Estimates of the Annual Net Carbon and Water Exchange of Forests: The EUROFLUX Methodology

Long-term investigation of methane and carbon dioxide emissions in two Italian landfills

Landfills play a key role as greenhouse gas (GHGs) emitters, and urgently need assessment and management plans development to swiftly reduce their climate impact. In this context, accurate emission measurements from landfills under different climate and management would reduce the uncertainty in emission accounting. In this study, more than one year of long-term high-frequency data of CO2 and CH4 fluxes were collected in two Italian landfills (Giugliano and Case Passerini) with contrasting management (gas recovery VS no management) using eddy covariance (EC), with the aim to i) investigate the relation between climate drivers and CO2 and CH4 fluxes at different time intervals and ii) to assess the overall GHG balances including the biogas extraction and energy recovery components. Results indicated a higher net atmospheric CO2 source (5.7 ± 5.3 g m2 d-1) at Giugliano compared to Case Passerini (2.4 ± 4.9 g m2 d-1) as well as one order of magnitude higher atmospheric CH4 fluxes (6.0 ± 5.7 g m2 d-1 and 0.7 ± 0.6 g m2 d-1 respectively). Statistical analysis highlighted that fluxes were mainly driven by thermal variables, followed by water availability, with their relative importance changing according to the time-interval considered. The rate of change in barometric pressure (dP/dt) influenced CH4 patterns and magnitude in the classes ranging from -1.25 to +1.25 Pa h-1, with reduction when dP/dt > 0 and increase when dP/dt < 0, whilst a clear pattern was not observed when all dP/dt classes were analyzed. When including management, the total atmospheric GHG balance computed for the two landfills of Giugliano and Case Passerini was 174 g m2 d-1 and 79 g m2 d-1 respectively, of which 168 g m2 d-1 and 20 g m2 d-1 constituted by CH4 fluxes.

Physiological and phenological adjustments in water and carbon fluxes of Aleppo pine forests under contrasting climates in the Eastern Mediterranean

The ability of plants to adjust to the adverse effects of climate change is important for their survival and for their contribution to the global carbon cycle. This is particularly true in the Mediterranean region, which is among the regions that are most vulnerable to climate change. Here, we carried out a 2-year comparative ecophysiological study of ecosystem function in two similar Eastern Mediterranean forests of the same tree species (Pinus halepensis Mill.) under mild (Sani, Greece) and extreme (Yatir, Israel) climatic conditions. The partial effects of key environmental variables, including radiation, vapor pressure deficit, air temperature and soil moisture (Rg, D, T and soil water content (SWC), respectively), on the ecosystems' CO2 and water vapor fluxes were estimated using generalized additive models (GAMs). The results showed a large adjustment between sites in the seasonal patterns of both carbon and water fluxes and in the time and duration of the optimal period (defined here as the time when fluxes were within 85% of the seasonal maximum). The GAM analysis indicated that the main factor influencing the seasonal patterns was SWC, while T and D had significant but milder effects. During the respective optimal periods, the two ecosystems showed strong similarities in the fluxes' responses to the measured environmental variables, indicating similarity in their underlying physiological characteristics. The results indicate that Aleppo pine forests have a strong phenotypic adjustment potential to cope with increasing environmental stresses. This, in turn, will help their survival and their continued contribution to the terrestrial carbon sink in the face of climate change in this region.

Warming, rather than drought, remains the primary factor limiting carbon sequestration

Steppe ecosystems in arid and semiarid regions are particularly sensitive to climate change and strongly regulate the global carbon balance. However, carbon fluxes respond differently to climate change in different growing seasons, and the mechanism of this control is not yet clear. Therefore, we (i) obtained carbon flux data observed by a field eddy station in Inner Mongolia from 2006 to 2021; (ii) investigated the constraint effects of climatic factors on carbon fluxes; (iii) explored the response mechanisms of carbon fluxes to coupled changes in temperature and moisture; (iv) investigated the adaptation of steppe ecosystem to changes in temperature and drought. The results showed that (i) the steppe ecosystem was a carbon sink, with an average annual carbon fixation of 73.55 g C m-2 yr-1 and a roughly N-shaped carbon sink accumulation process within one year. (ii) The constraint effect of temperature and Vapor Pressure Deficit (VPD) on Net Ecosystem Productivity (NEP) and Gross Primary Productivity (GPP) was parabolic, with a clear optimum point. (iii) Temperature and moisture in the soil played a greater role in ecosystem carbon sequestration. Soil Water Content (SWC) could alleviate the inhibitory effect of temperature changes on the carbon sequestration of ecosystem. (iv) This ecosystem was capable of adapting well to changes in temperature and drought. However, warming, rather than drought, remains the primary factor limiting carbon sequestration. Specifically, it was GPP that drives the adaptation of ecosystem carbon sequestration to changes in temperature and drought, rather than Ecosystem Respiration (RECO). Although the steppe ecosystem has a good adaptation to changes in temperature and drought, it is still in the boundary region of warming. We hope that our study will deepen our comprehensive understanding of the relationship between temperature and moisture and ecosystem carbon fluxes and provide evidence for steppe ecosystem adaptation to climate change.

