Lysenko 91,92 | Armin Macanović 93 | Parastoo Mahdavi 94 | Peter Manning 35 | Corrado Marcenò 13 | Vassiliy Martynenko 95 | Maurizio Mencuccini 96 | Vanessa Minden 97 | Jesper Erenskjold Moeslund 54 | Marco Moretti 98 | Jonas V. Müller 99 | 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. K E Y W O R D S biodiversity, community ecology, ecoinformatics, functional diversity, global scale, macroecology, phylogenetic diversity, plot database, sPlot, taxonomic diversity, vascular plant, vegetation relevé 166 |

This dataset provides the Global Naturalized Alien Flora (GloNAF) database, version 1.2. GloNAF represents a data compendium on the occurrence and identity of naturalized alien vascular plant taxa across geographic regions (e.g. countries, states, provinces, districts, islands) around the globe. The dataset includes 13,939 taxa and covers 1,029 regions (including 381 islands). The dataset is based on 210 data sources. For each taxon‐by‐region combination, we provide information on whether the taxon is considered to be naturalized in the specific region (i.e. has established self‐sustaining populations in the wild). Non‐native taxa are marked as “alien”, when it is not clear whether they are naturalized. To facilitate alignment with other plant databases, we provide for each taxon the name as given in the original data source and the standardized taxon and family names used by The Plant List Version 1.1 (http://www.theplantlist.org/). We provide an ESRI shapefile including polygons for each region and information on whether it is an island or a mainland region, the country and the Taxonomic Databases Working Group (TDWG) regions it is part of (TDWG levels 1–4). We also provide several variables that can be used to filter the data according to quality and completeness of alien taxon lists, which vary among the combinations of regions and data sources. A previous version of the GloNAF dataset (version 1.1) has already been used in several studies on, for example, historical spatial flows of taxa between continents and geographical patterns and determinants of naturalization across different taxonomic groups. We intend the updated and expanded GloNAF version presented here to be a global resource useful for studying plant invasions and changes in biodiversity from regional to global scales. We release these data into the public domain under a Creative Commons Zero license waiver (https://creativecommons.org/share-your-work/public-domain/cc0/). When you use the data in your publication, we request that you cite this data paper. If GloNAF is a major part of the data analyzed in your study, you should consider inviting the GloNAF core team (see Metadata S1: Originators in the Overall project description) as collaborators. If you plan to use the GloNAF dataset, we encourage you to contact the GloNAF core team to check whether there have been recent updates of the dataset, and whether similar analyses are already ongoing.

Aim Species–area relationships (SARs) are fundamental scaling laws in ecology although their shape is still disputed. At larger areas, power laws best represent SARs. Yet, it remains unclear whether SARs follow other shapes at finer spatial grains in continuous vegetation. We asked which function describes SARs best at small grains and explored how sampling methodology or the environment influence SAR shape. Location Palaearctic grasslands and other non‐forested habitats. Taxa Vascular plants, bryophytes and lichens. Methods We used the GrassPlot database, containing standardized vegetation‐plot data from vascular plants, bryophytes and lichens spanning a wide range of grassland types throughout the Palaearctic and including 2,057 nested‐plot series with at least seven grain sizes ranging from 1 cm2 to 1,024 m2. Using nonlinear regression, we assessed the appropriateness of different SAR functions (power, power quadratic, power breakpoint, logarithmic, Michaelis–Menten). Based on AICc, we tested whether the ranking of functions differed among taxonomic groups, methodological settings, biomes or vegetation types. Results The power function was the most suitable function across the studied taxonomic groups. The superiority of this function increased from lichens to bryophytes to vascular plants to all three taxonomic groups together. The sampling method was highly influential as rooted presence sampling decreased the performance of the power function. By contrast, biome and vegetation type had practically no influence on the superiority of the power law. Main conclusions We conclude that SARs of sessile organisms at smaller spatial grains are best approximated by a power function. This coincides with several other comprehensive studies of SARs at different grain sizes and for different taxa, thus supporting the general appropriateness of the power function for modelling species diversity over a wide range of grain sizes. The poor performance of the Michaelis–Menten function demonstrates that richness within plant communities generally does not approach any saturation, thus calling into question the concept of minimal area.

