Net Ecosystem Exchange Fluxes Research Articles

Resolving heterogeneous fluxes from tundra halves the growing season carbon budget

Abstract. Landscapes are often assumed to be homogeneous when interpreting eddy covariance fluxes, which can lead to biases when gap-filling and scaling up observations to determine regional carbon budgets. Tundra ecosystems are heterogeneous at multiple scales. Plant functional types, soil moisture, thaw depth, and microtopography, for example, vary across the landscape and influence net ecosystem exchange (NEE) of carbon dioxide (CO2) and methane (CH4) fluxes. With warming temperatures, Arctic ecosystems are changing from a net sink to a net source of carbon to the atmosphere in some locations, but the Arctic's carbon balance remains highly uncertain. In this study we report results from growing season NEE and CH4 fluxes from an eddy covariance tower in the Yukon–Kuskokwim Delta in Alaska. We used footprint models and Bayesian Markov chain Monte Carlo (MCMC) methods to unmix eddy covariance observations into constituent land-cover fluxes based on high-resolution land-cover maps of the region. We compared three types of footprint models and used two land-cover maps with varying complexity to determine the effects of these choices on derived ecosystem fluxes. We used artificially created gaps of withheld observations to compare gap-filling performance using our derived land-cover-specific fluxes and traditional gap-filling methods that assume homogeneous landscapes. We also compared resulting regional carbon budgets when scaling up observations using heterogeneous and homogeneous approaches. Traditional gap-filling methods performed worse at predicting artificially withheld gaps in NEE than those that accounted for heterogeneous landscapes, while there were only slight differences between footprint models and land-cover maps. We identified and quantified hot spots of carbon fluxes in the landscape (e.g., late growing season emissions from wetlands and small ponds). We resolved distinct seasonality in tundra growing season NEE fluxes. Scaling while assuming a homogeneous landscape overestimated the growing season CO2 sink by a factor of 2 and underestimated CH4 emissions by a factor of 2 when compared to scaling with any method that accounts for landscape heterogeneity. We show how Bayesian MCMC, analytical footprint models, and high-resolution land-cover maps can be leveraged to derive detailed land-cover carbon fluxes from eddy covariance time series. These results demonstrate the importance of landscape heterogeneity when scaling carbon emissions across the Arctic.

Atmospheric CO2 exchanges measured by eddy covariance over a temperate salt marsh and influence of environmental controlling factors

Abstract. Within the coastal zone, salt marshes are atmospheric CO2 sinks and represent an essential component of biological carbon (C) stored on earth due to a strong primary production. Significant amounts of C are processed within these tidal systems which requires a better understanding of the temporal CO2 flux dynamics, the metabolic processes involved and the controlling factors. Within a temperate salt marsh (French Atlantic coast), continuous CO2 fluxes measurements were performed by the atmospheric eddy covariance technique to assess the net ecosystem exchange (NEE) at diurnal, tidal and seasonal scales as well as the associated relevant biophysical drivers. To study marsh metabolic processes, measured NEE was partitioned into gross primary production (GPP) and ecosystem respiration (Reco) during marsh emersion allowing to estimate NEE at the marsh–atmosphere interface (NEEmarsh = GPP − Reco). During the year 2020, the net C balance from measured NEE was −483 g C m−2 yr−1 while GPP and Reco absorbed and emitted 1019 and 533 g C m−2 yr−1, respectively. The highest CO2 uptake was recorded in spring during the growing season for halophyte plants in relationships with favourable environmental conditions for photosynthesis, whereas in summer, higher temperatures and lower humidity rates increased ecosystem respiration. At the diurnal scale, the salt marsh was a CO2 sink during daytime, mainly driven by light, and a CO2 source during night-time, mainly driven by temperature, irrespective of emersion or immersion periods. However, daytime immersion strongly affected NEE fluxes by reducing marsh CO2 uptake up to 90 %. During night-time immersion, marsh CO2 emissions could be completely suppressed, even causing a change in metabolic status from source to sink under certain situations, especially in winter when Reco rates were lowest. At the annual scale, tidal immersion did not significantly affect the net C uptake of the studied salt marsh since similar annual balances of measured NEE (with tidal immersion) and estimated NEEmarsh (without tidal immersion) were recorded.

The influence of the hydrometeorological factors on the CO2 fluxes from the oligotrophic bog surface.

Global climate change is one of the most important and promising phenomena to study in actual time. One of the key causes of global climate change is increasing the greenhouse gas (GHG) concentrations in the atmosphere [IPCC, 2023]. The main greenhouse gases are methane, carbon dioxides and nitric oxide, which contribute to the greenhouse effect and global warming [Lashof, Ahuja, 1990]. Carbon dioxide (CO2) is one of the most significant and widespread gases involved in the planet's global carbon cycle [Lashof, Ahuja. 1990]. At the same time, living organisms play a key role in creation of atmosphere composition. Autotrophic organisms use a carbon dioxide to build their body structures, including complex organic compounds. During ecosystem functioning, the part of the carbon dioxide is released into the atmosphere through organism respiration, while another part is released through the decomposition of dead organic matter. Carbon dioxide may also be produced through natural and anthropogenic processes.
 Peatland ecosystems play a significant role in the planet's carbon cycle, both locally and globally. Peatlands in their natural undisturbed state are a significant long-term carbon sink1. However, the process of carbon deposition is not constant – in different years, peatlands may serve either as carbon sink or source2. The main factor stimulating the carbon sequestration by peatland ecosystems is climatic conditions [Harenda et al., 2018; Bond-Lamberty et al., 2018]. Peatlands are the second most significant carbon stock on Earth and the largest on land. Despite covering only 2.84% of the Earth's land surface, the amount of soil organic carbon stored in them accounts for about one-third of all soil organic carbon on Earth. Peatlands in the northern hemisphere play a particularly important role in carbon sequestration, with an estimated accumulated carbon quantity of ~473–621 Gt of carbon [Yu et al., 2010].
 The largest area of peatlands in Russia is located in Western Siberia, estimated at ~42% of the total Russian area [Vomperskiy et al., 1994; Sheng et al., 2004]. The territory of Western Siberia is featured to a high share of peatlands in original undisturbed state, making them an ideal location to study the impact of global changes on peatland biogeochemical functioning worldwide.
 The carbon balance of peatlands is mainly determined by two processes: photosynthesis and respiration [Harenda et al., 2018]. The main factors influencing the CO2 flux from peatlands are photosynthetically active radiation, atmospheric air temperature (Tavg), soil temperature (Tsoil), and water table level (WTL) [Miao et al., 2013; Juszczak et al., 2013; Dyukarev et al., 2019]. At the same time, the level of mutual influence and the degree of determination have not yet been fully determined.
 To study the carbon balance of terrestrial ecosystems, the chamber method [Davidson et al., 2002] is widely used. The chamber method allows to estimate the CO2 flux from the surface of the ecosystem. At the same time, the use of the modern automatic system LI-COR LI-8100A (LI-COR, USA) provides high-frequency continuous data on carbon dioxide fluxes over a long period of time, which makes it possible to assess the total accumulation of carbon and significantly improve the reliability of the identified relationships with environmental factors [Zarov et al., 2022].
 The purpose of this study was to assess carbon dioxide flluxes and discover the main hydrometeorological parameters that influence the flow in the hollows of the Mukhrino raised bog.
 
