Carbon Dioxide Exchange Research Articles

Carbon and Water Exchanges in a Mountain Meadow Ecosystem, Sierra Nevada, California

Ecosystem-atmosphere exchanges of carbon dioxide (CO2) and water vapor were investigated in a moist mountain meadow (Loney Meadow) at 1822 m MSL in the Sierra Nevada, California, USA. An eddy covariance (EC) tower was deployed for most of the snow-free period from May to September 2016. The meadow ecosystem progressed from a strong sink of CO2 in the peak of the growing season under saturated to wet soil conditions (−18.51 gC m−2 d−1) to a weak source (2.97 gC m−2 d−1) following a rapid decline in soil moisture as runoff decreased. The variability of Net Ecosystem Exchange (NEE) over diurnal, synoptic and seasonal timescales was dominated by Gross Primary Production (GPP) which ranged from 43 gC m−2 d−1 during the peak of the growing season to 19 gC m−2 d−1 during senescence. Ecosystem respiration was small in magnitude and variability compared to GPP. Approximations of annual NEE for the meadow ranged from −285 to −450 gC m−2 yr−1, which is high compared to grasslands, and more similar to mature wetland or forest ecosystems. At diurnal and synoptic scales, CO2 flux was driven most strongly by photosynthetically active radiation (PAR), while seasonally, the ecosystem was linked closely to changes in soil moisture. Light-use and water-use efficiencies of the meadow ecosystem were high compared with those found in most other ecosystems using comparable observations. These results suggest meadows have the potential to be large sinks of atmospheric CO2 and that their ability to do so is sensitive to water table height. This is important for understanding the future of carbon sequestration in mountain meadows in the context of changing hydroclimates and different land management decisions that impact meadow hydrology.

Upscaling Northern Peatland CO2 Fluxes Using Satellite Remote Sensing Data

Peatlands play an important role in the global carbon cycle as they contain a large soil carbon stock. However, current climate change could potentially shift peatlands from being carbon sinks to carbon sources. Remote sensing methods provide an opportunity to monitor carbon dioxide (CO2) exchange in peatland ecosystems at large scales under these changing conditions. In this study, we developed empirical models of the CO2 balance (net ecosystem exchange, NEE), gross primary production (GPP), and ecosystem respiration (ER) that could be used for upscaling CO2 fluxes with remotely sensed data. Two to three years of eddy covariance (EC) data from five peatlands in Sweden and Finland were compared to modelled NEE, GPP and ER based on vegetation indices from 10 m resolution Sentinel-2 MSI and land surface temperature from 1 km resolution MODIS data. To ensure a precise match between the EC data and the Sentinel-2 observations, a footprint model was applied to derive footprint-weighted daily means of the vegetation indices. Average model parameters for all sites were acquired with a leave-one-out-cross-validation procedure. Both the GPP and the ER models gave high agreement with the EC-derived fluxes (R2 = 0.70 and 0.56, NRMSE = 14% and 15%, respectively). The performance of the NEE model was weaker (average R2 = 0.36 and NRMSE = 13%). Our findings demonstrate that using optical and thermal satellite sensor data is a feasible method for upscaling the GPP and ER of northern boreal peatlands, although further studies are needed to investigate the sources of the unexplained spatial and temporal variation of the CO2 fluxes.

Seasonal variations in carbon dioxide exchange fluxes at a taiga–tundra boundary ecosystem in Northeastern Siberia

Arctic and boreal permafrost ecosystems in Eastern Siberia, considered crucial to the climate system and global carbon cycle, are particularly vulnerable to climate change. This study investigates carbon dioxide (CO2) exchange fluxes over northeastern Siberia from 2013 to 2015 in a taiga–tundra boundary ecosystem for which such measurements are scarce. The growing season (May–September) net CO2 exchange flux (NEE) was −39.4 (−60.1 to −20.2) gCm−2, with ecosystem respiration (RE) = 306.2 (288.1–317.9) gCm−2 and gross primary production (GPP) = −345.5 (−372.5 to −317.7) gCm−2. Microclimatic factors determining these CO2 exchange fluxes change seasonally. These fluxes are significantly affected by the timing of the onset of C uptake, which is reflected by changes in the soil temperature in spring and early summer, following which fluxes respond well to the photosynthetic photon flux density, especially for NEE. These CO2 exchange fluxes at the northeastern Siberian taiga–tundra boundary ecosystem are significantly smaller than those previously reported at southern-taiga forest sites. Spring snow meltwater-rich soil moisture conditions render southern-taiga sites as stronger CO2 sinks in June than taiga–tundra boundary ecosystem, which may be largely responsible for the pronounced north–south gradient in growing season NEE.

