The summer of 2022 was characterized by compound soil and atmospheric drought (CSAD; low soil water content, SWC, and high vapor pressure deficit, VPD) in Central Europe, threatening forest carbon sequestration and water balance, yet linked ecosystem- and tree-level hydraulic responses remain poorly resolved. We assessed the response and recovery of water relations of a beech-dominated montane mixed deciduous forest in Switzerland (CH-Lae) to the 2022 CSAD through a series of ecosystem-scale (evapotranspiration, ET; canopy conductance, Gs) as well as tree-scale measurements, including leaf-level (leaf water potential, LWP; stomatal conductance, gs), stem-level (nighttime stem rehydration, NSR) and root-level (root water uptake depth, RWU depth) variables. During peak CSAD, ET and Gs declined by up to 50%, driven primarily by low SWC. Midday and predawn LWP declined significantly. Beech and maple accessed deeper water (> 70 cm), maintaining NSR and gs during CSAD and fully recovering thereafter; spruce and fir relied on shallow water (< 30 cm), showing stronger NSR reductions but still full recovery post-CSAD. Our findings demonstrate that species-specific hydraulic traits drive forest-scale water dynamics under CSAD conditions. Integrating these insights into forest adaptation strategies will be critical for sustaining forests under intensifying compound droughts in the future.

Abstract. Agriculture is the largest anthropogenic source of nitrous oxide (N2O), primarily due to nitrogen (N) fertilization. Understanding how the influence of key drivers and the relative contribution of source processes change throughout the cropping season is crucial for developing effective strategies to mitigate N2O emissions. In this study, we combined high-resolution eddy covariance flux measurements and stable isotope analyses over one winter wheat cropping season and the subsequent summer cover crop season. Two phases, crop establishment and early spring, were identified as critical periods for N2O emissions, characterized by a mismatch between N supply and plant demand, resulting in surplus soil mineral N and elevated N2O fluxes under favorable environmental conditions. Gross primary productivity (GPP), used as a proxy for crop N uptake, suppressed N2O emissions, especially under high soil moisture, highlighting the importance of active vegetation in mitigating emissions. Source partitioning, based on stable isotopes, revealed denitrification as the dominant process of N2O production, driven by poor soil drainage and high soil moisture. Over the nine-month winter wheat season, the Tier 1 N2O emission factor was 1.8 %, with cumulative emissions of 5.5 kg N2O-N ha−1, offsetting 70 % of the net CO2 uptake. Our findings emphasize the need to better synchronize N supply with crop demand and to adopt agronomic practices that promote rapid crop establishment to mitigate N2O emissions in cropping systems.

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!

Gross primary productivity (GPP; ecosystem-level photosynthesis) represents the largest terrestrial carbon flux and is highly sensitive to temperature. Despite global warming, the trends and controlling factors of optimum temperature (Topt) and maximum rates of GPP (GPPmax) remain uncertain. We investigated the drivers of Topt and GPPmax trends during 2000-2019 using global observations of ground-based eddy covariance and satellite-based sun-induced chlorophyll fluorescence. Although GPPmax increased worldwide, Topt increased only in tropical and temperate regions but remained unchanged globally and in arid and cold regions. Thermal acclimation via shifting Topt was constrained by atmospheric and soil dryness, explaining less than 20% of the global GPPmax rise. In contrast, GPPmax trends were more strongly driven by stomatal regulation improving water-use efficiency and by enhanced canopy development under dryness constraints. These findings challenge the expectation that thermal acclimation is central to projecting GPP under warming and highlight dynamic physiological-structural shifts that sustain terrestrial carbon uptake.

Carbon sustains life, whereas mercury is a global toxin, yet their cycling in forests appears to be intimately linked. Here we show, using elemental stoichiometry, carbon and mercury isotopes and a global forest synthesis, that forests simultaneously couple and decouple mercury from carbon along contrasting ecosystem continua. Mercury/carbon ratios remain tightly conserved (0.5-0.9 × 10-6) along the aqueous-phase continuum, indicating proportional mercury transport with dissolved organic carbon. In comparison, mercury/carbon ratios increase by nearly three orders of magnitude from the atmosphere to soils (0.007-3.6 × 10-6) along the solid-phase continuum, reflecting progressive mercury enrichment during litter and soil organic matter decomposition. Standing litter acts concurrently as a net carbon source and mercury sink, whereas biomass regulates coupled carbon and mercury storage and litterfall deposition. These contrasting carbon-mercury trajectories reveal how forests both retain and redistribute atmospheric mercury and provide a conceptual framework for understanding terrestrial mercury cycling under environmental change.

Crassulacean acid metabolism (CAM) helps plants in arid regions to reduce water loss by opening their stomata and taking up carbon dioxide (CO2) during nighttime. While gas exchange in CAM plants has been mainly studied under controlled laboratory conditions, only a few ecosystem scale studies exist. Moreover, carbonyl sulfide (COS) has been used as a tracer for stomatal conductance, transpiration and photosynthesis in C3 and C4 plants, but no studies on CAM ecosystems have yet been published. Here we present the first ecosystem scale measurements of COS fluxes over Agave sisalana (CAM plant), commercially cultivated for its fiber. The measurements were made during the wet season in Kenya. The ecosystem was a consistent sink of COS, with higher uptake observed during nighttime (-11.5 pmol m m-2 s-1) than during daytime (-5.6 pmol m m-2 s-1). The magnitude of COS fluxes was comparable to non-growing season daytime fluxes reported for C3 and C4 plant dominated ecosystems. The soil was a small COS source (0.3 pmol m m-2 s-1), with highest emissions under high radiation and temperature conditions. Using random forest modeling, we found that vapor pressure deficit, air temperature and soil water content were the most important drivers of nighttime ecosystem COS exchange (variable importance 0.25, 0.23 and 0.20, respectively), indicating the importance of stomatal limitation for COS fluxes. During daytime, air temperature, photosynthetically active radiation and soil temperature were the most important drivers (variable importances 0.19, 0.18 and 0.18, respectively). COS fluxes were further used to track canopy stomatal conductance and transpiration and compared to another transpiration estimate from the conditional eddy covariance method, which is based on raw water vapor and vertical wind data from eddy covariance. Conductance values ranged from 0.03 +/- 0.06 mol m m-2 s s-1 during daytime to 0.06 +/- 0.02 mol m m-2 s s-1 during nighttime. Transpiration was thus higher during nighttime than during daytime, reflecting the CAM gas exchange strategy.

Intrinsic water use efficiency (iWUE) at the leaf level measures water expenditures by terestrial plants during photosynthesis, yet its global spatiotemporal dynamics and responses to water stress remain poorly understood. Using machine-learning models and carbon isotope observations in C3 foliage, here we elucidate global patterns, trends, and water-stress responses of leaf iWUE. We find high iWUE in cold, arid regions and lower values in warm, humid areas. From 2001 to 2020, global iWUE increases at 0.2 ± 0.02 μmol mol-1 year-1, with strong biome specific differences. Grasslands exhibit the highest mean iWUE but the slowest increase, whereas evergreen broadleaf forests show the lowest iWUE yet the fastest increase. iWUE rises with increasing water stress, but the rate of growth diminishes as water stress intensifies. Vapor pressure deficit influence iWUE more broadly than soil moisture. The ecological optimality model reproduces the spatial patterns of leaf iWUE and identifies vapor pressure deficit as the dominant driver, but overestimates mean iWUE and its trend. Our findings suggest that increasing water stress may slow the rate of global iWUE increase as the climate continues to warm. Climate change is altering how plants balance carbon gain and water loss. This study maps global leaf-level water-use efficiency over the past two decades, showing it is highest in regions that are cold or dry, increasing worldwide, and strongly influenced by atmospheric dryness.

Grasslands serve a unique role in the global carbon (C) cycle and cover about 30 % of the European and about 70 % of the Swiss agricultural area. Carbon dioxide (CO2) fluxes of managed grasslands are substantially influenced by land management practices and meteorological conditions, but the temporal development of drivers and their effects are still uncertain. We used 20 years (2005-2024) of eddy-covariance (EC) fluxes, meteorological data, and detailed management information collected from an intensively managed grassland site (Chamau) in Switzerland, and employed machine learning approaches, i.e., eXtreme Gradient Boosting (XGBoost) models in combination with SHapley Additive exPlanations (SHAP) analyses, to identify drivers and their temporal contributions over two decades. Our study aimed to (1) identify intra- and inter-annual variations in grassland CO2 fluxes, (2) assess magnitude and drivers of gross primary production (GPP) and ecosystem respiration (Reco) during regrowth periods (i.e., the period after mowing, grazing, or reseeding events until the next event), and (3) quantify driver contributions to GPP and Reco over time, with focus on management and extreme events. Our results showed pronounced intra- and inter-annual variations in CO2 fluxes, driven by both management activities as well as meteorological conditions. Despite significant increases in temperature and decreases in soil water content (SWC) during the two decades, GPP and Reco during regrowth periods remained stable, and no significant trend over time was detected, suggesting adapted, climate-smart decision making of the farmer. The most important drivers of GPP in the long-term were light, management, and temperature, while Reco was mainly driven by temperature, GPP, and management. However, during extreme drought periods in the peak growing seasons (June, July, August), SWC increased in importance and limited GPP. In contrast, the impact of nitrogen (N) fertilization was more differentiated, either acting in parallel with SWC, suggesting low N availability during drought periods, or increasing GPP in years after sward renewal despite low SWC. Overall, our study provided novel insights into relevant drivers of grassland CO2 fluxes and their complex temporal contributions in the short- and long-term. Our results suggest that even small climate-smart management adaptations could be promising solutions for stabilizing important grassland processes, such as grassland regrowth, under current and future climate.

Abstract. Agroecosystems regulate carbon, water, and nitrogen cycles, yet robust modeling of water and greenhouse gas (GHG) fluxes remains limited by incomplete or inaccessible information on field management practices. Although high-resolution remote sensing (RS) observations can detect management events such as mowing or harvest, their use for representing management intensity and associated impacts on ecosystem flux dynamics remains limited in existing models. Here, we developed an RS-assisted modeling framework to estimate daily latent heat flux (LE), net ecosystem CO2 exchange (NEE), nitrous oxide (N2O), and methane (CH4) fluxes across six Swiss FluxNet sites (two croplands and four grasslands) between 2016 and 2025. Sentinel-2 time series were used to derive leaf area index and RS-based field management indices (RS-FMIs), detecting mowing events, quantifying defoliation intensity, and identifying crop rotation and bare soil periods. These indicators were combined with meteorological drivers to train XGBoost models for each ecosystem type and target variable separately, and driver contributions were evaluated using SHapley Additive exPlanations (SHAP) analysis. The RS-FMIs effectively captured in situ recorded management events and enabled improved reconstruction of daily flux variability. Model performances were strong for LE (R2 ≈ 0.89–0.90) and NEE (R2 ≈ 0.59–0.71), whereas N2O and CH4 fluxes were reproduced with moderate accuracy (R2 ≈ 0.37–0.55). Models using RS-FMIs performed similarly to those using well-compiled in situ management records, supporting the ability of RS-derived vegetation and management indicators to represent management effects. LE variability was primarily energy-driven and dominated by meteorological conditions, whereas vegetation dynamics and RS-FMIs played stronger roles in shaping NEE, N2O, and CH4 variability. These results demonstrate that RS-FMIs offer new opportunities to reconstruct management information and improve the representation of management effects in agroecosystem flux modeling.

