Human populations are increasingly concentrated in cities, creating some of Earth’s most modified ecosystems. Yet, spatially explicit, observation-based assessments of urban climates and especially soils remain scarce. This limits evidence-based planning for climate adaptation and urban resilience. Here, we leverage over 80 million crowd-sensed plant observations from 326 European cities as “living sensors” to map high-resolution patterns of urban climate and soil properties. This approach builds on consolidated knowledge of plant ecological preferences, integrated through three new pan-European systems of ecological indicator values.Beyond the urban heat island, we identify additional consistent contrasts between built-up and green areas in moisture, light, soil pH, disturbance, and salinity. The magnitude of these within-city environmental gradients rivals those observed between cities thousands of kilometers apart across Europe. Environmental conditions in built-up areas are remarkably similar across cities, highlighting urban environmental homogenization. In contrast, urban forests maintain natural environmental diversity, contributing to cooling, moisture retention, and key ecosystem functions.Our new sensing approach, called mobile crowd sensing of environments (MCSE), supports participatory assessment of nature-based solutions and provides actionable insights for planners, policymakers, and local communities. It enables evidence-based decision-making for climate adaptation, sustainable urban development, and the promotion of human health and well-being under rapid urbanization and climate change.

Grasslands in Europe are important habitats for a significant portion of the continent's biodiversity yet have undergone substantial transformations due to land use and climate changes during the 20th century. As plant species have been differentially impacted by these alterations, conservation efforts must not only consider overall species diversity but also assess changes at the individual species level. We resurveyed vegetation plots recorded in Switzerland between 1884 and 1931, covering a wide range of grassland types and elevations (300-2500 ma. s.l.), to identify plant species that have either increased or decreased in frequency and those that have experienced elevational shifts. Our findings reveal a predominance of decreasing species (losers) compared to increasing species (winners), with this pattern weakening at higher elevations. Notably, declines affected both rare and common species, the latter often being overlooked in conservation strategies. Decreases were most frequently associated with geophytes and species adapted to low nutrient conditions and cooler temperatures. While the proportion of neophytes increased at the expense of indigenous species and archaeophytes, it remained low overall. The upward shifts in mean elevation of many species appeared to be primarily driven by intensified land use at lower elevations, whereas climate change was likely a more significant factor at higher elevations, where human influence is less intense. The results underscore the need for enhanced conservation measures to preserve and restore grassland habitats, limit eutrophication (especially at lower elevations), and take action against climate change to allow mountain regions to function as refugia for some species.

Plant functional traits are fundamental to ecosystem dynamics and Earth system processes, but their global characterization is limited by available field surveys and trait measurements. Recent expansions in biodiversity data aggregation-including vegetation surveys, citizen science observations, and trait measurements-offer new opportunities to overcome these constraints. Here we demonstrate that combining these diverse data sources with high-resolution Earth observation data enables accurate modeling of key plant traits at up to 1 km2 resolution. Our approach achieves correlations up to 0.63 (15 of 31 traits exceeding 0.50) and improved spatial transferability, effectively bridging gaps in under-sampled regions. By capturing a broad range of traits with high spatial coverage, these maps can enhance understanding of plant community properties and ecosystem functioning, while serving as tools for modeling global biogeochemical processes and informing conservation efforts. Our framework highlights the power of crowdsourced biodiversity data in addressing longstanding extrapolation challenges in global plant trait modeling, with continued advancements in data collection and remote sensing poised to further refine trait-based understanding of the biosphere.

Conservation and management policies for plant invasions often rely on coarse-scale data, while plant diversity effects on ecosystem functions and services are primarily driven by species interactions at small spatial scales. Yet, most evidence on invasion drivers at fine scales is limited to a single grain size, leaving uncertainty about their scale-dependency. Understanding such scale-dependency is essential for predicting and managing invasions effectively. We sampled plant communities across grassland habitats in Ukraine to assess how native species richness, environmental factors, and anthropogenic disturbances influence community invasion level - the proportions of all alien species, and separately for invasive species (fast-spreading aliens at advanced stages of invasion), archaeophytes (introduced before 1500 CE) and neophytes (post-1500 CE aliens). By analysing these groups across six fine-grain areas (0.001-100 m2), we tested for scale-dependent effects. Native species richness was the strongest driver of invasions, showing negative effects that weakened with increasing scale. Alien species were dominated by archaeophytes and occurred most in dry grasslands, and least in fringe, alpine, and mesic types, driven by climatic and disturbance gradients. A range of abiotic and anthropogenic drivers, including precipitation, temperature, disturbance, land use and urbanization also influenced invasion levels, but their importance varied with scale. Notably, the scale-dependency of invasion drivers differed among archaeophytes, neophytes, and invasive species. Our results highlight the importance of separating alien groups and considering multiple spatial grains to avoid overlooking key drivers of invasion. Focusing on scale- and group-specific factors can enhance the ecological relevance and efficiency of conservation and management strategies targeting plant invasions.

Aim The intentional or unintentional transport of non-native plants is key to overcoming geographic barriers. However, it remains unclear whether such introduction pathways associate with overcoming environmental barriers, which is key for successful invasion. Here, we test how intentionality of introduction associates with niche breadth and niche harshness. Location Europe. Time Period 1914-2020. Major Taxa Studied 220 plant species. Methods Across > 60,000 invaded vegetation plots, we tested whether intentionality of introduction (intentional, unintentional, or both) and characteristics of non-native plants (native climatic niche breadth, growth form, dispersal syndrome, height, residence time) were associated with their niche breadth, quantified through habitats, climate, and co-occurring flora. We tested how the intentionality of introduction was associated with environmental harshness (drought, salinity, oligotrophy, and elevation), while accounting for land-cover and habitat types. Results Non-native plants introduced both intentionally and unintentionally had a broader habitat range, compared to non-native plants introduced only unintentionally. A broad climatic niche in the native range was associated with a broader invaded climatic niche, while a long residence time was associated with broader habitat and biotic niches. Intentional introduction was associated with the invasion of dry habitats and forests, whereas unintentional introduction was linked to the invasion of saline, high-elevation, and disturbed environments. Main Conclusions In addition to triggering invasions, the type of process responsible for introduction can partly explain how non-native plants overcome environmental barriers in the invaded range. The intentionality of introduction was associated with niche breadth only in terms of habitat range, while the association with niche harshness depended on the type of stress, which highlights the importance of integrative niche assessments. The relationship between intentionality of introduction and the invaded niche could relate to intentionality-specific differences in biological attributes (environmental tolerance, dispersal capacity, and preference for disturbance) and the introduction process (propagule pressure and residence time).

Background : The majority of vegetation plots has been and still is being recorded on ordinal scales, meaning that the values have to be back-transformed to percent for many typical analyses. Little is known about how different back-transformation approaches affect this procedure. While generally the midpoints of the class borders are recommended for back transformation, one of the most widely used back-transformation for the 7-step Braun-Blanquet scale (as the most widely used ordinal scale) is the default back transformation in the software TURBOVEG. Thus, we asked whether this approach possibly biases results. Case study : We selected three datasets of different vegetation types recorded with percent and calculated how the use of the 7-step Braun-Blanquet scale with three possible back-transformations (arithmetic and geometric mid-point, TURBOVEG) would have influenced Shannon diversity, Shannon evenness and Simpson diversity. We found small and inconsistent changes for the first two but always substantial increases in case of the TURBOVEG back-transformation. Conclusions : The default TURBOVEG translation of the 7-step Braun-Blanquet scale can strongly bias analyses of vegetation plots stored in regional and collaborative databases in the case of cover-based biodiversity metrics, but likely also for any other analysis that involves species cover. It should thus be avoided.

Land use management can help address the human-induced climate and biodiversity crises. However, substantial transformations in land systems are needed to meet internationally agreed targets concerning nature conservation, restoration, sustainable agriculture, and tree cover. Such transformations influence land-atmosphere exchanges of energy, water, and carbon, and could have particularly strong effects on local to regional climate through changes in albedo and evapotranspiration. Here, we explore how land use management in Europe, consistent with the Kunming-Montreal Global Biodiversity Framework, the Nature Futures Framework, and a sustainable low-emissions scenario, would affect the European climate mid-century. Using Earth System Modelling and detailed land use, habitat, and species projections, we show that policy implementation guided by relational values (Nature as Culture) could lead to additional warming and drying further threatening biodiversity and human well-being. Conversely, promoting intrinsic values (Nature for Nature) or ecosystem services (Nature for Society) would not add major challenges for climate adaptation and mitigation. These different outcomes highlight the need to develop integrative land use scenarios that enhance biodiversity and stabilise the climate, while considering feedbacks from land to the atmosphere. Such scenarios could help navigate trade-offs and inform policy implementation in Europe.

Understanding why ecosystems respond differently to environmental drivers, and how vegetation mediates land–atmosphere fluxes of matter and energy, remains a central challenge in ecosystem functioning research. Lacking information on biodiversity—spanning species composition, plant functional traits, bioindication, understory vegetation, and vegetation dynamics— may have prevented significant progress here. FloraFlux enables the collection of this complementary “biodiversity layer” to unlock new opportunities for interpreting and modelling ecosystem fluxes and functions across flux tower sites.FloraFlux is a community-driven initiative to collect plant species occurrence data at eddy covariance flux sites worldwide. Integrated as a flux tower–specific project into the Flora Incognita app for automated plant identification, FloraFlux enables participants to document and share spatially and temporally explicit plant species occurrence information within tower footprints seamlessly with only a smartphone. Participation is simple and inclusive, requires no botanical expertise, and supports open data sharing within the flux tower community. Data processing pipelines linking FloraFlux observations to existing biodiversity and ecosystem research infrastructures are already in place, including: (1) pan-European bio-indication systems such as EIVE for local climate and soil conditions, (2) the European Disturbance Indicator Values for disturbance and management, and (3) the global plant trait data from the TRY Plant Trait Database.The first FloraFlux field season in 2025 already yielded >1,500 plant observations from >30 flux tower sites in Europe. ~40 participants contributed data, and > 50 newsletter subscribers prove the feasibility and acceptance of this collaborative effort. A Shiny web application will provide a map and site-level summaries of plant traits and bio-indicators (QR code on poster).We are starting to explore key questions, such as:How can plant functional traits and bio-indicator values help us understand ecosystem functional properties and spatial variation in fluxes?How do ecosystems with different biodiversity and local site conditions respond to environmental drivers such as drought, pests, or management interventions?What is the role of understory and herb-layer vegetation in modulating flux variability?How does functional diversity influence ecosystem resilience, for example in terms of recovery after drought or extreme events?How can integrating species-level traits and bio-indicators complement or refine traditional plant functional type classifications?First exploratory analyses show a strong relationship between maximum NEP and plant indicator values for soil nitrogen (R² = 0.45, rising to >0.9 when including further traits and bio-indicators) derived from species observations. These initial findings underscore the potential of FloraFlux to contribute the “missing biodiversity link” to long-term flux research and strengthen the scientific and societal value of networks such as ICOS or FLUXNET.All flux tower teams worldwide are invited to the 2026 FloraFlux season. Join us with your smartphone at the poster for assistance. More participants and observations enhance our collective understanding of biodiversity’s role in ecosystem functioning.Join FloraFlux and contribute to biodiversity–ecosystem functioning research effortlessly!

Despite extensive research, stabilizing mechanisms in ecosystems remain uncertain. Taylor's power law (TPL) is a pervasive ecological pattern that describes how variance scales with mean abundance (sigma(2) = a mu(b)). While TPL has been widely studied within populations, its role across species within communities and its implications for stability remain largely unexplored. A TPL scaling factor (b) < 2 implies an unexplored stabilizing effect of dominant species (hereafter the 'dominance effect'), where community stability arises from dominant species being relatively more stable than subordinates. This study aims to explore the influence of TPL exponent b on the dominance effect on stability and identify the biotic and abiotic community factors shaping it. Using data from over 9000 permanent vegetation plots globally, we investigated within-community TPL, linked it to the dominance effect, and examined drivers of b values. Results reveal a strong contribution of b, together with species evenness, to dominance effects on stability. A ubiquitous TPL (mode R-2 = 0.92) with a consistent b < 2 highlights widespread dominance effects. Lower b values were linked to resource-conservative strategies and climatic seasonality, reinforcing the role of environmental filtering in stability. These findings highlight the widespread dominance effect on community temporal stability, particularly driven by woody, large-seeded species in cold, seasonal climates. Moreover, results identify the TPL exponent b as a powerful indicator of dominant species' stabilizing effects, complementing the well-known role of species diversity.

Semi-natural dry grasslands in Central Europe harbor many rare and specialized species and face threats due to altered management practices and environmental change. However, more studies on vegetation change and management effects in dry grasslands are needed, especially with consideration of non-vascular taxa. Here we used a resurvey approach to analyze vegetation change in dry grasslands on loamy and sandy soils (Festuco-Brometea, Trifolio-Geranietea sanguinei and Koelerio-Corynephoretea canescentis) in Brandenburg, Northeastern Germany. We surveyed 157 plots (10 m2) at each of two time points, 1993-1997, and 20-25 years later, 2017-2018. We recorded a total of 362 vascular plants and 84 non-vascular taxa. Species richness per plot remained stable across surveys. We detected, on average, 32.2 and 21.9 species per plot in dry grasslands on loamy and sandy soils, respectively, including 3.25 and 4.8 non-vascular taxa and 7.6 and 2.2 endangered species according to the regional Red List. We found evidence for vegetation homogenization and a reduction in Shannon diversity and Shannon evenness in the recent survey, suggesting early signs of biodiversity decline. Analyses of mean ecological indicator values and plant traits, as well as of winner and loser species, revealed that changes in vegetation composition were accompanied by an increase in competitive, mesophytic species and a decline in disturbance-tolerant specialists. We further show that the highest diversity in dry grasslands on loamy soils was associated with intermediate levels of grazing. Our findings highlight the conservation significance of dry grasslands and suggest intermediate grazing pressure as a suitable management strategy.

Grassland ecosystems are facing rapid and ongoing change driven by intensified land-use and accelerated climate change, highlighting the urgent need to understand their potential adaptation and response to environmental change. We analyzed data from 52 980 vegetation plots spanning all major grassland habitats in Europe (including alpine, rocky, sandy, saline, dry, mesic and wet grasslands). We quantified competitive (C), stress-tolerant (S), and ruderal (R) strategies for 7858 plant species based on key functional traits and mapped the spatial patterns of C-, S- and R-strategies across European grasslands. Using random forest models, we evaluated the relative importance of environmental factors in shaping these patterns and explored potential changes in the distribution of C-, S- and R-strategies under future climate scenarios. We further investigated how these strategies and their environmental drivers vary across grassland habitats. Our results revealed a clear biogeographical gradient in the distribution of C-, S- and R-strategies from predominantly stress-tolerant strategies in Mediterranean grasslands to greater representation of competitive and ruderal strategies in temperate regions. Climate and soil factors emerged as major drivers shaping these patterns at the continental scale. Projected responses to future climate change varied among regions: grasslands in the Atlantic and Continental regions were projected to decrease in C-strategy and increase in both S- and R-strategy representation, whereas grasslands in Arctic and boreal regions exhibited contrasting trends. Mediterranean grasslands were projected to undergo a transition from mainly R-strategy toward S-strategy species predominance. Furthermore, the strategy patterns and their key drivers differed among grassland habitats, with patterns largely reflecting habitat-specific environmental constraints. This study demonstrates the utility of Grime's CSR framework for characterizing broad-scale patterns of plant adaptive strategies across diverse grassland habitats. It highlights region- and habitat-specific differences in potential responses to future climate change, with implications for targeted grassland management and restoration.

Human populations are increasingly concentrated in cities, creating some of Earth’s most modified ecosystems. However, we lack concepts for assessing heterogenous urban environments, especially their soils, at large spatial scales. Here we uncover fine-scale urban climate and soil patterns across 326 European cities by using more than 80 million crowd-sensed plant observations as living sensors of the environment. In addition to the urban heat island, we identify similar contrasts between the built-up and green areas for moisture, soil pH, salinity and soil disturbance. These within-city environmental contrasts correspond to differences between cities that are about 1,500–3,000 km apart. Climate, especially soil, conditions are more similar between cities for built-up areas than for forests, indicating urban homogenization tendencies. Urban forests serve as a source of environmental diversity, cooling and moisture retention. The crowd sensing of urban environments is facilitated by their citizens, which can support science, policy and help guide urban planning toward livable cities. This study finds that crowd-sensed plants as living sensors uncover climate and soil patterns in 326 European cities; extend the urban heat island effect to moisture, pH, salinity and disturbance; and show built-up areas homogenize whereas urban forests preserve environmental diversity.

Anthropogenic impacts are reshaping plant biodiversity patterns, yet how community-composition shifts track environmental change at large spatial and temporal scales remains unclear. Here, we quantified trends in community-mean plant ecological indicator values (light, temperature, soil moisture, soil nitrogen, and soil reaction) across European vegetation between 1960 and 2020. We used spatiotemporal interpolation based on 644,524 plots and analyzed 18,345 time series encompassing diverse habitats. We found a clear shift in community composition over the past six decades with a steep increase in nitrogen-demanding species across all main habitat types, accompanied by a moderate increase in shade-tolerant species. Forest communities shifted toward species associated with higher soil pH, while wetland communities showed a decline in moisture-dependent species over time. Conversely, temperature indicator values were largely stable, except for recent thermophilization in alpine habitats. Our results indicate a widespread trend toward denser vegetation driven by eutrophication and changes in management practices.

Aim European grasslands rank among the most species-rich ecosystems at small spatial scales, yet their biodiversity and functioning face significant threats from climate change and land-use intensification. Functional traits more effectively explain ecosystem functions (EFs) than species identity or diversity. This study examines how future climate and land cover changes will shape grassland functional composition, addressing gaps in trait-environment relationships and large-scale functional predictions.Location Europe.Time Period 1971-2000 and 2081-2100.Major Taxa Studied 4406 distinct grassland plant species.Methods We used Boosted Regression Trees to model trait-environment relationships based on vegetation plot data from sPlotOpen, GrassPlot, and the Nordic-Baltic Grassland Vegetation Database (NBGVD). We mapped the 17 trait community-weighted means (CWMs) and three functional richness (FRic) metrics under historical conditions and two future climate scenarios to assess temporal and spatial changes in grassland functional composition.Results The trait-environment relationships are highly trait-dependent: structural and size-related traits such as plant height, leaf area and seed number were consistently well-predicted, whereas other traits were less well predicted. Mean annual temperature emerged as the strongest predictor of grassland functional composition. Climate and land cover change were predicted to drive significant spatial shifts in trait CWMs and FRic. Specifically, leaf area was predicted to decline in the Baltic Sea region and Pannonian Basin, while plant height was expected to increase across Europe. Seed number was predicted to rise at higher latitudes and in mountainous regions. Moreover, FRic was expected to decrease in temperate grasslands but increase at high latitudes and mountainous regions.Main Conclusions Our findings reveal distinct spatial patterns in functional shifts, reflecting plant adaptation to future environmental conditions. The increase in FRic at high latitudes and mountainous regions also signals ecosystem transitions that may pose additional threats to further complicate grassland conservation efforts.

Predicting which non-native plant species will become established and where is critical for conserving and managing biodiversity. Theory suggests that the mycorrhizal strategy of non-native plants may predict their establishment success. Here we combine a global dataset of 440,788 vegetation plots with data on plant native status and mycorrhizal type to assess mycorrhizal strategy of non-native plants. The mycorrhizal strategy of non-native plants varies strongly across biomes. Across grassland and desert biomes, non-native species are more frequently non-mycorrhizal than native species, whereas in other biomes non-native species are more likely to be mycorrhizal, most commonly arbuscular-mycorrhizal. Disturbance type and intensity are key predictors of mycorrhizal strategy of non-native species, as mycorrhizal species are favoured by landscape modification and non-mycorrhizal species by natural and human-caused disturbance events. Facultatively mycorrhizal species are consistently under-represented among non-native plants compared with natives, suggesting that symbiotic flexibility does not confer an advantage for non-natives as previously expected. Our study shows that non-native mycorrhizal strategy varies across biogeographical contexts and disturbance, highlighting the need for region-specific prevention and management approaches to plant species introductions.

Light regulates ecological processes from organism performance to ecosystem functioning, yet its role in shaping plant diversity across spatial scales remains unresolved. Here, we combine > 650,000 vegetation plots, 14,835 species-specific light indicator values based on Ecological Indicator Values for Europe (EIVE), and Earth observation data to provide the first pan-European assessment of how light regimes near the ground shape plant diversity across scales. Incorporating light-regime metrics beyond macroclimatic and edaphic drivers improved predictions of plant diversity, with relative increases in explained variance of 3% and 27.4–34.5% at the local and landscape scale, respectively. Plant diversity peaked under intermediate-to-high light availability coupled with high spatial heterogeneity. Strikingly, at the landscape level, we identified a pronounced mismatch between the light regimes currently prevailing across Europe and those associated with high plant diversity. Together, these findings reveal light regime as a fundamental axis for plant biodiversity and suggest that widespread shifts towards very low light availability and reduced spatial heterogeneity may decrease plant diversity across Europe. Maintaining non-shaded or increasing spatial heterogeneity in light conditions near the ground could therefore help reduce this mismatch, expanding the extent of light regimes with high potential to support plant diversity.

Abstract Despite widespread concern over global biodiversity loss, the balance between gains and losses within local plant communities remains contentious, largely due to a scarcity of integrative, long-term and large-scale analyses across different habitats and multiple facets of biodiversity. Here, we analyse 57,390 vegetation-plot time series of vascular plants across Europe to quantify the average and habitat-specific trends in taxonomic, functional, phylogenetic, and gamma diversity, alongside with changes in threatened Red List, non-native, and specialist versus generalist species. We find that, over the last 100 years, plant communities gained on average 0.7% in vegetation cover and 0.2% in species number per year, associated with gains in functional and phylogenetic diversity, non-native, Red List, and generalist species. Diversity changes are most pronounced in mire and wetland communities. Differences among habitat types and habitat-change trajectory (stable, successional, disturbed), together with the most recent observation year, explain 2.1%–36.6% of the variation in diversity trends. Habitat-specific gamma diversity showed no general trends and only increased in stable grasslands and successional sparsely vegetated habitats. By integrating habitat types and change trajectories, we reconcile some of the conflicting narratives on local biodiversity change in favour of a more nuanced understanding of the observed variation in local biodiversity change.

ABSTRACT Understanding the factors governing grassland biodiversity across different spatial scales is crucial for effective conservation and management. However, most studies focus on single grain sizes, leaving the scale‐dependent mechanisms of biodiversity drivers unclear. We investigated how climate, soil properties, abiotic disturbance, and land use influence plant diversity across two fine spatial scales in various grassland types in Ukraine. Using spatially explicit data on plant species presence and their cover, collected at smaller (10 m2) and larger (100 m2) grain sizes, we assessed spatial β‐diversity—the variability of biodiversity between scales. We analyzed whether the effects of ecological drivers on β‐diversity are mediated by changes in species evenness, density (total cover), and intraspecific aggregation in plant community. In our study, the most influential factors of local plant diversity at both grain sizes were climate variables, followed by soil humus content, litter cover, and soil pH. Soil and litter effects were primarily driven by the response of locally rare species, while climate and grazing effects were driven by locally common species. The strength of most of these effects varied between spatial scales, affecting β‐diversity. Soil properties influenced β‐diversity through changes in total plant community cover, while the effects of climate and litter operated via changes in species evenness and aggregation. Our findings highlight that biodiversity responses to climate, soil factors, and litter depend on the size of the sampled area and reveal the role of total plant cover, evenness, and aggregation in driving fine‐scale β‐diversity in grasslands across different habitat types.