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.

Aim The number of naturalized (i.e. established) alien species has increased rapidly over recent centuries. Given the differences in environmental tolerances among species, little is known about what factors determine the extent to which the observed size of the naturalized range of a species and hence the extent to which the observed richness of naturalized species of a region approach their full potential. Here, we asked which region‐ and species‐specific characteristics explain differences between observed and expected naturalizations. Location Global. Time period Present. Major taxa studied Vascular plants. Methods We determined the observed naturalized distribution outside Europe for 1,485 species endemic to Europe using the Global Naturalized Alien Flora (GloNAF) database and their expected distributions outside Europe using species distribution models. First, we investigated which of seven socio‐economic factors related to introduction pathways, anthropogenic pressures and inventory effort best explained the differences between observed and expected naturalized European floras. Second, we examined whether distributional features, economic use and functional traits explain the extent to which species have filled their expected ranges outside Europe. Results In terms of suitable area, more than 95% of expected naturalizations of European plants were not yet observed. Species were naturalized in only 4.2% of their suitable regions outside of Europe (range filling) and in 0.4% of their unsuitable regions (range expansion). Anthropogenic habitat disturbance primarily explained the difference between observed and expected naturalized European floras, as did the number of treaties relevant to invasive species. Species of ornamental and economic value and with large specific leaf area performed better at filling and expanding beyond their expected range. Main conclusions The naturalization of alien plant species is explained by climate matching but also by the regional level of human development, the introduction pressure associated with the ornamental and economic values of the species and their adaptation to disturbed environments.

More than 40 million hectares of agricultural land were abandoned after the collapse of the Soviet Union. A significant part of the land is covered by spontaneously regenerating woody and shrubby vegetation. When identifying the forest regeneration, the stands with a tree cover of more than 50% are accurately identified. It is difficult to identify the initial stages of forest regeneration on the abandoned agricultural lands using summer satellite images because of little difference between the young trees and saplings due to their low height and low density on the one hand, and herbaceous vegetation on the other. The purpose of this work was to apply winter and early-spring satellite images for assessments of the tree cover of birch-dominated stands (Betula pen-dula Roth.) formed on the abandoned agricultural lands (See Fig. 1). We used 189 releves of birch forests on the abandoned agricultural lands in the broad-leaved forest zone of the Republic of Bashkortostan. A regression analysis of the evaluation of the tree cover was carried out using the values of the spectral reflectance of the RED, NIR, SWIR11, and SWIR12 bands, as well as the values of the NDFSI snow index from seven cloudless Sentinel-2 images taken between 04.11.2020 and 13.05.2021 (See Fig. 2, 3). When selecting optimal regression models, the values of correlation coefficients (R) and determination coefficients (R2) were used to assess the model quality. To test the possibility of using the obtained models for assessing the tree cover of the stand at earlier succession stages, we involved the data on the tree cover from 36 geobotanical releves, where the crown density of the stand was visually evaluated in July 2013. Then, the described procedure was applied to calculate the tree cover using the Landsat-8 image taken on 25.03.2014. When creating regression models to calculate the tree cover, the best results were obtained using the red band of early spring images during the period when snowpack is still solid (from mid-March to the first half of April) (See Table 1). The correlation between the tree cover and the spectral reflectance of the red band was -0.90. The model allowed us to determine accurately the tree cover of birch forests aged from 18 to 20 years which prevail in the zone of broad-leaved forests in the Republic of Bashkortostan. The accuracy of the model for determining the tree cover according to the obtained regression models for other dates is unstable and highly likely influenced by the snow depth and the seasonal dynamics of changes in the radiation intensity of the red and infrared bands (See Table 2, 3). To conclude, the equations calculated from modern satellite images can be used to assess the tree cover using retrospective images at earlier succession stages of the abandoned field recovery. When using early-spring images, the snow depth should be taken into account since the snowpack melting dates can vary greatly from year to year. The paper contains 3 Figures, 3 Tables, and 41 References. The Authors declare no conflict of interest.