Water-air Carbon Dioxide Exchange and Nutritional Controls in a Typical Karst River

To explore water-air carbon dioxide (CO2) exchange and its nutritional controls in karst rivers, water sampling and analyses were conducted in the Furong River as a representative karst river system. Regional hydrometeorological characteristics, carbonate system parameters, total organic carbon (TOC), nutrients and their stoichiometric ratios, and the riverine pressure of aqueous CO2 (pCO2) and its couplings to trophic status were analyzed. The results showed that gas transfer velocity of CO2 (k) varied between 2.71 and 13.0 m·d-1. Riverine pCO2 varied from 78.5 Pa to 21491.2 Pa and was significantly higher in the tributaries than the main stem. Riverine TOC, total nitrogen (TN), and total phosphorus (TP) concentrations were (302.8±50.1), (128.9±67.9), and (0.65±0.98) μmol·L-1, respectively, demonstrating the trophic status of P-limitation. Riverine pCO2 was tightly linked to P-related parameters, suggesting that in-situ metabolism triggered aquatic CO2 supersaturation. Water-air CO2 flux (F) averaged (534.5±801.4) mmol·(m2·d)-1 in the Furong River, which is higher than most of the world's rivers, and thus indicates high potential CO2 emissions.

Carbon dioxide and methane exchange of a patterned subarctic fen during two contrasting growing seasons

Abstract. The patterned microtopography of subarctic mires generates a variety of environmental conditions, and carbon dioxide (CO2) and methane (CH4) dynamics vary spatially among different plant community types (PCTs). We studied the CO2 and CH4 exchange between a subarctic fen and the atmosphere at Kaamanen in northern Finland based on flux chamber and eddy covariance measurements in 2017–2018. We observed strong spatial variation in carbon dynamics between the four main PCTs studied, which were largely controlled by water table level and differences in vegetation composition. The ecosystem respiration (ER) and gross primary productivity (GPP) increased gradually from the wettest PCT to the drier ones, and both ER and GPP were larger for all PCTs during the warmer and drier growing season 2018. We estimated that in 2017 the growing season CO2 balances of the PCTs ranged from −20 g C m−2 (Trichophorum tussock PCT) to 64 g C m−2 (string margin PCT), while in 2018 all PCTs were small CO2 sources (10–22 g C m−2). We observed small growing season CH4 emissions (< 1 g C m−2) from the driest PCT, while the other three PCTs had significantly larger emissions (mean 7.9, range 5.6–10.1 g C m−2) during the two growing seasons. Compared to the annual CO2 balance (−8.5 ± 4.0 g C m−2) of the fen in 2017, in 2018 the annual balance (−5.6 ± 3.7 g C m−2) was affected by an earlier onset of photosynthesis in spring, which increased the CO2 sink, and a drought event during summer, which decreased the sink. The CH4 emissions were also affected by the drought. The annual CH4 balance of the fen was 7.3 ± 0.2 g C m−2 in 2017 and 6.2 ± 0.1 g C m−2 in 2018. Thus, the carbon balance of the fen was close to zero in both years. The PCTs that were adapted to drier conditions provided ecosystem-level resilience to carbon loss due to water level drawdown.

Three new methods indicate that CO2 concentration affects plant respiration in the range relevant to global change.

Short-term responses of plant dark respiration to carbon dioxide concentration ([CO2]) in the range anticipated in the atmosphere with global change remain controversial, primarily because it is difficult to convincingly eliminate the many possible sources of experimental error in measurements of carbon dioxide or oxygen exchange rates. Plant dark respiration is a major component of the carbon balance of many ecosystems. In seedlings without senescent tissue, the rate of loss of dry mass during darkness indicates the rate of respiration. This method of measuring respiration was used to test for [CO2] effects on respiration in seedlings of three species with relatively large seeds. The time it took respiration to exhaust substrates and cause seedling death in darkness was used as an indicator of respiration rate in four other species with smaller seeds. The third method was measuring rates of CO2 exchange in excised petioles sealed in a cuvette submerged in water to prevent leaks. Petioles were utilized as the plant tissue type with the most reliable rates of respiration, for excised tissue. The rate of loss of dry mass in the dark decreased with increasing [CO2] in the range of 200-800 μmol mol-1 in all three large-seeded species. The seedling survival time in the dark increased with [CO2] in the same concentration range in all four of the smaller-seeded species. Respiration rates of excised petioles of several species also decreased over this [CO2] range. The data provide new evidence that the rate of dark respiration in plant tissue often decreases with increasing [CO2] in the 200-800 μmol mol-1 range.

Gap Filling of Net Ecosystem CO<sub>2</sub> Exchange (NEE) above Rain-Fed Maize Using Artificial Neural Networks (ANNs)

The eddy covariance technique is an accurate and direct tool to measure the Net Ecosystem Exchange (NEE) of carbon dioxide. However, sometimes conditions are not amenable to measurements using this technique. Thus, different methods have been developed to allow gap-filling and quality assessment of eddy covariance data sets. In this study first, two different Artificial Neural Networks (ANNs) approaches, the Multi-layer Perceptron (MLP) trained by the Back-Propagation (BP) algorithm, and the Radial Basis Function (RBF), were used to fill missing NEE data measured above rain-fed maize at the University of Nebraska-Lincoln Agricultural Research and Development Center near Mead, Nebraska. The gap-filled data were then compared by different statistical indices to gap-filled data obtained with the technique suggested by Suyker and Verma in 2005 [SV the structure of RBF and MLP (BP) networks was constant. However, data analysis indicated Papale’s approach gave better fits than the RBF and MLP (BP) methods. Thus, based on this work, Papale’s approach is the best method to estimate the missing data; though the applied statistical indices, which were used for model evaluation, show little difference between Papale’s approach and the RBF and MLP (BP).

Long‐term intercomparison of two pCO2 instruments based on ship‐of‐opportunity measurements in a dynamic shelf sea environment

AbstractThe partial pressure of carbon dioxide (pCO2) in surface seawater is an important biogeochemical variable because, together with the pCO2 in the atmosphere, it determines the direction of air–sea carbon dioxide exchange. Large‐scale observations of pCO2 are facilitated by Ships‐of‐Opportunity (SOOP‐CO2) equipped with underway measuring instruments. The need for expanding the observation capacity and the challenges involving the sustainability and maintenance of traditional equilibrator systems led the community toward developing simpler and more autonomous systems. Here we performed a comparison between a membrane‐based sensor and a showerhead equilibration sensor installed on two SOOP‐CO2 between 2013 and 2018. We identified time‐ and space‐adequate crossovers in the Skagerrak Strait, where the two ship routes often crossed. We found a mean total difference of 1.5 ± 10.6 μatm and a root mean square error of 11 μatm. The pCO2 values recorded by the two instruments showed a strong linear correlation with a coefficient of 0.91 and a slope of 1.07 (± 0.14), despite the dynamic nature of the environment and the difficulty of comparing measurements from two different vessels. The membrane‐based sensor was integrated with a FerryBox system on a ship with a high sampling frequency in the study area. We showed the strength of having a sensor‐based network with a high spatial coverage that can be validated against conventional SOOP‐CO2 methods. Proving the validity of membrane‐based sensors in coastal and continental shelf seas and using the higher frequency measurements they provide can enable a thorough characterization of pCO2 variability in these dynamic environments.

Influence of trace elements, applied in classical and nano forms, on photosynthesis of higher plants in relation to enhancement of crop productivity

One of the main factors of increasing the productivity of agricultural plants is intensifying the activity of the photo- synthetic apparatus, since the productivity of crops depends on the ability to absorb solar radiation and convert it into the energy of chemical bonds for further use in metabolic processes. The amount of photosynthetically active radia- tion absorbed by crops, in its turn, depends on the area, duration, and activity of the assimilation surface functioning. The use of fertilizers, that contain trace elements, can further achieve both raising the yield of cultivated plants and environmental protection. In this regard, the state-of-the-art research on the infl uence of the main trace elements (iron, zinc, manganese, molybdenum, cobalt, selenium, boron, titanium) and one macroelement - magnesium - on photosynthetic characteristics of plants and crops is discussed. Based on the literature data and the results of our own research, we documented the effect of trace elements on leaves carbon dioxide exchange rates, the content of photo- synthetic pigments, the antioxidant enzymes activity, as well as the traits of the photosynthetic apparatus capacity. The infl uence of nanometals on the content and ratio of pigments, net CO 2 assimilation rate, and the photochemical activity of photosystems, including the effect of stress factors, is discussed. The specifi cities of the infl uence of nanometals are discussed and possible mechanisms of the effect of low concentrations of trace elements on plant metabolism are analyzed. It is shown that trace elements infl uence photosynthetic processes in plants and the systems of their antioxi- dant protection. The relevance of trace elements in the development of new strategies to elaborate the technologies of cultivating next-generation plants, including those that will be based on new physical and chemical properties of macro- and micronutrients in a nano form, is highlighted

