Assessing ecosystem functioning is crucial for managing and conserving ecosystems and their services. Numerous ways to evaluate ecosystem functioning have been developed, using species traits, such as Plant Functional Types (PFTs), flux measurements with the Eddy Covariance (EC) technique, and remote sensing techniques. We propose that the spatial heterogeneity in ecosystem functioning at a regional scale can be assessed and monitored using satellite-derived Ecosystem Functional Types (EFTs): groups of ecosystems or patches of the land surface that share similar dynamics of matter and energy exchanges. We hypothesize that, as observed for PFTs, different EFTs should have distinct patterns and magnitudes of Net Ecosystem Exchange (NEE) of carbon dioxide measured using the EC technique. We derived EFTs from 2001-2014 time-series of satellite images of the Enhanced Vegetation Index (EVI) and compared them with NEE measurements (derived from in situ field observations using the EC technique) across 50 European sites. Our results show that distinct EFTs classes display significantly different dynamics and magnitudes of NEE and that EFTs perform marginally better than PFTs in explaining NEE regional patterns. Land-cover maps based on PFTs are difficult to update on an annual basis and are not sensitive to changes in ecosystem performance (e.g., droughts or pests) that do involve short-term changes in PFT composition. In contrast, satellite-derived EFTs are sensitive to short-term changes in ecosystem performance. Satellite-derived EFTs are an ecosystem functional classification built from satellite observations that allow the identification of homogeneous land patches based on ecosystem functions, e.g., ecosystem net productivity measured on the ground as NEE. Satellite-derived EFTs can be recalculated annually, providing a straightforward way to assess and monitor interannual changes in ecosystem functioning and functional diversity.

Flux-monitoring networks nowadays integrate several stations, with more than 20 years of records. However, many questions are still open, and this work focused on the following two: (i) what is known about carbon and energy exchanges and efficiencies of evergreen conifer forests in the hot and dry Mediterranean climate zone, and (ii) what can be learned by combining information derived from flux and tree ring measurements in this context? These issues are addressed in this study using micrometeorological and dendrochronological measurements from a Mediterranean pine forest, San Rossore, in central Italy. The forest's flux time series exceeds 20 years, merging two consecutive (not overlapping) time series of flux measurements above two evergreen conifer species: Pinus pinaster Aiton, 1789 (maritime pine) and Pinus pinea L., 1753 (stone pine). Despite both conifer species having shown high rates of photosynthesis, substantial differences have been found between them in terms of annual productivity, hydrological balance and efficiencies of carbon and water use. The more droughttolerant Pinus pinea L. has been less productive than the drought-avoiding Pinus pinaster Aiton: interannual net ecosystem productivity averages and standard errors have been estimated to be 441 +/- 46 gC m-2 y-1 and 224 +/- 35 gC m-2 y-1 for Pinus pinaster Aiton and Pinus pinea L., respectively, and the latter has been found to consume more water as a consequence of the sustained transpiration process during prolonged summer droughts. Annual carbon accumulation, based on eddy covariance flux measurements, and annual wood increments, based on tree ring widths, for the two species are in overall alignment in terms of absolute values; however, a weak correlation suggests the need for more detailed analyses to gain more information about the carbon dynamics of the ecosystem, because the two approaches do not quantify exactly the same processes.

A substantial portion of tropospheric O 3 dry deposition occurs after diffusion of O 3 through plant stomata. Simulating stomatal uptake of O 3 in 3D atmospheric chemistry models is important in the face of increasing drought induced declines in stomatal conductance and enhanced ambient O 3 . Here, we present a comparison of the stomatal component of O 3 dry deposition eg s from chemical transport models and estimates of eg s from observed CO 2 , latent heat, and O 3 flux. The dry deposition schemes were configured as single-point models forced with data collected at flux towers. We conducted sensitivity analyses to study the impact of model parameters that control stomatal moisture stress on modeled eg s . Examining six sites around the northern hemisphere, we find that the seasonality of observed flux-based eg s agrees with the seasonality of simulated eg s at times during the growing season with disagreements occurring during the later part of the growing season at some sites. We find that modeled water stress effects are too strong in a temperate-boreal transition forest. Some single-point models overestimate summertime eg s in a seasonally water-limited Mediterranean shrubland. At all sites examined, modeled eg s was sensitive to parameters that control the vapor pressure deficit stress. At specific sites that experienced substantial declines in soil moisture, the simulation of eg s was highly sensitive to parameters that control the soil moisture stress. The findings demonstrate the challenges in accurately representing the effects of moisture stress on the stomatal sink of O 3 during observed increases in dryness due to ecosystem specific plant-resource interactions.

