Mean Net Ecosystem Exchange Research Articles

Exploring the interplay between soil thermal and hydrological changes and their impact on carbon fluxes in permafrost ecosystems

Accelerated warming of the Arctic can affect the global climate system by thawing permafrost and exposing organic carbon in soils to decompose and release greenhouse gases into the atmosphere. We used a process-based biosphere model (DVM-DOS-TEM) designed to simulate biophysical and biogeochemical interactions between the soil, vegetation, and atmosphere. We varied soil and environmental parameters to assess the impact on cryohydrological and biogeochemical outputs in the model. We analyzed the responses of ecosystem carbon balances to permafrost thaw by running site-level simulations at two long-term tundra ecological monitoring sites in Alaska: Eight Mile Lake (EML) and Imnavait Creek Watershed (IMN), which are characterized by similar tussock tundra vegetation but differing soil drainage conditions and climate. Model outputs showed agreement with field observations at both sites for soil physical properties and ecosystem CO2 fluxes. Model simulations of Net Ecosystem Exchange (NEE) showed an overestimation during the frozen season (higher CO2 emissions) at EML with a mean NEE of 26.98 ± 4.83 gC/m2/month compared to observational mean of 22.01 ± 5.67 gC/m2/month, and during the fall months at IMN, with a modeled mean of 19.21 ± 7.49 gC/m2/month compared to observation mean of 11.9 ± 4.45 gC/m2/month. Our results underscore the importance of representing the impact of soil drainage conditions on the thawing of permafrost soils, particularly poorly drained soils, which will drive the magnitude of carbon released at sites across the high-latitude tundra. These findings can help improve predictions of net carbon releases from thawing permafrost, ultimately contributing to a better understanding of the impact of Arctic warming on the global climate system.

Spatiotemporal characteristics of Net Ecosystem Exchange in the Beijing-Tianjin sand source region and its response to drought

In the context of global change, the carbon budget in arid and semi-arid regions have changed significantly. Understanding these dynamic features and their response to climate change is essential for regional carbon cycle assessments. The Beijing-Tianjin Sand Source Region (BTSSR), a significant ecological project in China, is central to studies on carbon budget dynamics. While global change intensifies, understanding its carbon budget response to drought is crucial. By integrating data from the Net Ecosystem Exchange (NEE) and the Standardized Precipitation Evapotranspiration Index (SPEI), we analyzed the spatiotemporal attributes of NEE in this region and its response to drought. The BTSSR is currently in a carbon sink state, with the mean NEE being −45.13 gCm−2 and a rate of change at −0.005 gCm−2a-1. The maximum carbon sink occurs during the summer, whereas the winter is characterized by a net release of carbon to the atmosphere. In terms of spatial variation, the NEE shifts from positive to negative from southeast to northwest across the region. The impact of drought on summer NEE is notably significant, with the correlation and sensitivity being −0.717 (p < 0.05) and −3.911, respectively. As drought intensity increases, NEE changes from negative to positive, transforming BTSSR into a carbon source. NEE responded most significantly to strong drought and was less affected by light drought. The NEE of BTSSR showed a significant short-term response to drought, with a lag of 1–4 months. Considering different vegetation types, the temperate desert’s NEE is most significantly affected by drought and is the most sensitive, with correlation and sensitivity values of −0.841 (p < 0.05) and −12.570, respectively. In contrast, the warm temperate deciduous broadleaf forest shows stronger resistance to drought. This study elucidates how the carbon budget of different vegetation types in a typical ecological engineering area changes under the background of climate change and human activities, and contributes to the understanding of the impacts of drought events on the carbon cycle of different vegetation types, as well as the response of the latter to the former, especially the lagged response. It provides different perspectives for the subsequent ecological engineering construction.

Very high-resolution Net Ecosystem Exchange over India using Vegetation Photosynthesis and Respiration Model (VPRM) simulations

The terrestrial biosphere has a crucial role in controlling the rate of CO2 accumulation in the atmosphere. The quantification of Net Ecosystem Exchange (NEE) is critical to determine whether the regional terrestrial ecosystem is a net sink or source of CO2. This study uses a satellite-data derived light-use-efficiency model (the Vegetation Photosynthesis and Respiration Model, VPRM) to compute the biospheric CO2 fluxes over India from 2011–2020. A very high-resolution Land Use-Land Cover (LULC) data from the IRS-P6 satellite and MODIS derived surface reflectance are utilised to compute the NEE over distinct vegetation types at ∼9km× 9 km. The VPRM model for the Indian region captures the spatial pattern and seasonal features of NEE over the country. The magnitude of annual mean NEE over India from the VPRM model is relatively high compared to that from Carbon Tracker, FLUXCOM, and Soil Moisture Active Passive Level-4 carbon data products. However, the VPRM model simulated NEE agrees with the NEE observations from the eddy covariance estimates, which are accepted as the ground truth. The fusion of high-resolution LULC and surface reflectance data in VPRM suggests that the average NEE over the Indian region during 2011–2020 is −0.16 ± 0.02 PgC yr−1. Among this, the contribution from Gross Ecosystem Exchange is about −0.47 ± 0.02 PgC yr−1, and Respiration is 0.31 ± 0.01 PgC yr−1. The maximum biospheric CO2 absorption is during the post-monsoon season, and the minimum is during the pre-monsoon season. The very high spatial resolution and heterogeneity resolved in the NEE data derived in this work offer the first data product of this kind for a variety of NEE analyses over India.

Pixel-level parameter optimization of a terrestrial biosphere model for improving estimation of carbon fluxes with an efficient model–data fusion method and satellite-derived LAI and GPP data

Abstract. Inaccurate parameter estimation is a significant source of uncertainty in complex terrestrial biosphere models. Model parameters may have large spatial variability, even within a vegetation type. Model uncertainty from parameters can be significantly reduced by model–data fusion (MDF), which, however, is difficult to implement over a large region with traditional methods due to the high computational cost. This study proposed a hybrid modeling approach that couples a terrestrial biosphere model with a data-driven machine learning method, which is able to consider both satellite information and the physical mechanisms. We developed a two-step framework to estimate the essential parameters of the revised Integrated Biosphere Simulator (IBIS) pixel by pixel using the satellite-derived leaf area index (LAI) and gross primary productivity (GPP) products as “true values.” The first step was to estimate the optimal parameters for each sample using a modified adaptive surrogate modeling algorithm (MASM). We applied the Gaussian process regression algorithm (GPR) as a surrogate model to learn the relationship between model parameters and errors. In our second step, we built an extreme gradient boosting (XGBoost) model between the optimized parameters and local environmental variables. The trained XGBoost model was then used to predict optimal parameters spatially across the deciduous forests in the eastern United States. The results showed that the parameters were highly variable spatially and quite different from the default values over forests, and the simulation errors of the GPP and LAI could be markedly reduced with the optimized parameters. The effectiveness of the optimized model in estimating GPP, ecosystem respiration (ER), and net ecosystem exchange (NEE) were also tested through site validation. The optimized model reduced the root mean square error (RMSE) from 7.03 to 6.22 gC m−2 d−1 for GPP, 2.65 to 2.11 gC m−2 d−1 for ER, and 4.45 to 4.38 gC m−2 d−1 for NEE. The mean annual GPP, ER, and NEE of the region from 2000 to 2019 were 5.79, 4.60, and −1.19 Pg yr−1, respectively. The strategy used in this study requires only a few hundred model runs to calibrate regional parameters and is readily applicable to other complex terrestrial biosphere models with different spatial resolutions. Our study also emphasizes the necessity of pixel-level parameter calibration and the value of remote sensing products for per-pixel parameter optimization.

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).

OCO‐2 Satellite‐Imposed Constraints on Terrestrial Biospheric CO2 Fluxes Over South Asia