Accurate estimation of Gross Primary Productivity (GPP) for European winter wheat is critical for assessing regional food security and understanding land-atmosphere carbon exchange. Light Use Efficiency (LUE) models are widely applied in natural ecosystems, but their performance in dynamic agricultural landscapes, particularly for key crops like winter wheat, remains underexplored. To bridge this gap, we developed IB-WSE-LUE (INRAE-BORDEAUX-water stress enhanced-light use efficiency), a novel GPP model specifically tailored for winter wheat. This model leverages high-resolution Sentinel-2 satellite data and comprehensively integrates key environmental stress factors, enabling GPP simulation at an unprecedented 10-meter spatial resolution. We compared IB-WSE-LUE against thirteen established GPP models, using both tower-based meteorological data and the ERA5 reanalysis dataset (the latter ensuring broader applicability across large scales without reliance on extensive in-situ measurements). Validation demonstrated IB-WSE-LUE's superior performance, achieving average R2 improvements of 11.9% (with tower data) and 8.8% (with ERA5 dataset) in daily GPP simulations for European winter wheat. Furthermore, IB-WSE-LUE more accurately captured spatial, seasonal, and interannual GPP variations and significantly reduced the common underestimation at high GPP levels observed in other models. Its robust performance extended to drought and high-temperature conditions, demonstrating that water stress exerts a stronger influence on winter wheat GPP than temperature stress, a feature accurately captured by our model. This study provides a robust, high-resolution, and spatially transferable framework for accurately monitoring and predicting winter wheat GPP across large agricultural regions, offering key insights for food security assessments and improved agricultural land management in a changing climate.

Monitored seabird populations have declined by up to 70% worldwide since the 1950s. Yet, data on long-term seabird population dynamics prior to the anthropogenic era are largely unknown. This limits our ability to understand future population trajectories, particularly in the Southern Ocean, where seabirds are facing multiple environmental threats. Here, we use mercury (Hg) derived from seabird guano in peatland catchments as a tracer of colony population sizes on sub-Antarctic Bird Island (South Georgia). Peat Hg flux and isotope signature results show that the first sustained seabird colonies after deglaciation were established on the island between 6800 and 6100 years ago, predating evidence for colonization on other sub-Antarctic islands by more than 1,000 y. The four subsequent periods with large local seabird populations occurred during phases of less intense Southern Hemisphere westerly winds. Our study unveils significant and repeated millennial-scale shifts in seabird abundance in response to natural climate changes, implying that the present-day increase in westerly wind intensity may lead to further declines in seabird populations in the Southern Ocean.

As climate change leads to more frequent droughts, understanding forest ecosystem health becomes increasingly critical. Monitoring forest canopy water content provides valuable insights into their resilience to these stressors. Space-based optical vegetation indices like the normalized difference water index (NDWI) are often used to monitor the water content over more extended time periods in large areas. However, the top-of-canopy view of satellites limits the sensitivity as they neglect the lower canopy and understory vegetation. This study explores the seasonal correspondence between the NDWI retrieved from Sentinel-2 satellite data and in situ measured vegetation optical depth (VOD). We use a unique time series of concurrent and complementary measurements acquired in two contrasting forest ecosystems (i.e., an evergreen coniferous and a deciduous broadleaf forest) spanning four seasons. VOD is calculated from global navigation satellite system (GNSS) data measured with one receiver antenna above and one below the canopy, assessing the full vertical extent of the forest canopy. In addition, we used the Sentinel-2 derived enhanced vegetation index (EVI), eddy flux based evapotranspiration (ET) estimates, and measurements of soil moisture, air temperature, precipitation, and shortwave incoming radiation to facilitate our interpretation. Our results showed a large seasonal variation in VOD and NDWI in the deciduous forest, a pattern that coincided with a large variation in biomass, as expected and indicated by the EVI. We saw indications that a short-term summer drought in 2022 affected VOD and ET but not the NDWI in the deciduous forest. In contrast, in the evergreen forest, we found a pronounced seasonality of canopy water content only for ET, while VOD and NDWI followed different trajectories. We conclude that the satellite-based NDWI tended to saturate at higher levels of canopy water content. VOD showed a sensitivity to changing canopy water content, as indicated by ET and soil moisture dynamics, as well as to changing canopy biomass, as suggested by varying EVI. These initial exploratory insights into the sensitivity of VOD could stimulate discussions within the community and potentially help optimize the sampling design of future VOD networks.

