Root and rhizosphere contribution to the net soil COS exchange.

Background and aims: Partitioning the measured net ecosystem carbon dioxide (CO2) exchange into gross primary productivity (GPP) and ecosystem respiration remains a challenge, which scientists try to tackle by using the properties of the trace gas carbonyl sulfide (COS). Its similar pathway into and within the leaf makes it a potential photosynthesis proxy. The application of COS as an effective proxy depends, among other things, on a robust inventory of potential COS sinks and sources within ecosystems. While the soil received some attention during the last couple of years, the role of plant roots is mostly unknown. In our study, we investigated the effects of live roots on the soil COS exchange. Methods: An experimental setup was devised to measure the soil and the belowground plant parts of young beech trees observed over the course of 9 months. Results: During the growing season, COS emissions were significantly lower when roots were present compared to chambers only containing soil, while prior to the growing season, with photosynthetically inactive trees, the presence of roots increased COS emissions. The difference in the COS flux between root-influenced and uninfluenced soil was fairly constant within each month, with diurnal variations in the COS flux driven primarily by soil temperature changes rather than the presence or absence of roots. Conclusion: While the mechanisms by which roots influence the COS exchange are largely unknown, their contribution to the overall ground surface COS exchange should not be neglected when quantifying the soil COS exchange. Supplementary Information: The online version contains supplementary material available at 10.1007/s11104-023-06438-0.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

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.

Leaf-level coordination principles propagate to the ecosystem scale.

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.

Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects.

Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.

Effects of land use and climate on carbon and nitrogen pool partitioning in European mountain grasslands.

European mountain grasslands are increasingly affected by land-use changes and climate, which have been suggested to exert important controls on grassland carbon (C) and nitrogen (N) pools. However, so far there has been no synthetic study on whether and how land-use changes and climate interactively affect the partitioning of these pools amongst the different grassland compartments. We analyzed the partitioning of C and N pools of 36 European mountain grasslands differing in land-use and climate with respect to above- and belowground phytomass, litter and topsoil (top 23 cm). We found that a reduction of management intensity and the abandonment of hay meadows and pastures increased above-ground phytomass, root mass and litter as well as their respective C and N pools, concurrently decreasing the fractional contribution of the topsoil to the total organic carbon pool. These changes were strongly driven by the cessation of cutting and grazing, a shift in plant functional groups and a related reduction in litter quality. Across all grasslands studied, variation in the impact of land management on the topsoil N pool and C/N-ratio were mainly explained by soil clay content combined with pH. Across the grasslands, below-ground phytomass as well as phytomass- and litter C concentrations were inversely related to the mean annual temperature; furthermore, C/N-ratios of phytomass and litter increased with decreasing mean annual precipitation. Within the topsoil compartment, C concentrations decreased from colder to warmer sites, and increased with increasing precipitation. Climate generally influenced effects of land use on C and N pools mainly through mean annual temperature and less through mean annual precipitation. We conclude that site-specific conditions need to be considered for understanding the effects of land use and of current and future climate changes on grassland C and N pools.

Heatwave breaks down the linearity between sun-induced fluorescence and gross primary production.

Sun-induced fluorescence in the far-red region (SIF) is increasingly used as a remote and proximal-sensing tool capable of tracking vegetation gross primary production (GPP). However, the use of SIF to probe changes in GPP is challenged during extreme climatic events, such as heatwaves. Here, we examined how the 2018 European heatwave (HW) affected the GPP-SIF relationship in evergreen broadleaved trees with a relatively invariant canopy structure. To do so, we combined canopy-scale SIF measurements, GPP estimated from an eddy covariance tower, and active pulse amplitude modulation fluorescence. The HW caused an inversion of the photosynthesis-fluorescence relationship at both the canopy and leaf scales. The highly nonlinear relationship was strongly shaped by nonphotochemical quenching (NPQ), that is, a dissipation mechanism to protect from the adverse effects of high light intensity. During the extreme heat stress, plants experienced a saturation of NPQ, causing a change in the allocation of energy dissipation pathways towards SIF. Our results show the complex modulation of the NPQ-SIF-GPP relationship at an extreme level of heat stress, which is not completely represented in state-of-the-art coupled radiative transfer and photosynthesis models.

The albedo-climate penalty of hydropower reservoirs.

Hydropower emits less carbon dioxide than fossil fuels but the lower albedo of hydropower reservoirs compared to terrestrial landscapes results in a positive radiative forcing offsetting some of the negative radiative forcing by hydroelectricity generation. The cumulative effect of this lower albedo has not been quantified. Here we show, by quantifying the difference in remotely sensed albedo between globally distributed hydropower reservoirs and their surrounding landscape, that 19 % of all investigated hydropower plants required 40 years and more for the negative radiative forcing from the fossil fuel displacement to offset the albedo effect. The length of these break-even times depends on the specific combination of climatic and environmental constraints, power plant design characteristics and country-specific electricity carbon intensities. We conclude that future hydropower plants need to minimize the albedo penalty in order to make a meaningful contribution towards limiting global warming.

Temperature thresholds of ecosystem respiration at a global scale.

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.

Ecosystem transpiration and evaporation: Insights from three water flux partitioning methods across FLUXNET sites.

We apply and compare three widely applicable methods for estimating ecosystem transpiration (T) from eddy covariance (EC) data across 251 FLUXNET sites globally. All three methods are based on the coupled water and carbon relationship, but they differ in assumptions and parameterizations. Intercomparison of the three daily T estimates shows high correlation among methods (R between .89 and .94), but a spread in magnitudes of T/ET (evapotranspiration) from 45% to 77%. When compared at six sites with concurrent EC and sap flow measurements, all three EC-based T estimates show higher correlation to sap flow-based T than EC-based ET. The partitioning methods show expected tendencies of T/ET increasing with dryness (vapor pressure deficit and days since rain) and with leaf area index (LAI). Analysis of 140 sites with high-quality estimates for at least two continuous years shows that T/ET variability was 1.6 times higher across sites than across years. Spatial variability of T/ET was primarily driven by vegetation and soil characteristics (e.g., crop or grass designation, minimum annual LAI, soil coarse fragment volume) rather than climatic variables such as mean/standard deviation of temperature or precipitation. Overall, T and T/ET patterns are plausible and qualitatively consistent among the different water flux partitioning methods implying a significant advance made for estimating and understanding T globally, while the magnitudes remain uncertain. Our results represent the first extensive EC data-based estimates of ecosystem T permitting a data-driven perspective on the role of plants' water use for global water and carbon cycling in a changing climate.

Stomatal optimization based on xylem hydraulics (SOX) improves land surface model simulation of vegetation responses to climate.

Land surface models (LSMs) typically use empirical functions to represent vegetation responses to soil drought. These functions largely neglect recent advances in plant ecophysiology that link xylem hydraulic functioning with stomatal responses to climate. We developed an analytical stomatal optimization model based on xylem hydraulics (SOX) to predict plant responses to drought. Coupling SOX to the Joint UK Land Environment Simulator (JULES) LSM, we conducted a global evaluation of SOX against leaf- and ecosystem-level observations. SOX simulates leaf stomatal conductance responses to climate for woody plants more accurately and parsimoniously than the existing JULES stomatal conductance model. An ecosystem-level evaluation at 70 eddy flux sites shows that SOX decreases the sensitivity of gross primary productivity (GPP) to soil moisture, which improves the model agreement with observations and increases the predicted annual GPP by 30% in relation to JULES. SOX decreases JULES root-mean-square error in GPP by up to 45% in evergreen tropical forests, and can simulate realistic patterns of canopy water potential and soil water dynamics at the studied sites. SOX provides a parsimonious way to incorporate recent advances in plant hydraulics and optimality theory into LSMs, and an alternative to empirical stress factors.

The urban imprint on plant phenology.