Carbon and water balance of an afforested shallow drained peatland in Iceland

Drainage of peatlands increases the depth of the oxic peat layer and can turn them into a carbon (C) source to the atmosphere. Afforestation of drained peatlands could help to reverse this process since the trees may enhance C sequestration. We followed the C and water dynamics of an afforested drained peatland in S-Iceland during a 2 year period, during which the Black Cottonwood (Populus balsamifera ssp. trichocarpa) plantation was 23–25 year old. Net ecosystem exchange (NEE) of carbon dioxide (CO2) was measured with the eddy covariance method and C pools of trees and ground vegetation were measured using the stock change method. Lateral losses of dissolved and particulated organic C (DOC, POC) were estimated from weekly water-runoff samples. Unexpectedly, the afforested drained peatland was a strong sink of carbon during the two years, with an average NEE value of 714 g C m−2 yr−1. Only 0.5% of the total NEE was lost through lateral DOC and POC transport, leaving 710 g C m−2 yr−1 as the total net ecosystem production (NEP). Ca. 91% of the observed NEP could be explained by the annual biomass increment of the Black Cottonwood trees and 1.3% by the ground vegetation. This means that the remaining 7.5% of the total NEP most likely accumulated in peat soil and litter, contributing to the soil C stocks. The dormant-season CO2 emissions were unexpectedly low, which was explained by a high groundwater level at this drained site outside the ca. 5 months of the active growing season. On average, 66% of the annual measured precipitation was estimated to have evaporated back to the atmosphere. This left 416 mm for potential runoff, which was somewhat lower value than the measured runoff (662 mm). These results indicate that during the age span of ca. 20–25 years, afforestation was a valid method to reverse the expected negative C-balance of this drained grassland pasture in Iceland. Although the site is currently a soil C sink, simulation studies with process models are needed to test whether such sites could remain C sinks when managed for forestry over several tree-stand rotations.

Uncertainty and sensitivity analysis of modeling plant CO2 exchange in the built environment

The dynamics of carbon dioxide (CO2) exchange in the built environment, coupled with local microclimate modeling, is of critical importance to the understanding of emergent patterns of longterm urban climate evolution. In addition to the complex model physics, the difficulty is outstanding to characterize uncertainties inherited in the parameter space and its impact on the model performance and predictive skills. In this study, we conducted a series of numerical simulations based on advanced Markov chain Monte Carlo algorithms to quantify the sensitivity of a recently developed modeling framework by coupling the dynamics of CO2 transport into a single-layer urban canopy model. The results show that urban morphology (canyon aspect ratio), irrigation, and the physiological properties of urban vegetation predominate the processes of plant CO2 exchange in the built environment. In contrast, the CO2 budget is relatively insensitive to material properties of urban facets in the built environment. The findings in this study can help to unravel the interplay of urban carbon dynamics and the built environment, as well as to inform researchers and policy makers for sustainable urban development towards a low carbon city.

Variations in diurnal and seasonal net ecosystem carbon dioxide exchange in a semiarid sandy grassland ecosystem in China's Horqin Sandy Land

