential performed better. No function was among the best-fitting for all data sets. 4. For 10 plant growth form/dispersal mode combinations for which we had >3 data sets, we fitted ExP and LogS functions across multiple data sets to provide generalized dispersal kernels. We also fitted these functions to subdivisions of these growth form/dispersal mode combinations in terms of seed mass (for animal-dispersed seeds) or plant height (wind-dispersed) classes. These functions provided generally good fits to the grouped data sets, despite variation in empirical methods, local conditions, vegetation type and the exact dispersal process. 5. Synthesis. We synthesize the rich empirical information on seed dispersal distances to provide standardized dispersal kernels for 168 case studies and generalized kernels for plant growth form/ dispersal mode combinations. Potential uses include the following: (i) choosing appropriate dispersal functions in mathematical models; (ii) selecting informative dispersal kernels for one's empirical study system; and (iii) using representative dispersal kernels in cross-taxon comparative studies.

Plant traits have been widely used to characterize different aspects of the ecology of plant species. Despite its wide distribution and its proven significance at the level of individuals, communities, and populations, the ability to form mycorrhizal associations has been largely neglected in these studies so far. Analyzing plant traits associated with the occurrence of mycorrhizas in plants can therefore enhance our understanding of plant strategies and distributions. Using a comparative approach, we tested for associations between mycorrhizal status and habitat characteristics, life history traits, and plant distribution patterns in 1752 species of the German flora (a major part of the Central European flora). Data were analyzed using log-linear models or generalized linear models, both accounting for phylogenetic relationships. Obligatorily mycorrhizal (OM) species tended to be positively associated with higher temperature, drier habitats, and higher pH; and negatively associated with moist, acidic, and fertile soils. Competitive species were more frequently OM, and stress tolerators were non-mycorrhizal (NM), while ruderal species did not show any preference. Facultatively mycorrhizal (FM) species showed the widest geographic and ecological amplitude. Indigenous species were more frequently FM and neophytes (recent aliens) more frequently OM than expected. FM species differed markedly from OM and NM species in almost all analyzed traits. Specifically, they showed a wider geographic distribution and ecological niche. Our study of the relationships between mycorrhizal status and other plant traits provides a comprehensive test of existing hypotheses and reveals novel patterns. The clear distinction between FM and OM + NM species in terms of their ecology opens up a new field of research in plant-mycorrhizal ecology.

The stability of ecological communities is critical for the stable provisioning of ecosystem services, such as food and forage production, carbon sequestration, and soil fertility. Greater biodiversity is expected to enhance stability across years by decreasing synchrony among species, but the drivers of stability in nature remain poorly resolved. Our analysis of time series from 79 datasets across the world showed that stability was associated more strongly with the degree of synchrony among dominant species than with species richness. The relatively weak influence of species richness is consistent with theory predicting that the effect of richness on stability weakens when synchrony is higher than expected under random fluctuations, which was the case in most communities. Land management, nutrient addition, and climate change treatments had relatively weak and varying effects on stability, modifying how species richness, synchrony, and stability interact. Our results demonstrate the prevalence of biotic drivers on ecosystem stability, with the potential for environmental drivers to alter the intricate relationship among richness, synchrony, and stability.

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