Abstract. Agriculture is the dominant source of anthropogenic nitrous oxide (N2O), a potent greenhouse gas with a high global warming potential. In Switzerland, substantial changes in fertiliser use alongside climatic conditions have occurred over the past four decades, yet the relative contributions of management practices versus environmental change to long-term N2O emission trends remain incompletely understood. Here, we applied the biogeochemical model DayCent at 1 km resolution across Switzerland, integrating spatially explicit datasets on climate, soil properties and agricultural management, to quantify N2O emissions for the period 1981–2020 from croplands and grasslands and attribute emission changes to management versus climate drivers. Simulated national N2O emissions from agricultural soils declined by roughly 5 % from 4.0 to 3.8 kt N yr⁻¹ between the 1980s and 2010s, primarily due to a 25 % reduction in N fertiliser use. Our attribution simulations suggested that under real climate conditions, such a decrease in fertiliser N inputs (–25 %) over the period studied lowered emissions by 15.2 % in croplands and by 12.0 % in grasslands (including permanent meadows and pastures, and high alpine summer pastures). However, compared to a control scenario (in the absence of climate change), rising temperatures over the past 40 years offset these gains, increasing emissions by 5.7 % in croplands and 13.6 % in grasslands. These results show that warming-induced N2O emissions partially negate mitigation from improved fertiliser management, highlighting the need for integrated agricultural N2O mitigation strategies that are resilient to future warming.

Non-rainfall water (NRW, mainly dew and fog) and night-time evapotranspiration (ETnight) are opposite phenomena which induce water gain and water loss of ecosystems, respectively. However, how NRW inputs and ETnight vary across spatial scales, and what drives their flux magnitude is less clear. In this study, we combined highly accurate micro-lysimeters with environmental measurements to investigate the spatial variability of NRW inputs and ETnight at nine grasslands as well as the most important drivers of their flux magnitude. Further, we explored the influence of NRW inputs and ETnight on net ecosystem CO2 exchange in the morning hours. Our results showed that changes in NRW inputs and ETnight were independent of elevation, but strongly affected by terrain. Moreover, NRW inputs and ETnight were controlled by different environmental drivers, with NRW inputs mainly driven by air temperature changes and event duration, while ETnight was mainly driven by dew point depression, soil moisture, and wind speed. Net ecosystem exchange in the early morning hours did not benefit from NRW inputs during the previous night. Our study revealed that the relevance of NRW inputs for temperate grasslands was low, but increasing ETnight losses due to climate change will pose additional challenges to grasslands in the future.

Our understanding of forests as methane (CH4) and nitrous oxide (N2O) sinks or sources remains limited, contributing to large uncertainties in terrestrial greenhouse gas (GHG) budgets. We investigated the CH4 and N2O exchange in a subalpine spruce forest in Davos (Switzerland) at multiple scales over seven years. Measurements included forest-floor fluxes with automatic chambers, GHG concentrations along a vertical canopy profile, and eddy covariance (EC) fluxes below and above the canopy. The forest floor was a small net CH4 sink (-0.5 + 0.05 g CH4-C m-2 yr-1; mean + standard deviation), while the forest was a small net CH4 source (0.54+0.22 g CH4-C m-2 yr-1). CH4 concentrations near the forest floor were low, increased with height, and stayed relatively constant within and above the forest canopy (10 to 35 m). While supporting the observed forest-floor sink, the profiles could not explain the discrepancy to the ecosystem CH4 budget. Forest-floor CH4 fluxes measured by chambers and below-canopy EC showed comparable magnitudes and seasonal dynamics, driven by snow depth, soil temperature, soil moisture, and below-canopy photosynthetic photon flux density. These findings suggest a coupling between above-ground CO2 assimilation and below-ground CH4 dynamics, possibly mediated by plant-soil interactions. Above-canopy N2O fluxes were negligible, with annual net ecosystem N2O budgets close to zero (-0.012 to 0.035 g N2O-N m-2 yr-1). Considering the global warming potentials of CO2, CH4 and N2O over a 100-year period, the subalpine spruce forest remained a net GHG sink, though CH4 and N2O emissions offset its sink strength by 3-12%.

