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.

Aims: We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions.Results: ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun‐Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020.Conclusions: ReSurveyEurope is a new resource to address a wide range of research questions on fine‐scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well‐established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.

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.