Dimensions of invasiveness: Links between local abundance, geographic range size, and habitat breadth in Europe's alien and native floras

Understanding drivers of success for alien species can inform on potential future invasions. Recent conceptual advances highlight that species may achieve invasiveness via performance along at least three distinct dimensions: 1) local abundance, 2) geographic range size, and 3) habitat breadth in naturalized distributions. Associations among these dimensions and the factors that determine success in each have yet to be assessed at large geographic scales. Here, we combine data from over one million vegetation plots covering the extent of Europe and its habitat diversity with databases on species' distributions, traits, and historical origins to provide a comprehensive assessment of invasiveness dimensions for the European alien seed plant flora. Invasiveness dimensions are linked in alien distributions, leading to a continuum from overall poor invaders to super invaders - abundant, widespread aliens that invade diverse habitats. This pattern echoes relationships among analogous dimensions measured for native European species. Success along invasiveness dimensions was associated with details of alien species' introduction histories: earlier introduction dates were positively associated with all three dimensions, and consistent with theory-based expectations, species originating from other continents, particularly acquisitive growth strategists, were among the most successful invaders in Europe. Despite general correlations among invasiveness dimensions, we identified habitats and traits associated with atypical patterns of success in only one or two dimensions - for example, the role of disturbed habitats in facilitating widespread specialists. We conclude that considering invasiveness within a multidimensional framework can provide insights into invasion processes while also informing general understanding of the dynamics of species distributions.Deutsche Forschungsgemeinschaft (264740629) Grantová Agentura České Republiky (19-28491X) Grantová Agentura České Republiky (19-28807X) Grantová Agentura České Republiky (RVO 67985939) Austrian Science Fund (I 2086 - B29) Bundesministerium für Bildung und Forschung (01LC1807A) Eusko Jaurlaritza (IT299-10) National Research Foundation of Korea (2018R1C1B6005351) University of Latvia (AAp2016/B041//Zd2016/AZ03) Villum Fonden (16549

Post-glacial determinants of regional species pools in alpine grasslands

[Aim] Alpine habitats support unique biodiversity confined to high-elevation areas in the current interglacial. Plant diversity in these habitats may respond to area, environment, connectivity and isolation, yet these factors have been rarely evaluated in concert. Here we investigate major determinants of regional species pools in alpine grasslands, and the responses of their constituent species groups.[Location] European mountains below 50° N.[Time period] Between 1928 and 2019.[Major taxa studied] Vascular plants.[Methods] We compiled species pools from alpine grasslands in 23 regions, including 794 alpine species and 2,094 non-alpines. We used species–area relationships to test the influence of the extent of alpine areas on regional richness, and mixed-effects models to compare the effects of 12 spatial and environmental predictors. Variation in species composition was addressed by generalized dissimilarity models and by a coefficient of dispersal direction to assess historical links among regions.[Results] Pool sizes were partially explained by current alpine areas, but the other predictors largely contributed to regional differences. The number of alpine species was influenced by area, calcareous bedrock, topographic heterogeneity and regional isolation, while non-alpines responded better to connectivity and climate. Regional dissimilarity of alpine species was explained by isolation and precipitation, but non-alpines only responded to isolation. Past dispersal routes were correlated with latitude, with alpine species showing stronger connections among regions.[Main conclusions] Besides area effects, edaphic, topographic and spatio-temporal determinants are important to understand the organization of regional species pools in alpine habitats. The number of alpine species is especially linked to refugia and isolation, but their composition is explained by past dispersal and post-glacial environmental filtering, while non-alpines are generally influenced by regional floras. New research on the dynamics of alpine biodiversity should contextualize the determinants of regional species pools and the responses of species with different ecological profiles.The authors thank Daniela Gaspar for support in GIS analyses. B.J.-A. thanks the Marie Curie Clarín-COFUND program of the Principality of Asturias-EU (ACB17-26), the regional grant IDI/2018/000151, and the Spanish Research Agency grant AEI/ 10.13039/501100011033. J.V.R.-D. was supported by the ACA17-02FP7 Marie Curie COFUND-Clarín grant. G.P.M. was funded by US National Science Foundation award 1853665. C.M. was funded by grant no. 19-28491 of the Czech Science Foundation.Peer reviewe

sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots

Abstract Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records. Software format: Three main matrices (.csv), relationally linked

sPlot:a new tool for global vegetation analyses

Abstract Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale