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Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories - the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis - are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

While the eddy covariance (EC) technique is a well-established method for measuring water fluxes (i.e., evaporation or 'evapotranspiration’, ET), the measurement is susceptible to many uncertainties. One such issue is the potential underestimation of ET when relative humidity (RH) is high (>70%), due to low-pass filtering with some EC systems. Yet, this underestimation for different types of EC systems (e.g. open-path or closed-path sensors) has not been characterized for synthesis datasets such as the widely used FLUXNET2015 dataset. Here, we assess the RH-associated underestimation of latent heat fluxes (LE, or ET) from different EC systems for 163 sites in the FLUXNET2015 dataset. We found that the LE underestimation is most apparent during hours when RH is higher than 70%, predominantly observed at sites using closed-path EC systems, but the extent of the LE underestimation is highly site-specific. We then propose a machine learning based method to correct for this underestimation, and compare it to two energy balance closure based LE correction approaches (Bowen ratio correction, BRC, and attributing all errors to LE). Our correction increases LE by 189% for closed-path sites at high RH (>90%), while BRC increases LE by around 30% for all RH conditions. Additionally, we assess the influence of these corrections on ET-based transpiration (T) estimates using two different ET partitioning methods. Results show opposite responses (increasing vs. slightly decreasing T-to-ET ratios, T/ET) between the two methods when comparing T based on corrected and uncorrected LE. Overall, our results demonstrate the existence of a high RH bias in water fluxes in the FLUXNET2015 dataset and suggest that this bias is a pronounced source of uncertainty in ET measurements to be considered when estimating ecosystem T/ET and WUE.

The leaf economics spectrum1,2 and the global spectrum of plant forms and functions3 revealed fundamental axes of variation in plant traits, which represent different ecological strategies that are shaped by the evolutionary development of plant species2. Ecosystem functions depend on environmental conditions and the traits of species that comprise the ecological communities4. However, the axes of variation of ecosystem functions are largely unknown, which limits our understanding of how ecosystems respond as a whole to anthropogenic drivers, climate and environmental variability4,5. Here we derive a set of ecosystem functions6 from a dataset of surface gas exchange measurements across major terrestrial biomes. We find that most of the variability within ecosystem functions (71.8%) is captured by three key axes. The first axis reflects maximum ecosystem productivity and is mostly explained by vegetation structure. The second axis reflects ecosystem water-use strategies and is jointly explained by variation in vegetation height and climate. The third axis, which represents ecosystem carbon-use efficiency, features a gradient related to aridity, and is explained primarily by variation in vegetation structure. We show that two state-of-the-art land surface models reproduce the first and most important axis of ecosystem functions. However, the models tend to simulate more strongly correlated functions than those observed, which limits their ability to accurately predict the full range of responses to environmental changes in carbon, water and energy cycling in terrestrial ecosystems7,8.

We describe a new coordination activity and initial results for a global synthesis of eddy covariance CH4 flux measurements.

For the past decade, observations of carbonyl sulfide (OCS or COS) have been investigated as a proxy for carbon uptake by plants. OCS is destroyed by enzymes that interact with CO2 during photosynthesis, namely carbonic anhydrase (CA) and RuBisCO, where CA is the more important one. The majority of sources of OCS to the atmosphere are geographically separated from this large plant sink, whereas the sources and sinks of CO2 are co-located in ecosystems. The drawdown of OCS can therefore be related to the uptake of CO2 without the added complication of co-located emissions comparable in magnitude. Here we review the state of our understanding of the global OCS cycle and its applications to ecosystem carbon cycle science. OCS uptake is correlated well to plant carbon uptake, especially at the regional scale. OCS can be used in conjunction with other independent measures of ecosystem function, like solar-induced fluorescence and carbon and water isotope studies. More work needs to be done to generate global coverage for OCS observations and to link this powerful atmospheric tracer to systems where fundamental questions concerning the carbon and water cycle remain.

Light-use efficiency (LUE), which quantifies the plants' efficiency in utilizing solar radiation for photosynthetic carbon fixation, is an important factor for gross primary production estimation. Here we use satellite-based solar-induced chlorophyll fluorescence as a proxy for photosynthetically active radiation absorbed by chlorophyll (APARchl) and derive an estimation of the fraction of APARchl (fPARchl) from four remotely sensed vegetation indicators. By comparing maximum LUE estimated at different scales from 127 eddy flux sites, we found that the maximum daily LUE based on PAR absorption by canopy chlorophyll (εchlmax), unlike other expressions of LUE, tends to converge across biome types. The photosynthetic seasonality in tropical forests can also be tracked by the change of fPARchl, suggesting the corresponding (εchlmax) to have less seasonal variation. This spatio-temporal convergence of LUE derived from fPARchl can be used to build simple but robust gross primary production models and to better constrain process-based models.