Abstract. Grasslands are major terrestrial ecosystems in arid and semiarid regions, and they play important roles in the regional carbon dioxide (CO2) balance and cycles. Sandy grasslands are sensitive to climate change, yet the magnitudes, patterns, and environmental controls of their CO2 flows are poorly understood for some regions (e.g., China's Horqin Sandy Land). Here, we report the results from continuous year-round CO2 flux measurements for 5 years from a sandy grassland in China's Horqin Sandy Land. The grassland was a net CO2 source at an annual scale with a mean annual net ecosystem CO2 exchange (NEE) of 49 ± 8 gCm-2yr-1 for the years for which a complete dataset was available (2015, 2016, and 2018). Annual precipitation had the strongest effect on annual NEE; grassland carbon sequestration increased with the increasing precipitation since NEE depended on annual precipitation. In the spring, NEE decreased (i.e., C sequestration increased) with increasing magnitude of effective precipitation pulses, total monthly precipitation, and soil temperature (Tsoil). In the summer, NEE was dominated by the total seasonal precipitation and high precipitation pulses (> 20 mm). In the autumn, NEE increased (i.e., C sequestration decreased) with increasing effective precipitation pulses, Tsoil, and near-surface soil water content (SWC) but decreased with increased SWC deeper in the soil. In the winter, NEE decreased with increasing Tsoil and SWC. The sandy grassland was a net annual CO2 source because drought decreased carbon sequestration by the annual plants. Long-term observations will be necessary to reveal the true source or sink intensity and its response to environmental and biological factors.

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The evolution of biogeochemistry: revisited

The evolution of biogeochemistry, retraces the important historical steps in part, covered by Gorham (Biogeochemistry 13:199–239, 1991) in the 18–19th centuries—with new emergent linkages and trends in 20–21st centuries. In the post-phlogiston period, key synthetic connections are made between weathering, atmospheric chemistry, carbon cycling, and climate change. Early work in the 19th century, focused on weathering and the importance of organisms in the exchange of carbon dioxide between the rocks and the atmosphere, provided foundations for new analytical approaches. The role microbes in connecting abiotic and biotic processes begins to emerge, based largely on the existing knowledge of stoichiometry in agricultural soils and plants. This in part, leads to the founding of ecology and its linkages with evolution and biogeography. Verandsky boldly emerges in the 20th century, with his concepts of a biosphere and a noosphere, as concerns begin to arise about human impacts on nature. The development of organic geochemistry as a discipline, allowed for new roots to develop in the evolution of biogeochemistry through linkages between short and long-term carbon cycles. In the 20th century, a new interesting stoichiometry emerges in biogeochemistry—as related to the Green Revolution, human population growth, and eutrophication problems. The advent of long-term and large-scale experiments help to constrain the complexity of non-linearity and regional differences in fluxes and rates in biogeochemical work. A new age begins in the 21st century whereby molecular approaches (e.g. omics) combined with large-scale satellite, monitoring, survey, observatory approaches are combined in the development of Earth System models. These new connections with ecological/evolutionary genetics are one of the more dramatic and important aspects of biogeochemistry in modern times.

Biases in open-path carbon dioxide flux measurements: Roles of instrument surface heat exchange and analyzer temperature sensitivity

Eddy covariance (EC) measurements of ecosystem-atmosphere carbon dioxide (CO2) exchange provide the most direct assessment of the terrestrial carbon cycle. Measurement biases for open-path (OP) CO2 concentration and flux measurements have been reported for over 30 years, but their origin and appropriate correction approach remain unresolved. Here, we quantify the impacts of OP biases on carbon and radiative forcing budgets for a sub-boreal wetland. Comparison with a reference closed-path (CP) system indicates that a systematic OP flux bias (0.54μmolm−2s−1) persists for all seasons leading to a 110% overestimate of the ecosystem CO2 sink (cumulative error of 78 gC m−2). Two potential OP bias sources are considered: Sensor-path heat exchange (SPHE) and analyzer temperature sensitivity. We examined potential OP correction approaches including: i) Fast temperature measurements within the measurement path and sensor surfaces; ii) Previously published parameterizations; and iii) Optimization algorithms. The measurements revealed year-round average temperature and heat flux gradients of 2.9 °C and 16 W m−2 between the bottom sensor surfaces and atmosphere, indicating SPHE-induced OP bias. However, measured SPHE correlated poorly with the observed differences between OP and CP CO2 fluxes. While previously proposed nominally universal corrections for SPHE reduced the cumulative OP bias, they led to either systematic under-correction (by 38.1 gC m−2) or to systematic over-correction (by 17-37 gC m−2). The resulting budget errors exceeded CP random uncertainty and change the sign of the overall carbon and radiative forcing budgets. Analysis of OP calibration residuals as a function of temperature revealed a sensitivity of 5μmolm−3K−1. This temperature sensitivity causes CO2 calibration errors proportional to sample air fluctuations that can offset the observed growing season flux bias by 50%. Consequently, we call for a new OP correction framework that characterizes SPHE- and temperature-induced CO2 measurement errors.