Enhanced causal effect of ecosystem photosynthesis on respiration during heatwaves

Because of global warming, Earth's ecosystems have been experiencing more frequent and severe heatwaves. Heatwaves are expected to tip terrestrial carbon sequestration by elevating ecosystem respiration and suppressing gross primary productivity (GPP). Here, using the convergent cross-mapping technique, this study detected positive bidirectional causal effects between GPP and respiration in two unprecedented European heatwaves. Heatwaves enhanced the causal effect strength of GPP on respiration rather than respiration on GPP across 40 site-years of observations. Further analyses and global simulations revealed spatial heterogeneity in the heatwave response of the causal link strength between GPP and respiration, which was jointly driven by the local climate and vegetation properties. However, the causal effect strength of GPP on respiration showed considerable uncertainties in CMIP6 models. This study reveals an enhanced causal link strength between GPP and respiration during heatwaves, shedding light on improving projections for terrestrial carbon sink dynamics under future climate extremes.

Observational evidence of legacy effects of the 2018 drought on a mixed deciduous forest in Germany

Forests play a major role in the global carbon cycle, and droughts have been shown to explain much of the interannual variability in the terrestrial carbon sink capacity. The quantification of drought legacy effects on ecosystem carbon fluxes is a challenging task, and research on the ecosystem scale remains sparse. In this study we investigate the delayed response of an extreme drought event on the carbon cycle in the mixed deciduous forest site 'Hohes Holz' (DE-HoH) located in Central Germany, using the measurements taken between 2015 and 2020. Our analysis demonstrates that the extreme drought and heat event in 2018 had strong legacy effects on the carbon cycle in 2019, but not in 2020. On an annual basis, net ecosystem productivity was [Formula: see text] higher in 2018 ([Formula: see text]) and [Formula: see text] lower in 2019 ([Formula: see text]) compared to pre-drought years ([Formula: see text]). Using spline regression, we show that while current hydrometeorological conditions can explain forest productivity in 2020, they do not fully explain the decrease in productivity in 2019. Including long-term drought information in the statistical model reduces overestimation error of productivity in 2019 by nearly [Formula: see text]. We also found that short-term drought events have positive impacts on the carbon cycle at the beginning of the vegetation season, but negative impacts in later summer, while long-term drought events have generally negative impacts throughout the growing season. Overall, our findings highlight the importance of considering the diverse and complex impacts of extreme events on ecosystem fluxes, including the timing, temporal scale, and magnitude of the events, and the need to use consistent definitions of drought to clearly convey immediate and delayed responses.

Net greenhouse gas balance of fibre wood plantation on peat in Indonesia

Tropical peatlands cycle and store large amounts of carbon in their soil and biomass1-5. Climate and land-use change alters greenhouse gas (GHG) fluxes of tropical peatlands, but the magnitude of these changes remains highly uncertain6-19. Here we measure net ecosystem exchanges of carbon dioxide, methane and soil nitrous oxide fluxes between October 2016 and May 2022 from Acacia crassicarpa plantation, degraded forest and intact forest within the same peat landscape, representing land-cover-change trajectories in Sumatra, Indonesia. This allows us to present a full plantation rotation GHG flux balance in a fibre wood plantation on peatland. We find that the Acacia plantation has lower GHG emissions than the degraded site with a similar average groundwater level (GWL), despite more intensive land use. The GHG emissions from the Acacia plantation over a full plantation rotation (35.2 ± 4.7 tCO2-eq ha-1 year-1, average ± standard deviation) were around two times higher than those from the intact forest (20.3 ± 3.7 tCO2-eq ha-1 year-1), but only half of the current Intergovernmental Panel on Climate Change (IPCC) Tier 1 emission factor (EF)20 for this land use. Our results can help to reduce the uncertainty in GHG emissions estimates, provide an estimate of the impact of land-use change on tropical peat and develop science-based peatland management practices as nature-based climate solutions.

Advance methodological approaches for carbon stock estimation in forest ecosystems

The forests are a key player in maintaining ecological balance on the earth. They not only conserve biodiversity, reduce soil erosion, and protect watersheds but also promote the above and below-ground ecosystem services. Forests are known as air cleaners on the planet and play a significant role in mitigating greenhouse gas (GHG) emissions into the atmosphere. As per programs launched in the Conference of Parties (COP) 26, there is a need to promote policies and programs to reduce the atmospheric carbon (C) through the forest ecosystem; it is because forests can capture the atmospheric CO₂ for a long time and help to achieve the goals of net-zero emission CO₂ on the earth. Therefore, there is an urgent need to know the advanced technological approaches for estimating C stock in forest ecosystems. Hence, the present article is aimed at providing a comprehensive protocol for the four C stock estimation approaches. An effort has also been made to compare these methods. This review suggests that tree allometry is the most common method used for the quantification of C stock, but this method has certain limitations. However, the review shows that accurate results can be produced by a combination of two or more methods. We have also analyzed the results of 42 research studies conducted for C stock assessment along with the factors determining the amount of C in different types of forests. The C stock in vegetation is affected by temporal and spatial variation, plantation age, land use, cropping pattern, management practices and elevation, etc. Nevertheless, the available results have a large degree of uncertainty mainly due to the limitations of the methods used. The review supports the conclusion that the uncertainty in C stock measurements can be addressed by the integration of the above-mentioned methods.

Solar-induced chlorophyll fluorescence imperfectly tracks the temperature response of photosynthesis in winter wheat

Solar-induced fluorescence (SIF) is a promising proxy for photosynthesis, but it is unclear whether it performs well in tracking the gross primary productivity (GPP) under different environmental conditions. In this study, we investigated the dynamics of the two parameters from October 2020 to June 2021 in field-grown winter wheat (Triticum aestivum) and found that the ability of SIF to track GPP was weakened at low temperatures. Accounting for the coupling of light and temperature at a seasonal scale, we found that SIF yield showed a lower temperature sensitivity and had a lower but broader optimal temperature range compared with light-use efficiency (LUE), although both SIF yield and LUE decreased in low-temperature conditions. The discrepancy between the temperature responses of SIF yield and GPP caused an increase in the ratio of SIF/GPP in winter, which indicated the variation in the relationship between them during this period. The results of our study highlight the impact of low temperature on the relationship between SIF and GPP and show the necessity of reconsidering the dynamics of energy distribution inside plants under changing environments.

Ecosystem CO2 release driven by wind occurs in drylands at global scale

Subterranean ventilation is a non-diffusive transport process that provokes the abrupt transfer of CO₂ -rich air (previously stored) through water-free soil pores and cracks from the vadose zone to the atmosphere, under high-turbulence conditions. In dryland ecosystems, whose biological carbon exchanges are poorly characterized, it can strongly determine eddy-covariance CO₂ fluxes that are used to validate remote sensing products and constrain models of gross primary productivity. Although subterranean ventilation episodes (VE) may occur in arid and semi-arid regions, which are unsung players in the global carbon cycle, little research has focused on the role of VE CO₂ emissions in land-atmosphere CO₂ exchange. This study shows clear empirical evidence of globally occurring VE. To identify VE, we used in situ quality-controlled eddy-covariance open data of carbon fluxes and ancillary variables from 145 sites in different open land covers (grassland, cropland, shrubland, savanna, and barren) across the globe. We selected the analyzed database from the FLUXNET2015, AmeriFlux, OzFlux, and AsiaFlux networks. To standardize the analysis, we designed an algorithm to detect CO₂ emissions produced by VE at all sites considered in this study. Its main requirement is the presence of considerable and non-spurious correlation between the friction velocity (i.e., turbulence) and CO₂ emissions. Of the sites analyzed, 34% exhibited the occurrence of VE. This vented CO₂ emerged mainly from arid ecosystems (84%) and sites with hot and dry periods. Despite some limitations in data availability, this research demonstrates that VE-driven CO₂ emissions occur globally. Future research should seek a better understanding of its drivers and the improvement of partitioning models, to reduce uncertainties in estimated biological CO₂ exchanges and infer their contribution to the global net ecosystem carbon balance.

Evapotranspiration dynamics and their drivers in a temperate mixed forest in northeast China

Evapotranspiration (ET) is a vital part of the global water cycle and is closely related to carbon sequestration. Analysing ET dynamics and their drivers would benefit for improving our understanding of the global water and carbon cycles. Using an eddy covariance (EC) approach, we analysed ET dynamics and their drivers in a temperate mixed forest over northeast China from 2016 to 2017. The results showed that 43.55% of our eddy covariance data passed the quality control. In addition, the energy balance ratio was 0.62, indicating that measurements were reliable. The measured ET showed clear single peak patterns with seasonal and diurnal variations. The daily ET ranged from 0 to 7.75 mm d^-1 and the hourly ET ranged from 0 to 0.28 mm h^-1. The ranges of hourly ET floated from 0 to 0.05 mm h^-1 at non-growing season (November to April) while ranged from 0 to 0.28 mm h^-1 at active growing season (May to October). The diurnal ET dynamics during the non-growing season were driven by air temperature (T _a)_, but were governed by global radiation (R _g) during the active growing season. Leaf area index (LAI) comprehensively reflected the variations of T _a and R _g, and was found to be the primary factor shaping the seasonal dynamics of ET. The annual ET rates were 501.91 ± 5.30 mm year^-1 and 554.60 ± 11.24 mm year^-1 for 2016 and 2017, respectively. Therefore, energy supply, represented by T _a and R _g, governed ET dynamics in our temperate mixed forest, while variables representing the energy supply affecting ET dynamics differed among seasons and time scales. ET dynamics indicated that a temperate mixed forest is important to the global water cycle. Our results improved our understanding of ET dynamics in the studied region.

Does Below-Above Canopy Air Mass Decoupling Impact Temperate Floodplain Forest CO2 Exchange?