With ongoing climate change, effective science communication has become increasingly important. Anthropogenic climate change, driven by excessive greenhouse gas emissions ‒ primarily CO₂ ‒ requires innovative solutions for mitigation. Among those, nature-based solutions have gained significant attention to offset some of the anthropogenic CO₂ emissions. One of the best available methods to study land-atmosphere CO₂ exchange, i.e., CO 2 fluxes, is the eddy covariance (EC) technique, which results in continuous long-term time series of half-hourly CO 2 fluxes. While such data are extensively used in scientific research, for instance to evaluate the impacts of climate change and land management on ecosystems, effective communication of these findings to the general public remains a challenge. Global and regional EC networks, such as FLUXNET and ICOS, hold a great potential to engage with lay persons to increase public understanding of climate change effects on ecosystems as well as of feedbacks ecosystems have on the atmosphere. Within the Swiss FluxNet, the Swiss national EC network, CO₂ fluxes have been measured across different land use types ‒ grasslands, forests, and croplands for many years and decades. Since measurements began at one site in 1997, five permanent measuring sites have been added since then. Now, the Swiss FluxNet has collected a total of 129 years of CO₂ flux data from these six long-term sites, and it continues to grow steadily. Such a research database also faces the challenges of an effective communication to the public. Therefore, we initiated an interdisciplinary collaboration between science and visual art. The goal was to create a visually engaging and meaningful representation of the flux data, using accessible and intuitive colours and an attractive design, thus simplifying scientific data without compromising content. The collaboration resulted in a figure that showcases annual CO₂ budgets across multiple sites with a uniform colour scale, highlighting year-to-year differences in ecosystem performance as well as typical characteristics of the respective ecosystem (Fig. 1). While the scientists provide flux data and information about the sites, the artist engages with the historical, artistic, and cultural significance of colours, and both partners address accessibility for colour-blind individuals. This approach involves a critical examination of how natural scenes are represented in artworks across diverse cultural contexts, how their corresponding colour scales look like and can be used, with insights from this research applied to the field of data visualization. First outputs of the project were presented at the Sustainable University Day at the University of Zurich and ETH Zurich in November 2024. The presented work exhibited the background research and the rationale behind the choice of colours (Fig. 2), and the scientific concepts of ecosystem CO₂ exchange as well as the final visual representation of the CO 2 fluxes (Fig. 1). The public, including individuals from diverse fields such as marketing, waste management, and sustainability, responded very positively, acknowledging the value of the collaboration and the clarity of the communication. This experience stresses the importance of interdisciplinary collaboration between science and art, showcasing how we can bridge the gap between complex scientific data and public understanding.

Many different techniques are available to observe and quantify ecosystem functions and services provided by grasslands. Measurements need to be analysed and integrated to translate data into management recommendations for adoption in sustainable grassland management. Here, we provide an overview of techniques available to collect data about grasslands. Different spatio-temporal scales require different modes of data collection to capture grassland dynamics. Examples are provided, e.g., how high temporal resolution measurements of greenhouse gas exchange are used to quantify soil carbon sequestration and detect trade-offs between C sequestration and N2O losses; how image analyses help in restoration projects; how remote sensing is used to improve grassland farming; and how models help predicting biomass production and long-term carbon sequestration rates. The benefits of FAIR (Findability, Accessibility, Interoperability, and Reusability) data sharing as well as strengths and weaknesses of techniques are addressed, management options outlined and gaps in knowledge identified.