AbstractThe spatiotemporal variability of terrestrial biospheric carbon dioxide (CO2) fluxes over South Asia has large uncertainty. The Orbiting Carbon Observatory 2 (OCO‐2) satellite provides much‐needed retrievals of column‐average CO2 on a global‐scale, with the highest sensitivity to surface CO2 fluxes and spatiotemporal resolution available to‐date. This study conducted global inverse model simulations, assimilating in situ (IS) data and OCO‐2 retrievals, to assess optimized CO2 net ecosystem exchange (NEE) fluxes for South Asia. Annual Net Biome Exchange (NBE = NEE + biomass burning) fluxes over South Asia were estimated to be near neutral (0.04 ± 0.14 PgC yr−1) using both IS and OCO‐2 observations. The most robust result found by assimilating OCO‐2 observations was the constraint imposed on the seasonal cycle of NBE fluxes. The amplitude of the seasonal cycle of NEE was found to be larger than previously assumed. The OCO‐2 inversion led to an NBE seasonal amplitude of 0.34 PgC month−1, which was larger compared to IS constrained NBE (0.19 PgC month−1) and MsTMIP ensemble mean NEE (0.16 PgC month−1). Moreover, OCO‐2 data imposed a phase shift in the NBE seasonal cycle predicted by the prior model. The larger magnitude of NEE seasonality, and phase shift, simulated when assimilating OCO‐2 observations are in general agreement with previous studies assimilating regional aircraft observations in addition to global IS observations. This result suggests that OCO‐2 provides valuable data that allows for the estimate of NBE on a regional scale in a similar manner as regional in situ aircraft networks.

Rainfall stimulates large carbon dioxide emission during growing season in a forest wetland catchment

Forest wetland catchments are widely distributed in middle-high latitude and their hydrological and biogeochemical processes are sensitive to climate change. The net ecosystem exchange (NEE), meteorological forcing, and hydrological data in the Shuidong forest wetland catchment (SFWC) were continuously measured by eddy covariance (EC) tower and water monitoring instruments from 2019 to 2020. During rainy season, large carbon dioxide emission was detected with mean NEE value of 1.85 g C m−2 d-1 from local footprint area. Significant positive correlation was observed between daily NEE and air temperature (Tair), relative humidity (RH). We further found that the NEE was mainly controlled by ecosystem respiration (RE) instead of gross primary production (GPP), which might be caused by local high Q10 value. In addition, dissolved organic carbon (DOC) and dissolved organic (DON) concentrations near the stream outlet also had significant positive relationship with NEE, indicating the hydrological transport from upland forests may trigger the soil priming effect and result in higher CO2 emission within the local footprint area. Soil CO2 flux measurements from different land uses suggested that wetland may be the primary CO2 emission source during rainy season. Under the Representative Concentration Pathway (RCP) 8.5 scenario, the CO2 emission hotspot was expected to occur in this forest wetland catchment due to more frequent rainfall events predicted in this region.

Variations in seasonal and inter-annual carbon fluxes in a semi-arid sandy maize cropland ecosystem in China's Horqin Sandy Land.

Sandy cropland ecosystems are major terrestrial ecosystems in semi-arid regions of northern China's Horqin Sandy Land, where they play an important role in the regional carbon balance. Continuous observation of the CO2 flux was conducted from 2014 to 2018 using the eddy covariance technique in a sandy maize cropland ecosystem in the Horqin Sandy Land. We analyzed carbon fluxes (the net ecosystem exchange (NEE) of CO2, ecosystem respiration (Reco), and the gross primary productivity (GPP) and their responses to environmental factors at different temporal scales using Random Forest models and correlation analysis. We found that the sandy cropland was a carbon sink, with an annual mean NEE of -124.4 g C m-2 yr-1. However, after accounting for carbon exports and imports, the cropland became a net carbon source, with net biome production ranging from -501.1 to -266.7 g C m-2 yr-1. At a daily scale, the Random Forest algorithm revealed that photosynthetic photon flux density, soil temperature, and soil moisture were the main drivers for variation of GPP, Reco, and NEE at different integration periods. At a monthly scale, GPP and Reco increased with increasing leaf area index (LAI), so the maize ecosystem's carbon sequestration capacity increased with increasing LAI. At an annual scale, water availability (precipitation and irrigation) played a dominant role in explaining inter-annual variability of GPP and Reco. Affected by climate (e.g., precipitation) and field management (e.g., cultivation, irrigation), carbon fluxes differed greatly between years in the maize system.

A model for urban biogenic CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; fluxes: Solar-Induced Fluorescence for Modeling Urban biogenic Fluxes (SMUrF v1)

Abstract. When estimating fossil fuel carbon dioxide (FFCO2) emissions from observed CO2 concentrations, the accuracy can be hampered by biogenic carbon exchanges during the growing season, even for urban areas where strong fossil fuel emissions are found. While biogenic carbon fluxes have been studied extensively across natural vegetation types, biogenic carbon fluxes within an urban area have been challenging to quantify due to limited observations and differences between urban and rural regions. Here we developed a simple model representation, i.e., Solar-Induced Fluorescence (SIF) for Modeling Urban biogenic Fluxes (“SMUrF”), that estimates the gross primary production (GPP) and ecosystem respiration (Reco) over cities around the globe. Specifically, we leveraged space-based SIF, machine learning, eddy-covariance (EC) flux data, and ancillary remote-sensing-based products, and we developed algorithms to gap-fill fluxes for urban areas. Grid-level hourly mean net ecosystem exchange (NEE) fluxes are extracted from SMUrF and evaluated against (1) non-gap-filled measurements at 67 EC sites from FLUXNET during 2010–2014 (r&gt;0.7 for most data-rich biomes), (2) independent observations at two urban vegetation and two crop EC sites over Indianapolis from August 2017 to December 2018 (r=0.75), and (3) an urban biospheric model based on fine-grained land cover classification in Los Angeles (r=0.83). Moreover, we compared SMUrF-based NEE with inventory-based FFCO2 emissions over 40 cities and addressed the urban–rural contrast in both the magnitude and timing of CO2 fluxes. To illustrate the application of SMUrF, we used it to interpret a few summertime satellite tracks over four cities and compared the urban–rural gradient in column CO2 (XCO2) anomalies due to NEE against XCO2 enhancements due to FFCO2 emissions. With rapid advances in space-based measurements and increased sampling of SIF and CO2 measurements over urban areas, SMUrF can be useful to inform the biogenic CO2 fluxes over highly vegetated regions during the growing season.

CLASSIC v1.0: the open-source community successor to the Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM) – Part 2: Global benchmarking

Abstract. The Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC) is an open-source community model designed to address research questions that explore the role of the land surface in the global climate system. Here, we evaluate how well CLASSIC reproduces the energy, water, and carbon cycle when forced with quasi-observed meteorological data. Model skill scores summarize how well model output agrees with observation-based reference data across multiple statistical metrics. A lack of agreement may be due to deficiencies in the model, its forcing data, and/or reference data. To address uncertainties in the forcing, we evaluate an ensemble of CLASSIC runs that is based on three meteorological data sets. To account for observational uncertainty, we compute benchmark skill scores that quantify the level of agreement among independent reference data sets. The benchmark scores demonstrate what score values a model may realistically achieve given the uncertainties in the observations. Our results show that uncertainties associated with the forcing and observations are considerably large. For instance, for 10 out of 19 variables assessed in this study, the sign of the bias changes depending on what forcing and reference data are used. Benchmark scores are much lower than expected, implying large observational uncertainties. Model and benchmark score values are mostly similar, indicating that CLASSIC performs well when considering observational uncertainty. Future model development should address (i) a positive albedo bias and resulting shortwave radiation bias in parts of the Northern Hemisphere (NH) extratropics and Tibetan Plateau, (ii) an out-of-phase seasonal gross primary productivity cycle in the humid tropics of South America and Africa, (iii) a lacking spatial correlation of annual mean net ecosystem exchange with site-level measurements, (iv) an underestimation of fractional area burned and corresponding emissions in the boreal forests, (v) a negative soil organic carbon bias in high latitudes, and (vi) a time lag in seasonal leaf area index maxima in parts of the NH extratropics. Our results will serve as a baseline for guiding and monitoring future CLASSIC development.

Contrasting Regional Carbon Cycle Responses to Seasonal Climate Anomalies Across the East-West Divide of Temperate North America.

Across temperate North America, interannual variability (IAV) in gross primary production (GPP) and net ecosystem exchange (NEE) and their relationship with environmental drivers are poorly understood. Here, we examine IAV in GPP and NEE and their relationship to environmental drivers using two state‐of‐the‐science flux products: NEE constrained by surface and space‐based atmospheric CO measurements over 2010–2015 and satellite up‐scaled GPP from FluxSat over 2001–2017. We show that the arid western half of temperate North America provides a larger contribution to IAV in GPP (104% of east) and NEE (127% of east) than the eastern half, in spite of smaller magnitude of annual mean GPP and NEE. This occurs because anomalies in western ecosystems are temporally coherent across the growing season leading to an amplification of GPP and NEE. In contrast, IAV in GPP and NEE in eastern ecosystems is dominated by seasonal compensation effects, associated with opposite responses to temperature anomalies in spring and summer. Terrestrial biosphere models in the MsTMIP ensemble generally capture these differences between eastern and western temperate North America, although there is considerable spread between models.

Analysis of the 21-years long carbon dioxide flux dataset from a Central European tall tower site

Eddy-covariance based carbon flux datasets spanning decades are becoming available worldwide due to the effort of associated scientists. Tall tower based monitoring stations are relatively rare, but provide important information about the carbon balance of a larger region surrounding the tower. In this study we report and analyze the 21-year-long dataset provided by the Hungarian tall tower site, Hegyhátsál. The daily and annual cycles of net ecosystem exchange (NEE), gross primary production, and total ecosystem respiration are presented. Footprint analysis reveals that the fluxes mostly originate from the surrounding arable lands; the main source region is located within 1 km around the tower. Long-term, mean NEE was -0.467 gC m-2 day-1, or -170 gC m-2 year-1, revealing that the complex region was a net carbon sink from the atmospheric perspective. Trend analysis indicates that overall, NEE decreased (i.e. became more negative, which means stronger sink) by 12 gC m-2 year-1, a trend that is explained by improved agrotechnology and climate change. Net biome production (NBP) was estimated using crop census data and assumptions about the management practices that affect lateral carbon flux. Long term mean NBP was -30 gC m-2 year-1, which indicates that the soils may be losing carbon, though this loss is within the range of uncertainty of the measurements (~50 gC m-2 year-1). Analysis of county-scale yield statistics suggested that the results can be representative to at least county scale (1651 km2). Interannual variability was analyzed by using environmental variables such as maximum and minimum temperature, precipitation, vapor pressure deficit, soil water content, and satellite based vegetation index aggregated at monthly and longer time intervals. The results indicate that environmental conditions in spring have a major role in the annual carbon balance. Moreover, water availability represented by soil water content rather than by precipitation is a major driver of the interannual variability of NEE. The statistical analysis suggested that the large positive NEE anomaly during 2001–2003 was caused by interplay among the environmental drivers, in particular maximum temperature, vapor pressure deficit and radiation in April, followed by a soil water content deficit during the growing season. This novel statistical analysis provides insight into the drivers of the carbon balance of a mixed agricultural region.

Patterns of Carbon Sequestration in a Young Forest Ecosystem after Clear-Cutting

A large area of Estonian hemiboreal forest is recovering from clear-cut harvesting and changing carbon (C) balance of the stands. However, there is a lack of information about C- source/sink relationships during recovery of such stands. The eddy covariance technique was used to estimate C-status through net ecosystem exchange (NEE) of CO2 in two stands of different development stages located in southeast Estonia in 2014. Measured summertime (June–September) mean CO2 concentration was 337.75 ppm with mean NEE −1.72 µmol m−2 s−1. June NEE was −4.60 µmol m−2 s−1; July, August, and September NEE was −1.17, −0.77, and −0.25 µmol m−2 s−1, respectively. The two stands had similar patterns of CO2 exchange; measurement period temperature drove NEE. Our results show that after clear-cutting a 6-year-old forest ecosystem was a light C-sink and 8-year-old young stand demonstrated a stronger C-sink status during the measurement period.

Livestock grazing and rainfall manipulation alter the patterning of CO2 fluxes and biomass development of the herbaceous community in a humid savanna

Overgrazing by livestock and the changing patterns of rainfall, characterized by severe drought and floods during dry and wet seasons, respectively, threaten the sustainable productivity of the savannas. To understand the implications of such changes in Lambwe Valley—Kenya, we simulated 50% decrease (50%) and increase (150%) in ambient rainfall (100%), respectively, in grazed (G) and ungrazed (U) sites during dry and wet months. CO2 exchange and biomass production were quantified using chamber method and direct biomass sampling technique, respectively. Plots were named by combining the first letters of the sites followed by rainfall amount, i.e., U150%. Soil moisture (VWC) increased along a rainfall gradient of 50–150%. Grazing reduced the VWC, net ecosystem exchange (NEE), and total biomass by 19.07%, 57.14%, and 37.03%, respectively, with severe effects during the dry months. 50% rainfall strongly influenced the VWC, NEE (negative and positive signs indicate CO2 uptake and net carbon loss, respectively), and biomass compared to 150% rainfall. The U150% plot reported the highest mean NEE (– 8.80 ± 2.26 µmol m−2 s−1), AGB (1208.41 g m−2), and total biomass (1589.06 g m−2) during the wet months. Lower VWC in the G50% plot triggered a net carbon loss of 3.68 ± 0.81 µmol m−2 s−1 (NEE). Our results show that livestock grazing during the dry months hinders herbaceous CO2 uptake and standing biomass. Proper understanding of the interaction between livestock grazing and rainfall variability in humid savannas is essential for sustainable management strategies to regulate the herbaceous productivity.

Three-Year Variability Of Energy And Carbon Dioxide Fluxes At Clear-Cut Forest Site In The European Southern Taiga

Forest clearing strongly influences the energy, water and greenhouse gas exchange at the land sur face - atmosphere inter face. To estimate effects of clear cutting on sensible (H), latent heat (LE) and CO 2 fluxes the continuous eddy covariance measurements were provided at the recently clear-cut area situated in the western part of Russia from spring 2016 to the end of 2018. The possible effects of surrounding forest on the air flow disturbances and on the spatial pattern of horizontal advection terms within the selected clear-cut area were investigated using a process-based 3D momentum, energy and CO 2 exchange model. The modeling results showed a very low contribution of horizontal advection term into total turbulent momentum fluxes at flux tower location in case of the southern wind direction. The results of field flux measurements indicated a strong inter- and intra-annual variability of energy and CO 2 fluxes. The energy budget is characterized by higher daily and monthly LE fluxes throughout the entire period of measurements excepting the first two months after timber harvest. The mean Bowen ratio ( β =H/LE) was 0.52 in 2016, 0.30 - in 2017 and 0.35 - in 2018. Analysis of CO 2 fluxes during the first year following harvest showed that the monthly CO 2 release at the clear-cut area consistently exceeded the CO 2 uptake rates. The mean net ecosystem exchange (NEE) in the period was 3.3±1.3 gC∙m-2∙d-1. During the second and the third years of the flux measurements the clear-cut was also a prevailed sink of CO 2 for the atmosphere excepting short periods in June and in the first part of July when daily CO 2 uptake was higher than CO 2 release rates. The mean NEE rates averaged for the entire warm period of corresponding years were 1.2±2.3 g С ∙m -2 ∙d -1 in 2017 and 2.8±2.5 gC∙m -2 ∙d -1 in 2018, respectively. The mean ratio between gross primary production (GPP) and ecosystem respiration (TER) was 0.58 in 2016, 0.84 - in 2017 and 0.74 - in 2018.

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.

Burning increases post-fire carbon emissions in a heathland and a raised bog, but experimental manipulation of fire severity has no effect

Large amounts of carbon are stored in northern peatlands. There is concern that greater wildfire severity following projected increases in summer drought will lead to higher post-fire carbon losses. We measured soil carbon dynamics in a Calluna heathland and a raised peat bog after experimentally manipulating fire severity. A gradient of fire severity was achieved by simulating drought in 2 × 2 m plots. Ecosystem respiration (ER), net ecosystem exchange (NEE), methane (CH4) flux and concentration of dissolved organic carbon ([DOC], measured at the raised bog only) were measured for up to two years after burning. The response of these carbon fluxes to increased fire severity in drought plots was similar to plots burnt under ambient conditions associated with traditional managed burning. Averaged across all burnt plots, burning altered mean NEE from a net carbon sink at the heathland (−0.33 μmol CO2 m−2 s−1 in unburnt plots) to a carbon source (0.50 μmol m−2 s−1 in burnt plots) and at the raised bog (−0.38 and 0.16 μmol m−2 s−1, respectively). Burning also increased CH4 flux at the raised bog (from 1.16 to 25.3 nmol m−2 s−1 in the summer, when it accounted for 79% of the CO2-equivalent emission). Burning had no significant effect on soil water [DOC].

Carbon Exchange between the Atmosphere and a Subtropical Evergreen Mountain Forest in Taiwan

Tropical, temperate, and boreal forests are the subject of various eddy covariance studies, but less is known about the subtropical region. As there are large areas of subtropical forests in the East Asian monsoon region with possibly high carbon uptake, we used three years (2011–2013) of eddy covariance data to estimate the carbon balance of a subtropical mountain forest in Taiwan. Two techniques of flux partitioning are applied to evaluate ecosystem respiration, thoroughly evaluate the validity of the estimated fluxes, and arrive at an estimate of the yearly net ecosystem exchange (NEE). We found that advection is a strong player at our site. Further, when used alone, the nighttime flux correction with the so-called u∗ method (u∗ = friction velocity) cannot avoid underestimating the nighttime respiration. By using a two-technique method employing both nighttime and daytime parameterizations for flux corrections, we arrive at an estimate of the three-year mean NEE of −561 (±standard deviation 114) g·C·m−2·yr−1. The corrected flux estimate represents a rather large uptake of CO2 for this mountain cloud forest, but the value is in good agreement with the few existing comparable estimates for other subtropical forests.

First results of energy and mass exchange in a salt marsh on southeastern South America

Salt marshes are vulnerable ecosystems since they are found in locations often preferred for urban development. They produce a great amount of biomass, and also are of great interest because of the ecosystem services they provide from which carbon storage stands out. This work aims to study the energy and mass exchanged by a salt marsh located in southeastern Buenos Aires province (Argentina) and to characterize its net ecosystem production. A field campaign was carried out from February 2014 to March 2015. Sensible heat, water vapor (H2O) and carbon dioxide (CO2) fluxes were measured with eddy covariance technique at 6 m height over a Spartina densiflora canopy. Fifty five percent of the data were lost and 15% more were discarded due to low turbulence conditions. This gaps were filled with a combination of techniques (look-up tables and mean diurnal variations), which allowed the estimation of monthly mean net ecosystem exchange, gross primary production and ecosystem respiration. As in other marshes, the latent heat flux consumed more than 55% of the available energy of the system, reaching up to 85% after a large flood event. This flux systematically exceeds the values of sensible heat measured throughout the study period. Unlike other environments, this southern salt marsh behaved as a CO2 sink throughout the year. The net ecosystem production from March 2014 to February 2015 was approximately −10.5 t of CO2 ha−1 yr−1 which is greater than reported results for other wetlands. These preliminary results for a southern S. densiflora salt marsh are encouraging, although new field studies are under way to confirm their accuracy.

Spatiotemporal variations of CO2 fluxes in aCynodon-dominated riparian zone of the Three Gorges Reservoir (TGR), China

Aims Riparian ecosystems play an important role in overall ecosystem function, including the global carbon cycle of terrestrial ecosystems, at both landscape and global scales. Yet few studies have reported in situ measurements of CO2 in riparian areas where flooding is a unique disturbance to carbon cycling. Methods At multiple locations across riparian zones (RZ) with different water submergences in Xiangxi Bay (XXB), we studied seasonal variations of CO2 exchange between this Cynodon-dominated community and the atmosphere for 2 years by using static chambers. Important Findings We found that the seasonal changes in CO2 fluxes were apparent and dependent on the biophysical environment. In the beginning of spring, low gross primary productivity (GPP) in lightly flooded zones (LFZ) resulted in a positive net ecosystem exchange (NEE), indicating a net CO2 source. With the increase in temperature, more species and vegetation abundance appeared, and the increased GPP turned the LFZ from a net CO2 source into a sink. This transition seemed predominantly controlled by the physiological growth of vegetation. The mean NEEs, REs and the light-use efficiency (alpha) of the vegetation at HFZ and MFZ were significantly higher than those at LFZ and UFZ. Yet the coefficients of variation (CV) of NEE and RE at MFZ and HFZ were lower than those at LFZ and UFZ. Submergence promoted the emission and uptake of CO2 to the atmosphere. Elongated submergence reduced the number of species and lowered the spatial variability of the RZ, further lowering the variation of the CO2 exchange.