Net Ecosystem Exchange Research Articles

Technical note: Flagging inconsistencies in flux tower data

Abstract. Global collections of synthesized flux tower data such as FLUXNET have accelerated scientific progress beyond the eddy covariance community. However, remaining data issues in FLUXNET data pose challenges for users, particularly for multi-site synthesis and modelling activities. Here, we present complementary consistency flags (C2Fs) for flux tower data, which rely on multiple indications of inconsistency among variables, along with a methodology to detect discontinuities in time series. The C2F relates to carbon and energy fluxes, as well as to core meteorological variables, and consists of the following: (1) flags for daily data values, (2) flags for entire-site variables, and (3) flags at time stamps that mark large discontinuities in the time series. The flagging is primarily based on combining outlier scores from a set of predefined relationships among variables. The methodology to detect break points in the time series is based on a non-parametric test for the difference in distributions of model residuals. Applying C2F to the FLUXNET 2015 dataset reveals the following: (1) among the considered variables, gross primary productivity and ecosystem respiration data were flagged most frequently, in particular during rain pulses under dry and hot conditions. This information is useful for modelling and analysing ecohydrological responses. (2) There are elevated flagging frequencies for radiation variables (shortwave, photosynthetically active, and net). This information can improve the interpretation and modelling of ecosystem fluxes with respect to issues in the driver. (3) The majority of long-term sites show temporal discontinuities in the time series of latent energy, net ecosystem exchange, and radiation variables. This should be useful for carefully assessing the results in terms of interannual variations in and trends of ecosystem fluxes. The C2F methodology is flexible for customizing and allows for varying the desired strictness of consistency. We discuss the limitations of the approach that can present starting points for future developments.

Radiative and Chemical Effects of Non‐Homogeneous Methane on Terrestrial Carbon Fluxes in Asia

AbstractMethane (CH4) plays a crucial role in shaping terrestrial ecosystems due to its radiative effect and atmospheric photochemical reactions. In this study, we employed an enhanced regional climate‐chemistry‐ecosystem model (RegCM‐Chem‐YIBs) to comprehensively evaluate the impacts of both radiative and chemical effects of CH4 on terrestrial carbon fluxes across the East, South, and Southeast Asia (EA, SA, SEA) during the year 2010. Our findings showed that the radiative effects of CH4 yielded a positive influence on carbon fluxes. Specifically, the EA region experienced a significant increase in the gross primary production (GPP), reaching up to 0.515 Pg C Yr−1. In comparison, the SEA region exhibited a decrease in the net ecosystem exchange (NEE) of approximately −0.066 Pg C Yr−1. Further analysis revealed that alterations in radiation and vapor pressure deficit (VPD) were dominant drivers. Conversely, the chemical effects of CH4 lead to heightened regional surface ozone (O3) concentrations (2.704–3.115 ppb) and generate a negative response in carbon fluxes. Within the SEA region, GPP observed a decrease of up to −0.144 Pg C Yr−1, while NEE displayed a significant increase of 0.022 Pg C Yr−1. Taken together, the combined radiative and chemical effects of CH4 indicated a positive impact on regional carbon fluxes, with GPP increasing by 0.632 Pg C Yr−1 and NEE decreasing by −0.09 Pg C Yr−1. This holistic perspective is crucial for comprehending the intricate interactions linking climate change, atmospheric pollution, and the global carbon cycle.

Wet canopy photosynthesis in a temperate Japanese cypress forest.

This study aimed to reveal the mechanism and significance of wet canopy photosynthesis during and after rainfall in temperate coniferous ecosystems by evaluating the influence of abaxial leaf interception on wet canopy photosynthesis. We used the eddy covariance method in conjunction with an enclosed-path gas analyser to conduct continuous ecosystem CO2 flux observations in a Japanese cypress forest within the temperate Asian monsoon area over 3years. The observation shows that wet-canopy CO2 uptake predominantly occurred during the post-rainfall canopy-wet period rather than the during-rainfall period. Then, the measured canopy-wet net ecosystem exchange was compared with the soil-vegetation-atmosphere transfer multilayer model simulations under different parameter settings of the abaxial (lower) leaf surface wet area ratio. The multilayer model predicted net ecosystem exchange most accurately when it assumed the wet area ratio of the abaxial surface was 50% both during and after rainfall. For the wet canopy both during and after rainfall, the model overestimated CO2 uptake when it assumed no abaxial interception in the simulation, but underestimated CO2 uptake when it assumed that the entire abaxial leaf surface was wet. These results suggest that the abaxial surface of the Japanese cypress leaf is only partly wet to maintain stomatal openness and a low level of photosynthesis. These results allow for an evaluation of the effect of rainfall on forest carbon circulation under a changing climate, facilitating an improvement of ecosystem carbon exchange models.

A Typical Small Watershed in Southwestern China Is Demonstrated as a Significant Carbon Sink

Small watersheds are fundamental units for natural processes and social management in Southwestern China. Accurately assessing carbon sinks in small watersheds is crucial for formulating carbon sink management policies. However, there has been a lack of assessment of the dynamics of carbon fluxes in the major ecosystems of small watersheds. Here, we selected the Reshuihe River watershed, which is a typical small watershed in Southwestern China, to measure carbon fluxes using eddy covariance systems for two years (October 2021 to September 2023) from three major ecosystems, namely forest, cropland, and non-timber forest. We compared variations and controlling factors of net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (Re) among different ecosystems, and estimated annual watershed carbon flux based on the land cover areas of the three ecosystems. This study found that three ecosystems were net annual carbon sinks during the study period. Forest was the strongest (−592.8 and −488.1 gC m−2 a−1), followed by non-timber forest (−371.0 gC m−2 a−1), and cropland was the smallest (−92.5 and −71.6 gC m−2 a−1), after taking fallow period into account. Weeds were a significant source of carbon flux in non-timber forest ecosystems. It was also found that variations in daily NEE were controlled by photosynthetically active radiation and soil volumetric water content, with weak effects related to temperature also being observed. However, when the temperature exceeded 21 °C, GPP and Re were significantly reduced in cropland. Finally, it was discovered that the total carbon sink of the three ecosystems in the watershed for one year was −52.15 Gg C. Overall, we found that small watersheds dominated by forest ecosystems in Southwestern China have a strong carbon sink capacity.

Differential responses of respiration and photosynthesis to air temperature over a moist tundra ecosystem of Alaska and its impact on changing carbon cycle

This study analyzed the sensitivities of carbon cycle to surface air temperature using the CO2 flux data collected from June to September for six years (2014–2019) over a moist tundra site in Council, Alaska. The tundra ecosystem was a strong sink of carbon in June and July, a weak sink in August with rapidly decreasing photosynthesis, and a carbon source in September. The ecosystem respiration (Re) and gross primary production (GPP) were obtained from the net ecosystem exchange (NEE) of eddy-covariance system. Both the Re and GPP increased with temperature, enhancing carbon emission and uptake during observation period. Notably, Re showed higher sensitivity to temperature than GPP did. This result means that as global warming continues, the increase in carbon release is greater than the increase in carbon uptake. In other words, the tundra ecosystem is expected to become a weaker carbon sink in June and July and a stronger source of carbon in September. Possible mechanism of different temperature sensitivities of Re and GPP as well as temporal variations of temperature sensitivities are suggested. Present results highlight the importance of understanding the temperature sensitivities of Re and GPP in various tundra ecosystems to accurately understand changes in the carbon cycle in the Arctic region.

Carbon fluxes of China's coastal wetlands and impacts of reclamation and restoration.

Coastal wetlands play an important role in regulating atmospheric carbon dioxide (CO2) concentrations and contribute significantly to climate change mitigation. However, climate change, reclamation, and restoration have been causing substantial changes in coastal wetland areas and carbon exchange in China during recent decades. Here we compiled a carbon flux database consisting of 15 coastal wetland sites to assess the magnitude, patterns, and drivers of carbon fluxes and to compare fluxes among contrasting natural, disturbed, and restored wetlands. The natural coastal wetlands have the average net ecosystem exchange of CO2 (NEE) of -577 g C m-2 year-1, with -821 g C m-2 year-1 for mangrove forests and -430 g C m-2 year-1 for salt marshes. There are pronounced latitudinal patterns for carbon dioxide exchange of natural coastal wetlands: NEE increased whereas gross primary production (GPP) and respiration of ecosystem decreased with increasing latitude. Distinct environmental factors drive annual variations of GPP between mangroves and salt marshes; temperature was the dominant controlling factor in salt marshes, while temperature, precipitation, and solar radiation were co-dominant in mangroves. Meanwhile, both anthropogenic reclamation and restoration had substantial effects on coastal wetland carbon fluxes, and the effect of the anthropogenic perturbation in mangroves was more extensive than that in salt marshes. Furthermore, from 1980 to 2020, anthropogenic reclamation of China's coastal wetlands caused a carbon loss of ~3720 Gg C, while the mangrove restoration project during the period of 2021-2025 may switch restored coastal wetlands from a carbon source to carbon sink with a net carbon gain of 73 Gg C. The comparison of carbon fluxes among these coastal wetlands can improve our understanding of how anthropogenic perturbation can affect the potentials of coastal blue carbon in China, which has implications for informing conservation and restoration strategies and efforts of coastal wetlands.

Modeling net ecosystem exchange of CO2 with gated recurrent unit neural networks

The complex forcing mechanisms of biophysical drivers on ecosystem productivity, as well as some unknown relationships, stipulates the application of artificial intelligence techniques in modeling the ecosystem carbon cycle. In particular, various deep learning algorithms have been successfully applied to comprehend temporal relationships, though some issues regarding capturing temporal features for modeling CO2 fluxes across time scales remain unsolved. In this study, a gated recurrent unit (GRU) model was trained for simulating half-hourly net ecosystem exchange of CO2 (NEE) using 12-year continuous flux data (2009–2020) from seven experimental bioenergy crops in southwest Michigan, USA. The fields were historically managed either as corn-soybean rotation agricultural (AGR) or Conservation Reserve Program (CRP) lands and planted to no-till corn (AGR-C and CRP-C), restored-prairie (AGR-Pr and CPR-Pr), switchgrass (AGR-Sw and CRP-Sw) and smooth brome grass (CRP-Ref). We compared NEE simulations for the entire year, growing season, and non-growing season datasets, and analyzed relative importance of biophysical variables on variations of NEE. GRU performed well in simulating NEE at single site, with R2 of 0.89–0.93, 0.85–0.90, and 0.61–0.85 for the annual, growing season, and non-growing season datasets, respectively, which provided comparable accuracy and 6 % of run-time shorter than those of long short-term memory. R2 reached 0.70 and 0.80 across all sites and unique land-cover types. Radiation parameters contributed most to the variability of NEE. Contributions of individual variables appear more complex during the non-growing season and include incoming shortwave radiation, day of year, temperature, Monin-Obukhov stability, wind direction, and soil water content. The six most important forcing variables are consistent with our current understanding, although their ranked importance varied by ecosystem type and modeling scale. These results bring renewed insights in modeling observations at seasonal scales and provide guidance for variable selection to scale up measurements from one site to multiple land-cover types across the landscape.

Canopy Heterogeneity and Environmental Variability Drive Annual Budgets of Net Ecosystem Carbon Exchange in a Tidal Marsh

AbstractTidal salt marshes are important ecosystems in the global carbon cycle. Understanding their net carbon exchange with the atmosphere is required to accurately estimate their net ecosystem carbon budget (NECB). In this study, we present the interannual net ecosystem exchange (NEE) of CO2 derived from eddy covariance (EC) for a Spartina alterniflora salt marsh. We found interannual NEE could vary up to 3‐fold and range from −58.5 ± 11.3 to −222.9 ± 12.4 g C m−2 year−1 in 2016 and 2020, respectively. Further, we found that atmospheric CO2 fluxes were spatially dependent and varied across short distances. High biomass regions along tidal creek and estuary edges had up to 2‐fold higher annual NEE than lower biomass marsh interiors. In addition to the spatial variation of NEE, regions of the marsh represented by distinct canopy zonation responded to environmental drivers differently. Low elevation edges (with taller canopies) had a higher correlation with river discharge (R2 = 0.61), the main freshwater input into the system, while marsh interiors (with short canopies) were better correlated with in situ precipitation (R2 = 0.53). Lastly, we extrapolated interannual NEE to the wider marsh system, demonstrating the potential underestimation of annual NEE when not considering spatially explicit rates of NEE. Our work provides a basis for further research to understand the temporal and spatial dynamics of productivity in coastal wetlands, ecosystems which are at the forefront of experiencing climate change induced variability in precipitation, temperature, and sea level rise that have the potential to alter ecosystem productivity.

Joint assimilation of satellite-based surface soil moisture and vegetation conditions into the Noah-MP land surface model

This study explores the potential of integrating satellite retrievals of surface soil moisture (SSM) and vegetation conditions into the Noah-MP land surface model. In total, five data assimilation (DA) experiments were carried out. One of the experiments only assimilates SSM retrievals from the Soil Moisture Active Passive mission, two experiments only assimilate retrievals of vegetation conditions: either optical retrievals of leaf area index (LAI) from the Copernicus Global Land Service, or X-band microwave-based retrievals of vegetation optical depth (VOD) from the Advanced Microwave Scanning Radiometer 2. Additionally, two joint DA experiments are performed, each incorporating SSM and one of the vegetation products. The DA experiments are compared with a model-only run, and all experiments are evaluated using independent ground reference data of soil moisture, evapotranspiration, net ecosystem exchange and gross primary production (GPP). Assimilating only SSM improves estimates of the soil moisture profile (median SSM anomaly correlation improves with 0.02 compared to a model-only run), whereas assimilating LAI predominantly improves GPP estimates (reduction in median RMSD of 0.024 gC m−2 day−1 compared to a model-only run). The joint assimilation of SSM and vegetation conditions captures both of these improvements in a single, physically consistent analysis product. The DA increments show that this combined setup allows one satellite product to compensate for potential degradations introduced into the system by the other product. Furthermore, the joint SSM and VOD DA experiment has the smallest ensemble spread in its estimates (21% reduction in SSM spread compared to a model-only run). Overall, our results underline the potential of multi-sensor and multivariate DA, in which information from different sources is combined to improve the estimates of several land surface states and fluxes simultaneously.

Drainage Influences Coastal Salt Marsh Productivity and Soil Biogeochemistry

Coastal wetlands display ecohydrological zonation such that horizontal differences in plant zones are driven by soil aeration and varying groundwater levels. However, it is less clear how variable levels of drainage directly impact biotic and abiotic factors in coastal wetland ecosystems. To determine the impacts of drainage levels, simulated tides in mesocosms with varying degrees of drainage were created with Spartina alterniflora and Salicornia pacifica, the dominant coastal salt marsh plant species on the United States’ Atlantic and Pacific coasts respectively. We measured biomass production and photosynthesis as indicators of plant health, and we also measured soil and porewater characteristics to help interpret patterns of productivity. These measures included above and belowground biomass, porewater pH, salinity, ammonium concentration, sulfide concentration, soil redox potential, net ecosystem exchange, photosynthesis rate, respiration rate, and methane flux. We found the greatest plant production in soils with intermediate drainage levels, with production values that were 13.7% higher for S. alterniflora and 57.7% higher for S. pacifica. Understanding how drainage impacts plant species is important for predicting wetland resilience to sea level rise, as increasing water levels alter ecohydrological zonation.

Comparison of carbon and water fluxes and the drivers of ecosystem water use efficiency in a temperate rainforest and a peatland in southern South America

Abstract. The variability and drivers of carbon and water fluxes and their relationship to ecosystem water use efficiency (WUE) in natural ecosystems of southern South America are still poorly understood. For 8 years (2015–2022), we measured carbon dioxide net ecosystem exchange (NEE) and evapotranspiration (ET) using eddy covariance towers in a temperate rainforest and a peatland in southern Chile. NEE was partitioned into gross primary productivity (GPP) and ecosystem respiration (Reco), while ET was partitioned into evaporation (E) and transpiration (T) and used to estimate different expressions of ecosystem WUE. We then used the correlation between detrended time series and structural equation modelling to identify the main environmental drivers of WUE, GPP, ET, E and T. The results showed that the forest was a consistent carbon sink (−486 ± 23 g C m−2 yr−1), while the peatland was, on average, a small source (33 ± 21 g C m−2 yr−1). WUE is low in both ecosystems and likely explained by the high annual precipitation in this region (∼ 2100 mm). Only expressions of WUE that included atmospheric water demand showed seasonal variation. Variations in WUE were related more to changes in ET than to changes in GPP, while T remained relatively stable, accounting for around 47 % of ET for most of the study period. For both ecosystems, E increased with higher global radiation and higher surface conductance and when the water table was closer to the surface. Higher values for E were also found with increased wind speeds in the forest and higher air temperatures in the peatland. The absence of a close relationship between ET and GPP is likely related to the dominance of plant species that either do not have stomata (i.e. mosses in the peatland or epiphytes in the forest) or have poor stomatal control (i.e. anisohydric tree species in the forest). The observed increase in potential ET in the last 2 decades and the projected drought in this region suggests that WUE could increase in these ecosystems, particularly in the forest, where stomatal control may be more significant.

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.

The Productivity and Carbon Exchange of an Intensively Managed Pasture in Central Kentucky

Intensive pasture management that aims at providing season-long forage while minimizing soil degradation is increasingly becoming an important grazing strategy in Kentucky. Typically, it involves the use of high-yielding warm and cool season forage species that are well suited to local soil and climate conditions, meeting the dual-purpose provision of high nutritional value while remaining resilient to grazing pressure and changing climate. Monitoring carbon exchange is a crucial component for effective pasture management to promote sustainable pastureland management practices. We hypothesized that pasturelands, when intensively managed, would exhibit a small but important CO2 cumulative uptake year-round. We used the Eddy covariance method to measure the net ecosystem exchange of CO2 (NEE) and productivity of an intensively managed pastureland at Kentucky State University Research and Demonstration station from 2015 to 2020. The study has two objectives: to quantify interannual variability in net ecosystem exchange, and examine the controlling environmental factors, in particular temperature, sunlight, and precipitation of NEE. Diurnal and seasonal fluctuations followed typical patterns of carbon uptake and release. Overall, the pasture site consistently was carbon sink except for 2016, in part due to a warmer winter season than usual, sequestering 1394 gCm−2 over the study period. Precipitation and temperature were critical environmental factors underpinning seasonal CO2 uptake and release. Of critical importance was the net carbon uptake during the non-growing season.

Variables controlling growing season carbon dynamics in desert shrub ecosystem

Arid and semi-arid lands (drylands) are under the influence of extreme environmental conditions and cover large areas on Earth’s land surface. Determining temporal and spatial variations of the greenhouse gas and energy exchange in these ecosystems will provide a better understanding of both, the dynamics between the drylands’s surface and the atmosphere and the importance in climate change. In this study, CO2 exchanges over a shrub steppe ecosystem were determined using the Eddy Covariance method during both dry and wet growing seasons in the Gobi Desert, Mongolia. The net ecosystem exchange (NEE) was modeled using the extreme gradient boosting method (XGBOOST). Variables influencing NEE were estimated employing the SHapley Additive exPlanations algorithm (SHAP). The XGBOOST predictions demonstrated impressive results across all growing seasons, with high performance metrics (R2 = 0.821; NSE = 0.817), particularly notable during the wet season (R2 = 0.932; NSE = 0.929). The total NEE changed between 79.7 and -110.4 gC m−2 throughout the growing seasons. Especially the precipitation before the growing period has a positive impact on carbon sequestration in the shrub ecosystem in the following dry season. A high similarity was found in the patterns of daily NEE of all growing seasons and normalized difference vegetation index (NDVI), albedo, soil water content, temperature, sensible heat flux, the difference between air and soil temperature in desert shrub ecosystem. Although NDVI was the dominant factor during the wet season, there was a weaker relationship between these factors and NEE in the dry season than in the wet season.

A drained nutrient-poor peatland forest in boreal Sweden constitutes a net carbon sink after integrating terrestrial and aquatic fluxes.

Northern peatlands provide a globally important carbon (C) store. Since the beginning of the 20th century, however, large areas of natural peatlands have been drained for biomass production across Fennoscandia. Today, drained peatland forests constitute a common feature of the managed boreal landscape, yet their ecosystem C balance and associated climate impact are not well understood, particularly within the nutrient-poor boreal region. In this study, we estimated the net ecosystem carbon balance (NECB) from a nutrient-poor drained peatland forest and an adjacent natural mire in northern Sweden by integrating terrestrial carbon dioxide (CO2 ) and methane (CH4 ) fluxes with aquatic losses of dissolved organic C (DOC) and inorganic C based on eddy covariance and stream discharge measurements, respectively, over two hydrological years. Since the forest included a dense spruce-birch area and a sparse pine area, we were able to further evaluate the effect of contrasting forest structure on the NECB and component fluxes. We found that the drained peatland forest was a net C sink with a 2-year mean NECB of -115 ± 5 g C m-2 year-1 while the adjacent mire was close to C neutral with 14.6 ± 1.7 g C m-2 year-1 . The NECB of the drained peatland forest was dominated by the net CO2 exchange (net ecosystem exchange [NEE]), whereas NEE and DOC export fluxes contributed equally to the mire NECB. We further found that the C sink strength in the sparse pine forest area (-153 ± 8 g C m-2 year-1 ) was about 1.5 times as high as in the dense spruce-birch forest area (-95 ± 8 g C m-2 year-1 ) due to enhanced C uptake by ground vegetation and lower DOC export. Our study suggests that historically drained peatland forests in nutrient-poor boreal regions may provide a significant net ecosystem C sink and associated climate benefits.

Influence of the microtopography of patagonian peatbogs on the fluxes of greenhouse gasses and dissolved carbon in porewater

Peatlands play an important role in global carbon cycling, as they act as a natural sink of carbon dioxide (CO2) or as a source of methane (CH4). The influence of microtopography (lawns and hummock-hollow complexes) in the biogeochemical dynamics of dissolved organic and inorganic carbon (DOC and DIC) and dissolved CH4 and CO2 is generally miss-considered. Southernmost Patagonia has huge areas of pristine peatlands, which are still in a largely natural state with scarce anthropogenic influence. In this study we provide foundational insights into the dynamics of greenhouse gasses (GHGs) and DOC in Sphagnum dominated peatlands of Southern Patagonia, assessing the impact of microtopography on these dynamics. The stocks of dissolved GHGs and DOC in hummock-hollows complex and lawns were analysed at three depths (25, 50, and 75 cm) in four ombrotrophic peatbogs. CH4, N2O and CO2 fluxes, net ecosystem exchange (NEE) and gross primary productivity (GPP) were also studied. CO2 and CH4 fluxes were strongly affected by microtopography. Hummock-hollows showed higher CO2 fluxes, and temperature and radiation were the main drivers for respiration and GPP, respectively. In addition, in this microtopography, higher DOC concentrations were observed at the top depth. In contrast, lawns acted as a source of CH4, with higher emission rates and high dissolved GHGs concentration throughout the depth profile.

Constraining biospheric carbon dioxide fluxes by combined top-down and bottom-up approaches

Abstract. While the growth rate of atmospheric CO2 mole fractions can be measured with high accuracy, there are still large uncertainties in its attribution to specific regions and diverse anthropogenic and natural sources and sinks. A major source of uncertainty is the net flux of carbon dioxide from the biosphere to the atmosphere, the net ecosystem exchange (NEE). There are two major approaches to quantifying NEE: top-down approaches that typically use atmospheric inversions and bottom-up estimates that rely on process-based or data-driven models or inventories. Both top-down and bottom-up approaches have known strengths and limitations. Atmospheric inversions (e.g., those used in global carbon budgets) produce estimates of NEE that are consistent with the atmospheric CO2 growth rate at regional and global scales but are highly uncertain at smaller scales. Bottom-up data-driven models based on eddy-covariance measurements (e.g., FLUXCOM) match local observations of NEE and their spatial variability but have difficulty in accurately upscaling to a reliable global estimate. In this study, we propose combining the two approaches to produce global NEE estimates, with the goal of capitalizing on each approach's strengths and mitigating their limitations. We do this by constraining the data-driven FLUXCOM model with regional estimates of NEE derived from an ensemble of atmospheric inversions from the Global Carbon Budget 2021. To do this, we need to overcome a series of scientific and technical challenges when combining information about diverse physical variables, which are influenced by different processes at different spatial and temporal scales. We design a modeling structure that optimizes NEE by considering both the model's performance at the in situ level, based on eddy-covariance measurements, and at the level of large regions, based on atmospheric inversion estimates of NEE and their uncertainty. This resulting “dual-constraint” data-driven flux model improves on information based on single constraints (either top down or bottom up), producing robust locally resolved and globally consistent NEE spatio-temporal fields. Compared to reference estimates of the global land sink from the literature, e.g., Global Carbon Budgets, our double-constraint inferred global NEE shows a considerably smaller bias in global and tropical NEE compared to the underlying bottom-up data-driven model estimates (i.e., single constraint). The mean seasonality of our double-constraint inferred global NEE is also more consistent with the Global Carbon Budget and atmospheric inversions. At the same time, our model allows for more robustly spatially resolved NEE. The improved performance of the double-constraint model across spatial and temporal scales demonstrates the potential for adding a top-down constraint to a bottom-up data-driven flux model.

Atmospheric CO2exchanges 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.

Full phenology cycle carbon flux dynamics and driving mechanism of Moso bamboo forest.

Moso bamboo forests, widely distributed in subtropical regions, are increasingly valued for their strong carbon sequestration capacity. However, the carbon flux variations and the driving mechanisms of Moso bamboo forest ecosystems of each phenology period have not been adequately explained. Hence, this study utilizes comprehensive observational data from a Moso bamboo forest eddy covariance observation for the full phenological cycle (2011-2015), fitting a light response equation to elucidate the evolving dynamics of carbon fluxes and photosynthetic characteristics throughout the entire phenological cycle, and employing correlation and path analysis to reveal the response mechanisms of carbon fluxes to both biotic and abiotic factors. The results showed that, First, the net ecosystem exchange (NEE) of Moso bamboo forest exhibits significant variations across six phenological periods, with LSOFF demonstrating the highest NEE at -23.85 ± 12.61 gC·m-2·5day-1, followed by LSON at -19.04 ± 11.77 gC·m-2·5day-1 and FGON at -17.30 ± 9.58 gC·m-2·5day-1, while NFOFF have the lowest value with 3.37 ± 8.24 gC·m-2·5day-1. Second, the maximum net photosynthetic rate (Pmax) and apparent quantum efficiency (α) fluctuated from 0.42 ± 0.20 (FGON) to 0.75 ± 0.24 mg·m-2·s-1 (NFOFF) and from 2.3 ± 1.3 (NFOFF) to 3.3 ± 1.8 μg·μmol-1 (LSOFF), respectively. Third, based on the path analysis, soil temperature was the most important driving factor of photosynthetic rate and NEE variation, with path coefficient 0.81 and 0.55, respectively, followed by leaf area index (LAI), air temperature, and vapor pressure difference, and precipitation. Finally, interannually, increased LAI demonstrated the potential to enhance the carbon sequestration capability of Moso bamboo forests, particularly in off-years, with the highest correlation coefficient with NEE (-0.59) among the six factors. The results provide a scientific basis for carbon sink assessment of Moso bamboo forests and provide a reference for developing Moso bamboo forest management strategies.

Enhanced net CO2 exchange of a semideciduous forest in the southern Amazon due to diffuse radiation from biomass burning

Abstract. Carbon cycling in the Amazon fundamentally depends on the functioning of ecosystems and atmospheric dynamics, which are highly intricate. Few studies have hitherto investigated or measured the radiative effects of aerosols on the Amazon and Cerrado. This study examines the effects of atmospheric aerosols on solar radiation and their effects on net ecosystem exchange (NEE) in an area of semideciduous tropical forest in the north of Mato Grosso. Our results show that for a relative irradiance (f) 1.10–0.67, a decrease in incident solar radiation is associated with a reduction in the NEE. However, an average increase of 25 %–110 % in NEE was observed when pollution levels and aerosol optical depth (AOD) were above ≈ 1.25 and f < 0.5. The increase NEE was attributed to the increase of up to 60 % in the diffuse fraction of photosynthetically active radiation. The change in AOD and f was mainly attributable to biomass burning organic aerosols from fires. Important influences on vapor pressure deficit (VPD) as well as air temperature (Tair) and canopy (LCT), induced by the interaction between solar radiation and high aerosol load in the observation area, were also noticed. On average, a cooling of about 3–4 ∘C was observed for Tair and LCT, and a decrease of up to 2–3 hPa was observed for VPD. Given the long-distance transport of aerosols emitted by burning biomass, significant changes in atmospheric optical properties and irradiance will impact the CO2 flux of semideciduous forests distributed in the region.