Environmental conditions influence forest ecosystems and consequently, its productivity. Thus, the quantification of forest CO2 exchange is a critical requirement to estimate the CO2 balance of forests on a local and regional scale. Besides interpreting the annual CO2 exchange corresponding to environmental conditions over the studied years (2015–2020) at the floodplain forest in Lanžhot, Czech Republic (48.6815483 N, 16.9463317 E), the influence of below-above canopy air mass decoupling on above canopy derived CO2 exchange is the focus of this study. For this purpose, we applied the eddy covariance (EC) method above and below the forest canopy, assessing different single- and two-level flux filtering strategies. We focused on one example year (2019) of concurrent below and above canopy EC measurements. We hypothesized that conventional single-level EC flux filtering strategies such as the friction velocity (u*) filtering approach might not be sufficient to fully capture the forest CO2 exchange at the studied ecosystem. Results suggest that decoupling occurs regularly, but the implication on the above canopy derived EC CO2 fluxes appears to be negligible on an annual scale. We attribute this to the open canopy and flat EC tower surrounding terrain which inhibits horizontal removal of below-canopy respired CO2.

Net ecosystem CO2 exchange from jute crop (Corchorus olitorius L.) and its environmental drivers in tropical Indo-Gangetic plain using open-path eddy covariance technique

Present study is a maiden attempt to assess net ecosystem exchange (NEE) of carbon dioxide (CO₂) flux from jute crop (Corchorus olitorius L.) in the Indo-Gangetic plain by using open-path eddy covariance (EC) technique. Diurnal variations of NEE were strongly influenced by growth stages of jute crop. Daytime peak NEE varied from - 5 µmol m^-2 s^-1 (in germination stage) to - 23 µmol m^-2 s^-1 (in fibre development stage). The ecosystem was net CO₂ source during nighttime with an average NEE value of 5-8 μmol m^-2 s^-1. Combining both daytime and nighttime CO₂ fluxes, jute ecosystem was found to be a net CO₂ sink on a daily basis except the initial 9 days from date of sowing. Seasonal and growth stage-wise NEEs were computed, and the seasonal total NEE over the jute season was found to be - 268.5 gC m^-2 (i.e. 10.3 t CO₂ ha^-1). In different jute growth stages, diurnal variations of NEE were strongly correlated (R² > 0.9) with photosynthetic photon flux density (PPFD). Ecosystem level photosynthetic efficiency parameters were estimated at each growth stage of jute crop using the Michaelis-Menten equation. The maximum values of photosynthetic capacity (P_max, 63.3 ± 1.15 µmol CO₂ m^-2 s^-1) and apparent quantum yield (α, 0.072 ± 0.0045 µmol CO₂ µmol photon^-1) were observed during the active vegetative stage, and the fibre development stage, respectively. Results of the present study would significantly contribute to understanding of the carbon flux from the Indian agro-ecosystems, which otherwise are very sparse.

Methane emission dynamics from a Danish landfill: The effect of changes in barometric pressure

This study investigates temporal variability on landfill methane (CH₄) emissions from an old abandoned Danish landfill, caused by the rate of changes in barometric pressure. Two different emission quantification techniques, namely the dynamic tracer dispersion method (TDM) and the eddy covariance method (EC), were applied simultaneously and their results compared. The results showed a large spatial and temporal CH₄ emission variation ranging from 0 to 100 kg h^-1 and 0 to 12 μmol m^-2 s^-1, respectively. Landfill CH₄ emissions dynamics were influenced by two environmental factors: the rate of change in barometric pressure (a strong negative correlation) and wind speed (a weak positive correlation). The relationship between CH₄ emissions and the rate of change in barometric pressure was more complicated than a linear one, thereby making it difficult to estimate accurately annual CH₄ emissions from a landfill based on discrete measurements. Furthermore, the results did not show any clear relationship between CH₄ emissions and ambient temperature. Large seasonal variations were identified by the two methods, whereas no diurnal variability was observed throughout the investigated period. CH₄ fluxes measured with the EC method were strongly correlated with emissions from the TDM method, even though no direct relationship could be established, due to the different sampling ranges of the two methods and the spatial heterogeneity of CH₄ emissions.

Energy Balance Closure Problem over a Tropical Seasonal Rainforest in Xishuangbanna, Southwest China: Role of Latent Heat Flux

The unresolved energy-unclosed problem in micrometeorology refers to the fact that the sum of turbulent fluxes (sensible and latent heat fluxes, Hs and LE) monitored by eddy covariance (EC) methods tends to be lower than the available energy (net radiation (Rn), soil heat flux (G), and heat storage (S)). The lack of energy balance closure (EBC) increases evapotranspiration-measurement uncertainty. Using EC data from Xishuangbanna, a Southeast Asian tropical seasonal rainforest, we analyzed the energy distribution and closure based on micrometeorological features. We found that: (1) the EBC in the rainy season exceeds that in other seasons and that the seasonal moisture content, frictional wind velocity (u*), and LE contribute to the high seasonal variability in EBC; (2) the annual closure is approximately 65%, and energy non-closure is influenced by turbulence intensity and atmospheric stability. When the atmospheric state is unstable to near neutral, u* is greatest, and EBC can reach nearly 80%. (3) energy is mainly allocated to LE, and energy non-closure leads to LE underestimation, especially in the foggy-cool and hot-dry seasons. (4) Heat storage and large time-scale flux effects on EBC were excluded. The causes of energy non-closure in the tropical calm zone need further investigation.

