Sabine Rumpf

Climate warming has triggered shifts in plant distributions, resulting in changes within communities, characterized by an increase in warm‐demanding species and a decrease in cold‐adapted species – referred to as thermophilization. Researchers conventionally rely on co‐occurrence data from vegetation assemblages to examine these community dynamics. Despite the increasing availability of presence‐only data in recent decades, their potential has largely remained unexplored due to concerns about their reliability. Our study aimed to determine whether climate‐induced changes in community dynamics, as inferred from presence‐only data from the Global Biodiversity Information Facility (GBIF), corresponded with those derived from co‐occurrence plot data. To assess the differences between these datasets, we computed a community temperature index (CTI) using a transfer function, weighted‐averaging partial least squares regression (WA‐PLS). We calibrated the transfect function model based on the species–temperature relationship using data before recent climate warming. Then we assessed the differences in CTI and examined the temporal trend in thermophilization. In a preliminary analysis, we assessed the performance of this calibration using three datasets: 1) Norwegian co‐occurrence data, 2) presence‐only data from a broader European region organized into pseudo‐plots (potentially capturing a larger part of the species niches), and 3) a combined dataset merging 1) and 2). The transfer function including the combined dataset performed best. Subsequently, we compared the CTI for the co‐occurrence plots paired up spatially and temporally with presence‐only pseudo‐plots. The results demonstrated that presence‐only data can effectively evaluate species assemblage responses to climate warming, with consistent CTI and thermophilization values to what was found for the co‐occurrence data. Employing presence‐only data for evaluating community responses opens up better spatial and temporal resolution and much more detailed analyses of such responses. Our results therefore outline how a large amount of presence‐only data can be used to enhance our understanding of community dynamics in a warmer world.

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.