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 (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 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.

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 upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO2 net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ETT), at high spatial (0.05 degrees) 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 bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual 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 74.7x10(3) +/- 0.9x10(3) 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 is 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 upscaling 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.

A primary sink of air pollutants and their precursors is dry deposition. Dry deposition estimates differ across chemical transport models, yet an understanding of the model spread is incomplete. Here, we introduce Activity 2 of the Air Quality Model Evaluation International Initiative Phase 4 (AQMEII4). We examine 18 dry deposition schemes from regional and global chemical transport models as well as standalone models used for impact assessments or process understanding. We configure the schemes as single-point models at eight Northern Hemisphere locations with observed ozone fluxes. Single-point models are driven by a common set of site-specific meteorological and environmental conditions. Five of eight sites have at least 3 years and up to 12 years of ozone fluxes. The interquartile range across models in multiyear mean ozone deposition velocities ranges from a factor of 1.2 to 1.9 annually across sites and tends to be highest during winter compared with summer. No model is within 50 % of observed multiyear averages across all sites and seasons, but some models perform well for some sites and seasons. For the first time, we demonstrate how contributions from depositional pathways vary across models. Models can disagree with respect to relative contributions from the pathways, even when they predict similar deposition velocities, or agree with respect to the relative contributions but predict different deposition velocities. Both stomatal and nonstomatal uptake contribute to the large model spread across sites. Our findings are the beginning of results from AQMEII4 Activity 2, which brings scientists who model air quality and dry deposition together with scientists who measure ozone fluxes to evaluate and improve dry deposition schemes in the chemical transport models used for research, planning, and regulatory purposes.

Microclimate research gained renewed interest over the last decade and its importance for many ecological processes is increasingly being recognized. Consequently, the call for high-resolution microclimatic temperature grids across broad spatial extents is becoming more pressing to improve ecological models. Here, we provide a new set of open-access bioclimatic variables for microclimate temperatures of European forests at 25 × 25 m2 resolution.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

Research in global change ecology relies heavily on global climatic grids derived from estimates of air temperature in open areas at around 2 m above the ground. These climatic grids do not reflect conditions below vegetation canopies and near the ground surface, where critical ecosystem functions occur and most terrestrial species reside. Here, we provide global maps of soil temperature and bioclimatic variables at a 1‐km 2 resolution for 0–5 and 5–15 cm soil depth. These maps were created by calculating the difference (i.e. offset) between in situ soil temperature measurements, based on time series from over 1200 1‐km 2 pixels (summarized from 8519 unique temperature sensors) across all the world's major terrestrial biomes, and coarse‐grained air temperature estimates from ERA5‐Land (an atmospheric reanalysis by the European Centre for Medium‐Range Weather Forecasts). We show that mean annual soil temperature differs markedly from the corresponding gridded air temperature, by up to 10°C (mean = 3.0 ± 2.1°C), with substantial variation across biomes and seasons. Over the year, soils in cold and/or dry biomes are substantially warmer (+3.6 ± 2.3°C) than gridded air temperature, whereas soils in warm and humid environments are on average slightly cooler (−0.7 ± 2.3°C). The observed substantial and biome‐specific offsets emphasize that the projected impacts of climate and climate change on near‐surface biodiversity and ecosystem functioning are inaccurately assessed when air rather than soil temperature is used, especially in cold environments. The global soil‐related bioclimatic variables provided here are an important step forward for any application in ecology and related disciplines. Nevertheless, we highlight the need to fill remaining geographic gaps by collecting more in situ measurements of microclimate conditions to further enhance the spatiotemporal resolution of global soil temperature products for ecological applications.