Phenology is the dominant control of methane emissions in a tropical non-forested wetland

Tropical wetlands are a significant source of atmospheric methane (CH₄), but their importance to the global CH₄ budget is uncertain due to a paucity of direct observations. Net wetland emissions result from complex interactions and co-variation between microbial production and oxidation in the soil, and transport to the atmosphere. Here we show that phenology is the overarching control of net CH₄ emissions to the atmosphere from a permanent, vegetated tropical swamp in the Okavango Delta, Botswana, and we find that vegetative processes modulate net CH₄ emissions at sub-daily to inter-annual timescales. Without considering the role played by papyrus on regulating the efflux of CH₄ to the atmosphere, the annual budget for the entire Okavango Delta, would be under- or over-estimated by a factor of two. Our measurements demonstrate the importance of including vegetative processes such as phenological cycles into wetlands emission budgets of CH₄.

Tropical wetlands are a significant but understudied source of methane. Here, methane emissions were measured over three years in a perennial tropical swamp in the Okavango Delta, Botswana, finding phenology was the overarching control of emissions.

Environmental Controls on Multi-Scale Dynamics of Net Carbon Dioxide Exchange From an Alpine Peatland on the Eastern Qinghai-Tibet Plateau

Peatlands are characterized by their large carbon storage capacity and play an essential role in the global carbon cycle. However, the future of the carbon stored in peatland ecosystems under a changing climate remains unclear. In this study, based on the eddy covariance technique, we investigated the net ecosystem CO₂ exchange (NEE) and its controlling factors of the Hongyuan peatland, which is a part of the Ruoergai peatland on the eastern Qinghai-Tibet Plateau (QTP). Our results show that the Hongyuan alpine peatland was a CO₂ sink with an annual NEE of -226.61 and -185.35 g C m^-2 in 2014 and 2015, respectively. While, the non-growing season NEE was 53.35 and 75.08 g C m^-2 in 2014 and 2015, suggesting that non-growing seasons carbon emissions should not be neglected. Clear diurnal variation in NEE was observed during the observation period, with the maximum CO₂ uptake appearing at 12:30 (Beijing time, UTC+8). The Q₁₀ value of the non-growing season in 2014 and 2015 was significantly higher than that in the growing season, which suggested that the CO₂ flux in the non-growing season was more sensitive to warming than that in the growing season. We investigated the multi-scale temporal variations in NEE during the growing season using wavelet analysis. On daily timescales, photosynthetically active radiation was the primary driver of NEE. Seasonal variation in NEE was mainly driven by soil temperature. The amount of precipitation was more responsible for annual variation of NEE. The increasing number of precipitation event was associated with increasing annual carbon uptake. This study highlights the need for continuous eddy covariance measurements and time series analysis approaches to deepen our understanding of the temporal variability in NEE and multi-scale correlation between NEE and environmental factors.

A comparative study of three stomatal conductance models for estimating evapotranspiration in a dune ecosystem in a semi-arid region

The accurate simulation of stomatal conductance is crucial for not only revealing the carbon and water cycle processes of an ecosystem, but also to improve the accuracy of simulations of evapotranspiration (ET). This study coupled three stomatal conductance models, i.e. the Stannard (ST), Jarvis-Stewart (JS), and Ball-Berry (BB) models, with the Shuttleworth-Wallace (SW) model to estimate ET for a mobile dune ecosystem in the Horqin Sandy Land, North China. These models were calibrated and validated using eddy covariance (EC) measurements taken during the growing season between 2013 and 2018. The results indicated that the SW-BB model showed better performance in comparison to the SW-JS and SW-ST models at half-hourly and daily timescales. The stomatal conductance models incorporating soil moisture (SM) content generally showed better performance during the extreme drought period, with the rank of the three models according to performance being: SW-BB > SW-JS > SW-ST. The models showed the highest sensitivity to SM when incorporating the effect of SM on stomatal conductance, indicating that SM has an important effect on stomatal conductance and ET. The results of this study indicate that of the models assessed, the Ball-Berry stomatal conductance model coupled with the SW model is optimal for estimating ET in dune ecosystems with sparse vegetation.

Unveiling the changes in urban atmospheric CO2 in the time of COVID-19 pandemic: A case study of Florence (Italy)

The outbreak of COVID-19 pandemic was accompanied by global mobility restrictions and slowdown in manufacturing activities. Accordingly, cities experienced a significant decrease of CO₂ emissions. In this study, continuous measurements of CO₂ fluxes, atmospheric CO₂ concentrations and δ¹³C-CO₂ values were performed in the historical center of Florence (Italy) before, during and after the almost two-month long national lockdown. The temporal trends of the analyzed parameters, combined with the variations in emitting source categories (from inventory data), evidenced a fast response of flux measurements to variations in the strength of the emitting sources. Similarly, the δ¹³C-CO₂ values recorded the change in the prevailing sources contributing to urban atmospheric CO₂, confirming the effectiveness of carbon isotopic data as geochemical tracers for identifying and quantifying the relative contributions of emitting sources. Although the direct impact of restriction measurements on CO₂ concentrations was less clear due to seasonal trends and background fluctuations, an in-depth analysis of the daily local CO₂ enhancement with respect to the background values revealed a progressive decrease throughout the lockdown phase at the end of the heating season (>10 ppm), followed by a net increase (ca. 5 ppm) with the resumption of traffic. Finally, the investigation of the shape of the frequency distribution of the analyzed variables revealed interesting aspects concerning the dynamics of the systems.