The modification of the surface radiation and energy balance in urban areas causes the temperatures in these areas to exceed those of the surrounding countryside. It has thus been suggested that urban environments may serve as field laboratories for studying the effects of a warming climate on biota in a space-for-time substitution. Here we investigated changes in the timing of plant phenology and temperature across study sites that differed in the degree of urbanization using publicly available pan-European datasets for the period 1981-2010. We found a significant advancement in the phenological phases of leaf development, flowering and fruiting with higher degrees of urbanization, whereas a significant delay was observed for phenological phases of leaf senescence. In addition to these phenological changes, an increase in air temperature with higher degrees of urbanization was observed. This increase was largest during the periods of leaf development, flowering and fruiting and smallest during the period of leaf senescence. On the basis of these results, we show that the apparent temperature sensitivity of phenological phases to urban warming is either significantly dampened (leaf development, flowering and fruiting) or reversed (leaf senescence) compared with the temperature sensitivity inferred from temporal changes in phenology and temperature. We conclude that gradients in urbanization represent a poor analogue for the temporal changes in plant phenology, apparently owing to confounding factors associated with urbanization.

Soil carbonyl sulfide exchange in relation to microbial community composition: insights from a managed grassland soil amendment experiment.

The viability of carbonyl sulfide (COS) measurements for partitioning ecosystem-scale net carbon dioxide (CO2) fluxes into photosynthesis and respiration critically depends on our knowledge of non-leaf sinks and sources of COS in ecosystems. We combined soil gas exchange measurements of COS and CO2 with next-generation sequencing technology (NGS) to investigate the role of soil microbiota for soil COS exchange. We applied different treatments (litter and glucose addition, enzyme inhibition and gamma sterilization) to soil samples from a temperate grassland to manipulate microbial composition and activity. While untreated soil was characterized by consistent COS uptake, other treatments reduced COS uptake and even turned the soil into a net COS source. Removing biotic processes through sterilization led to positive or zero fluxes. We used NGS to link changes in the COS response to alterations in the microbial community composition, with bacterial data having a higher explanatory power for the measured COS fluxes than fungal data. We found that the genera Arthrobacter and Streptomyces were particularly abundant in samples exhibiting high COS emissions. Our results indicate co-occurring abiotic production and biotic consumption of COS in untreated soil, the latter linked to carbonic anhydrase activity, and a strong dependency of the COS flux on the activity, identity, abundance of and substrate available to microorganisms.

On the calculation of daytime CO2 fluxes measured by automated closed transparent chambers.

Automated transparent chambers have gained increasing popularity in recent years to continuously measure net CO2 fluxes between low-statured canopies and the atmosphere. In this study, we carried out four field campaigns with chamber measurements in a variety of mountainous grasslands. A mathematic stationary point (or critical point, a point at which the derivative of a function is zero) in the CO2 mixing ratio time series was found in a substantial fraction of the measurements at all the sites, which had a significant influence on the performances of the regression algorithms. The stationary point was probably due to condensed water on the inner wall of the chamber dome, which reduced the solar radiation and resulted in a reversal of the CO2 mixing ratio time series in the chamber (so called Clouded-Glass Effect or CGE in this study). This effect may be the cause of the observed underestimation of daytime CO2 fluxes when using common linear and exponential regression models on continuous automated chamber observations. In order to avoid biased flux estimation of daytime CO2 fluxes, we introduced a linearly increasing term to the exponential function so as to compensate for the influence of the CGE, which gives acceptable model errors and improves the CO2 flux estimation by 5 % for temperate mountainous grasslands. We conclude that exponential regression models should be favoured over linear models and recommend to account for the effects of CGE by either excluding ambiguous observations from the flux computations where stationary points can be identified in the CO2 mixing ratio time series, or by adding a linearly increasing term to the exponential regression model.

Weakened growth of cropland-N2 O emissions in China associated with nationwide policy interventions.

