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.

Trait‐based ecology has already revealed main independent axes of trait variation defining trait spaces that summarize plant adaptive strategies, but often ignoring intraspecific trait variability (ITV). By using empirical ITV‐level data for two independent dimensions of leaf form and function and 167 species across five habitat types (coastal dunes, forests, grasslands, heathlands, wetlands) in the Italian peninsula, we found that ITV: (i) rotated the axes of trait variation that define the trait space; (ii) increased the variance explained by these axes and (iii) affected the functional structure of the target trait space. However, the magnitude of these effects was rather small and depended on the trait and habitat type. Our results reinforce the idea that ITV is context‐dependent, calling for careful extrapolations of ITV patterns across traits and spatial scales. Importantly, our study provides a framework that can be used to start integrating ITV into trait space analyses.

Beach litter threatens coastal dunes integrity across the world. European countries are committed to improving the environmental status of the marine and coastal environment by 2020, and to do this, they need to reduce the gap of knowledge about litter accumulation patterns in coastal environments. We analyzed the distribution pattern of waste, differentiated by material and origin, in the coastal dune vegetation mosaic along protected natural areas in the Adriatic seashore (central Italy). Litter data were collected following a random stratified procedure. We registered litter occurrence on 180 (2 × 2 m) sampling plots randomly distributed in the different habitats of European conservation concern mapped for the analyzed protected areas. Litter was classified by origin and material, and their abundance on different habitats was explored by multivariate ordination techniques and tested by nonparametric ANOVA followed by Mann-Whitney pairwise post-hoc tests. Most of the plots included at least one waste element being plastic. Plastic was the most abundant material, and fishing and touristic the most polluting activities. Waste distribution varies across coastal dune vegetation types and involves the back dune zone too. Our results stress the need for (a) specific cleaning tasks able to preserve the ecological value of coastal dune habitats and (b) actions aimed at preventing litter production and accumulation.

Invasive alien species represent a major threat to global biodiversity and the sustenance of ecosystems. Globally, mountain ecosystems have shown a degree of resistance to invasive species due to their distinctive ecological features. However, in recent times, the construction of linear infrastructure, such as roads, might weaken this resistance, especially in the Mediterranean basin region. Roads, by acting as efficient corridors, facilitate the dispersal of alien species along elevation gradients in mountains. Here, we investigated how the ecological features and road-associated disturbance in native plant communities affected both the occurrence and cover of alien plant species in Central Apennines (Italy). We implemented the MIREN road survey in three mountain transects conducting vegetation sampling in plots located both adjacent to and distant from the roads at intervals of ~ 100 m in elevation. We then used community-weighted means of Ecological Indicator Values for Europe together with Disturbance Indicator Values applied to plant species of native communities as predictors of alien species occurrence and cover in a machine-learning classification and regression framework. Our analyses showed that alien species’ occurrence was greater in proximity to the road where high soil disturbance occurred and in warm- and light-adapted native communities. On the other hand, alien species cover was more strongly related to moderate grazing pressure and the occurrence of nitrophilic plant communities. These findings provide a baseline for the current status of alien plant species in this Mediterranean mountain region, offering an ecological perspective to address the challenges associated with their management under global change.

We analyzed plant functional diversity (FD) and redundancy (FR) in Mediterranean high-mountain communities to explore plant functional patterns and assembly rules. We focused on three above-ground plant traits: plant height (H), a good surrogate of competition for light strategies, and specific leaf area (SLA) and leaf dry matter content (LDMC), useful indicators of resource exploitation functional schemes. We used the georeferenced vegetation plots and field-measured plant functional traits of four widely spread vegetation types growing on screes, steep slopes, snowbeds and ridges, respectively. We calculated Rao’s FD and FR followed by analysis of standardized effect size, and compared FD and FR community values using ANOVA and the Tukey post hoc test. Assemblage rules varied across plant communities and traits. The High FR_H registered on snowbeds and ridges is probably linked to climatic filtering processes, while the high FD_H and low FD_SLA and FD_LDMC on steep slopes could be related with underlying competition mechanisms. The absence of FD patterns in scree vegetation pinpoint random assembly processes which are typical of highly unstable or disturbed ecosystems. Improved knowledge about the deterministic/stochastic processes shaping species coexistence on high mountain ecosystems should help researchers to understand and predict vegetation vulnerability to environmental changes.