Methane (CH4) and nitrous oxide (N2O) substantially contribute to global greenhouse gas (GHG) emissions together with carbon dioxide (CO2). To understand their impact on future climate change, prioritizing the study of CH4 and N2O fluxes becomes critical. Forest ecosystems, primarily investigated for CO2 exchange, are less explored concerning their exchange of CH4 and N2O. Forests are known to be sinks for CH4, while their role in N2O fluxes varies, acting as either sources or sinks. However, comprehensive studies that concurrently examine CH4 and N2O fluxes in forests, particularly over extended periods and at high elevation, remain scarce. At high altitudes, measuring GHG fluxes with chambers during snowy periods is challenging, leading to a lack of winter flux data which are crucial for understanding flux dynamics related to freeze-thaw cycles and snow patterns. This study addresses this gap by investigating long-term CH4 and N2O fluxes in a subalpine Norway spruce forest (Davos, CH-Dav, ICOS Class 1 Ecosystem station, Switzerland), encompassing both soil and canopy interactions with the atmosphere.Over five years (2017, 2020-2023 for CH4; 2017, 2020 for N2O), we employed automatic chambers to measure forest-floor fluxes, complemented by below-canopy eddy covariance CH4 flux measurements starting from May 2023, as well as static chamber measurements in 2023. Our research objectives were to 1) characterize the magnitude and seasonal dynamics of CH4 and N2O forest-floor fluxes, and 2) compare CH4 fluxes using chamber and eddy covariance techniques to better understand the interaction of soil and vegetation with the atmosphere.We hypothesized that the forest floor primarily acts as a net sink for CH4, with soil temperature and snow dynamics being important drivers due to their impact on microbial activity and diffusion rates between soil and atmosphere. Given the low nitrogen availability at the study site, we anticipated very low N2O emissions. Additionally, we hypothesized that comparing CH4 fluxes from chambers and eddy covariance would reveal small differences in their magnitudes, attributable to the distinct measurement scales and scopes of these two techniques. Our results confirmed the forest floor as a consistent CH4 sink, exhibiting substantial short-term fluctuations driven predominantly by air temperature and snow cover. N2O fluxes were negligible over the two-year observation period. Our study contributes to a deeper understanding of how environmental drivers and seasonal dynamics influence CH4 and N2O fluxes in high-elevation forests.

Climate change is increasing frequency and intensity of droughts across Europe, with major consequences for forest ecosystems. Often soil and atmospheric droughts occur simultaneously, resulting in combined soil atmospheric drought (CSAD) events. Which effects such CSAD events have on forest CO2 fluxes is not clear. At the Lägeren site (CH-Lae), a mixed deciduous forest in Switzerland, we identified the three years with the lowest cumulative precipitation and the highest cumulative vapor pressure deficit (VPD) during the growing season (May – September), namely 2015, 2018 and 2022, since net ecosystem CO2 exchange (NEE) measurements started in 2005. We then determined the CSAD events, i.e., periods in which soil and atmospheric drought occurred simultaneously. Our objectives were to (1) quantify the impacts of CSAD events in 2015, 2018 and 2022 on CO2 fluxes against the long-term mean, (2) identify the environmental drivers of net ecosystem production (NEP) in 2015, 2018 and 2022 and forest floor respiration (Rff) in 2018 and 2022 compared to the long-term fluxes, (3) assess the temporal course of the effects of soil and atmospheric drought on NEP and Rff during the CSAD events against the long-term means. CO2 fluxes were measured continuously with the eddy covariance technique at two distinct locations at the CH-Lae forest: above the canopy at a height of 47 meters (from 2005 to 2022) and below the canopy at 1.5 meters (from 2018 to 2022). The drivers of NEP and Rff were determined with machine learning approaches, i.e., random forest conditional variable importance and Shapley Additive exPlenations (SHAP). We found a decrease in NEP of 35%, 38% and 41% during the CSAD events in 2015, 2018 and 2022 respectively compared to the mean 2005-2022, and a decrease of 16% and 41% in the Rff during the CSAD events in 2018 and 2022 compared to the mean 2019-2021. Light is usually the main driver of NEP during the growing season, as we found in 2015, 2018 and in the mean 2005-2022. While soil water content (SWC) was the main driver of NEP for the growing season in 2022, enhancing the key effect of soil drought in the 2022 growing season. The SHAP analysis revealed the negative impacts of high temperature, high VPD, and low SWC on NEP during all CSAD events, with low SWC and high VPD in 2022 having the larger impacts on NEP. Rff was mainly decreased by low SWC in 2018 and 2022. This led to a decrease in temperature sensitivity of Rff during CSAD events compared to the mean 2019-2021. With this study we assessed the impacts CSAD events on the CO2 fluxes of a mixed deciduous forest. Yet, the intensity, the timing, and the pre-conditions of CSAD events are crucial to explain ecosystem responses to such events. Furthermore, the increase in frequency and intensity of droughts and precipitation events with global warming call into question the predictability of forests capacity to store carbon, which is crucial for climate change mitigation through nature-based solutions.