Dry deposition is an important sink of tropospheric ozone that affects surface concentrations and impacts crop yields, the land carbon sink, and the terrestrial water cycle. Dry deposition pathways include plant uptake via stomata and non-stomatal removal by soils, leaf surfaces, and chemical reactions. Observational studies indicate that ozone deposition exhibits substantial temporal variability that is not reproduced by atmospheric chemistry models due to a simplified representation of vegetation uptake processes in these models. In this study, we explore the importance of stomatal and non-stomatal uptake processes in driving ozone dry deposition variability on diurnal to seasonal timescales. Specifically, we compare two land surface ozone uptake parameterizations – a commonly applied big leaf parameterization (W89; Wesely, 1989) and a multi-layer model (MLC-CHEM) constrained with observations – to multi-year ozone flux observations at two European measurement sites (Ispra, Italy, and Hyytiälä, Finland). We find that W89 cannot reproduce the diurnal cycle in ozone deposition due to a misrepresentation of stomatal and non-stomatal sinks at our two study sites, while MLC-CHEM accurately reproduces the different sink pathways. Evaluation of non-stomatal uptake further corroborates the previously found important roles of wet leaf uptake in the morning under humid conditions and soil uptake during warm conditions. The misrepresentation of stomatal versus non-stomatal uptake in W89 results in an overestimation of growing season cumulative ozone uptake (CUO), a metric for assessments of vegetation ozone damage, by 18 % (Ispra) and 28 % (Hyytiälä), while MLC-CHEM reproduces CUO within 7 % of the observation-inferred values. Our results indicate the need to accurately describe the partitioning of the ozone atmosphere–biosphere flux over the in-canopy stomatal and non-stomatal loss pathways to provide more confidence in atmospheric chemistry model simulations of surface ozone mixing ratios and deposition fluxes for large-scale vegetation ozone impact assessments.

A Correction to this paper has been published: https://doi.org/10.1038/s41597-021-00851-9.

Ecosystem respiration is a major component of the global terrestrial carbon cycle and is strongly influenced by temperature. The global extent of the temperature-ecosystem respiration relationship, however, has not been fully explored. Here, we test linear and threshold models of ecosystem respiration across 210 globally distributed eddy covariance sites over an extensive temperature range. We find thresholds to the global temperature-ecosystem respiration relationship at high and low air temperatures and mid soil temperatures, which represent transitions in the temperature dependence and sensitivity of ecosystem respiration. Annual ecosystem respiration rates show a markedly reduced temperature dependence and sensitivity compared to half-hourly rates, and a single mid-temperature threshold for both air and soil temperature. Our study indicates a distinction in the influence of environmental factors, including temperature, on ecosystem respiration between latitudinal and climate gradients at short (half-hourly) and long (annual) timescales. Such climatological differences in the temperature sensitivity of ecosystem respiration have important consequences for the terrestrial net carbon sink under ongoing climate change.