China has experienced rapid agricultural development over recent decades, accompanied by increased fertilizer consumption in croplands; yet, the trend and drivers of the associated nitrous oxide (N2 O) emissions remain uncertain. The primary sources of this uncertainty are the coarse spatial variation of activity data and the incomplete model representation of N2 O emissions in response to agricultural management. Here, we provide new data-driven estimates of cropland-N2 O emissions across China in 1990-2014, compiled using a global cropland-N2 O flux observation dataset, nationwide survey-based reconstruction of N-fertilization and irrigation, and an updated nonlinear model. In addition, we have evaluated the drivers behind changing cropland-N2 O patterns using an index decomposition analysis approach. We find that China's annual cropland-N2 O emissions increased on average by 11.2 Gg N/year2 (p < .001) from 1990 to 2003, after which emissions plateaued until 2014 (2.8 Gg N/year2 , p = .02), consistent with the output from an ensemble of process-based terrestrial biosphere models. The slowdown of the increase in cropland-N2 O emissions after 2003 was pervasive across two thirds of China's sowing areas. This change was mainly driven by the nationwide reduction in N-fertilizer applied per area, partially due to the prevalence of nationwide technological adoptions. This reduction has almost offset the N2 O emissions induced by policy-driven expansion of sowing areas, particularly in the Northeast Plain and the lower Yangtze River Basin. Our results underline the importance of high-resolution activity data and adoption of nonlinear model of N2 O emission for capturing cropland-N2 O emission changes. Improving the representation of policy interventions is also recommended for future projections.

Industrial point source CO2 emission strength estimation with aircraft measurements and dispersion modelling.

CO2 remains the greenhouse gas that contributes most to anthropogenic global warming, and the evaluation of its emissions is of major interest to both research and regulatory purposes. Emission inventories generally provide quite reliable estimates of CO2 emissions. However, because of intrinsic uncertainties associated with these estimates, it is of great importance to validate emission inventories against independent estimates. This paper describes an integrated approach combining aircraft measurements and a puff dispersion modelling framework by considering a CO2 industrial point source, located in Biganos, France. CO2 density measurements were obtained by applying the mass balance method, while CO2 emission estimates were derived by implementing the CALMET/CALPUFF model chain. For the latter, three meteorological initializations were used: (i) WRF-modelled outputs initialized by ECMWF reanalyses; (ii) WRF-modelled outputs initialized by CFSR reanalyses and (iii) local in situ observations. Governmental inventorial data were used as reference for all applications. The strengths and weaknesses of the different approaches and how they affect emission estimation uncertainty were investigated. The mass balance based on aircraft measurements was quite succesful in capturing the point source emission strength (at worst with a 16% bias), while the accuracy of the dispersion modelling, markedly when using ECMWF initialization through the WRF model, was only slightly lower (estimation with an 18% bias). The analysis will help in highlighting some methodological best practices that can be used as guidelines for future experiments.

Eddy covariance carbonyl sulphide flux measurements with a quantum cascade laser absorption spectrometer.

The trace gas carbonyl sulphide (COS) has lately received growing interest in the eddy covariance (EC) community due to its potential to serve as an independent approach for constraining gross primary production and canopy stomatal conductance. Thanks to recent developments of fast-response high-precision trace gas analysers (e.g. quantum cascade laser absorption spectrometers (QCLAS)), a handful of EC COS flux measurements have been published since 2013. To date, however, a thorough methodological characterisation of QCLAS with regard to the requirements of the EC technique and the necessary processing steps has not been conducted. The objective of this study is to present a detailed characterization of the COS measurement with the Aerodyne QCLAS in the context of the EC technique, and to recommend best EC processing practices for those measurements. Data were collected from May to October 2015 at a temperate mountain grassland in Tyrol, Austria. Analysis of the Allan variance of high-frequency concentration measurements revealed sensor drift to occur under field conditions after an averaging time of around 50 s. We thus explored the use of two high-pass filtering approaches (linear detrending and recursive filtering) as opposed to block averaging and linear interpolation of regular background measurements for covariance computation. Experimental low-pass filtering correction factors were derived from a detailed cospectral analysis. The CO2 and H2O flux measurements obtained with the QCLAS were compared against those obtained with a closed-path infrared gas analyser. Overall, our results suggest small, but systematic differences between the various high-pass filtering scenarios with regard to the fraction of data retained in the quality control and flux magnitudes. When COS and CO2 fluxes are combined in the so-called ecosystem relative uptake rate, systematic differences between the high-pass filtering scenarios largely cancel out, suggesting that this relative metric represents a robust key parameter comparable between studies relying on different post-processing schemes.