As a result of long-term research carried out in the Southern Ural region, extensive information on the species richness and phytosociological diversity has been obtained for the broad-leaved forests belonging to the alliance Aconito lycoctoni–Tilion cordatae Solomeshch et Grigoriev in Willner et al. 2016 (order Carpinetalia betuli P. Fukarek 1968, class Carpino-Fagetea sylvaticae Jakucs ex Passarge 1968). The study is based on the analysis of 787 relevés made between 1989 and 2019. Relevés and their further analysis were performed according to the Braun-Blanquet aproach (Braun-Blanquet, 1964; Westhoff, Maarel, 1978). Two suballiances, 5 associations, 14 subassociations, 12 variants, and 1 facies were described in the alliance Aconito-Tilion. The combinations of diagnostic species were determined for each syntaxa. Nomenclatural types for new syntaxa are given in phytocoenotic tables and in the text. Сommunities of the alliance Aconito-Tilion are distributed meridionally from the southern taiga subzone (southern border of Perm Krai and Sverdlovsk Region), where they border with boreal forests. They are replaced by thermophilous oak forests of the alliance Lathyro pisiformis–Quercion roboris Solomeshch et Grigoriev in Willner et al. 2015 in the southern edge of the Ural Mountains and the Ural River basin of Orenburg Region (Fig. 1). In the latitudinal direction, forests of the alliance Aconito-Tilion are distributed in the forest-steppe zone of Bashkir Urals, Bugulma-Belebey Upland and foothills of western macroslope of Ural Mountains. Eastwards, they border hemiboreal light-coniferous–small-leaved herbaceous forests of the order Chamaecytiso ruthenici–Pinetalia sylvestris Solomeshch et Ermakov in Ermakov et al. 2000, class Brachypodio pinnati–Betuletea pendulae Ermakov, Korolyuk et Lashchinsky 1991. In the west, the communities of the alliance Aconito-Tilion are replaced by mesophytic broad-leaved forests of the­ ­alliance Querco roboris–Tilion cordatae Solomeshch et Laivinņš ex Bulokhov et Solomeshch in Bulokhov et Semenishchenkov 2015. According to floristic and structural-physiognomic characters, two suballiances were distinguished within this alliance. Suballiance Aconito lycoctoni–Tilienion cordatae suball. nov. combines broad-leaved forests typical for the region. Suballiance Tilio cordatae–Pinenion sylvestris suball. nov. includes pine–broad-leaved forests which represent ecotone communities in the transition stripe between European temperate broad-leaved forests of the class Carpino-Fagetea and Siberian hemiboreal light-coniferous–small-leaved herbaceous forests of the class Brachypodio-Betuletea. Suballiance Aconito-Tilienion (holotypus: Stachyo sylvaticae–Tilietum cordatae ass. Martynenko et al. 2005) includes broad-leaved forests growing near the eastern border of their range. In these forests, the main dominants of the tree layer are Tilia cordata, Ulmus glabra and Acer platanoides. Co-dominants of herb layer are shade-tolerant broad herb species — Asarum europaeum, Aegopodium podagraria, Dryopteris filix-mas, Galium odoratum, Pulmonaria obscura, Viola mirabilis, etc., as well as Ural and Siberian tall-herb species such as Aconitum lycoctonum, Crepis sibirica, Bupleurum longifolium, Heracleum sibiricum, Cacalia hastata, Cicerbita uralensis. The suballiance is represented by two associations: Brachypodio pinnate–Tilietum cordatae Grigoriev ex Martynenko et al. 2005 and Stachyo sylvaticae–Tilietum cordatae Martynenko et al. 2005. Within these associations, four new subassociations were described: Brachypodio pinnate–Tilietum cordatae pulmonarietosum mollis subass. nov. (Table 1, columns 2, 3; Table 2, rel. 1–30), Stachyo sylvaticae–Tilietum cordatae alliarietosum petiolatae subass. nov. (Table 1, column 12; Table 2, rel. 31–46), S. s.–T. c. violetosum hirtae Grigoriev ex subass. nov. (Table 1, column 11), S. s.