—The Global Biodiversity Information Facility (GBIF) is the largest source of open scientific data on the biodiversity of Russian: over 4.3 million species occurrences became available through GBIF as of May 2020; the most abundant among them are data on vascular plant occurrence (over 1.9 million) and bird occurrence (over 900 thousand). The representativeness of data for other taxonomic groups and most of the regions of the country still remains low, although the amount of available information continues to grow owing to the mobilization of data from scientific collections and personal archives of researchers, as well as from citizen science projects, iNaturalist, and eBird. Data available through the GBIF portal are of great interest to ecologists who work with methods for modeling the spatial distribution of species. However, the existing data gaps for the Russian territory limit the possibilities of their reuse, and it is necessary to address additional sources of information to achieve adequate results.

Significance: To do the right thing at the right time, organisms need to glean cues from their environment. How they respond can then be described by reaction norms, i.e., by the relationship between the phenotype expressed (the phenology of an event) and the environment (the date when a given number of degree-days are achieved). We use information on 178 phenological events across the former Soviet Union. We found the timing of events to differ more between sites in spring and less in autumn. These patterns of local adaptation translate to a massive imprint on nature’s calendar: geographic variation in phenology is more pronounced in spring and less pronounced in autumn than if organisms were to respond equally everywhere.

We present an extensive, large-scale, long-term and multitaxon database on phenological and climatic variation, involving 506,186 observation dates acquired in 471 localities in Russian Federation, Ukraine, Uzbekistan, Belarus and Kyrgyzstan. The data cover the period 1890–2018, with 96% of the data being from 1960 onwards. The database is rich in plants, birds and climatic events, but also includes insects, amphibians, reptiles and fungi. The database includes multiple events per species, such as the onset days of leaf unfolding and leaf fall for plants, and the days for first spring and last autumn occurrences for birds. The data were acquired using standardized methods by permanent staff of national parks and nature reserves (87% of the data) and members of a phenological observation network (13% of the data). The database is valuable for exploring how species respond in their phenology to climate change. Large-scale analyses of spatial variation in phenological response can help to better predict the consequences of species and community responses to climate change.

The article provides primary data on repeated tree measurements collected during two censuses on a permanent sampling plot (440 m × 200 m) established in the old-growth polydominant broad-leaved forest in the Kaluzhskie Zaseki State Nature Reserve (centre of European Russia). The time span between the inventories was 30 years, and a total of 11 578 individuals of ten tree, one shrub species, and several undefined tree species of three known genera were registered. During the surveys, tree identity, stem diameter at breast height (DBH) of 1.3 m, and life status (alive or dead) were recorded for every tree individual with DBH ≥ 5 cm. Additional attributes were determined for some individuals. Field data were digitised and compiled into the PostgreSQL database. An accurate data quality assessment, validation, and cleaning (with documentation of changes) have been performed before data standardisation according to the Darwin Core standard. Standardised data were published through the GBIF repository. From 1986 to 1988, 9811 individuals were recorded within the initial census, including 3920 Corylus avellana individual shrubs. Corylus avellana shrubs were recorded without measuring DBH. From 2016 to 2018, 7658 stems were recorded in the recensus, including 3090 living trees marked during the initial census, and 1641 other living trees reaching the DBH of at least 5 cm. Corylus avellana was not included in the recensus. Thus, over 30 years, about 65% of living tree individuals have survived, but the total number of living trees has not changed considerably. The mean diameter of shade-intolerant tree species (Quercus robur, Fraxinus excelsior, Populus tremula, and Betula spp.) has increased the most remarkably during 30 years. For these species, the increase in average diameter, along with the decrease in numbers, is associated with the death of young trees, presumably due to low illumination under the canopy. Contrastingly, shade-tolerant tree species (Ulmus glabra, Tilia cordata, Acer platanoides) increased in number, while their mean diameter increased slightly or even decreased, that evidences the successful regeneration of these species under the canopy. These data are relevant for investigating forest ecology questions at spatiotemporal scales as a model of natural succession.

The ground-based surveys of areas affected by storms might be difficult or even impossible because of the limited ability to move within the damaged area. Therefore, this work was aimed to estimate storm damage based on aerial photography and open biodiversity data available via the Internet. The study was carried out in the old-growth hemiboreal forests of the Kologrivsky Forest State Nature Reserve (Kostroma Region, Russia), which was affected by a catastrophic windthrow caused by a storm on 15.05.2021. The sampling area was 100 000 m2. We used our previous ground-survey studies and open-access biodiversity data available through the Global Biodiversity Information Facility for describing the forest stands composition before the catastrophic event. The aerial photography data were used for estimating tree stands damages after the windthrow. For remote data collecting, we used an unmanned aerial vehicle – quadrocopter DJI Phantom 4. Agisoft Metashape software was used for aerial photographs processing. The obtained photogrammetric digital elevation model (DEM) and orthophoto-mosaic were processed with QGIS software. Damaged areas were detected automatically based on the DEM. Individual fallen trees were visually detected using the orthophoto-mosaic. We found before the windthrow the study area was covered by old-growth stands developed naturally over a long time. The stand structure was multi-layered and uneven-aged. The ontogenetic spectra of late-successional tree species Picea abies (hereinafter – spruce) and Tilia cordata (hereinafter – linden) were normal. The old-growth stands were heterogeneous before the windthrow: the canopy closed multi-layered and uneven-aged stands, decaying spruce stands and areas where spruce completely fell out and the tree stand was absent. In addition, old-growth linden stands were present. According to the obtained results, the stand structure was critically changed caused by the windthrow. The DEM-processing results showed the windthrow strongly damaged 33.1% stands in the study area. Using the orthophoto-mosaic, we visually detected 759 fallen trees. Among them, 82.9% were associated with strongly-damaged areas. According to the DEM classification, the rest of the visually detected fallen trees were in non-damaged areas and canopy gaps established before the windthrow. The analysis showed that these were less damaged areas with survived stands or groups of trees after the storm. Thus, our results showed that it is necessary to use both the DEM and the orthophoto-mosaic for more accurate estimates. Our exploratory analysis of different tree stand damages found that apparently, spruce stands were more affected by the storm than linden stands. It is explained by the different wind resistance of spruce and linden and differences in regrowth density and species composition in these stands.