Control for Carbon Dioxide Exchange Process in a Membrane Oxygenator Using Online Self-Tuning Fuzzy-PID Controller

Background and objectiveThe aim of this study is to evaluate the performance of conventional PID that is tuned using Zeigler-Nichols continuous cycling, Fuzzy Logic Controller (FLC) and self-tuning Fuzzy-PID (self-tuning FPID) methods to control the rate of CO2 removal from a membrane oxygenator during extracorporeal blood purification process. MethodsSweep gas flow rate is chosen as the manipulated variable of arterial CO2 partial pressure (pCO2) in blood. The performance of these controllers is evaluated based on their response in controlling task and also by the calculation of three performance indices, namely Integral Absolute Error (IAE), Integral Squared Error (ISE) and Integral Time Absolute Error (ITAE). The robustness of the controllers using these tuning methods is then assessed for set point tracking and load disturbance rejection tests. ResultsResults indicated that the self-tuning FPID is observed as the best controller compared to conventional PID and FLC with lower oscillation, overshoot and shorter settling time. As for quantitative measurement, self-tuning FPID outshines the other controllers with 0.854, 1.084 and 41.450 for IAE, ISE and ITAE, respectively in set point tracking task while 0.532 IAE, 0.016 ISE and 28.970 ITAE measured for load disturbance rejections. ConclusionIt can be concluded that self-tuning FPID is the best controller to be used in the automation of extracorporeal circulation control for both set point tracking and load disturbance rejection tests.

A long-term (2005–2016) dataset of hourly integrated land–atmosphere interaction observations on the Tibetan Plateau

Abstract. The Tibetan Plateau (TP) plays a critical role in influencing regional and global climate, via both thermal and dynamical mechanisms. Meanwhile, as the largest high-elevation part of the cryosphere outside the polar regions, with vast areas of mountain glaciers, permafrost and seasonally frozen ground, the TP is characterized as an area sensitive to global climate change. However, meteorological stations are biased and sparsely distributed over the TP, owing to the harsh environmental conditions, high elevations, complex topography and heterogeneous surfaces. Moreover, due to the weak representation of the stations, atmospheric conditions and the local land–atmosphere coupled system over the TP as well as its effects on surrounding regions are poorly quantified. This paper presents a long-term (2005–2016) in situ observational dataset of hourly land–atmosphere interaction observations from an integrated high-elevation and cold-region observation network, composed of six field stations on the TP. These in situ observations contain both meteorological and micrometeorological measurements including gradient meteorology, surface radiation, eddy covariance (EC), soil temperature and soil water content profiles. Meteorological data were monitored by automatic weather stations (AWSs) or planetary boundary layer (PBL) observation systems. Multilayer soil temperature and moisture were recorded to capture vertical hydrothermal variations and the soil freeze–thaw process. In addition, an EC system consisting of an ultrasonic anemometer and an infrared gas analyzer was installed at each station to capture the high-frequency vertical exchanges of energy, momentum, water vapor and carbon dioxide within the atmospheric boundary layer. The release of these continuous and long-term datasets with hourly resolution represents a leap forward in scientific data sharing across the TP, and it has been partially used in the past to assist in understanding key land surface processes. This dataset is described here comprehensively for facilitating a broader multidisciplinary community by enabling the evaluation and development of existing or new remote sensing algorithms as well as geophysical models for climate research and forecasting. The whole datasets are freely available at the Science Data Bank (https://doi.org/10.11922/sciencedb.00103; Ma et al., 2020) and additionally at the National Tibetan Plateau Data Center (https://doi.org/10.11888/Meteoro.tpdc.270910, Ma 2020).