Spatially and temporally continuous estimation of plant photosynthetic carbon fixation (or gross primary production, GPP) is crucial to our understanding of the global carbon cycle and the impact of climate change. Besides spatial, seasonal and interannual variations, GPP also exhibits strong diurnal variations. Satellite retrieved solar-induced chlorophyll fluorescence (SIF) provides a spatially continuous, but temporally discrete measurement of plant photosynthesis, and has the potential to be used to estimate GPP at global scale. However, it remains unclear whether the seasonal time series of SIF snapshots taken at a fixed time of the day can be used to infer daily total GPP variation at spatial and seasonal scales. In this study, we first used GPP estimates from 135 eddy covariance flux sites, covering a wide range of geographic locations and biome types, to investigate the relationship between the instantaneous GPP (GPPᵢₙₛₜ) and daily GPP (GPPdₐᵢₗy) on the seasonal course for different times of the day. Latitudinal and diurnal patterns were found to correspond to variations in photosynthetically active radiation (PAR) and light use efficiency (LUE), respectively. We then used the Soil-Canopy Observation Photosynthesis and Energy Balance (SCOPE) model and the FluxCom GPP product to investigate the instantaneous and daily SIF-GPP relationships at five flux tower sites along a latitudinal gradient and at a global scale for different biome types. The results showed that daily SIF had a stronger linear correlation with daily GPP than instantaneous SIF at the seasonal scale, with an instantaneous to daily SIF conversion factor following the latitudinal and seasonal pattern driven by PAR. Our study highlights the necessity to take the latitudinal and diurnal factors into consideration for SIF-GPP relationship analyses or for physiological phenology analyses based on SIF.

Abstract. For the past decade, observations of carbonyl sulfide (OCS or COS) have been investigated as a proxy for carbon uptake by plants. OCS is destroyed by enzymes that interact with CO2 during photosynthesis, namely carbonic anhydrase (CA) and RuBisCO, where CA is the more important. The majority of sources of OCS to the atmosphere are geographically separated from this large plant sink, whereas the sources and sinks of CO2 are co-located in ecosystems. The drawdown of OCS can therefore be related to the uptake of CO2 without the added complication of co-located emissions comparable in magnitude. Here we review the state of our understanding of the global OCS cycle and its applications to ecosystem carbon cycle science. OCS uptake is correlated well to plant carbon uptake, especially at the regional scale. OCS can be used in conjunction with other independent measures of ecosystem function, like solar-induced fluorescence and carbon and water isotope studies. More work needs to be done to generate global coverage for OCS observations and to link this powerful atmospheric tracer to systems where fundamental questions concerning the carbon and water cycle remain.

Current climate models disagree on how much carbon dioxide land ecosystems take up for photosynthesis. Tracking the stronger carbonyl sulfide signal could help.

The anthropogenic and biogenic contributions of isoprene, monoterpenes, sesquiterpenes and methanol in an urban area were estimated based on direct eddy covariance flux observations during four campaigns between 2018 and 2021. While these compounds are typically thought to be dominated by biogenic sources on regional and global scales, the role of potentially significant anthropogenic emissions in urban areas has been recently debated. Typical fluxes of isoprene, monoterpenes and sesquiterpenes were on the order of 0.07 ± 0.02, 0.09 and 0.003 nmol m -2 s -1 during spring. During summer, emission fluxes of isoprene, monoterpenes and sesquiterpenes were higher on the order of 0.85 ± 0.09, 0.11 and 0.004 nmol m -2 s -1. It was found that the contribution of the anthropogenic part is strongly seasonally dependent. For isoprene, the anthropogenic fraction can be as high as 64 % in spring but is typically very low < 18 % during the summer season. For monoterpenes, the anthropogenic fraction was estimated to be between 43 % in spring and less than 20 % in summer. With values of 2.8 nmol m -2 s -1 in spring and 3.2 nmol m -2 s -1 in summer, methanol did not exhibit a significant seasonal variation of observed surface fluxes. However, there was a difference in emissions between weekdays and weekends (about 2.3 times higher on weekdays in spring). This suggests that methanol emissions are likely influenced by anthropogenic activities during all seasons. [ABSTRACT FROM AUTHOR]

