The factors that promote invasive behavior in introduced plant species occur across many scales of biological and ecological organization. Factors that act at relatively small scales, for example, the evolution of biological traits associated with invasiveness, scale up to shape species distributions among different climates and habitats, as well as other characteristics linked to invasion, such as attractiveness for cultivation (and by extension propagule pressure). To identify drivers of invasion it is therefore necessary to disentangle the contribution of multiple factors that are interdependent. To this end, we formulated a conceptual model describing the process of invasion of central European species into North America based on a sequence of "drivers." We then used confirmatory path analysis to test whether the conceptual model is supported by a statistical model inferred from a comprehensive database containing 466 species. The path analysis revealed that naturalization of central European plants in North America, in terms of the number of North American regions invaded, most strongly depends on residence time in the invaded range and the number of habitats occupied by species in their native range. In addition to the confirmatory path analysis, we identified the effects of various biological traits on several important drivers of the conceptualized invasion process. The data supported a model that included indirect effects of biological traits on invasion via their effect on the number of native range habitats occupied and cultivation in the native range. For example, persistent seed banks and longer flowering periods are positively correlated with number of native habitats, while a stress-tolerant life strategy is negatively correlated with native range cultivation. However, the importance of the biological traits is nearly an order of magnitude less than that of the larger scale drivers and highly dependent on the invasion stage (traits were associated only with native range drivers). This suggests that future research should explicitly link biological traits to the different stages of invasion, and that a failure to consider residence time or characteristics of the native range may seriously overestimate the role of biological traits, which, in turn, may result in spurious predictions of plant invasiveness.

Summary1. Macroecology has prospered in recent years due in part to the wide array of climatic data, such as those provided by the WorldClim and CliMond data sets, which has become available for research. However, important environmental variables have still been missing, including spatial data sets on UV-B radiation, an increasingly recognized driver of ecological processes. 2. We developed a set of global UV-B surfaces (glUV) suitable to match common spatial scales in macroecology. Our data set is based on remotely sensed records from NASA's Ozone Monitoring Instrument (Aura-OMI). Following a similar approach as for the WorldClim and CliMond data sets, we processed daily UV-B measurements acquired over a period of eight years into monthly mean UV-B data and six ecologically meaningful UV-B variables with a 15-arc minute resolution. These bioclimatic variables represent Annual Mean UV-B, UV-B Seasonality, Mean UV-B of Highest Month, Mean UV-B of Lowest Month, Sum of Monthly Mean UV-B during Highest Quarter and Sum of Monthly Mean UV-B during Lowest Quarter. We correlated our data sets with selected variables of existing bioclimatic surfaces for land and with Terra-MODIS Sea Surface Temperature for ocean regions to test for relations to known gradients and patterns. 3. UV-B surfaces showed a distinct seasonal variance at a global scale, while the intensity of UV-B radiation decreased towards higher latitudes and was modified by topographic and climatic heterogeneity. UV-B surfaces were correlated with global mean temperature and annual mean radiation data, but exhibited variable spatial associations across the globe. UV-B surfaces were otherwise widely independent of existing bioclimatic surfaces. 4. Our data set provides new climatological information relevant for macroecological analyses. As UV-B is a known driver of numerous biological patterns and processes, our data set offers the potential to generate a better understanding of these dynamics in macroecology, biogeography, global change research and beyond. The glUV data set containing monthly mean UV-B data and six derived UV-B surfaces is freely available for download at: http://www.ufz.de/gluv.

Summary1. Plant diversity is globally threatened by anthropogenic land use including management and modification of the natural environment. At regional and local scales, numerous studies world-wide have examined land use and its effects on plant diversity, but evidence for declining species diversity is mixed. This is because, first, land use comes in many variations, hampering comparisons of studies. Second, land use directly affects the environment, but indirect effects extend beyond the boundaries of the land in use. Third, land-use effects greatly depend on the environmental, historical and socio-economic context. 2. To evaluate the generality and variation of studies' findings about land-use effects, we undertook a quantitative synthesis using meta-analytic techniques. 3. Using 572 effect sizes from 375 studies distributed globally relating to 11 classes of land use, we found that direct and indirect effects of land use on plant diversity (measured as species richness) are variable and can lead to both local decreases and increases. Further, we found evidence (best AIC model) that land-use-specific covariables mostly determine effectsize variation and that in general land-use effects differ between biomes. 4. Synthesis and applications. This extensive synthesis provides the most comprehensive and quantitative overview to date about the effects of the most widespread and relevant land-use options on plant diversity and their covariables. We found important covariables of specific land-use classes but little evidence that land-use effects can be generally explained by their environmental and socio-economic context. We also found a strong regional bias in the number of studies (i.e. more studies from Europe and North America) and highlight the need for an overarching and consistent land-use classification scheme. Thereby, our study provides a new vantage point for future research directions.

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