–T. c. pulmonarietosum mollis Khaziakhmetov, Solomeshch, Grigoriev et Muldashev ex Shirokikh, Martynenko, Baisheva, Fedorov, Muldashev et Naumova 2021 subass. nov. (Table 1, column 13). Suballiance Tilio-Pinenion (holotypus: Tilio cordatae–Pinetum sylvestris ass. nov.) combines mixed pine–broad-leaved forests in the Southern Urals and the eastern edge of the Russian Plain with the dominance of Pinus sylvestris in the tree layer and broad-leaved tree species in the lower one (Acer platanoides, Quercus robur, Tilia cordata, Ulmus glabra). There are both species typical for European broad-leaved forests and Siberian hemiboreal light-coniferous herbaceous forests in the composition of these forests. On the Ufa and Zilair Plateaus and in the hilly terrains of the central part of the Southern Urals, these forests are distributed mainly in contact zone with hemiboreal forests of the order Chamaecytiso-Pi­netalia, and, less often with dark-coniferous–broad-leaved forests of the class Asaro europaei–Abietetea sibiricae Ermakov, Mucina et Zhitlukhina in Willner et al. 2016 (Fig. 1). Additionally, small massifs of these forests occur in the Fore-Ural region and Bugulma-Belebey Upland. Three associations with a number of smaller syntaxonomic units are described within this suballiance (Table 3). The results of the classification are confirmed by cluster analysis (Fig. 2). Ass. Tilio cordatae–Pinetum sylvestris ass. nov. (Table 3, columns 1–3, Table 4, 5) represents the most typical communities of the suballiance Tilio-Pine­nion. Four subassociations are described within the association: T. c.–P. s. typicum subass. nov. (Table 3, columns 1–2; Table 4), T. c.–P. s. caricetosum pilosae subass. nov. (Table 3, column 3; Table 5, rel. 21–33), T. c.–P. s. cerastietosum pauciflori subass. nov. (Table 3, columns 4–5; Table 6), T. c.–P. s. galietosum odorati (Martynenko et Zhigunov in Martynenko et al. 2005) stat. nov. (Table 3, column 6; Table 6, rel. 44–57). Ass. Carici arnellii–Pinetum sylvestris Solomeshch et Martynenko ass. nov. (Table 3, column 8; Table 7) combines the most mesophytic communities of the suballiance, which grow in valleys of mountain rivers on rich grey forest soils with periodic short-term waterlogging. Ass. Euonymo verrucosae–Pinetum sylvestris Martynenko et al. 2007 includes the most xerophytic communities of the suballiance, distributed on steep southern slopes of hills and on the Ufa Plateau. The similarities and differences between investigated broad-leaved, pine–broad-leaved and hemiboreal forests are reflected in the ordination diagram (Fig. 3). The pine–broad-leaved forests of the suballiance Tilio-Pinenion occupy intermediate position between the communities of the suballiance Aconito-Tilienion and the hemiboreal forests of the order Chamaecytiso-Pinetalia. Therefore, it was difficult to clarify the place of the first suballiance in the system of higher units. Two syntaxonomic decisions were possible: the suballiance can be considered as: — the extreme western variant of the alliance Trollio europaea–Pinion sylvestris Fedorov ex Ermakov et al. 2000 within the order Chamaecytiso-Pinetalia (hemiboreal light-coniferous Siberian herbaceous fo­rests); — a part of the alliance Aconito-Tilion of the order Carpinetalia betuli (broad-leaved forests of the Southern Urals). Both points of view have sufficiently strong evidence, but the authors have settled on the second decision which is supported by the fact that after felling hemiboreal forests of the order Chamaecytiso-Pinetalia are replaced by secondary birch or aspen forests, whereas the pine–broad-leaved forests of the suballiance Tilio-Pinenion — by dense broad-leaved forests with nemoral species. In addition, the lower tree layer of Tilio-Pinenion forests is formed by tree species typical for Urals broad-leaved forests — Acer platanoides, Quercus robur, Tilia cordata, and Ulmus glabra. In the Southern Ural all these species, besides linden, grow near the eastern border of their range which indicates that communities of the suballiance Tilio-Pinenion should be assigned to European forests of the order Carpinetalia betuli rather than to Siberian forests of the order Chamaecytiso-Pinetalia.

Noninfectious virus particles were produced in Ehrlich ascites tumor cells infected intraperitoneally with fowl plague virus. The PFU yield of virus per cell was less than 0.1 and the ratio PFU/HA units in the progeny virus was less than 10(3). The virus particles had the same morphology and size as egg-grown virus but were more fragile. They were disrupted by centrifugation through sucrose and caesium chloride gradients, but this disruption was avoided by fixing the particles with formaldehyde before centrifugation. Analysis of polypeptides by SDS-PAGE showed that ascites-grown virus particles contained reduced amounts of matrix protein compared with egg-grown virus.