Evaluation of LandscapeDNDC Model Predictions of CO2 and N2O Fluxes from an Oak Forest in SE England

Process-based biogeochemical models are valuable tools to evaluate impacts of environmental or management changes on the greenhouse gas (GHG) balance of forest ecosystems. We evaluated LandscapeDNDC, a process-based model developed to simulate carbon (C), nitrogen (N) and water cycling at ecosystem and regional scales, against eddy covariance and soil chamber measurements of CO2 and N2O fluxes in an 80-year-old deciduous oak forest. We compared two LandscapeDNDC vegetation modules: PSIM (Physiological Simulation Model), which includes the understorey explicitly, and PnET (Photosynthesis–Evapotranspiration Model), which does not. Species parameters for both modules were adjusted to match local measurements. LandscapeDNDC was able to reproduce daily micro-climatic conditions, which serve as input for the vegetation modules. The PSIM and PnET modules reproduced mean annual net CO2 uptake to within 1% and 15% of the measured values by balancing gains and losses in seasonal patterns with respect to measurements, although inter-annual variations were not well reproduced. The PSIM module indicated that the understorey contributed up to 21% to CO2 fluxes. Mean annual soil CO2 fluxes were underestimated by 32% using PnET and overestimated by 26% with PSIM; both modules simulated annual soil N2O fluxes within the measured range but with less interannual variation. Including stand structure information improved the model, but further improvements are required for the model to predict forest GHG balances and their inter-annual variability following climatic or management changes.

An Interannual Comparative Study on Ecosystem Carbon Exchange Characteristics in the Dinghushan Biosphere Reserve, a Dominant Subtropical Evergreen Forest Ecosystem

Compared with other forest systems, research interest in the potential for a stronger ecosystem carbon sequestration of evergreen forests throughout subtropical China has greatly increased. The eddy covariance technique is widely employed to determine accurate forest-atmosphere carbon dioxide (CO₂) flux, which is subsequently used to determine forest ecosystem carbon exchange characteristics. The Dinghushan Biosphere Reserve, a subtropical monsoon evergreen broad-leaved forest, is a suitable study area due to its warm and humid climate (compared with other regions within the same latitude), consequently playing a role in the carbon cycle in the region. For this study, we hypothesized that the forest land in this region generally acts as a carbon sink, and that its carbon sequestration capacity increases over time despite the influence of climatic factors. Here, we compared net CO₂ flux data derived from the eddy covariance technique over an 8-year study window. Additionally, we ascertained the effects of various environmental factors on net CO₂ flux, while also using the Michaelis-Menten model and a physiologically based process model to track and report on ecosystem carbon exchange characteristics. We observed seasonal trends in daily ecosystem flux, indicative of sensitivity to climatic factors, such as air temperature, precipitation, and sunlight. The carbon sequestration capacity of the region exhibited seasonal variability, increasing from October to March (-264 g C m^-2 year^-1, i.e., 48.4%) while weakening from April to September (-150 g C m^-2 year^-1, i.e., 40.4%) on average. The net ecosystem exchange (NEE) rate varied from -518 to -211 g C m^-2 year^-1; ecosystem respiration (Re) varied from 1,142 to 899 g C m^-2 year^-1; and gross primary production (GPP) varied from 1,552 to 1,254 g C m^-2 year^-1. This study found that even though the Dinghushan Biosphere Reserve generally acts as a carbon sink, its carbon sequestration capacity did not increase significantly throughout the study period. The techniques (models) used in this study are suitable for application in other ecosystems globally, which can aid in their management and conservation. Finally, the Dinghushan Biosphere Reserve is both an exemplary and a model forest system useful in exploring CO₂ absorption and sequestration from the atmosphere.

Eddy covariance measurements of ozone flux above and below a southern subtropical forest canopy

While extensive eddy covariance (EC) measurements of ozone (O₃) flux have been reported in American and European forests, such measurements in Asian forests are scarce. Here, we presented the first EC measurements of O₃ flux at two levels (above and below the canopy) in a Chinese forest. Above the canopy, O₃ always moved downward, with a maximum O₃ flux intensity of -15 ~ -10 nmol m^-2 s^-1 occurring at 9:00-14:00 LT and a maximum O₃ deposition velocity of 1.23 cm s^-1 occurring at 9:00 LT; both of these values fell to nearly 0 at night. The O₃ deposition flux and O₃ deposition velocity below the canopy were both lower than those above the canopy. This discrepancy reached the maximum at 9:00-15:00 local time (LT), with the O₃ deposition flux and O₃ deposition velocity below the canopy being approximately 35 and 42% of those above the canopy, respectively. The O₃ flux was well correlated with the CO₂ flux and the latent heat flux, suggesting the important role of stomatal uptake in O₃ deposition. The O₃ deposition velocity increased with the increase in the air temperature, relative humidity, photosynthetically active radiation and friction velocity, but when these meteorological factors exceeded their optimum values, the increase in the O₃ deposition velocity tended to be flat. These findings advanced our understanding of the interactions between forests and the atmosphere. This unique dataset is also of great significance for the validation of relevant models concerned with the various impacts of the rapid increase in global O₃ concentrations.