 MATERIALS AND METHODS 
 The research was carried out at the «Mukhrino» field station [Dyukarev et al., 2021], located in the central part of Western Siberia, 30 km southwest of the city of Khanty-Mansiysk. The climate is featured by high repeatability of anticyclonic conditions, rapid changes in weather conditions, a humid, moderately warm summer, and a fairly harsh, snowy winter. The chamber system was installed in a homogeneous area of the peatland, dominated by Sph. balticum, C. limosa, and Scheuchzeria palustris, with the presence of E. vaginatum on the periphery. The plant composition inside the chambers was not determined, but the most homogeneous and similar areas were selected for installation (Figure 2).
 Carbon dioxide flux measurements were carried out using the automated chamber method, using a portable soil respiration analysis system LI-8100A (LI-COR, USA). The flues were measured by four automated chambers installed in the raised bog area of Mukhrino (Figure 3). The first group of chambers – NEE (2 LI-COR 8100-104s chambers), measured net ecosystem exchange (NEE); the second group – Reco (2 LI-COR 8100-104 cameras), measured ecosystem respiration (Reco). Measurements were taken for 2 minutes every 30 minutes for all cameras. Wooden walkways were installed in the peatland area to minimize potential negative impacts on the study surface.
 The fluxes were calculated using a linear model of specialized software LI-8100 File Viewer 3.0.0 (LI-COR). R programming language packages dplyr [Wickham, 2016], ggplot2 [Wickham, 2016], lubridate [Grolemund, Wickham, 2011] were used for data processing and visualization. To analyze the dynamics of NEE and Reco fluxes, the obtained values were averaged between LI-COR 8100-104s chambers (for NEE) and LI-COR 8100-104 chambers (for Reco). Gross primary production (GPP) was calculated using the equation GPP=NEE-Reco [Connolly et al., 2009]. For further analysis, measurements with a coefficient of determination (R2) of linear regression above 0.5 were selected to minimize significant noise in the data. Spearman's rank correlation method was chosen to identify dependencies of flux on hydrometeorological properties. The dependence was determined based on the data of the flux and hydrometeorological properties averaged over 30 minutes.
 
