Erik Welk

Aim: The Global Biodiversity Information Facility (GBIF) is the most prominent source of species occurrence data for modeling climate niches, but exhibits strong unevenness in its data coverage across different geographic regions. The impact of this spatial bias on the reliability of GBIF-based plant climate niches in Europe remains unexplored. This study aims to address this gap, and to investigate whether the targeted integration of additional atlas data can reduce the potential impact of the spatial bias. Location: Europe. Time period: 1950s - 2024 Major taxa studied: European grassland plant species. Methods: We analyzed the climate niches of a large number of grassland species, with diverse distribution patterns across Europe, based on a) GBIF and b) on an enriched version of GBIF with national atlas data from Eastern European countries (GBIF+), where data coverage is currently low in GBIF. We followed best practices in niche characterization, particularly by performing environmental subsampling. The accuracy in climate niche properties was determined by comparing niches based on GBIF and GBIF+ data with niches based on a careful implementation of expert range maps as reference dataset. We focused on niche optimum position and niche similarity. Additionally, we investigated how biogeographical indicators can predict variability in climate niche accuracy. Results: Most species exhibited reliable climate niche characterization using GBIF data, especially for widely distributed species. Yet, reliability decreased with continentality; that is, when species were primarily distributed in Eastern Europe. Integrating additional data did not significantly reduce this bias in niche characterization. Main conclusions: Despite the spatial bias in its records, GBIF can be used to reliably characterize the climate niches of many species in Europe if uneven sampling effort is accounted for. The laborious integration of additional data to address spatial bias does not yield the desired increase in niche reliability.

Summary: Plant invasions are biogeographical phenomena that may involve shifts in belowground plant–fungal interactions, such as the release from fungal pathogens or more beneficial interactions with mutualists in nonnative ranges. However, native and nonnative ranges are not uniform but environmentally heterogeneous, and plant–fungal interactions are strongly shaped by spatio‐environmental context. Intense discussion at the 45 ^th New Phytologist Symposium revealed that we lack information on how well spatio‐environmental variation within ranges has been considered in samplings and analyses of studies comparing plant–fungal interactions between ranges. Through a systematic review, we assessed the sampling quality of recent biogeographical studies. We found that the majority relied on a limited population sampling within each range, often covering only a small fraction of the species' spatial distribution and macroclimatic niche. Additionally, low similarity between the sampled climatic gradients in the native and nonnative ranges might have introduced false‐positive differences across ranges. These sampling deficiencies may undermine the robustness and representativeness of range comparisons, thereby restricting our ability to accurately assess the role of plant–fungal interactions in invasion success. We recommend that future research incorporate broader and more comparable spatio‐environmental variation in both ranges, and we provide practical guidelines for improving sampling designs.

Globally, rising temperatures are increasingly favoring warm-affiliated species. Although changes in community composition are typically measured by the mean temperature affinity of species (the community temperature index, CTI), they may be driven by different processes and accompanied by shifts in the diversity of temperature affinities and breadth of species thermal niches. To resolve the pathways to community warming in Finnish flora and fauna, we examined multidecadal changes in the dominance and diversity of temperature affinities among understory forest plant, freshwater phytoplankton, butterfly, moth, and bird communities. CTI increased for all animal communities, with no change observed for plants or phytoplankton. In addition, the diversity of temperature affinities declined for all groups except butterflies, and this loss was more pronounced for the fastest-warming communities. These changes were driven in animals mainly by a decrease in cold-affiliated species and an increase in warm-affiliated species. In plants and phytoplankton the decline of thermal diversity was driven by declines of both cold- and warm-affiliated species. Plant and moth communities were increasingly dominated by thermal specialist species, and birds by thermal generalists. In general, climate warming outpaced changes in both the mean and diversity of temperature affinities of communities. Our results highlight the complex dynamics underpinning the thermal reorganization of communities across a large spatiotemporal gradient, revealing that extinctions of cold-affiliated species and colonization by warm-affiliated species lag behind changes in ambient temperature, while communities become less thermally diverse. Such changes can have important implications for community structure and ecosystem functioning under accelerating rates of climate change.

Climate and land‐use change are key drivers of global change. Full‐factorial field experiments in which both drivers are manipulated are essential to understand and predict their potentially interactive effects on the structure and functioning of grassland ecosystems. Here, we present 8 years of data on grassland dynamics from the Global Change Experimental Facility in Central Germany. On large experimental plots, temperature and seasonal patterns of precipitation are manipulated by superimposing regional climate model projections onto background climate variability. Climate manipulation is factorially crossed with agricultural land‐use scenarios, including intensively used meadows and extensively used (i.e., low‐intensity) meadows and pastures. Inter‐annual variation of background climate during our study years was high, including three of the driest years on record for our region. The effects of this temporal variability far exceeded the effects of the experimentally imposed climate change on plant species diversity and productivity, especially in the intensively used grasslands sown with only a few grass cultivars. These changes in productivity and diversity in response to alterations in climate were due to immigrant species replacing the target forage cultivars. This shift from forage cultivars to immigrant species may impose additional economic costs in terms of a decreasing forage value and the need for more frequent management measures. In contrast, the extensively used grasslands showed weaker responses to both experimentally manipulated future climate and inter‐annual climate variability, suggesting that these diverse grasslands are more resistant to climate change than intensively used, species‐poor grasslands. We therefore conclude that a lower management intensity of agricultural grasslands, associated with a higher plant diversity, can stabilize primary productivity under climate change.