Effect of climate warming on the annual terrestrial net ecosystem CO2 exchange globally in the boreal and temperate regions.

The net ecosystem CO2 exchange is the result of the imbalance between the assimilation process (gross primary production, GPP) and ecosystem respiration (RE). The aim of this study was to investigate temperature sensitivities of these processes and the effect of climate warming on the annual terrestrial net ecosystem CO2 exchange globally in the boreal and temperate regions. A database of 403 site-years of ecosystem flux data at 101 sites in the world was collected and analyzed. Temperature sensitivities of rates of RE and GPP were quantified with Q 10, defined as the increase of RE (or GPP) rates with a temperature rise of 10 °C. Results showed that on the annual time scale, the intrinsic temperature sensitivity of GPP (Q 10sG ) was higher than or equivalent to the intrinsic temperature sensitivity of RE (Q 10sR ). Q 10sG was negatively correlated to the mean annual temperature (MAT), whereas Q 10sR was independent of MAT. The analysis of the current temperature sensitivities and net ecosystem production suggested that temperature rise might enhance the CO2 sink of terrestrial ecosystems both in the boreal and temperate regions. In addition, ecosystems in these regions with different plant functional types should sequester more CO2 with climate warming.

Revisiting the choice of the driving temperature for eddy covariance CO2 flux partitioning.

So-called CO2 flux partitioning algorithms are widely used to partition the net ecosystem CO2 exchange into the two component fluxes, gross primary productivity and ecosystem respiration. Common CO2 flux partitioning algorithms conceptualize ecosystem respiration to originate from a single source, requiring the choice of a corresponding driving temperature. Using a conceptual dual-source respiration model, consisting of an above- and a below-ground respiration source each driven by a corresponding temperature, we demonstrate that the typical phase shift between air and soil temperature gives rise to a hysteresis relationship between ecosystem respiration and temperature. The hysteresis proceeds in a clockwise fashion if soil temperature is used to drive ecosystem respiration, while a counter-clockwise response is observed when ecosystem respiration is related to air temperature. As a consequence, nighttime ecosystem respiration is smaller than daytime ecosystem respiration when referenced to soil temperature, while the reverse is true for air temperature. We confirm these qualitative modelling results using measurements of day and night ecosystem respiration made with opaque chambers in a short-statured mountain grassland. Inferring daytime from nighttime ecosystem respiration or vice versa, as attempted by CO2 flux partitioning algorithms, using a single-source respiration model is thus an oversimplification resulting in biased estimates of ecosystem respiration. We discuss the likely magnitude of the bias, options for minimizing it and conclude by emphasizing that the systematic uncertainty of gross primary productivity and ecosystem respiration inferred through CO2 flux partitioning needs to be better quantified and reported.

Phenotypic differences determine drought stress responses in ecotypes of Arundo donax adapted to different environments.

Arundo donax has been identified as an important biomass and biofuel crop. Yet, there has been little research on photosynthetic and metabolic traits, which sustain the high productivity of A. donax under drought conditions. This study determined phenotypic differences between two A. donax ecotypes coming from stands with contrasting adaptation to dry climate. We hypothesized that the Bulgarian (BG) ecotype, adapted to drier conditions, exhibits greater drought tolerance than the Italian (IT) ecotype, adapted to a more mesic environment. Under well-watered conditions the BG ecotype was characterized by higher photosynthesis, mesophyll conductance, intrinsic water use efficiency, PSII efficiency, isoprene emission rate and carotenoids, whereas the IT ecotype showed higher levels of hydroxycinnamates. Photosynthesis of water-stressed plants was mainly limited by diffusional resistance to CO2 in BG, and by biochemistry in IT. Recovery of photosynthesis was more rapid and complete in BG than in IT, which may indicate better stability of the photosynthetic apparatus associated to enhanced induction of volatile and non-volatile isoprenoids and phenylpropanoid biosynthesis. This study shows that a large phenotypic plasticity among A. donax ecotypes exists, and may be exploited to compensate for the low genetic variability of this species when selecting plant productivity in constrained environments.