Taxonomic inventory and distributions of Chenopodiaceae (Amaranthaceae s.l.) in Orenburg Region, Russia.

Background: Orenburg Region is located in the South Urals, mostly in the steppe zone and is characterised by various landscapes suitable for many Chenopodiaceae. The species of Chenopodiaceae are present in all major plant communities (saline vegetation, steppes, on limestone, chalk and sand, and as degraded or ruderal communities). In the steppe zone, many native subshrubby species (Atriplexcana, Caroxylonlaricinum, Suaedaphysophora) playing a crucial role in semi-deserts (known as southern steppes in the recent Russian literature) located southwards of Orenburg Region are locally found, and several annuals (Salicorniaperennans, Suaeda spp.) are most common dominants in plant communities. Some typical semi-desert species (Kalidiumfoliatum, Bassiahyssopifolia, Sodafoliosa, Spirobassiahirsuta) are found in the easternmost part of the region. New information: We compiled a checklist of Chenopodiaceae in Orenburg Region, with two new records (Chenopodiumvirgatum, Corispermumlaxiflorum), based on our critical revision, comprehensive inventory of herbarium specimens and documented observations and field research. In total, we report 76 species in the Region, which is the third-highest number of the Chenopodiaceae species compared with other administrative territories of European Russia, North Caucasus and West Siberia. Alien and native taxa are distinguished. Zonal patterns of species distributions are confirmed. A preliminary conservation status is proposed for each native species. Three species are recommended for exclusion from the Red Data Book of Orenburg Region: Petrosimoniatriandra (because of its extensive distribution), Kalidiumfoliatum and Anabasissalsa (because of the lack of actual threat to their populations). Arthrophytumlehmannianum and Salsolarosacea are considered threatened (Vulnerable) because of their restricted occurrence and population size and because their localities are under anthropogenic pressure. Atriplexhortensis, Atriplexrosea, Chenopodiumacuminatum, C.karoi, C.praetericola, C.vulvaria, Climacopteraaffinis, C.crassa, Halimocnemiskarelinii, Salsolapaulsenii and Xylosalsolaarbuscula are excluded from the checklist, based on various reasons as discussed in the paper. Point distribution maps are provided for each species. Agriophyllumpungens (Vahl) Link is accepted as the correct authorship instead of "M.Bieb. ex C.A.Mey."

Temporal change in plant communities and its relationship to soil salinity and microtopography on the Caspian Sea coast.

The gradual drying up of saltwater bodies creates habitats that are characterised by changing environmental conditions and might be available only for a subset of plants from the local flora. Using two terrestrial areas with different ages on the Caspian Coast as a chronosequence, we investigated factors including microtopography, ground water level and soil salinity that drive plant community succession after the retreat of the sea. Vegetation of the two key sites appearing after the retreat of the Caspian Sea about 365 and 1412 years ago were compared in terms of both evolutionary and ecological traits of plants. Both edaphic conditions and vegetation differed between the two sites with harsher edaphic conditions and more xerophytes on the elder site. Species that grew only in the 'early' site were dispersed across the phylogenetic tree, but their loss on the 'late' site was not random. Species that grew only on the 'late' site were phylogenetically clustered. On the level of microtopography, elevated spots were more densely populated in the 'early' site than lowered spots, but on the 'late' site the situation was opposite. The main edaphic factors that drive the difference in vegetation composition between the two sites are likely salinity and moisture. During environmental changes, different plant traits are important to survive and to appear in the community de novo. Microtopography is important for forming plant communities, and its role changes with time.

MHA Herbarium: Eastern European collections of vascular plants.

BACKGROUND: World herbaria with 387.5M specimens (Thiers 2019) are being rapidly digitised. At least 79.9M plant specimens (20.6%) are already databased throughout the globe in the standard form of GBIF-mediated data. The contribution of smaller herbaria has been steadily growing over the last few years due to cost reduction, usage of platforms and solutions developed by the leaders. A web-resource the Moscow Digital Herbarium (Seregin 2020b) was launched by the Lomonosov Moscow State University in October, 2016 for publication of specimens imaged and databased in the Moscow University Herbarium (MW). As of 31 December 2018, the web-portal included 968,031 images of 971,732 specimens digitised in MW. This dataset is available in GBIF (Seregin 2020). The global trend is largely the same in Russia, where a dozen herbaria started to scan their holdings after imaging of the nation's second largest herbarium (Kislov et al. 2017, Kovtonyuk et al. 2019, Seregin 2020a). In 2019, we started to use Moscow Digital Herbarium as a web-repository for digitised herbarium specimens from some Russian collections, starting with the Herbarium of Tsitsin Main Botanical Gaden, Russian Academy of Sciences (MHA). Due to this, a single-university system became a multi-institutional consortium in April 2019 (Seregin 2020a). The dataset of the Moscow collections and partly of the Eastern European collections of the MHA Herbarium is now available in GBIF (Seregin and Stepanova 2020). NEW INFORMATION: MHA Herbarium imaged 64,008 specimens from Moscow Region and partly from other regions of Eastern Europe at 600 dpi and provided key metadata. These data are now fully available in the Moscow Digital Herbarium and GBIF. Complete georeferencing of the specimens from the City of Moscow was a key task in 2020. As of May 2020, 50,324 specimens, including 49,732 specimens from Russia, have been georeferenced (78.6%) and 39,448 specimens have fully-captured label transcriptions (61.6%). Based on these data, we give a detailed overview of the collections including spatial, temporal and taxonomic description of the dataset.