Lakes in the Alpine region are recognized as critical methane (CH4) emitters, but a robust characterization of the magnitude and variability of CH4 fluxes is missing. We developed a mobile platform for CH4 eddy covariance (EC) flux measurements to tackle this gap. The mobile system was deployed at nine lakes across a latitudinal transect in the Alps and validated by comparing the measured fluxes with fixed on‐shore EC station and to chamber and boundary layer flux estimates. Our approach was shown to be well suited to capture different CH4 emission pathways and to integrate the within lake variability, therefore, overcoming the limitations of other methods (e.g., boundary layer method). Additionally, this mobile system offers a tool to characterize inter‐lake variability of fluxes with consistent measurements. Methane fluxes were explained by dissolved nitrogen, total phosphorus, dissolved oxygen, seston and lake size. The highest fluxes and most substantial seasonal variability were found in a shallow low‐altitude lake in the Southern Alps. We suggest that characterizing the intra‐lake emission heterogeneity and consistent measurements for a better understanding of inter‐lake emission differences is fundamental for a solid estimate of freshwater CH4 budgets. Plain Language Summary: Our paper focuses on lakes in the Alpine region that release a greenhouse gas called methane (CH4) which is relevant for global warming. Even though we know these lakes emit methane, there is still the need to understand how much is released and how it changes over time. To address this, we built a special mobile tool to measure methane emissions using a method called eddy covariance. Eddy covariance is used to measure the exchange of gases, like methane, between the Earth's surface and the atmosphere by tracking the local changes in wind speed and gas concentration. We tested our mobile tool at nine different lakes across the eastern Alps and compared our measurements with data from common methods like estimating methane from the water close to the lake's surface. We found that the presence of nutrients, the lake's size, and the organic material in the water were associated with how much methane is released. Our mobile tool also helped us describe the variability of methane emissions among different parts of the same lake. This information is crucial because it helps us figure out how much methane these lakes are releasing and better understand the differences between lakes. Key Points: We developed and validated a mobile eddy covariance platform for capturing CH4 fluxes across lakes in the Alpine region for 2 yearsCH4 emissions varied substantially within and among the studied lakes which need consideration for accurate emission assessmentsStatistical models with a few in situ physicochemical and biological variables could describe the observed CH4 fluxes [ABSTRACT FROM AUTHOR]

The presence of a seasonal snowpack decisively modulates the albedo of terrestrial land surfaces. Global warming-driven decreases in the duration of the seasonal snow cover are thus expected to lower annual albedo, result in a positive radiative forcing and thus represent a positive feedback to climate change. Here we quantify future (up to the year 2100) scenarios of albedo change and the associated radiative forcing for Austria using a machine learning approach which leverages satellite-derived albedo data and future scenarios of snow depth. Albedo was calculated from the MODIS MCD43A1 v006 BRDF/albedo product for the period 2002–2019. Snow depth was taken from a novel dataset for Austria (FuSE-AT) covering the period 1951–2100. A machine-learning model (using LightGBM) was then trained to predict albedo separately for each land cover type (MODIS MCD12Q1 v006) using snow depth, days since last snowfall, as well as several predictors related to plant canopy structure (leaf area index, canopy height) and topography (latitude, longitude, elevation above sea level, inclination, exposition). LAI turned out to be an important predictor in simulating albedo in both snow free and snow covered points in time. Time since last snowfall, as a surrogate for snow aging, was more important for short land cover types than for forests. The correlation coefficients of the trained models varied widely across the different land cover types, ranging from 0.70 to 0.94. In 5 out of the 6 scenarios used, a significant decline of albedo could be observed. The cumulative time-dependent emission equivalent resulting from the albedo changes between 2020–2100 corresponds to 0.25–1 (RCP 2.6), 0.8–2.25 (RCP 4.5) or 1–5 (RCP 8.5) times the annual CO2-equivalent emissions of Austria for the year 2021. [ABSTRACT FROM AUTHOR]

Reliable and fine resolution estimates of surface net-radiation are required for estimating latent and sensible heat fluxes between the land surface and the atmosphere. However, currently, fine resolution estimates of net-radiation are not available and consequently it is challenging to develop multi-year estimates of evapotranspiration at scales that can capture land surface heterogeneity and are relevant for policy and decision-making. We developed and evaluated a global net-radiation product at 5 km and 8-day resolution by combining mutually consistent atmosphere and land data from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra. Comparison with net-radiation measurements from 154 globally distributed sites (414 site-years) from the FLUXNET and Surface Radiation budget network (SURFRAD) showed that the net-radiation product agreed well with measurements across seasons and climate types in the extratropics (Wilmott's index ranged from 0.74 for boreal to 0.63 for Mediterranean sites). Mean absolute deviation between the MODIS and measured net-radiation ranged from 38.0 ± 1.8 W.m-2 in boreal to 72.0 ± 4.1 W.m-2 in the tropical climates. The mean bias was small and constituted only 11%, 0.7%, 8.4%, 4.2%, 13.3%, and 5.4% of the mean absolute error in daytime net-radiation in boreal, Mediterranean, temperate-continental, temperate, semi-arid, and tropical climate, respectively. To assess the accuracy of the broader spatiotemporal patterns, we upscaled error-quantified MODIS net-radiation and compared it with the net-radiation estimates from the coarse spatial (1° x 1°) but high temporal resolution gridded net-radiation product from the Clouds and Earth's Radiant Energy System (CERES). Our estimates agreed closely with the net-radiation estimates from the CERES. Difference between the two was less than 10W.m-22 in 94% of the total land area. MODIS net-radiation product will be a valuable resource for the science community studying turbulent fluxes and energy budget at the Earth's surface.

Mapping in-situ eddy covariance measurements of terrestrial land-atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO 2 net ecosystem exchange (NEE), gross primary productivity (GPP) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ETT), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at -5.75 ± 0.33 Pg C ⋅ yr -1 for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C ⋅ yr -1 for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7x10³ ± 0.9x10³ km 3 globally for the years 2001–2020, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57 % of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates. [ABSTRACT FROM AUTHOR]

Mapping in-situ eddy covariance measurements of terrestrial land-atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented up-scaling framework, FLUXCOM-X. The X-BASE products comprise of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GP P) as well as evapotranspiration (ET) and, for the first time, a novel fully data-driven global transpiration product (ETT ), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at -5.75 ± 0.33 P g C · yr−1 for the period 2001-2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site-years resulting in a wider coverage of bio-climatic conditions. However, X-BASE global net ecosystem exchange shows a very low inter-annual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 P gC · yr−1 for the same period, X-BASE GP P is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7x103 ± 0.9x103 km3 globally for the years 2001-2020, but exceeds precipitation in many dry areas likely indicating overestimation in these regions. On average 57% of evapotranspiration are estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous up-scaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy-covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates. [ABSTRACT FROM AUTHOR]

The anthropogenic and biogenic contributions of isoprene, monoterpenes, sesquiterpenes and methanol in an urban area were estimated based on direct eddy covariance flux observations during four campaigns between 2018 and 2021. While these compounds are typically thought to be dominated by biogenic sources on regional and global scales, the role of potentially significant anthropogenic emissions in urban areas has been recently debated. Typical fluxes of isoprene, monoterpenes and sesquiterpenes were on the order of 0.09 nmol m−2 s−1, 0.09 nmol m−2 s−1 and 0.003 nmol m−2 s−1 during spring. During summer, emission fluxes of isoprene, monoterpenes and sesquiterpenes were higher on the order of 0.85 nmol m−2 s−1, 0.11 nmol m−2 s−1, 0.004 nmol m−2 s−1. It was found that the contribution of the anthropogenic part is strongly seasonally dependent. For isoprene the anthropogenic fraction can be as high as 64 % in spring, but is typically very low < 18 % during the summer season. For monoterpenes the anthropogenic fraction was estimated between 43 % in spring and less than 20 % in summer. With values of 2.8 nmol m−2 s−1 in spring and 3.2 nmol m−2 s−1 in summer, methanol did not exhibit a significant seasonal variation of observed surface fluxes. However, there was a difference in emissions between weekdays and weekends (about 2.3 times higher on weekdays in spring). This suggests that methanol emissions are likely influenced by anthropogenic activities during all seasons. [ABSTRACT FROM AUTHOR]

The adverse effects of heatwaves on viticulture could be, at least partly, mitigated by generous soil water availability. As climate change will also likely reduce irrigation water, knowing to which extent soil water availability could be decreased under the heatwaves without compromising plant performances would be important. In this pot experiment, we differentiated soil water availability by compensating 100% (T100), 70% (T70), 40% (T40) and 10% (T10) of vine transpiration. Grapevines (cv. Sauvignon) were then subjected to a 11-day heatwave (Tmax 40 °C) and to a post-heat stress recovery phase. Soil water potential between -0.05 to -0.2 MPa, respectively, in T100 and T70 enabled the plants to maintain high net CO2 assimilation (Pn), stomatal conductance (gs), and leaf transpiration (Eleaf) which kept the leaf temperature (Tleaf) below the ambient temperature and promoted the plant growth. During the heatwave, T100 and T70 vines decreased their photochemical yield and dissipated the excess energy via regulated non-photochemical heat dissipation, and resumed their photochemical activities upon removing the heat stress. Further reduction in soil water potential to -0.4 and and -1.2 MPa in T40 and T10, respectively, decreased Pn and gs and restrained Eleaf, causing a significant increase in Tleaf during the heatwave, and limited the plant recovery after the heat stress. Nonetheless, the maximum efficiency of PSII (Fv/Fm) showed quite high resistance to heat stress in all treatments. These findings suggest that decreasing soil water availability to reach soil water potential levels close to -0.2 MPa implies higher efficiency in using water resources during a heat wave without limiting plant growth. [ABSTRACT FROM AUTHOR]