Integrating Aquatic Metabolism and Net Ecosystem CO2 Balance in Short- and Long-Hydroperiod Subtropical Freshwater Wetlands

How aquatic primary productivity influences the carbon (C) sequestering capacity of wetlands is uncertain. We evaluated the magnitude and variability in aquatic C dynamics and compared them to net ecosystem CO2 exchange (NEE) and ecosystem respiration (Reco) rates within calcareous freshwater wetlands in Everglades National Park. We continuously recorded 30-min measurements of dissolved oxygen (DO), water level, water temperature (Twater), and photosynthetically active radiation (PAR). These measurements were coupled with ecosystem CO2 fluxes over 5 years (2012–2016) in a long-hydroperiod peat-rich, freshwater marsh and a short-hydroperiod, freshwater marl prairie. Daily net aquatic primary productivity (NAPP) rates indicated both wetlands were generally net heterotrophic. Gross aquatic primary productivity (GAPP) ranged from 0 to − 6.3 g C m−2 day−1 and aquatic respiration (RAq) from 0 to 6.13 g C m−2 day−1. Nonlinear interactions between water level, Twater, and GAPP and RAq resulted in high variability in NAPP that contributed to NEE. Net aquatic primary productivity accounted for 4–5% of the deviance explained in NEE rates. With respect to the flux magnitude, daily NAPP was a greater proportion of daily NEE at the long-hydroperiod site (mean = 95%) compared to the short-hydroperiod site (mean = 64%). Although we have confirmed the significant contribution of NAPP to NEE in both long- and short-hydroperiod freshwater wetlands, the decoupling of the aquatic and ecosystem fluxes could largely depend on emergent vegetation, the carbonate cycle, and the lateral C flux.

Dynamics of CO2 fluxes and controlling environmental factors in sugarcane (C4)-wheat (C3) ecosystem of dry sub-humid region in India

In this study, CO₂ exchange over sugarcane and wheat growing season was quantified by continuous measurement of CO₂ fluxes using eddy covariance (EC) system from January 2014 to June 2015. We also elaborated on the response of CO₂ fluxes to environmental variables. The results show that the ecosystem has seasonal and diurnal dynamics of CO₂ with a distinctive U-shaped curve in both growing seasons with maximal CO₂ absorption reaching up to -8.94 g C m^-2 day^-1 and -6.08 g C m^-2 day^-1 over sugarcane and wheat crop, respectively. The ecosystem as a whole acted as a carbon sink during the active growing season while it exhibits a carbon source prior to sowing and post-harvesting of crops. The cumulative net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (R_eco) were -923.04, 3316.65, and 2433.18 g C m^-2 over the sugarcane growing season while the values were -192.30, 621.47, and 488.34 g C m^-2 over the wheat growing season. The sesbania (green manure) appeared to be a carbon source once it is incorporated into soil. The response of day-time NEE to photosynthetically active radiation (PAR) under two vapor pressure deficit (VPD) sections (0-20 h Pa and 20-40 h Pa) seems more effective over sugarcane (R² = 0.41-0.61) as compared to the wheat crop (R² = 0.25-0.40). A decrease in net CO₂ uptake was observed under higher VPD conditions. Similarly, night-time NEE was exponentially related to temperature at different soil moisture conditions and showed higher response to optimum soil moisture conditions for sugarcane (R² = 0.87, 0.33 ≤ SWC < 0.42 m³ m^-3) and wheat (R² = 0.75, 0.31 ≤ SWC < 0.37 m³ m^-3) crop seasons. The response of daily averaged NEE to environmental variables through path analysis indicates that PAR was the dominant predictor with the direct path coefficient of -0.65 and -0.74 over sugarcane and wheat growing season, respectively. Satellite-based GPP products from Moderate Resolution Imaging Spectroradiometer (GPP_MOD) and Vegetation Photosynthetic model (GPP_VPM) were also compared with the GPP obtained from EC (GPP_EC) technique. The seasonal dynamics of GPP_EC and GPP_VPM agreed well with each other. This study covers the broad aspects ranging from micro-meteorology to remote sensing over C4-C3 cropping system.