The genus Stipa L. comprises over 150 species, all native to the Old World, where they grow in warm temperate regions throughout Europe, Asia, and North Africa. It is one of the largest genera in the family Poaceae in Middle Asia, where one of its diversity hotspots is located. However, identification of Middle Asian Stipa species is difficult because of the lack of new, comprehensive taxonomic studies including all of the species recorded in the region. We present a critical review of the Mid-Asian representatives of Stipa, together with an identification key and taxonomic listing. We relied on both published and unpublished information for the taxa involved, many of which are poorly known. For each taxon, we present a taxonomic and nomenclatural overview, habitat preferences, distribution, altitudinal range, and additional notes as deemed appropriate. We describe four new nothospecies: S. ×balkanabatica M. Nobis & P. D. Gudkova, S. ×dzungarica M. Nobis, S. ×pseudomacroglossa M. Nobis, S. ×subdrobovii M. Nobis & A. Nowak, one subspecies S. caucasica Schmalh. subsp. nikolai M. Nobis, A. Nobis & A. Nowak, and eight varieties: S. araxensis Grossh. var. mikojanovica M. Nobis, S. caucasica var. fanica M. Nobis, P. D. Gudkova & A. Nowak, S. drobovii (Tzvelev) Czerep. var. jarmica M. Nobis, S. drobovii var. persicorum M. Nobis, S. glareosa P. A. Smirn. var. nemegetica M. Nobis, S. kirghisorum P. A. Smirn. var. balkhashensis M. Nobis & P. D. Gudkova, S. richteriana Kar. & Kir. var. hirtifolia M. Nobis & A. Nowak, and S. ×subdrobovii var. pubescens M. Nobis & A. Nowak. Additionally, 12 new combinations, Achnatherum haussknechtii (Boiss.) M. Nobis, A. mandavillei (Freitag) M. Nobis, A. parviflorum (Desf.) M. Nobis, Neotrinia chitralensis (Bor) M. Nobis, S. badachschanica Roshev. var. pamirica (Roshev.) M. Nobis, S. borysthenica Klokov ex Prokudin var. anomala (P. A. Smirn.) M. Nobis, S. holosericea Trin. var. transcaucasica (Grossh.) M. Nobis, S. kirghisorum P. A. Smirn. var. ikonnikovii (Tzvelev) M. Nobis, S. macroglossa P. A. Smirn. var. kazachstanica (Kotuchov) M. Nobis, S. macroglossa var. kungeica (Golosk.) M. Nobis, S. richteriana var. jagnobica (Ovcz. & Czukav.) M. Nobis & A. Nowak, and S. zalesskii Wilensky var. turcomanica (P. A. Smirn.) M. Nobis are proposed, and the lectotypes for 14 taxa (S. arabica Trin. & Rupr., S. bungeana Trin. ex Bunge, S. caspia K. Koch, S. ×consanguinea Trin. & Rupr., S. effusa Mez, S. ×heptapotamica Golosk., S. jacquemontii Jaub. & Spach., S. kungeica Golosk., S. margelanica P. A. Smirn., S. richteriana, S. rubentiformis P. A. Smirn., S. sareptana A. K. Becker, S. tibetica Mez, and Timouria saposhnikovii Roshev.) are designated. In Middle Asia the genus Stipa comprises 98 taxa, including 72 species, four subspecies, and 22 varieties. Of the 72 species of feather grasses, 23 are of hybrid origin (nothospecies). In Middle Asia, feather grasses can be found at elevations from (0 to)300 to 4500(to 5000) m, but most are montane species. The greatest species richness is observed at altitudes between 1000 and 2500 m. Nineteen species grow above 3000 m, but only nine above 4000 m. The number of taxa (species and subspecies) growing in each country also varies considerably, with the highest noted in Kazakhstan (42), Tajikistan (40), and Kyrgyzstan (35). Of the 76 taxa of Stipa (species and subspecies) recorded in Middle Asia, 41 are confined to the region, with some being known only from a single country or mountain range. Distribution maps of selected species are provided.