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Wetland soils are the greatest source of nitrous oxide (N 2 O), a critical greenhouse gas and ozone depleter released by microbes. Yet, microbial players and processes underlying the N 2 O emissions from wetland soils are poorly understood. Using in situ N 2 O measurements and by determining the structure and potential functional of microbial communities in 645 wetland soil samples globally, we examined the potential role of archaea, bacteria, and fungi in nitrogen (N) cycling and N 2 O emissions. We show that N 2 O emissions are higher in drained and warm wetland soils, and are correlated with functional diversity of microbes. We further provide evidence that despite their much lower abundance compared to bacteria, nitrifying archaeal abundance is a key factor explaining N 2 O emissions from wetland soils globally. Our data suggest that ongoing global warming and intensifying environmental change may boost archaeal nitrifiers, collectively transforming wetland soils to a greater source of N 2 O. The wetland soil microbiome has a major impact on greenhouse gas emissions. Here the authors characterize how a group of archaea contribute to N 2 O emissions and find that climate and land use changes could promote these organisms.

Native biodiversity decline and non-native species spread are major features of the Anthropocene. Both processes can drive biotic homogenization by reducing trait and phylogenetic differences in species assemblages between regions, thus diminishing the regional distinctiveness of biotas and likely have negative impacts on key ecosystem functions. However, a global assessment of this phenomenon is lacking. Here, using a dataset of >200,000 plant species, we demonstrate widespread and temporal decreases in species and phylogenetic turnover across grain sizes and spatial extents. The extent of homogenization within major biomes is pronounced and is overwhelmingly explained by non-native species naturalizations. Asia and North America are major sources of non-native species; however, the species they export tend to be phylogenetically close to recipient floras. Australia, the Pacific and Europe, in contrast, contribute fewer species to the global pool of non-natives, but represent a disproportionate amount of phylogenetic diversity. The timeline of most naturalisations coincides with widespread human migration within the last ~500 years, and demonstrates the profound influence humans exert on regional biotas beyond changes in species richness. Human-driven movements and extinctions of species have made plant communities across biomes more homogenous. Here the authors quantify plant vascular species and phylogenetic homogenization across the globe, finding that non-native species naturalisations have been a major driver.

Although species with larger body size and slow pace of life have a higher risk of extinction at a global scale, it is unclear whether this global trend will be consistent across biogeographic realms. Here we measure the functional diversity of terrestrial and freshwater vertebrates in the six terrestrial biogeographic realms and predict their future changes through scenarios mimicking a gradient of extinction risk of threatened species. We show vastly different effects of extinctions on functional diversity between taxonomic groups and realms, ranging from almost no decline to deep functional losses. The Indo-Malay and Palearctic realms are particularly inclined to experience a drastic loss of functional diversity reaching 29 and 31%, respectively. Birds, mammals, and reptiles regionally display a consistent functional diversity loss, while the projected losses of amphibians and freshwater fishes differ across realms. More efficient global conservation policies should consider marked regional losses of functional diversity across the world. Anthropogenic extinctions are driving functional shifts in biological communities, but these changes might differ considerably among taxa and biogeographic regions. Here the authors show that projected losses of functional diversity among land and freshwater vertebrates are unevenly distributed across the world.

Plant traits determine how individual plants cope with heterogeneous environments. Despite large variability in individual traits, trait coordination and trade-offs 1 , 2 result in some trait combinations being much more widespread than others, as revealed in the global spectrum of plant form and function (GSPFF 3 ) and the root economics space (RES 4 ) for aboveground and fine-root traits, respectively. Here we combine the traits that define both functional spaces. Our analysis confirms the major trends of the GSPFF and shows that the RES captures additional information. The four dimensions needed to explain the non-redundant information in the dataset can be summarized in an aboveground and a fine-root plane, corresponding to the GSPFF and the RES, respectively. Both planes display high levels of species aggregation, but the differentiation among growth forms, families and biomes is lower on the fine-root plane, which does not include any size-related trait, than on the aboveground plane. As a result, many species with similar fine-root syndromes display contrasting aboveground traits. This highlights the importance of including belowground organs to the GSPFF when exploring the interplay between different natural selection pressures and whole-plant trait integration. The authors analyse the coordination and trade-off of the aboveground and fine-root traits of vascular plants using global trait databases.

When restoring habitat for biodiversity, the most effective outcome will be achieved by restoration projects which target several organism groups or ecosystem types. Such integrated approaches require direct comparisons among different ecological communities while evaluating success of restoration. The Community Completeness Index (CCI) is a recently developed metric that allows such comparisons by accounting for both present and absent but otherwise suitable taxa. We empirically evaluated the applicability of CCI for assessing the outcome of ecological restoration. We analyzed how species richness and the completeness of ecological communities recover after restoration, for different ecological groups and ecosystem types, and how it develops over time after restoration. Analyses were performed on 18 datasets with per site presence-absence data from Northern Europe. Each dataset represented one of the three habitat types (mire, forest, grassland) and different ecological groups (plants, flying insects, epigeic invertebrates). Datasets contained pristine, degraded and restored sites. We calculated the dark diversity and subsequently CCI based on species co-occurrences. Our multiple-study analyses revealed that CCI of grassland plant communities increased faster after restoration than invertebrate communities or plant communities in forests and mires. In addition, flying insect communities demonstrated significantly highest CCI in pristine mires. Some results were significant only for richness but not for CCI indicating species pool effect. Finally, completeness and species richness of restored communities increased with time since restoration. As such, our study demonstrated that CCI is a useful tool in evaluating restoration success across different organism groups and ecosystem types.