Quantification of water stress induced within-field variability of carbon dioxide fluxes in a sugar beet stand

Net ecosystem exchange of carbon dioxide (NEE) and soil respiration at field scale can exhibit considerable spatial variability linked to the heterogeneity of soil properties and state variables. In this study, we measured NEE with the eddy covariance (EC) method in a sugar beet field characterized by high spatial variability in soil physical properties. We further measured NEE and soil respiration by chambers as well as soil water content and temperature at 18 locations within the field.Spatially averaged chamber-measured NEE showed good agreement to the EC-based data. During a dry period high spatial variation of within-field NEE was detected with the chamber method. The coefficient of variation was on average 0.57 during the dry period, with a maximum of 0.72. Based on the depth-specific soil water content measurements the AgroC ecosystem model was inverted for soil hydraulic properties at each of the 18 locations, where soil water content was measured. Analyzing the model results revealed that root water uptake stress was the main driver of spatial and temporal variability in crop development and NEE, whereby the soil coarse material fraction (gravel content) and thickness of the layer above a gravel dominated soil layer were identified as the main influencing soil properties.The chamber-measured NEE and the flux footprint analysis showed that particularly during periods of severe root water uptake stress EC-based measurements would be prone to biases. A combination of the footprint model with the AgroC ecosystem model estimated a bias of 14 % for the dry period and a vegetation period bias of 6 % in relation to the average CO2 flux.

A long-term (2005–2019) eddy covariance data set of CO<sub>2</sub> and H<sub>2</sub>O fluxes from the Tibetan alpine steppe

Abstract. The Tibetan alpine steppe ecosystem covers an area of roughly 800 000 km2 and contains up to 3.3 % soil organic carbon in the uppermost 30 cm, summing up to 1.93 Pg C for the Tibet Autonomous Region only (472 037 km2). With temperatures rising 2 to 3 times faster than the global average, these carbon stocks are at risk of loss due to enhanced soil respiration. The remote location and the harsh environmental conditions on the Tibetan Plateau (TP) make it challenging to derive accurate data on the ecosystem–atmosphere exchange of carbon dioxide (CO2) and water vapor (H2O). Here, we provide the first multiyear data set of CO2 and H2O fluxes from the central Tibetan alpine steppe ecosystem, measured in situ using the eddy covariance technique. The calculated fluxes were rigorously quality checked and carefully corrected for a drift in concentration measurements. The gas analyzer self-heating effect during cold conditions was evaluated using the standard correction procedure and newly revised formulations (Burba et al., 2008; Frank and Massman, 2020). A wind field analysis was conducted to identify influences of adjacent buildings on the turbulence regime and to exclude the disturbed fluxes from subsequent computations. The presented CO2 fluxes were additionally gap filled using a standardized approach. The very low net carbon uptake across the 15-year data set highlights the special vulnerability of the Tibetan alpine steppe ecosystem to become a source of CO2 due to global warming. The data are freely available at https://doi.org/10.5281/zenodo.3733202 (Nieberding et al., 2020a) and https://doi.org/10.11888/Meteoro.tpdc.270333 (Nieberding et al., 2020b) and may help us to better understand the role of the Tibetan alpine steppe in the global carbon–climate feedback.

On the inter- and intra-annual variability of ecosystem evapotranspiration and water use efficiency of an oak savanna and annual grassland subjected to booms and busts in rainfall.

Whether annual evapotranspiration of native ecosystems is increasing or decreasing with time as CO2 concentrations are rising, the climate is warming and rainfall experiences booms and busts, remains an unanswered question in the field of global change biology. To answer this question, we measured evapotranspiration and carbon dioxide exchange over and under an oak savanna and over an annual grassland in the Mediterranean climate of California, USA, from 2001 through 2019 with the eddy covariance method; during this 19-year period, CO2 rose 40ppm, air temperature increased by 1°C and annual rainfall ranged between 133 and 890mm/year. No temporal trend in evapotranspiration or water use efficiency was observed over this time duration. Many competing positive and negative feedbacks among stomatal sensitivity to carbon dioxide concentrations, soil moisture, and vapor pressure deficit, the impact of temperature on saturation vapor pressure and access to groundwater muted the response of evapotranspiration to its changing world when integrated to the ecosystem scale and annual time steps. At the intra-annual time scale, we found that plants transmit information on soil moisture status through their influence on the vapor pressure deficit of the atmospheric boundary layer. The inter-annual variations in evaporative water use by the savanna and annual grassland were relatively decoupled from the booms and busts in rainfall. Instead, variations in length of growing season and access to groundwater explained much of this year-to-year variation in annual evapotranspiration. The access of groundwater by the oak savanna may make these ecosystems more robust in a warmer world, than was previously thought. This is a scale emergent property that needs better consideration in coupled climate-ecosystem models.