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.

The species of holoparasitic genera from the family Orobanchaceae have a specific lifestyle associated with the host, greatly reduced vegetative organs, very variable features and quickly lose their color, resulting in difficulties and mistakes in identification. This study represents the first comprehensive monograph of 36 species from the four holoparasitic genera, Cistanche, Diphelypaea, Phelipanche and Orobanche (Orobanchaceae), in Armenia. This country, as a part of the Caucasus, is one of the most important biodiversity centers in the world, a diversity which includes rich and insufficiently understood holoparasitic plants. Our investigations were based on five years of field work in the Caucasus, and complemented by examination of ca. 1200 herbarium sheets with ca. 3000 specimens from 37 herbaria. We present information on distribution, list of localities, habitat, phenology, host range, taxonomic clarification, illustrations and descriptions for problematic ones, images from the field, proposals for new synonymisations, new combination Phelipanche cernua subsp. sinaica (Beck) Piwow., Ó. Sánchez & Moreno Mor., 20 lectotypes, two epitypes, one neotype are designated here, as well as a key and geospatial conservation assessments for all species based on IUCN criteria.

Aims Understanding fine‐grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine‐grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location Palaearctic biogeographic realm. Methods We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m2 and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi‐natural) grasslands and natural grasslands are the richest vegetation type. The open‐access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions The GrassPlot Diversity Benchmarks provide high‐quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation‐plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology.