Mountain ecosystems are highly sensitive to climate variations. At fine spatial scales, high-elevation microclimates play a critical role in shaping biodiversity, hydrological processes, and ecosystem services, while also influencing the occurrence of natural hazards such as landslides, avalanches, and floods. Heat waves, which have been increasing in frequency and intensity due to global climate change, present significant challenges to these vulnerable environments. This study examines the impacts of summer heat waves on mountain microthermal conditions in three compartments: rockwalls, soils, and lakes. We assembled data across a latitudinal and elevational gradient in the French Alps including years of two recent heat wave events (2015 and 2022). We calculated thermal indicators to evaluate the buffering or amplifying effects of the atmospheric signal on the investigated compartments. The average summer temperature and the growing/thawing degree days were more responsive to heat waves than the phenological indicator (e.g., spring mixing date in lakes) and maximum temperature. We found significant anomalies for both the 2015 and 2022 heat waves across almost all compartments and indicators. Lakes tended to amplify atmospheric temperatures (especially in 2022) whereas rockwalls and soils tended to buffer them. However, residues from the relationship between compartment and atmospheric temperatures were large during heat waves, suggesting that these events may reduce the compartments’ buffering capacity. Our study underscores the importance of long-term monitoring of microthermal conditions to provide a more integrative assessment of mountain ecosystem response to extreme meteorological events.

Understanding how climate shapes ecosystem productivity through both energetic constraints and biodiversity‑mediated pathways remains a major challenge in global change ecology, particularly in mountain grasslands where rapid warming and strong environmental gradients interact. Here, we disentangle and map direct climatic controls on productivity from indirect effects mediated by canopy functional structure across the European Alps. Using Sentinel‑2 time series (2017–2024), we quantified canopy functional structure from spectral proxies of pigment investment and water status, functional richness, and vegetation productivity using near‑infrared reflectance of vegetation (NIRv). We combined causal inference with piecewise structural equation modelling to partition total climate effects into direct and trait‑mediated components and used varying‑coefficient models to evaluate how these pathways vary along environmental gradients. We identified two concurrent pathways linking climate to productivity. Warmer growing seasons directly increased productivity but simultaneously reduced canopy pigment investment and water status, generating negative indirect effects that partly offset direct gains. Greater winter snow accumulation reduced productivity both directly, by shortening the effective growing season, and indirectly, through increases in canopy water content associated with lower productivity. Climatic water deficit produced opposing effects, with weakly positive direct impacts counteracted by negative indirect effects mediated by pigment‑related traits, resulting in minimal net productivity change. Trait diversity showed relatively weak climate responses and modest contributions to indirect effects. Environmental context strongly modulated climate–vegetation relationships. Baseline temperature and moisture availability most strongly shaped climate effects on canopy traits and productivity, whereas biodiversity–functioning relationships varied little across space. Strongest positive productivity responses to warming occurred in moist, mid‑elevation regions, while responses weakened or became neutral at high elevations, snow‑rich areas, and dry sites.

Climate change increases plant species richness in alpine ecosystems. However, to what extent this diversity enrichment masks extinction dynamics of resident species remains elusive. In this study, we used floristic resurvey data from 896 permanent vegetation plots across 62 European mountain summits to show that local extinctions have increased over the past 21 years. Extinction rates rose with the magnitude of warming, and species were more likely to go extinct toward their low-elevation range margins and in communities undergoing stronger thermophilization. Moreover, local extinctions were significantly related to preceding abundance declines, which can serve as an early warning signal. These findings suggest that despite increasing plant species richness, plant assemblages above the treeline face an accelerating but so far neglected loss of their most characteristic species.

Shrub encroachment has become a global phenomenon in recent decades. While global warming in the Arctic is often cited as the primary cause, human-managed mountain regions have experienced intense historical land-use that may also play a considerable role. Shrub encroachment has significant implications for biodiversity, carbon storage, and transformation of mountain landscapes. However, disentangling between the effects of present-day environmental conditions and historical land-use trajectories in explaining present-day shrubland distribution remains challenging. We use early 19th-century land registry records - rare historical sources documenting past land-use and vegetation cover - to assess whether these legacy conditions influence present-day shrub distribution. By combining these archive data with dendrochronological sampling and a diachronic analysis of shrub expansion based on historical aerial photographs, we provide a comprehensive analysis of shrub colonisation. Our results reveal an increase in shrub cover over the past two centuries, primarily driven by the expansion of common juniper Juniperus communis. Dendrochronological analyses from never-mown or ploughed plots indicate that shrub recruitment began around 1870, intensified until the 1970s, and then slowed slightly thereafter. While shrubs preferentially establish on steep, south-facing slopes and topographically rough terrain, their distribution remains highly heterogeneous and is strongly shaped by pre-industrial land-use patterns. Parcels that were ploughed or mown 200 years ago remain largely devoid of shrubs, even decades after mowing ceased. In contrast, surrounding areas - whether grazed or unused - have experienced shrub encroachment. We hypothesize that the low shrub density on former ploughed lands and hay meadows may reflect persistent legacy effects of dense, competitive herbaceous communities, which hinder the establishment of woody species. This study demonstrates that pre-industrial land-use continues to constrain both the distribution and recent dynamics of shrub expansion, highlighting the importance of accounting for land-use legacies when interpreting contemporary shrub encroachment.

Recent changes in alpine vegetation are often attributed to climate warming, particularly community composition shifts towards more warmth-associated species, or thermophilization. Here we assess the link between thermophilization and warming across 53 European mountain summits. We combine long-term macroclimatic and microclimatic temperature time series with vegetation surveys in 724 permanent plots, monitored over 21 years, to evaluate a possible thermophilization signal and relate it to rates of change in 10 temperature metrics. We find evidence of both thermophilization of alpine plant communities and an increase in temperatures. However, although these two trends are related when averaged across mountain regions, their relationship is weak at the individual plot scale, especially when considering microclimatic temperature metrics. Instead, substrate conditions and particularly the availability of thermophilic colonizers in the surrounding vegetation have a major influence on plot-level thermophilization rates. We conclude that the response of plant communities to climate change strongly depends on the abiotic and biotic context, and intensified monitoring efforts are needed to reduce the resulting uncertainties.

In Europe, alpine treelines are shifting upward under the combined influence of climate and land-use change. In the Mediterranean basin, historical human pressure has significantly lowered treeline elevations, and these legacy effects continue to shape their present-day trajectories. Such legacies are expected to contribute to the contrasting patterns observed between the Alps and the Apennines, the two main Italian mountain ranges. Because treeline ecotones are key for mountain biodiversity and ecosystem services, consistent monitoring is crucial. Satellite remote sensing—especially multi-decadal time series of vegetation indices (VIs)— offers a promising avenue to study forest dynamics and treeline shift. Here, we present a semi-automatic and reproducible method to delineate the uppermost forestlines and to identify significant hotspots of change. We then evaluate the main topographic, climatic, and anthropogenic factors predisposing to treeline dynamics according to the long-term increase of VIs. We integrated national and international open-source datasets within a semi-automatic workflow to detect uppermost forestlines based on vertical distances between forest pixels and their relative highest peaks. We assessed greening along a forestline buffer representing the treeline ecotone using a 40-year Landsat NDVI time series (1984–2023). Trend significance was tested with contextual Mann–Kendall statistics, while Theil–Sen slopes quantified the magnitude of change. Finally, we used Random Forest models to investigate the relative importance of predisposing factors. Highest forestline elevations occur in the Alps, where larger elevation ranges and the dominance of conifers appear to be associated with upward shifts. In contrast, Apennine treelines are mainly formed by European beech; its heavier seeds likely limit upslope encroachment, favouring gap infilling processes over treeline upward shift. Overall, this study contributes a standardized framework for mapping forestlines and analysing the predisposing factors of greening dynamics. The approach is transferable to other mountain regions, supporting comparisons across space and time.

There is growing interest in hyperspectral imaging to complement observation needs and techniques required to capture the critical zone dynamics. It is already widely used in remote sensing satellite imagery, for regional-scale monitoring of canopies (Asner et al. 2004), or suspended sediment transport (Yepez et al. 2017). Spectral imaging offers dense, remote and non-intrusive measurement coverage. Its implementation at fixed-station for fine temporal monitoring would ensure maximum temporal coverage to study the phenology and functioning of ecosystems (vegetation-water-soil interactions) and watersheds (sediment dynamics), at integrative scales (e.g. watershed outlets), or over experimental plots. On-site hyperspectral data also enable links to the regional scale through cross-comparison with data from space (de Moura et al. 2017). It would then enables to better control measurement biases, offering in that way better opportunity for standardizing observables, as required by international research infrastructures. In recent years, both technological progresses and applications for commercial uses made these kind of cameras more reliable, compact, and affordable, making feasible on-site hand-held or UAV-based experiments (Stuart et al. 2019). Nevertheless, deployment for continuous monitoring remains uncommon, and limited to specific applications (de Moura et al. 2017, Woodgate et al. 2020), due to a still high instrumental complexity and costs. Furthermore, correct data exploitation requires a complete mastery of the calibration, acquisition, normalization and processing chain, that can be complex with “black-box” commercial systems. The development of a dedicated spectral camera is thus preferred. Such a camera is developed within the program TERRA FORMA from the French Agency for Research (Longuevergne et al. 2022). This program aims to implement integrated socio-ecosystem observatories, in support of the French RZA and OZCAR infrastructures, by developing and deploying a dozen types of state-of-the-art sensors dedicated to environmental monitoring at national-scale until 2029. A part of this project is dedicated to the deployment up to 20 spectral cameras, within two scientific topics: monitoring of plant canopies, monitoring of suspended sediment dynamics in rivers. monitoring of plant canopies, monitoring of suspended sediment dynamics in rivers. The instrumental solution we are implementing is based on developments carried out at IPAG since 2016 in compact spectral imaging for spaceborne Earth Observation (Gousset et al. 2019, Le Coarer et al. 2021). In addition to its compactness and optical simplicity, the main advantage of this kind of camera lies in its ability to acquire all spectral and spatial information in a single acquisition (“snapshot”) of a fraction of a second. By opposite to pushbroom or linescanner concepts, which require tens of seconds of exposure under stable illumination conditions. The TERRA FORMA camera complements these instruments with a frugal, less expensive solution, suitable for deployment as a stand-alone fixed station or for handle-held/UAV acquisitions on the field. Since May 2024, we integrated and tested in laboratory an operational camera (Fig. 1), with the following specifications: Field of view 22 by 12°, for 365 by 200 pixels 1 cm / pixel at 9 m distance 42 spectral channels between 400 and 780 nm (up to 850) Spectral resolution 10 nm (up to 6 nm) 10 x 10 x 6 cm, 0.6 kg, powered by LiPo battery Field of view 22 by 12°, for 365 by 200 pixels 1 cm / pixel at 9 m distance 42 spectral channels between 400 and 780 nm (up to 850) Spectral resolution 10 nm (up to 6 nm) 10 x 10 x 6 cm, 0.6 kg, powered by LiPo battery We carried out a first field test in August 2024 at the eLTER site Lautaret / Roche Noire (French Alps). During this single day of acquisition, we acquired data over the landscape jointly to a reference commercial non-imaging spectrometer. This last is shown on Fig. 2, demonstrating a good adequacy between hyperspectral data from the camera and reference spectra. The next steps for 2025 are on site campaigns, lasting 3 to 6 months at fixed stations on pilot sites. On the biodiversity topic: acquisition during a full growing season in a snow-covered mountain grassland equipped with a flux tower should enable: To compare the series of data from hyperspectral imagery with the installed multi-spectral NDVI sensor (only two channels in red and near infrared). To compare spectral measurements with balances of radiative fluxes, and with CO 2 and H 2 O exchanges in the soil-plant-atmosphere continuum. To identify the best optical proxies for inferring vegetation water status and CO 2 fixation capacity during a season. To compare the series of data from hyperspectral imagery with the installed multi-spectral NDVI sensor (only two channels in red and near infrared). To compare spectral measurements with balances of radiative fluxes, and with CO 2 and H 2 O exchanges in the soil-plant-atmosphere continuum. To identify the best optical proxies for inferring vegetation water status and CO 2 fixation capacity during a season. Mid-term objective is to be able to increase the effective footprint of the tower, then to be able to infer canopy function and structure using imagery, through integrated and continuous measurement of several biodiversity parameters at the same time, complementary to data collected as part of the eLTER and ICOS infrastructures. On the hydrology topic: another camera will be deployed on hydrological stations (campus of Grenoble, then Galabre river (Legout et al. 2021)). The aggregation of data should enable: To identify optical proxies for quantifying suspended solids concentrations. To evaluate the robustness of this approach in a concentration range from 0 to a few tens of g/l, currently well measured by the combined turbidimetry and sampling approach (Navratil et al. 2011). To identify optical proxies capable of discriminating between the different types of suspended solids transported in rivers during floods. To apply an approach based on these optical proxies to trace the sources of suspended solids using mixture models, and compare these results with those obtained using the spectro-colorimetric manual suspended solids tracing method implemented on the Galabre site since 2013 (Legout et al. 2013). To identify optical proxies for quantifying suspended solids concentrations. To evaluate the robustness of this approach in a concentration range from 0 to a few tens of g/l, currently well measured by the combined turbidimetry and sampling approach (Navratil et al. 2011). To identify optical proxies capable of discriminating between the different types of suspended solids transported in rivers during floods. To apply an approach based on these optical proxies to trace the sources of suspended solids using mixture models, and compare these results with those obtained using the spectro-colorimetric manual suspended solids tracing method implemented on the Galabre site since 2013 (Legout et al. 2013). The final objective is to be able to complement in situ techniques (turbidimetry) and river sampling with a remote, robotized measurement method, providing better temporal coverage of flood episodes, more reliable than submerged sensors.

AbstractMultidecadal time series of satellite observations, such as those from Landsat, offer the possibility to study trends in vegetation greenness at unprecedented spatial and temporal scales. Alpine ecosystems have exhibited large increases in vegetation greenness as seen from space; nevertheless, the ecological processes underlying alpine greening have rarely been investigated. Here, we used a unique dataset of forest stand and structure characteristics derived from manually orthorectified high‐resolution diachronic images (1983 and 2018), dendrochronology and LiDAR analysis to decipher the ecological processes underlying alpine greening in the southwestern French Alps, formerly identified as a hotspot of greening at the scale of the European Alps by previous studies. We found that most of the alpine greening in this area can be attributed to forest dynamics, including forest ingrowth and treeline upward shift. Furthermore, we showed that the magnitude of the greening was highest in pixels/areas where trees were first established at the beginning of the Landsat time series in the mid‐80s corresponding to a specific forest successional stage. In these pixels, we observe that trees from the first wave of establishment have grown between 1984 and 2023, while over the same period, younger trees established in forest gaps, leading to increases in both vertical and horizontal vegetation cover. This study provides an in‐depth description of the causal relationship between forest dynamics and greening, providing a unique example of how ecological processes translate into radiometric signals, while also paving the way for the study of large‐scale treeline dynamics using satellite remote sensing.

Estimating SOC stocks and stability, as well as modeling their response to rising temperatures, is crucial for predicting climate change impacts. This is particularly true in mountainous regions, where low temperatures slow down SOC decomposition, resulting in higher SOC stocks compared to soils at lower elevations. However, these stocks are also more vulnerable to warming, increasing the risk of SOC depletion. Such conditions create the potential for a positive feedback loop in which warming accelerates SOC losses, further amplifying climate change impacts on these sensitive ecosystems. To better understand the factors controlling SOC stocks and stability in mountain soils, we sampled 170 soil profiles along 29 elevation gradients in the western Alps from 280 to 3160 m a.s.l. We assessed SOC stocks and chemical composition using mid-infrared spectroscopy method and SOC stability with Rock-Eval (R) thermal analysis. Our findings, based on an unprecedented dataset, reveal a clear elevational pattern in SOC properties. SOC stocks increase with elevation up to the montane belt (1200-1500 m a.s.l.), remain relatively stable through the subalpine zone, and then decline beyond the subalpine/alpine boundary (2200-2400 m a.s.l.). Notably, this transition is also marked by a significant drop in SOC stability, suggesting a shift in the dominant stabilization processes at higher elevations. Our results also indicate that SOC stocks and stability are influenced by a complex interplay of factors. At higher elevations, climate emerges to be the dominant factor, whereas lithology and weathering play a more significant role at lower elevations. These results suggest that at high-elevations, harsh climatic conditions favor stabilization of SOC, while less developed soils limit organo-mineral interactions. In contrast, at warmer, lower elevations with higher carbon fluxes, more developed soils facilitate organo-mineral interactions, thereby enhancing SOC stability in the long term. Consequently, alpine grasslands, which contain substantial stocks of labile carbon stabilized by climatic conditions, appear to be particularly vulnerable to the effects of climate warming.

Over the past four decades, seasonal snow cover has declined rapidly in temperate alpine regions. However, the fine-scale dynamics of snowmelt preceding the ongoing warming period remain largely unknown, limiting our understanding of the long-term influence of past snow cover on alpine ecosystems. Here we rely upon the spatial similarities in melt-out patterns and a temperature-based model of fractional snow cover area, to reconstruct fine-scale snow cover changes over the past 250 years in instrumented catchments of the southwestern Alps. We provide evidence that, until the 1980s, prolonged snow cover in many late-lying snowfields delayed ecosystem development and explain why current vegetation cover, soil organic matter content, and mineral weathering are significantly lower in these areas than in surrounding ecosystems. These findings highlight the long-term legacy of snow cover on alpine landscapes and underscore the need to re-evaluate its effects on ecosystem structure, functioning, and responsiveness to ongoing changes.

In recent decades significant forest expansion into treeless alpine zones has been observed across global mountain ranges, including the Alps, driven by a complex interplay of global warming and land-use changes. The upward shift of treelines has far-reaching implications for ecosystem functioning, biodiversity, and biogeochemical cycles. However, climate variables alone account for only a fraction of treeline dynamics, highlighting substantial research gaps concerning the influence of non-climatic factors. This study addresses these gaps by combining dendrochronological methods, high-resolution bioclimatic data, and historical land-use records to investigate treeline dynamics in the southern French Alps. Our results reveal a marked acceleration in tree establishment, starting in the early 2000s, attributable primarily to climate change rather than the pastoral abandonment of the 19th century. We demonstrate that historical land-use changes created predisposing conditions for tree establishment, while recent climate change has increasingly acted as an accelerator for this dynamic. While key climatic factors, such as thermal indicators and growing season length, are identified as significant contributors to treeline shifts, our study highlights the need for further research to disentangle the specific drivers of tree recruitment and survival in the context of ongoing climate change.

In harsh environments such as Alpine screes, the substrate represents one of the main selective constraints for plants. The substrate’s influence on species distributions has been well characterised using major lithological classes. However, our understanding of the local heterogeneity of substrates and the consequent impact on plants, particularly in mountainous environments, remains limited. By analysing multiple facets of the local substrates, we tried to identify if ecological barriers separate scree specialist species. We sampled substrates in contact with the rhizosphere of plants from a species complex within the genus Noccaea, in 53 sites distributed across the Alps. We analysed the composition and properties of the substrates, in addition with climatic and topographic variables. We compared multiple aspects of substrate between pairs of species and discuss the potential impact of edaphic diversity in terms of plant physiology. The analyses demonstrated that the edaphic diversity forms a continuum rather than distinct classes, and shelter a very large diversity of conditions, particularly within carbonated rocks. We found that Alpine endemic Noccaea species grow in substrates that significantly differ in chemical properties and concentrations in toxic elements, while the topography and climate occupied by different species remain comparatively similar. This study demonstrates that the local diversity of edaphic conditions in alpine screes has been underestimated. The fine-scale differences in the concentration of nutrient or toxic elements appear to be a key factor in the distribution and adaptation of plants, and possibly a reason for the high degree of endemism observed in scree habitats within the Alps.

Mountain areas crown their surrounding landscapes and host a great diversity of ecosystems and human activities. Due to their high altitudes and low temperatures, mountains, in many regions of the world, including Europe, allow the existence of the solid phase of water, ice, seasonally or perennially, which is found in glaciers, snow cover and permafrost, key components of the cryosphere. In the European Alps, the air temperature has increased by about 2 °C compared to the pre-industrial period (end of 19th century), alongside with a slight change in the seasonality of precipitation. Both are projected to intensify in the future. The increase in temperature induces profound changes for the mountain cryosphere with in particular the scarcity of snow cover, the retreat of glaciers and the thawing of permafrost. These changes are causing a cascade of upheavals for the water cycle, mountain ecosystems, the economic and touristic activity of mountain societies. They also induce changes in the natural hazards associated with the cryosphere such as avalanches, risks of glacial and peri-glacial origins as well as floods and droughts. Thus, in a changing climate, the fragile beauty and balance of the European Alps is undergoing profound disruptions whose consequences extend to the lowlands. These will continue to intensify as long as the temperature continues to rise and this is why every increment of temperature matters for the state of the European mountains.

Information on the spatial-temporal variability of seasonal snow cover duration over long time periods is critical for studying the responses of mountain ecosystems to climate change. However, this information is often lacking due to the sparse distribution of in situ observations or the lack of adequate remote sensing products. Here, we combined snow cover data from 10 different optical platforms, i.e. SPOT (Satellites Pour l'Observation de la Terre) 1-5, Landsat 5-8, and Sentinel-2A and Sentinel-2B, to build a time series of the annual snow melt-out day (SMOD, i.e. the first day of no snow cover) at 20 m resolution across the French Alps and Pyrenees (43 x 103 km2). We evaluated the pixel-wise accuracy of the computed SMOD using in situ snow measurements at 276 stations. We found that the residuals are unbiased (median error of 1 d) despite a dispersion (RMSE of 28 d), which suggests that this dataset can be used to study SMOD trends after spatial aggregation. We found average reductions of 21.4 d (5.78 dperdecade) over the French Alps and 16 d (4.33 dperdecade) over the Pyrenees over the period 1986-2023. The SMOD reduction is robust and significant in most parts of the French Alps and can reach 1 month above 3000 m. The trends are less consistent and more spatially variable in the Pyrenees. This dataset is available for future studies of mountain ecosystem changes and is updated every year using Sentinel-2 data.

Soil organic carbon (SOC) is crucial for ecosystem function and carbon storage, especially in mountain regions where cooler temperatures limit microbial activity, leading to higher SOC stocks compared to lowlands. However, the available data are insufficient to fully understand the distribution of SOC properties along elevation and snow cover duration gradients. Given that climate change models predict a reduction in snow cover duration, it is essential to better characterize these properties at a finer, mesotopographic scale (e.g., ridges and slopes), corresponding to the distribution of mountain plant communities. This study investigates the impact of microclimate on SOC content and stability in European mountain grasslands. We focused on two types of grasslands on acidic soils to maintain homogeneity in key parameters such as soil properties and plant communities. These grasslands, located across temperate European mountain ranges (Alps, Pyrenees, Vosges, Balkans, Carpathians, Black Forest, Bohemian Forest, and Sudetes), span a gradient of snow cover duration, ranging from frost-exposed ridges dominated by Carex curvula, to intermediate grasslands, without frost, dominated by Nardus stricta. SOC content and stability were assessed using Rock-Eval (R) thermal analysis across all sites. The results indicate that microclimate significantly influences SOC properties. Cooler temperatures, driven by elevation and reduced snow cover duration, were associated with increased SOC content but decreased stability. On windy ridges, extended growing seasons combined with intense winter freezing led to higher SOC lability, as freezing slows down mineralization processes. In contrast, intermediate grasslands, with longer growing seasons, showed enhanced SOC stability due to higher decomposition activity. These findings provide valuable insights into how SOC properties may evolve under climate change, particularly in relation to rising temperatures and shifting snow cover dynamics.

Over recent decades, cold-climate ecosystems have exhibited a pronounced increase in vegetation greenness, and shrub encroachment is a major ecological process underlying these changes. Our knowledge of these dynamics remains limited in the temperate mountains of Eastern Europe, which have experienced significant land-use shifts, especially following the collapse of the communist regime. It is noteworthy that the contribution of shrubs has not been evaluated, partly due to the difficulty of providing high-resolution mapping of shrublands. In this study, we integrated four decades of Landsat-derived NDVI time series with a customized land cover classification based on Sentinel-2 imagery to investigate greenness dynamics above 1500 m elevation in the Carpathian Mountains. The classification targeted key shrubland types using spectral indices tailored to seasonal pigment variations. We also conducted diachronic visual analysis of aerial photographs, including Cold War-era satellite images, to evaluate long-term vegetation changes. We found significant positive greenness trends in 44% of the study area, with the highest magnitude located at mid-elevations (1800–2300 m) and on north-facing slopes. High-resolution land cover mapping revealed that Ericaceous and Juniperus -dominated shrublands were the strongest contributors to greening. Visual interpretation of historical imagery confirmed widespread woody encroachment in these areas. We suggest that the decline of traditional land-use, particularly extensive grazing practices, is a key driver of these ecological shifts, promoting the resurgence of previously more widespread subalpine shrublands. Our findings highlight the importance of integrating high-resolution remote sensing observations and diachronic analysis of aerial photographs to disentangle the complexity of vegetation greening in high-elevation ecosystems.

Documenting long-term snow cover changes at high spatial resolution is especially challenging in mountain environments due to limited high-elevation ground observations and the coarse resolution of current climate models. This paper presents a dataset of snow melt-out dates (SMOD) at 30-m spatial resolution for two periods-the 1990s (1985-1996) and the 2010s (2011-2022)-across temperate European mountain ranges (Pyrenees, European Alps, and Greater Caucasus), derived from Landsat time series. To address the limited number of observations in the Landsat archive, data were aggregated over 12-year periods, enabling assessment of SMOD changes over four decades at a spatial resolution relevant to above-treeline ecosystems. The SMOD dataset was validated using snow depth station records (R2 ~ 0.75, MAE ~ 7 days) and soil temperature data (R2 ~ 0.7, MAE ~ 10 days) from the Pyrenees and European Alps. Potential applications of the dataset extend beyond alpine ecology, with possible contributions to risk assessments, hydrology, and snow climatology in the context of climate change.

ABSTRACTAimLand surface models (LSMs) currently represent each plant functional type (PFT) as an average phenotype, characterised by a set of fixed parameters. This rigid and constant representation is a limit in understanding the dynamics of highly diverse ecosystems, such as permanent grasslands, and their response to global change.LocationFrance.Time Period2001–2019.Major TaxaGrassland plant species.MethodsWe incorporated spatially explicit trait variability at the France scale in the ORCHIDEE land surface model to assess how the net primary productivity (NPP) will spatially vary over the years. More precisely, we focused on three key functional traits that govern the NPP of grassland ecosystems: specific leaf area (SLA) and leaf nitrogen content (LNC), as measured traits, and leaf lifespan (LLS) as an estimated trait. Community‐weighted means (CWM) were implemented in various combinations with prescribed and spatially varying traits. We compared the outcomes of each NPP simulation to remotely sensed proxies of productivity by using the MODIS satellite‐driven NPP products.ResultsThe sensitivity of NPP to traits depends on climate conditions, such as temperature and water limitation. Considering trait variability decreases the NPP in the most productive regions (plains) and increases the NPP in the less productive regions (mountains) compared to the case with constant trait values. This leads to a more homogenous NPP across France. Compared to the observed MODIS NPP and FLUXCOM GPP, the simulation using varying traits improves the spatial NPP and GPP variations in several regions and most climate conditions.Main ConclusionsBased on the existing trait data, we revealed that incorporating the CWM of traits in an LSM such as ORCHIDEE can be effectively performed. Improving the modelling and predictions by considering the relationships between biodiversity, functional biogeography, and ecosystem functioning is essential in current and future ecological research.