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 log-normal 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.

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 (R² = 0.60) included dispersal syndrome, growth form, and terminal velocity as fixed effects. Reasonable predictions of maximum dispersal distance (R² = 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.

Locally observed biodiversity always consists of only a fraction of its site‐specific species pool. Why some suitable species are absent, shaping dark diversity of that site, is a basic yet increasingly crucial question in the face of global biodiversity degradation. The ultimate processes underlying dark diversity associate with either dispersal or persistence limitations, or both. These two limitations in turn link to several characteristics of individual species and sites, making it challenging to detect the exact factors contributing to dark diversity in a particular metacommunity. Here, we propose a metric, dark diversity affinity (DDA), which measures the tendencies of individual species to be absent from suitable sites and of individual sites to miss suitable species. We developed a Bayesian model interrelating four types of datasets: metacommunity matrix of species presences in sites, species‐sites suitability matrix, species functional traits and site characteristics. In the model, DDA operates as an adjustment bridging the disparity between site‐specific suitability and observed presence/absence of each species at each site. Furthermore, DDA can be related to individual properties of species and sites through logistic regression sub‐models. We demonstrated our framework using nine empirical datasets of vertebrate, invertebrate and vascular plant metacommunities. We show the decomposed roles of species traits and site characteristics in defining DDA and, therefore, dark diversity in metacommunities. In the empirical datasets, various functional traits, which related to morphology, reproduction, dispersal ability, population attributes, resource specificity and life history, significantly affected species‐level DDA, while site characteristics regarding habitat types and attributes, resource availability, pollution, and edaphic and water conditions influenced DDA at the site level. Our framework provides a concept and methodological toolbox that allows identification of the processes underlying dark diversity and advances both the theory of community ecology and biodiversity conservation. Conservation actions can be more successful by knowing whether species loss in a particular metacommunity is associated to some species traits or site characteristics and what their relative contributions are.

1. Trait differences among plants are expected to influence the outcome of competition; competition should be strongest between similar species (or individuals) under limiting similarity, and between dissimilar species within competitive hierarchies. These hypotheses are often used to infer competitive dynamics from trait patterns within communities. However, plant traits are frequently plastic in response to competition. This variation is poorly accounted for in trait-based studies of competition and community assembly. 2. To explore the relationship between trait responses and competitive outcomes, we grew 15 species alone, in monoculture and in mixture. We measured traits relating to leaf and root tissue morphology as well as biomass allocation and related competition-induced changes in these traits to intra- and interspecific competition using multi-model inference. Additionally, we tested how traits from different competitive environments influenced potential community assembly inferences. 3. The competitive environment had large effects on species' traits, although many effects were species specific. Differences among species in how competition affected trait expression were linked to both intra- and interspecific competition, frequently affecting competitive hierarchies. Intraspecific competition was lower for species that limited competition-induced increases in root allocation and had less variability in this trait overall. Interspecific competition was lower for species with larger leaves and lower specific leaf area than their neighbours. Switching to more stress-tolerant strategies by increasing root diameter and leaf tissue density also reduced competition. However, dissimilarity in root tissue density also minimized competition, consistent with limiting similarity affecting competitive outcomes. Moreover, changes in these traits were linked to changes in functional diversity, suggesting that competition affects functional diversity by affecting trait expression. 4. Synthesis. Both trait hierarchies and trait dissimilarity affect the outcome of competition by acting on different traits, although competition-induced changes in trait expression can alter competitive outcomes. Moreover, the magnitude of these trait changes suggests that the source environment where plant traits are collected can affect the inferences drawn from trait patterns within communities. Combined, our results suggest that considering the effect of competition on trait expression is critical to understanding the relationship between traits and community assembly.

Although experiments show a positive association between vascular plant and arbuscular mycorrhizal fungal (AMF) species richness, evidence from natural ecosystems is scarce. Furthermore, there is little knowledge about how AMF richness varies with belowground plant richness and biomass. We examined relationships among AMF richness, above‐ and belowground plant richness, and plant root and shoot biomass in a native North American grassland. Root‐colonizing AMF richness and belowground plant richness were detected from the same bulk root samples by 454‐sequencing of the AMF SSU rRNA and plant trnL genes. In total we detected 63 AMF taxa. Plant richness was 1.5 times greater belowground than aboveground. AMF richness was significantly positively correlated with plant species richness, and more strongly with below‐ than aboveground plant richness. Belowground plant richness was positively correlated with belowground plant biomass and total plant biomass, whereas aboveground plant richness was positively correlated only with belowground plant biomass. By contrast, AMF richness was negatively correlated with belowground and total plant biomass. Our results indicate that AMF richness and plant belowground richness are more strongly related with each other and with plant community biomass than with the plant aboveground richness measures that have been almost exclusively considered to date.