Ecological research heavily relies on coarse‐gridded climate data based on standardized temperature measurements recorded at 2 m height in open landscapes. However, many organisms experience environmental conditions that differ substantially from those captured by these macroclimatic (i.e. free air) temperature grids. In forests, the tree canopy functions as a thermal insulator and buffers sub‐canopy microclimatic conditions, thereby affecting biological and ecological processes. To improve the assessment of climatic conditions and climate‐change‐related impacts on forest‐floor biodiversity and functioning, high‐resolution temperature grids reflecting forest microclimates are thus urgently needed. Combining more than 1200 time series of in situ near‐surface forest temperature with topographical, biological and macroclimatic variables in a machine learning model, we predicted the mean monthly offset between sub‐canopy temperature at 15 cm above the surface and free‐air temperature over the period 2000–2020 at a spatial resolution of 25 m across Europe. This offset was used to evaluate the difference between microclimate and macroclimate across space and seasons and finally enabled us to calculate mean annual and monthly temperatures for European forest understories. We found that sub‐canopy air temperatures differ substantially from free‐air temperatures, being on average 2.1°C (standard deviation ± 1.6°C) lower in summer and 2.0°C higher (±0.7°C) in winter across Europe. Additionally, our high‐resolution maps expose considerable microclimatic variation within landscapes, not captured by the gridded macroclimatic products. The provided forest sub‐canopy temperature maps will enable future research to model below‐canopy biological processes and patterns, as well as species distributions more accurately.

Tropospheric ozone (O-3) is probably the air pollutant most damaging to vegetation. Understanding how plants respond to O(3)pollution under different climate conditions is of central importance for predicting the interactions between climate change, ozone impact and vegetation. This work analyses the effect of O(3)fluxes on net ecosystem productivity (NEP), measured directly at the ecosystem level with the eddy covariance (EC) technique. The relationship was explored with artificial neural networks (ANNs), which were used to model NEP using environmental and phenological variables as inputs in addition to stomatal O(3)uptake in Spring and Summer, when O(3)pollution is expected to be highest. A sensitivity analysis allowed us to isolate the effect of O-3, visualize the shape of the O-3-NEP functional relationship and explore how climatic variables affect NEP response to O-3. This approach has been applied to eleven ecosystems covering a range of climatic areas. The analysis highlighted that O(3)effects over NEP are highly non-linear and site-specific. A significant but small NEP reduction was found during Spring in a Scottish shrubland (-0.67%), in two Italian forests (up to -1.37%) and during Summer in a Californian orange orchard (-1.25%). Although the overall seasonal effect of O(3)on NEP was not found to be negative for the other sites, with episodic O(3)detrimental effect still identified. These episodes were correlated with meteorological variables showing that O(3)damage depends on weather conditions. By identifying O(3)damage under field conditions and the environmental factors influencing to that damage, this work provides an insight into O(3)pollution, climate and weather conditions.

AbstractThis paper describes the formation of, and initial results for, a new FLUXNET coordination network for ecosystem-scale methane (CH4) measurements at 60 sites globally, organized by the Glob...

ABSTRACT A field campaign in a deciduous forest in Ispra, Italy, was performed by the Joint Research Centre, Ispra, Italy, together with University of Innsbruck, Austria, in 2013, using PTR-ToF-MS (proton transfer reaction – time-of-flight – mass spectrometry), PTR-QMS (proton transfer reaction – quadrupole mass spectrometry), FIS (fast isoprene sensor) and other instrumentations. The main purpose of the campaign was to measure volatile organic carbon (VOC). One of the outcomes of this investigation was the comparison between the three VOC measurement techniques, focusing on the VOC-flux values that could be measured, VOC-volume-mixing-ratio (VOC-VMR) values that could be measured, the number of VOCs identified/measured, and finally if any oxidation products from the primary emitted VOC could be identified/measured. To the best of our knowledge, it is the first time that these three techniques have been used simultaneously during a campaign in a forest, and the comparison of the three techniques is presented in details (PTR-ToF-MS, PTR-QMS and FIS). It was concluded that the isoprene data generated by the three instruments were in good agreement. With PTR-ToF-MS, the following main results were achieved during the summer campaign 2013: The VMR of isoprene was measured up to 16 ppb; large fluxes of isoprene with values up to 53 nmol m−2 s−1 by PTR-ToF-MS; mean diurnal (24 h) averages of VMR of isoprene of (1.07 ± 0.53) ppb and mean diurnal (24 h) flux of isoprene of (5.20 ± 2.42) nmol m−2 s−1. For the isoprene oxidation products methyl-vinyl-ketone/methacrolein (MVK/MACR), VMRs of (0.42 ± 0.22) ppb were measured as a mean diurnal (24 h) average. Mean diurnal (24 h) flux of MVK/MACR were measured to be (0.06 ± 0.04) nmol m−2 s−1; for the monoterpenes, the VMR was measured to be (0.10 ± 0.09) ppb mean diurnal (24 h) and mean diurnal (24 h) flux of monoterpenes to be (0.08 ± 0.05) nmol m−2 s−1. Detailed descriptions of the fluxes/VMRs of other VOCs, acetone/methanol/acetaldehyde, are also presented. The results obtained here have also been compared to several other similar studies and campaigns.

Biogenic emission algorithms predict that oak forests account for ∼ 70 % of the total European isoprene budget. Yet the isoprene emission potentials (IEPs) that underpin these model estimates are calculated from a very limited number of leaf-level observations and hence are highly uncertain. Increasingly, micrometeorological techniques such as eddy covariance are used to measure whole-canopy fluxes directly, from which isoprene emission potentials can be calculated. Here, we review five observational datasets of isoprene fluxes from a range of oak forests in the UK, Italy and France. We outline procedures to correct the measured net fluxes for losses from deposition and chemical flux divergence, which were found to be on the order of 5–8 and 4–5 %, respectively. The corrected observational data were used to derive isoprene emission potentials at each site in a two-step process. Firstly, six commonly used emission algorithms were inverted to back out time series of isoprene emission potential, and then an average isoprene emission potential was calculated for each site with an associated uncertainty. We used these data to assess how the derived emission potentials change depending upon the specific emission algorithm used and, importantly, on the particular approach adopted to derive an average site-specific emission potential. Our results show that isoprene emission potentials can vary by up to a factor of 4 depending on the specific algorithm used and whether or not it is used in a big-leaf or canopy environment (CE) model format. When using the same algorithm, the calculated average isoprene emission potential was found to vary by as much as 34 % depending on how the average was derived. Using a consistent approach with version 2.1 of the Model for Emissions of Gases and Aerosols from Nature (MEGAN), we derive new ecosystem-scale isoprene emission potentials for the five measurement sites: Alice Holt, UK (10 500 ± 2500 µg m−2 h−1); Bosco Fontana, Italy (1610 ± 420 µg m−2 h−1); Castelporziano, Italy (121 ± 15 µg m−2 h−1); Ispra, Italy (7590 ± 1070 µg m−2 h−1); and the Observatoire de Haute Provence, France (7990 ± 1010 µg m−2 h−1). Ecosystem-scale isoprene emission potentials were then extrapolated to the leaf-level and compared to previous leaf-level measurements for Quercus robur and Quercus pubescens, two species thought to account for 50 % of the total European isoprene budget. The literature values agreed closely with emission potentials calculated using the G93 algorithm, which were 85 ± 75 and 78 ± 25 µg g−1 h−1 for Q. robur and Q. pubescens, respectively. By contrast, emission potentials calculated using the G06 algorithm, the same algorithm used in a previous study to derive the European budget, were significantly lower, which we attribute to the influence of past light and temperature conditions. Adopting these new G06 specific emission potentials for Q. robur (55 ± 24 µg g−1 h−1) and Q. pubescens (47 ± 16 µg g−1 h−1) reduced the projected European budget by ∼ 17 %. Our findings demonstrate that calculated isoprene emission potentials vary considerably depending upon the specific approach used in their calculation. Therefore, it is our recommendation that the community now adopt a standardised approach to the way in which micrometeorological flux measurements are corrected and used to derive isoprene, and other biogenic volatile organic compounds, emission potentials.

•Two canopy-level Gs models were tested in two Mediterranean forests (pine and oak).•Canopy-level stomatal ozone flux was estimated in both forests using the Gs models.•Maximum stomatal conductance was 72% higher in Umbrella pine than in Holm oak.•Inclusion of a soil water function improved the performance of the Jarvis-type model.•Soil water status affected m in the BWB model in Umbrella pine but not in Holm oak.