 RESULTS AND DISCUSSION
 The average daily variation of CO2 flows for July, September, October 2021 is shown in Fig. 5. The simultaneous use of dark and light chambers allowed to assess the flows that are released in the ecosystem as a result of the respiration of plants, animals and microorganisms (Reco), the intensity of CO2 absorption in the process photosynthesis (GPP), and net ecosystem exchange (NEE), which is the difference between the specific absorption rate (GPP) of carbon dioxide excretion (Reco). The average daily variation of Reco (Fig. 5) in July was featured by the highest values during daylight hours; the CO2 flux reaches its maximum value at 11:00 (1.44 µmol m‑2s‑1). For September and October, the daily dynamics of Reco were weakly expressed. The highest CO2 emissions were typical for evening and night time. The maximum Reco in the daily cycle was observed at 19:00 (0.47 µmol m‑2s‑1) for September, and at 00:00 (0.17 µmol m‑2s‑1) for October. The average daily cycle of GPP (Fig. 5) had a pronounced absorption maximum during daylight hours with maximum radiation, for July – at 11:00 (-3.47 µmol m‑2s‑1), for September – at 12:00 (-1.53 µmol m‑2s‑1), for October – at 11:00 (-0.45 µmol m‑2s‑1). The absorption of carbon dioxide from the atmosphere (GPP) had different daily durations depending on the month (Fig. 5), which is associated with a decrease in daylight hours by autumn. In July, carbon dioxide absorption was observed from 4:00 to 20:00 (16 hours), in September – from 5:00 to 18:00 (13 hours), in October – from 7:00 to 17:00 (10 hours). For the diurnal cycle of NEE (Fig. 5), the CO2 absorption process (GPPReco) predominated in the daytime, while the carbon dioxide emission process (GPPReco) dominated at night. The maximum NEE value in the daily cycle in July was estimated at 1.01 µmol m‑2s‑1 at 22:00, in September 0.49 µmol m‑2s‑1 at 20:00, in October 0.17 µmol m‑2s‑1 at 21:00. The minimum NEE value in July was -2.03 µmol m‑2s‑1 at 11:00, in September: -1.01 µmol m‑2s‑1 at 12:00, in October 0.39 µmol m‑2s‑1 at 11:00.
 A total of 1711, 2625 and 1597 Reco measurements were taken in July, September and October, respectively. The highest average daily rate of ecosystem respiration Reco occurred in the third ten days of July (July 19); by the last days of October, ecosystem respiration reached its minimum in the annual course (Fig. 7). The average Reco in July was 1.05±0.25 µmol m‑2s‑1, and in October 0.13±0.01 µmol m‑2s‑1. These estimates were obtained on a sufficient array of data and therefore can be considered reliable. The peak intensity of photosynthesis was recorded on July 22, when vegetation absorbed the largest amount of CO2. After July 22, there was a gradual decline in GPP; the rate of carbon dioxide absorption in the last days of October decreased significantly, but did not drop to zero. The presence of photosynthesis in the hollow of an oligotrophic bog even in late autumn and at low air temperatures is probably due to the activity of sphagnum mosses. Net ecosystem exchange (Fig. 7) was negative every day in July, thereby the absorption of carbon dioxide from the atmosphere daily dominated its release. In September, ecosystem absorption of carbon dioxide prevailed until September 10, after which both negative and positive NEE values were observed. During this period, intense precipitation occurred, a decrease in air temperature and the amount of incoming radiation, which led to the ecosystem switching from a sink to a temporary source of CO2. In October, the number of days on which the ecosystem acted as a carbon sink decreased; on most days, carbon dioxide emissions predominated. According to average monthly values, carbon dioxide absorption prevailed in July (-0.53±0.13 µmol m‑2s‑1) and September (-0.11±0.18 µmol m‑2s‑1), in October (0.02±0.04 µmol m‑2s‑1) CO2 evolution predominated. The number of measurements according to NEE (Table 2) is greatest in September (2584) and least in July (1709).
 Reco was most influenced in July (Table 3) by air and soil temperature; in September – soil temperature and marsh water level. In October, when daily temperature variability decreased, the most significant factor for Reco was PAR (-0.59). The degree of correlation of Reco with Tavg and Tsoil in July qualifies as high; these factors are directly related to Reco – the higher the temperature, the greater the release of carbon dioxide into the atmosphere by the ecosystem. This is caused by an increase in the activity of microorganisms under the influence of increased temperature [Nikonova et al., 2019]. In September, the influence of Tsoil (0.81) and water level (-0.78) increased, while the influence of Tavg (0.54) decreased. The degree of correlation of these parameters with Reco in September was classified as high. It is assumed that the strong influence of water level (-0.78) on the Reco flux in September may be associated with a sharp rise in water level (Fig. 6F), which could lead to a disruption of the optimum life activity of microorganisms. Similar flow behavior was found for North American peatlands [Miao et al., 2013]. In October, the greatest influence on Reco was exerted by PAR (-0.59), the degree of correlation is weak negative; At the same time, the correlation of the indicator with PAR in July was weakly positive. The highest correlation for GPP (Table 3) was obtained with photosynthetically active radiation for all months of the study. The PAR correlation level for all months was classified as high. The inverse correlation is due to the fact that as PAR increases, CO2 absorption increases (negative GPP flux). PAR is a key factor influencing plant photosynthesis, which in turn affects their ability to assimilate CO2 and produce GPP. As PAR intensity increases, plants increase the rate of photosynthesis and absorb carbon dioxide from the atmosphere faster, which increases GPP. The greatest influence on NEE was caused by PAR (Table 3) in July, in September and October (-0.91, -0.74 and -0.71, respectively). The level of PAR correlation in July and September was high, in October it was moderate. When PAR levels increase, plants use carbon dioxide more actively to produce organic matter and increase the level of GPP in the ecosystem, which leads to an increase in NEE flux. On the other hand, when PAR levels decrease, plants become less active in photosynthesis, which leads to the prevalence of Reco and a decrease in NEE flux. Analysis of correlation coefficients calculated from data for the entire field season, the best relationship for Reco was found with soil temperature (0.88), air temperature (0.71) and water level (-0.73). PAR has the greatest influence on GPP (-0.89) and NEE (-0.73).
 
 CONCLUSIONS 
 Automated high temporal resolution chamber measurements of carbon dioxide flux provided a data for analyzing CO2 fluxes in the peatland area. The results provided detailed information that was used to analyze the impact of environmental hydrometeorological parameters on the flux. The highest ecosystem respiration (Reco) value during a 24-hour period was recorded in July at 11:00 (1.44 µmol m‑2s‑1), in September at 19:00 (0.47 µmol m‑2s‑1), and in October at 00:00 (0.17 µmol m‑2s‑1). The maximum gross primary production (GPP) for all months occurred between 11-12 hours: in July at 11:00 (-3.47 µmol m‑2s‑1), in September at 12:00 (-1.53 µmol m‑2s‑1), and in October at 11:00 (-0.45 µmol m‑2s‑1). By autumn, the duration of GPP throughout a day decreased, as well as the amplitude of diurnal variation for all flux indicators. The highest average daily CO2 flux for all indicators was recorded in July, while the lowest was in October. In net ecosystem exchange (NEE), absorption predominated from July 14 to September 9, with days dominated by ecosystem respiration from September 10 onwards. The amplitude of the average daily flux for all indicators decreased by October.
 Based on the Spearman correlation data, the highest seasonal correlation for ecosystem respiration (Reco) was with soil temperature (0.88), air temperature (0.71), and water level (-0.73). In July, the best correlation is with air temperature (0.70) and soil temperature (0.68), in September with soil temperature (0.81) and water level (-0.78), and in October with photosynthetically active radiation (PAR) (-0.59). Gross primary production (GPP) correlates best with PAR. In July, the correlation coefficient is -0.95, in September -0.86, in October -0.79, and for the entire field season -0.89. Net ecosystem exchange (NEE), similar to GPP, is most dependent on PAR. In July, the correlation coefficient is -0.91, in September -0.74, in October -0.71, and for the entire field season -0.73.
 In general, the article calculates carbon dioxide fluxes from the surface of a hollow in an oligotrophic peatland. The seasonal and average daily dynamics of hydrometeorological properties are described, and their influence on CO2 flows is assessed. It is worth noting that throughout the entire growing season, the influence of external factors on fluxes decreases, reaching a minimum mutual correlation in the coldest month (October).