Terrestrial ecosystems affect climate by reflecting solar irradiation, evaporative cooling, and carbon sequestration. Yet very little is known about how plant traits affect climate regulation processes (CRPs) in different habitat types. Here, we used linear and random forest models to relate the community‐weighted mean and variance values of 19 plant traits (summarized into eight trait axes) to the climate‐adjusted proportion of reflected solar irradiation, evapotranspiration, and net primary productivity across 36,630 grid cells at the European extent, classified into 10 types of forest, shrubland, and grassland habitats. We found that these trait axes were more tightly linked to log evapotranspiration (with an average of 6.2% explained variation) and the proportion of reflected solar irradiation (6.1%) than to net primary productivity (4.9%). The highest variation in CRPs was explained in forest and temperate shrubland habitats. Yet, the strength and direction of these relationships were strongly habitat‐dependent. We conclude that any spatial upscaling of the effects of plant communities on CRPs must consider the relative contribution of different habitat types.

Climate and land-use change are key drivers of global change. Full-factorial field experiments in which both drivers are manipulated are essential to understand and predict their potentially interactive effects on the structure and functioning of grassland ecosystems. Here, we present eight years of data on grassland dynamics from the Global Change Experimental Facility (GCEF) in Central Germany. On large experimental plots, temperature and seasonal patterns of precipitation are manipulated by superimposing regional climate model projections onto background climate variability. Climate manipulation is factorially crossed with agricultural land-use scenarios, including intensively used meadows and extensively used (i.e. low-intensity) meadows and pastures. Inter-annual variation of background climate during our study years was high, including three of the driest years on record for our region. The effects of this temporal variability far exceeded the effects of the experimentally imposed climate change on plant species diversity and productivity, especially in the intensively used, species-poor grasslands. These changes in productivity and diversity in response to alterations in climate were due to immigrant species replacing the target forage cultivars. This shift from forage cultivars to immigrant species may impose additional economic costs in terms of a decreasing fodder value and the need for more frequent management measures. In contrast, the extensively used, species-rich grasslands showed weaker responses to both experimentally manipulated future climate and inter-annual climate variability, suggesting that these diverse grasslands are more resistant to climate change than intensively used, species-poor grasslands. We therefore conclude that an extensive management of agricultural grasslands, together with other measures to increase species diversity, can stabilize primary productivity under climate change.

The biogeographic origin of the species‐rich steppe grasslands in central Europe has long been debated. The alternative hypotheses are long‐term species persistence in situ versus immigration from the south‐east, either after the last glacial maximum (LGM) or after the Neolithic landscape deforestation. We ask whether macroclimate‐based models of habitat suitability support either of these hypotheses and search for macroclimatically suitable ‘source areas' from which species could colonise the areas occupied in Europe today. We modelled habitat suitability for 104 species of the central European steppes and projected these models to 10 periods between the LGM and the present using downscaled CCSM3 simulations. By simulating postglacial migration, we identified potential source areas for each species in the LGM and mid‐Holocene and examined whether their location differed among three ecological and five chorological species groups. The central European macroclimate during the cold phases of the Late Pleistocene was suitable for species now typical of Asian desert steppes, whereas the warmer Bølling–Allerød and Holocene macroclimates supported the occurrence of present‐day central European steppe flora. The models suggest that the LGM source areas of these species ranged from south‐eastern France through the Adriatic region and the Balkan Peninsula to the Black‐Sea region but extended to central Europe in the mid‐Holocene. Their locations differed considerably among ecological and chorological groups in both periods. Therefore, our models support the hypothesis that during the Pleistocene cold periods, the largest populations of these species occurred in southern and south‐eastern Europe and some of them may have later colonised central Europe. If some populations occurred in central Europe during the LGM, as suggested by recent genetic analyses, they were likely restricted to microrefugia embedded in the landscape matrix of species‐poor cold steppe. The precipitation‐rich mid‐Holocene climate had no direct negative impact on the central European steppe flora.

Motivation: Detailed knowledge on the climatic tolerances of species is crucial to understand, quantify and predict the impact of climate change on biodiversity and ecosystem functions. However, quantitative data are limited; often, only expert‐based qualitative estimates are available. With the ClimPlant database, we capitalize on the link between species distribution ranges and macroclimate to infer the realized climatic niches of 968 European forest plant species.Main types of variables contained: The ClimPlant database contains information on the distribution of monthly, growing‐season and annual mean, minimum and maximum temperature and total precipitation within the distribution range of 968 European forest plants.Spatial location and grain: Europe in 10 arc‐min grid cells; the study area has been cropped rectangularly at 15° W (Atlantic Ocean), 60° E (Ural Mountains), 25° N (Sahara) and 75° N (Arctic Ocean).Time period and grain: The distribution ranges of forest plant species are based on two renowned distribution atlases. The monthly mean, minimum and maximum temperature and precipitation between 1970 and 2000 were extracted from WorldClim v.2.Major taxa and level of measurement: Nine hundred and sixty‐eight vascular plant species of European forests, with taxonomy following the Euro+Med PlantBase nomenclature .Software format: Data in 56 CSV files, with 1,000 values for monthly, growing season and annual observations of mean, minimum and maximum temperature and precipitation in the distribution range for every species. One summary CSV file with summary statistics (mean, median, fifth and 95th percentile), for every species, of each climatic variable, together with seven key geographical descriptors: area of the distribution range, latitude and longitude of the centroid, and northern, eastern, western and southern range limits within the study area.