Stable isotopes contain substantial additive information about terrestrial carbon and water cycling

Stable isotope ratios of H (δ 2 H), O (δ 18O), and C (δ 13C) are linked to key biogeochemical processes of the water and carbon cycles; however, the degree to which isotope-associated processes are reflected in macroscale ecosystem flux observations remains unquantified. Here through formal information assessment, new measurements of δ 13C of net ecosystem exchange (NEE) as well as δ 2H and δ 18O of latent heat (LH) fluxes across the United States National Ecological Observation Network (NEON) are used to determine conditions under which isotope measurements are informative of environmental exchanges. We find all three isotopic datasets individually contain comparable amounts of information about NEE and LH fluxes as wind speed observations. Such information from isotope measurements, however, is largely unique. Generally, δ 13C provides more information about LH as aridity increases or mean annual precipitation decreases. δ 2H provides more information about LH as temperatures or mean annual precipitation decreases, and also provides more information about NEE as temperatures decrease. Overall, we show that the stable isotope datasets collected by NEON contribute non-trivial amounts of new information about bulk environmental fluxes useful for interpreting biogeochemical and ecohydrological processes at landscape scales. However, the utility of this new information varies with environmental conditions at continental scales. This study provides an approach for quantifying the value adding non-traditional sensing approaches to environmental monitoring sites and the patterns identified here are expected to aid in modeling and data interpretation efforts focused on constraining carbon and water cycles’ mechanisms.

Modelling Net Ecosystem Exchange in the Biebrza Wetlands using satellite and meteorological data

Abstract The CO2 flux on Biebrza Wetlands in Poland is analysed by ground measurements and satellite data. The main goal of this study was to determine the Net Ecosystem Exchange (NEE) for sedges, reeds and grasses using meteorological, soil and vegetation parameters and satellite indicators. The calculations are based on chamber measurements scattered over the main habitats and meteorological registrations, and compared to the 2015–2022 eddy covariance (EC) measurements. The NEE model, to get its distribution throughout the day, was elaborated using modelled gross primary production GPP and modelled respiration RESP. The model of ecosystem respiration was developed applying air temperature, soil temperature, soil moisture and NDVI. The satellite vegetation index NDVI, surface and air difference temperature (TS-TA), and NDII proved to be good predictors for the daily mean GPP. The data from the EC tower was used to compare the results from modelled NEE and CO2 flux.

Uncertainty in land carbon budget simulated by terrestrial biosphere models: the role of atmospheric forcing

Global estimates of the land carbon sink are often based on simulations by terrestrial biosphere models (TBMs). The use of a large number of models that differ in their underlying hypotheses, structure and parameters is one way to assess the uncertainty in the historical land carbon sink. Here we show that the atmospheric forcing datasets used to drive these TBMs represent a significant source of uncertainty that is currently not systematically accounted for in land carbon cycle evaluations. We present results from three TBMs each forced with three different historical atmospheric forcing reconstructions over the period 1850–2015. We perform an analysis of variance to quantify the relative uncertainty in carbon fluxes arising from the models themselves, atmospheric forcing, and model-forcing interactions. We find that atmospheric forcing in this set of simulations plays a dominant role on uncertainties in global gross primary productivity (GPP) (75% of variability) and autotrophic respiration (90%), and a significant but reduced role on net primary productivity and heterotrophic respiration (30%). Atmospheric forcing is the dominant driver (52%) of variability for the net ecosystem exchange flux, defined as the difference between GPP and respiration (both autotrophic and heterotrophic respiration). In contrast, for wildfire-driven carbon emissions model uncertainties dominate and, as a result, model uncertainties dominate for net ecosystem productivity. At regional scales, the contribution of atmospheric forcing to uncertainty shows a very heterogeneous pattern and is smaller on average than at the global scale. We find that this difference in the relative importance of forcing uncertainty between global and regional scales is related to large differences in regional model flux estimates, which partially offset each other when integrated globally, while the flux differences driven by forcing are mainly consistent across the world and therefore add up to a larger fractional contribution to global uncertainty.

Analysis of regional CO2 contributions at the high Alpine observatory Jungfraujoch by means of atmospheric transport simulations and δ13C

Abstract. In this study, we investigated the regional contributions of carbon dioxide (CO2) at the location of the high Alpine observatory Jungfraujoch (JFJ, Switzerland, 3580 m a.s.l.). To this purpose, we combined receptor-oriented atmospheric transport simulations for CO2 concentration in the period 2009–2017 with stable carbon isotope (δ13C–CO2) information. We applied two Lagrangian particle dispersion models driven by output from two different numerical weather prediction systems (FLEXPART–COSMO and STILT-ECMWF) in order to simulate CO2 concentration at JFJ based on regional CO2 fluxes, to estimate atmospheric δ13C–CO2, and to obtain model-based estimates of the mixed source signatures (δ13Cm). Anthropogenic fluxes were taken from a fuel-type-specific version of the EDGAR v4.3 inventory, while ecosystem fluxes were based on the Vegetation Photosynthesis and Respiration Model (VPRM). The simulations of CO2, δ13C–CO2, and δ13Cm were then compared to observations performed by quantum cascade laser absorption spectroscopy. The models captured around 40 % of the regional CO2 variability above or below the large-scale background and up to 35 % of the regional variability in δ13C–CO2. This is according to expectations considering the complex Alpine topography, the low intensity of regional signals at JFJ, and the challenging measurements. Best agreement between simulations and observations in terms of short-term variability and intensity of the signals for CO2 and δ13C–CO2 was found between late autumn and early spring. The agreement was inferior in the early autumn periods and during summer. This may be associated with the atmospheric transport representation in the models. In addition, the net ecosystem exchange fluxes are a possible source of error, either through inaccuracies in their representation in VPRM for the (Alpine) vegetation or through a day (uptake) vs. night (respiration) transport discrimination to JFJ. Furthermore, the simulations suggest that JFJ is subject to relatively small regional anthropogenic contributions due to its remote location (elevated and far from major anthropogenic sources) and the limited planetary boundary layer influence during winter. Instead, the station is primarily exposed to summertime ecosystem CO2 contributions, which are dominated by rather nearby sources (within 100 km). Even during winter, simulated gross ecosystem respiration accounted for approximately 50 % of all contributions to the CO2 concentrations above the large-scale background. The model-based monthly mean δ13Cm ranged from − 22 ‰ in winter to − 28 ‰ in summer and reached the most depleted values of − 35 ‰ at higher fractions of natural gas combustion, as well as the most enriched values of − 17 ‰ to − 12 ‰ when impacted by cement production emissions. Observation-based δ13Cm values were derived independently from the simulations by a moving Keeling-plot approach. While model-based estimates spread in a narrow range, observation-based δ13Cm values exhibited a larger scatter and were limited to a smaller number of data points due to the stringent analysis prerequisites.

Strong Correspondence in Evapotranspiration and Carbon Dioxide Fluxes Between Different Eddy Covariance Systems Enables Quantification of Landscape Heterogeneity in Dryland Fluxes

AbstractThe eddy covariance method is widely used to investigate fluxes of energy, water, and carbon dioxide at landscape scales, providing important information on how ecological systems function. Flux measurements quantify ecosystem responses to environmental perturbations and management strategies, including nature‐based climate‐change mitigation measures. However, due to the high cost of conventional instrumentation, most eddy covariance studies employ a single system, limiting spatial representation to the flux footprint. Insufficient replication may be limiting our understanding of ecosystem behavior. To address this limitation, we deployed eight lower‐cost eddy covariance systems in two clusters around two conventional eddy covariance systems in the Chihuahuan Desert of North America for a period of 2 years. These dryland settings characterized by large temperature variations and relatively low carbon dioxide fluxes represented a challenging setting for eddy covariance. We found very good closure of energy and water balance across all systems (within ±9% of unity). We found very good correspondence between the lower‐cost and conventional systems' fluxes of sensible heat (with concordance correlation coefficient (CCC) of ≥0.87), latent energy (evapotranspiration; CCC ≥ 0.89), and useful correspondence in the net ecosystem exchange ((NEE); with CCC ≥ 0.4) at the daily temporal resolution. Relative to the conventional systems, the low‐frequency systems were characterized by a higher level of random error, particularly in the NEE fluxes. Lower‐cost systems can enable wider deployment affording better replication and sampling of spatiotemporal variability at the expense of greater measurement noise that might be limiting for certain applications. Replicated eddy covariance observations may be useful when addressing gaps in the existing monitoring of critical and underrepresented ecosystems and for measuring areas larger than a single flux footprint.

Net ecosystem exchange of carbon dioxide fluxes and its driving mechanism in the forests on the Tibetan Plateau

Boreal forests sequester massive amounts of atmospheric carbon dioxide (CO2), and the contribution from the mid-high-latitude coniferous forests is considerable. This study quantified the net ecosystem exchange (NEE) of CO2 flux and its driving factors in a spruce forest in the Qilian Mountains. The results indicated that the NEE presented a robust temporal pattern ranging from −26.09 to 12.35 g C m−2 on a day-to-day basis. Furthermore, cumulative monthly NEE flux varied between −194.61 g C m−2 and 33.56 g C m−2. Forest ecosystems are vital carbon sinks that sequester/store carbon dioxide from April to September, especially from June to August. The annual NEE flux was a robust carbon sink of 545.99 g C m−2. Forest NEE was significantly driven by latent heat flux, net radiation, air temperature, and precipitation (P < 0.001). Regression coefficient of fitting model was 49.2% using latent heat flux, air temperature, and precipitation. In addition, future warming and precipitation scenarios may have considerably negative and positive effects, respectively, on the carbon sink.

A 10-year global monthly averaged terrestrial net ecosystem exchange dataset inferred from the ACOS GOSAT v9 XCO2 retrievals (GCAS2021)

Abstract. A global gridded net ecosystem exchange (NEE) of CO2 dataset is vital in global and regional carbon cycle studies. Top-down atmospheric inversion is one of the major methods to estimate the global NEE; however, the existing global NEE datasets generated through inversion from conventional CO2 observations have large uncertainties in places where observational data are sparse. Here, by assimilating the GOSAT ACOS v9 XCO2 product, we generate a 10-year (2010–2019) global monthly terrestrial NEE dataset using the Global Carbon Assimilation System, version 2 (GCASv2), which is named GCAS2021. It includes gridded (1∘×1∘), globally, latitudinally, and regionally aggregated prior and posterior NEE and ocean (OCN) fluxes and prescribed wildfire (FIRE) and fossil fuel and cement (FFC) carbon emissions. Globally, the decadal mean NEE is -3.73±0.52 PgC yr−1, with an interannual amplitude of 2.73 PgC yr−1. Combining the OCN flux and FIRE and FFC emissions, the net biosphere flux (NBE) and atmospheric growth rate (AGR) as well as their inter-annual variabilities (IAVs) agree well with the estimates of the Global Carbon Budget 2020. Regionally, our dataset shows that eastern North America, the Amazon, the Congo Basin, Europe, boreal forests, southern China, and Southeast Asia are carbon sinks, while the western United States, African grasslands, Brazilian plateaus, and parts of South Asia are carbon sources. In the TRANSCOM land regions, the NBEs of temperate N. America, northern Africa, and boreal Asia are between the estimates of CMS-Flux NBE 2020 and CT2019B, and those in temperate Asia, Europe, and Southeast Asia are consistent with CMS-Flux NBE 2020 but significantly different from CT2019B. In the RECCAP2 regions, except for Africa and South Asia, the NBEs are comparable with the latest bottom-up estimate of Ciais et al. (2021). Compared with previous studies, the IAVs and seasonal cycles of NEE of this dataset could clearly reflect the impacts of extreme climates and large-scale climate anomalies on the carbon flux. The evaluations also show that the posterior CO2 concentrations at remote sites and on a regional scale, as well as on vertical CO2 profiles in the Asia-Pacific region, are all consistent with independent CO2 measurements from surface flask and aircraft CO2 observations, indicating that this dataset captures surface carbon fluxes well. We believe that this dataset can contribute to regional- or national-scale carbon cycle and carbon neutrality assessment and carbon dynamics research. The dataset can be accessed at https://doi.org/10.5281/zenodo.5829774 (Jiang, 2022).

The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales.

High-quality atmospheric CO2 measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2 . In this study, we present the first 6years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal ( ) that has a marked seasonal cycle with an amplitude of about 4ppm. At both seasonal and inter-annual scales, we find differences in phase between and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of . In addition, we present how the 2015-2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.

Carbon dioxide isotopic compositions during tundra ecosystem respiration and photosynthesis in relation to environmental variables in maritime Antarctica

Stable carbon isotope ratios (13C/12C) have been extensively used to trace carbon flow, and partition net ecosystem CO2 exchange. However, the CO2 isotopic data are still very limited in terrestrial ecosystems of maritime Antarctica. Here, we chose six tundra sites to investigate the isotopic compositions of CO2 during ecosystem respiration and photosynthesis, and the relationships with environmental variables using the static chamber method. For all tundra sites, ecosystem respirated-CO2 was 13C-depleted while vegetation photosynthesis resulted in the enrichment of 13C in the chamber headspace, compared with local atmospheric CO2. The δ13C-CO2 showed a strong negative correlation with CO2 concentrations in the chamber headspace both under dark condition (r2 = 0.70, p < 0.01) and under light condition (r2 = 0.29, p < 0.05), whereas δ18O-CO2 was almost stable, only with a small fluctuation from − 7.7 to − 8.3‰. The δ13C of ecosystem-respired (δr) and photoassimilated-CO2 (δp) fluctuated from − 12.4 to − 15.1‰ and − 10.5 to − 12.6‰, respectively, indicating that lower C isotopic discrimination occurred during plant photosynthesis and tundra ecosystem respiration, compared with reported data from other global ecosystems. Overall there was a small but distinct negative carbon isotopic disequilibrium (D: − 1 to − 3‰) between δr and δp at the spatial or summertime scale. The δp and δr showed consistent summertime variation patterns with significant positive correlation (r2 = 0.95, p < 0.01). The δr and δp significantly negatively correlated with respiration rates (r2 = 0.91, p < 0.01) and photosynthesis rates (r2 = 0.86, p < 0.01), respectively, and the δr, instead of δp, significantly correlated with net ecosystem exchange fluxes (r2 = 0.75, p = 0.012). The summertime patterns of δr, δp and D sensitively corresponded to changing temperature, precipitation and sunlight intensity, supporting the links between CO2 isotope fractionation and environmental variables during ecosystem respiration and plant photosynthesis. It was found that penguin activities had no significant effect on δr and δp although their activities significantly increased tundra ecosystem respiration and photosynthesis fluxes. The investigation of CO2 isotopic compositions contributes to better understanding of carbon cycling in maritime Antarctic tundra ecosystems.

Carbon Dioxide and Methane Flux Response and Recovery From Drought in a Hemiboreal Ombrotrophic Fen

Globally peatlands store 500 Gt carbon (C), with northern blanket bogs accumulating 23 g C m−2 y−1 due to cool wet conditions. As a sink of carbon dioxide (CO2) peat bogs slow anthropogenic climate change, but warming climate increases the likelihood of drought which may reduce net ecosystem exchange (NEE) and increase soil respiration, tipping C sinks to sources. High water tables make bogs a globally important source of methane (CH4), another greenhouse gas (GHG) with a global warming potential (GWP) 34 times that of CO2. Warming may increase CH4 emissions, but drying may cause a reduction. Predicted species composition changes may also influence GHG balance, due to different traits such as erenchyma, e.g., Eriophorum vaginatum (eriophorum) and non-aerenchymatous species, e.g., Calluna vulgaris (heather). To understand how these ecosystems will respond to climate change, it is vital to measure GHG responses to drought at the species level. An automated chamber system, SkyLine2D, measured NEE and CH4 fluxes near-continuously from an ombrotrophic fen from August 2017 to September 2019. Four ecotypes were identified: sphagnum (Sphagnum spp), eriophorum, heather and water, hypothesizing that fluxes would significantly differ between ecotypes. The 2018 drought allowed comparison of fluxes between drought and non-drought years (May to September), and their recovery the following year. Methane emissions differed between ecotypes (p &amp;lt; 0.02), ordered high to low: eriophorum &amp;gt; sphagnum &amp;gt; water &amp;gt; heather, ranging from 23 to 8 mg CH4-C m−2 d−1. Daily NEE was similar between ecotypes (p &amp;gt; 0.7), but under 2018 drought conditions all ecotypes were greater sources of CO2 compared to 2019, losing 1.14 g and 0.24 g CO2-C m−2 d−1 respectively (p &amp;lt; 0.001). CH4 emissions were ca. 40% higher during 2018 than 2019, 17 mg compared to 12 mg CH4-C m−2 d−1 (p &amp;lt; 0.0001), and fluxes exhibited hysteresis with water table depth. A lag of 84–88 days was observed between rising water table and increased CH4 emissions. A significant interaction between ecotype and year showed fluxes from open water did not return to pre-drought levels. Our findings suggest that short-term drought may lead to a net increase in C emissions from northern wetlands.

Description of local carbon flux from large scale gridded climate data by a dynamic global vegetation model at variable time steps: Example of Euroflux sites

Dynamic Global Vegetation Models (DGVMs) are commonly used to describe the land biogeochemical processes and regulate carbon and water pools. However, the simulation efficiency and validation of DGVMs are limited to varying temporal and spatial resolutions. Additionally, the uncertainties caused by different interpolation methods used in DGVMs are still not clear. In this study, we employ Socio-Economic and natural Vegetation ExpeRimental (SEVER) DGVM to simulate Net Ecosystem Exchange (NEE) flux with large scale National Centers for Environmental Prediction (NCEP) daily climate data as inputs for the years 1997–2000 at 14 Euroflux sites. It is shown that daily local NEE flux on chosen sites can be reasonably simulated, and daily temperature and shortwave radiation are the most essential inputs for daily NEE simulation compared with precipitation and the ratio of sunshine hours. Different running means (1 to 30 days) methods are analysed for each Euroflux site, and the best results of both averaged regression coefficient and averaged slope of regression are discovered by using 5 days running mean method. SEVER DGVM, driven by linearly interpolated daily climate data is compared at the monthly time step with Lund-Potsdam-Jena (LPJ) DGVM, which combines the linear interpolation of daily temperature with stochastic generation of daily precipitation. The comparison demonstrates that the stochastic generation of daily precipitation provides an acceptable fit to local observed NEE, but with a slight decrease in accuracy. Simulation experiments with SEVER DGVM demonstrate that daily local NEE flux inside a grid cell for a region as large as Europe can be modelled by DGVMs, using only large scale climate data as inputs.

A novel robotic chamber system allowing to accurately and precisely determining spatio-temporal CO2 flux dynamics of heterogeneous croplands

The precise and accurate assessment of carbon dioxide (CO2) exchange is crucial to identify terrestrial carbon (C) sources and sinks and for evaluating their role within the global C budget. The substantial uncertainty in disentangling the management and soil impact on measured CO2 fluxes are largely ignored especially in cropland. The reasons for this lies in the limitation of the widely used eddy covariance as well as manual and automatic chamber systems, which either account for short-term temporal variability or small-scale spatial heterogeneity, but barely both. To address this issue, we developed a novel robotic chamber system allowing for dozens of spatial measurement repetitions, thus enabling CO2 exchange measurements in a sufficient temporal and high small-scale spatial resolution. The system was tested from 08th July to 09th September 2019 at a heterogeneous field (100 m × 16 m), located within the hummocky ground moraine landscape of northeastern Germany (CarboZALF-D). The field is foreseen for a longer-term block trial manipulation experiment extending over three erosion induced soil types and was covered with spring barley. Measured fluxes of nighttime ecosystem respiration (Reco) and daytime net ecosystem exchange (NEE) showed distinct temporal patterns influenced by crop phenology, weather conditions and management practices. Similarly, we found clear small-scale spatial differences in cumulated (gap-filled) Reco, gross primary productivity (GPP) and NEE fluxes affected by the three distinct soil types. Additionally, spatial patterns induced by former management practices and characterized by differences in soil pH and nutrition status (P and K) were also revealed between plots within each of the three soil types, which allowed compensating for prior to the foreseen block trial manipulation experiment. The results underline the great potential of the novel robotic chamber system, which not only detects short-term temporal CO2 flux dynamics but also reflects the impact of small-scale spatial heterogeneity.

C-exchange and balance following clear-cutting in hemiboreal forest ecosystem under summer drought

Growth of CO2 concentration level has strong interactions with forests. Forests are able to sequester carbon (C) through photosynthesis and can help to mitigate the effects of climate warming, as well as to reduce the CO2 concentration in the atmosphere. Drought and other extreme weather conditions play a key role in ecosystem functioning and the C-cycle. The eddy covariance (EC) method can be used to better understand forest ecosystems CO2 exchange by directly measuring net carbon and water fluxes. In our study, EC results for measurement of fluxes between the atmosphere and forest canopy are reported for the study period from May to August 2018 in Järvselja, Estonia. Stand-replacing disturbance (clear-cutting) took place in April 2013. The young forest stand is dominated by Norway spruce (Picea abies) and birch (Betula spp.). Findings so far include (1) a C-budget for the study period that showed a slight C-sink status; (2) net ecosystem exchange (NEE) was −0.0084 µmol m−2 s−1 indicating C-uptake during the measurement period; (3) in May, June, July and August, NEE was −0.027, −0.015, 0.001 and 0.006 µmol m−2 s−1, respectively; (4) NEE fluxes are lower in drought conditions and are affected by temperature that averaged 15 °C.

Prior biosphere model impact on global terrestrial CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; fluxes estimated from OCO-2 retrievals

Abstract. This study assesses the impact of different state of the art global biospheric CO2 flux models, when applied as prior information, on inverse model “top-down” estimates of terrestrial CO2 fluxes obtained when assimilating Orbiting Carbon Observatory 2 (OCO-2) observations. This is done with a series of observing system simulation experiments (OSSEs) using synthetic CO2 column-average dry air mole fraction (XCO2) retrievals sampled at the OCO-2 satellite spatiotemporal frequency. The OSSEs utilized a 4-D variational (4D-Var) assimilation system with the GEOS-Chem global chemical transport model (CTM) to estimate CO2 net ecosystem exchange (NEE) fluxes using synthetic OCO-2 observations. The impact of biosphere models in inverse model estimates of NEE is quantified by conducting OSSEs using the NASA-CASA, CASA-GFED, SiB-4, and LPJ models as prior estimates and using NEE from the multi-model ensemble mean of the Multiscale Synthesis and Terrestrial Model Intercomparison Project as the “truth”. Results show that the assimilation of simulated XCO2 retrievals at OCO-2 observing modes over land results in posterior NEE estimates which generally reproduce “true” NEE globally and over terrestrial TransCom-3 regions that are well-sampled. However, we find larger spread among posterior NEE estimates, when using different prior NEE fluxes, in regions and seasons that have limited OCO-2 observational coverage and a large range in “bottom-up” NEE fluxes. Seasonally averaged posterior NEE estimates had standard deviations (SD) of ∼10 % to ∼50 % of the multi-model-mean NEE for different TransCom-3 land regions with significant NEE fluxes (regions/seasons with a NEE flux ≥0.5 PgC yr−1). On a global average, the seasonally averaged residual impact of the prior model NEE assumption on the posterior NEE spread is ∼10 %–20 % of the posterior NEE mean. Additional OCO-2 OSSE simulations demonstrate that posterior NEE estimates are also sensitive to the assumed prior NEE flux uncertainty statistics, with spread in posterior NEE estimates similar to those when using variable prior model NEE fluxes. In fact, the sensitivity of posterior NEE estimates to prior error statistics was larger than prior flux values in some regions/times in the tropics and Southern Hemisphere where sufficient OCO-2 data were available and large differences between the prior and truth were evident. Overall, even with the availability of spatiotemporally dense OCO-2 data, noticeable residual differences (up to ∼20 %–30 % globally and 50 % regionally) in posterior NEE flux estimates remain that were caused by the choice of prior model flux values and the specification of prior flux uncertainties.

On what scales can GOSAT flux inversions constrain anomalies in terrestrial ecosystems?

Abstract. Interannual variations in temperature and precipitation impact the carbon balance of terrestrial ecosystems, leaving an imprint in atmospheric CO2. Quantifying the impact of climate anomalies on the net ecosystem exchange (NEE) of terrestrial ecosystems can provide a constraint to evaluate terrestrial biosphere models against and may provide an emergent constraint on the response of terrestrial ecosystems to climate change. We investigate the spatial scales over which interannual variability in NEE can be constrained using atmospheric CO2 observations from the Greenhouse Gases Observing Satellite (GOSAT). NEE anomalies are calculated by performing a series of inversion analyses using the GEOS-Chem adjoint model to assimilate GOSAT observations. Monthly NEE anomalies are compared to “proxies”, variables that are associated with anomalies in the terrestrial carbon cycle, and to upscaled NEE estimates from FLUXCOM. Statistically significant correlations (P&lt;0.05) are obtained between posterior NEE anomalies and anomalies in soil temperature and FLUXCOM NEE on continental and larger scales in the tropics, as well as in the northern extratropics on subcontinental scales during the summer (R2≥0.49), suggesting that GOSAT measurements provide a constraint on NEE interannual variability (IAV) on these spatial scales. Furthermore, we show that GOSAT flux inversions are generally better correlated with the environmental proxies and FLUXCOM NEE than NEE anomalies produced by a set of terrestrial biosphere models (TBMs), suggesting that GOSAT flux inversions could be used to evaluate TBM NEE fluxes.

Cushion bogs are stronger carbon dioxide net sinks than moss-dominated bogs as revealed by eddy covariance measurements on Tierra del Fuego, Argentina

Abstract. The near-pristine bog ecosystems of Tierra del Fuego in southernmost Patagonia have so far not been studied in terms of their current carbon dioxide (CO2) sink strength. CO2 flux data from Southern Hemisphere peatlands are scarce in general. In this study, we present CO2 net ecosystem exchange (NEE) fluxes from two Fuegian bog ecosystems with contrasting vegetation communities. One site is located in a glaciogenic valley and developed as a peat moss-dominated raised bog, and the other site is a vascular plant-dominated cushion bog located at the coast of the Beagle Channel. We measured NEE fluxes with two identical eddy covariance (EC) setups at both sites for more than 2 years. With the EC method, we were able to observe NEE fluxes on an ecosystem level and at high temporal resolution. Using a mechanistic modeling approach, we estimated daily NEE models to gap fill and partition the half-hourly net CO2 fluxes into components related to photosynthetic uptake (gross primary production, GPP) and to total ecosystem respiration (TER). We found a larger relative variability of annual NEE sums between both years at the moss-dominated site. A warm and dry first year led to comparably high TER sums. Photosynthesis was also promoted by warmer conditions but less strongly than TER with respect to absolute and relative GPP changes. The annual NEE carbon (C) uptake was more than 3 times smaller in the warm year. Close to the sea at the cushion bog site, the mean temperature difference between both observed years was less pronounced, and TER stayed on similar levels. A higher amount of available radiation in the second observed year led to an increase in GPP (5 %) and NEE (35 %) C uptake. The average annual NEE-C uptake of the cushion bog (-122±76 gm-2a-1, n=2) was more than 4 times larger than the average uptake of the moss-dominated bog (-27±28 gm-2a-1, n=2).

Observing the Whole-Canopy Short-Term Dynamic Response to Natural Step Changes in Incident Light: Characteristics of Tropical and Temperate Forests

We examine the physical and biological responses of forest canopies to step changes in light caused by passing low cumulus clouds that intermittently block the direct solar beam. Using data obtained at a tropical rainforest and at a midlatitude deciduous forest, we estimate the course of sensible heat flux, net ecosystem exchange, evapotranspiration, and water-use efficiency in response to the rapid changes in the incident radiative flux. To describe these fluxes during the interval over which the effects of stomatal time delays can be most influential, eddy fluxes are estimated over minute or shorter intervals by invoking a conditional-sampling procedure based on forming a Reynolds-average ensemble. The most important differences between the two forests’ physical responses are in the thermal balances and heat-flux time response constants. During the initial period after the light transition the only mean variables that show appreciable changes are the blackbody and air temperatures, the other scalars being little affected. We find that a distinct transient thermal internal boundary layer appears ≈ 20 m thick above the temperate deciduous forest and ≈ 45 m thick above the tropical rainforest. At each forest, the effective thickness of the inferred thermal outer-canopy ‘big leaf’ is about 1 mm. Twenty minutes after the abrupt change in incident light, ensemble eddy-flux estimates approach those found using conventional time averaging, confirming the validity of the ensemble approach. Previously unrecognized transient maxima in net ecosystem exchange and evapotranspiration are evident 5–10 min following the shadow-to-light transition, longer than the average light interval between shadows observed on partly-cloudy days in each case. Short-term variations in sensible heat flux, net ecosystem exchange, and evapotranspiration approximate an exponential adjustment, implying that first-order time-dependent single-leaf models are adequate to describe whole-canopy processes in these cases, providing an experimental method for determining whole-canopy bulk stomatal time constants. During the sunlit interval (direct and diffuse radiative fluxes combined) net ecosystem exchange is enhanced, while under cloud shadow (only diffuse radiative flux) water-use efficiency increases. This light and shadow alternation provides a mechanism describing the observed enhanced net ecosystem exchange and water-use efficiency under certain types of partly-cloudy sky. We apply empirical flux-response curves to an idealized case of radiative flux varying in a regular on–off light and shadow pattern. For this case, an analytical solution for mean net ecosystem exchange flux as a function of diffuse-radiation fraction yields results that strongly resemble previous findings based on conventional time-averaged fluxes. Our analysis and modelling indicates that a well-known correlation between diffuse radiative flux and enhanced net ecosystem exchange and water-use efficiency on cloudy days is in many cases not causal, but rather to be a consequence of time averaging over light-and-shadow intervals. By linking processes associated with photosynthesis in fluctuating light at the leaf scale to the canopy scale, our efforts facilitate the scaling-up of leaf responses to the ecosystem scale.