Is Agriculture Always a GHG Emitter? A Combination of Eddy Covariance and Life Cycle Assessment Approaches to Calculate C Intake and Uptake in a Kiwifruit Orchard

While a substantial reduction of GHG (greenhouse gases) is urged, large-scale mitigation implies a detailed and holistic knowledge on the role of specific cropping systems, including the effect of management choices and local factors on the final balance between emissions and removals, this last typical of cropping systems. Here, a conventionally managed irrigated kiwifruit orchard has been studied to assess its greenhouse gases emissions and removals to determine its potential action as a C sink or, alternately, as a C source. The paper integrates two independent approaches. Biological CO2 fluxes have been monitored during 2012 using the micrometeorological Eddy covariance technique, while life cycle assessment quantified emissions derived from the energy and material used. In a climatic-standard year, total GHG emitted as consequence of the management were 4.25 t CO2-eq−1 ha−1 yr−1 while the net uptake measured during the active vegetation phase was as high as 4.9 t CO2 ha−1 yr−1. This led to a positive contribution of the crop to CO2 absorption, with a 1.15 efficiency ratio (sink-source factor defined as t CO2 stored/t CO2 emitted). The mitigating activity, however, completely reversed under extremely unfavorable climatic conditions, such as those recorded in 2003, when the efficiency ratio became 0.91, demonstrating that the occurrence of hotter and drier conditions are able to compromise the capability of Actinidia to offset the GHG emissions, also under appropriate irrigation.

Carbon Sequestration in Mixed Deciduous Forests: The Influence of Tree Size and Species Composition Derived from Model Experiments

Forests play an important role in climate regulation due to carbon sequestration. However, a deeper understanding of forest carbon flux dynamics is often missing due to a lack of information about forest structure and species composition, especially for non-even-aged and species-mixed forests. In this study, we integrated field inventory data of a species-mixed deciduous forest in Germany into an individual-based forest model to investigate daily carbon fluxes and to examine the role of tree size and species composition for stand productivity. This approach enables to reproduce daily carbon fluxes derived from eddy covariance measurements (R2 of 0.82 for gross primary productivity and 0.77 for ecosystem respiration). While medium-sized trees (stem diameter 30–60 cm) account for the largest share (66%) of total productivity at the study site, small (0–30 cm) and large trees (>60 cm) contribute less with 8.3% and 25.5% respectively. Simulation experiments indicate that vertical stand structure and shading influence forest productivity more than species composition. Hence, it is important to incorporate small-scale information about forest stand structure into modelling studies to decrease uncertainties of carbon dynamic predictions.

Assessing model performance via the most limiting environmental driver in two differently stressed pine stands

Climate change will impact forest productivity worldwide. Forecasting the magnitude of such impact, with multiple environmental stressors changing simultaneously, is only possible with the help of process-based models. In order to assess their performance, such models require careful evaluation against measurements. However, direct comparison of model outputs against observational data is often not reliable, as models may provide the right answers due to the wrong reasons. This would severely hinder forecasting abilities under unprecedented climate conditions. Here, we present a methodology for model assessment, which supplements the traditional output-to-observation model validation. It evaluates model performance through its ability to reproduce observed seasonal changes of the most limiting environmental driver (MLED) for a given process, here daily gross primary productivity (GPP). We analyzed seasonal changes of the MLED for GPP in two contrasting pine forests, the Mediterranean Pinus halepensis Mill. Yatir (Israel) and the boreal Pinus sylvestris L. Hyytiälä (Finland) from three years of eddy-covariance flux data. Then, we simulated the same period with a state-of-the-art process-based simulation model (LandscapeDNDC). Finally, we assessed if the model was able to reproduce both GPP observations and MLED seasonality. We found that the model reproduced the seasonality of GPP in both stands, but it was slightly overestimated without site-specific fine-tuning. Interestingly, although LandscapeDNDC properly captured the main MLED in Hyytiälä (temperature) and in Yatir (soil water availability), it failed to reproduce high-temperature and high-vapor pressure limitations of GPP in Yatir during spring and summer. We deduced that the most likely reason for this divergence is an incomplete description of stomatal behavior. In summary, this study validates the MLED approach as a model evaluation tool, and opens up new possibilities for model improvement.

The role of emissions and meteorology in driving CO2 concentrations in urban areas

A multi-year dataset of measurements of CO₂ concentrations, eddy covariance fluxes, and meteorological parameters over the city centre of Florence (Italy) has been analysed to assess the role of anthropogenic emissions and meteorology in controlling urban CO₂ concentrations. The latter exhibited a negative correlation with air temperature, wind speed, solar radiation, and sensible heat flux and a positive one with relative humidity and emissions. A linear and an artificial neural network (ANN) model have been developed and validated for short-term modelling of 3-h CO₂ concentrations. The ANN model performed better, with mean bias of 0.58 ppm, root mean square error within 30 ppm, and r²=0.49. Data clustering through the self-organized maps allowed to disentangle the role played by emissions and meteorological parameters in influencing CO₂ concentrations. Sensitivity analysis of CO₂ concentrations revealed a primary role played by the meteorological parameters, particularly wind speed. These results highlighted that (i) emission reduction actions at local urban scale should be better tied to actual and expected meteorological conditions and (ii) those actions alone have limited effects (e.g. a 20% emission reduction would result in a 3% CO₂ concentrations reduction). For all these reasons, large-scale policies would be needed.

Energy Balance Closure in the Tugai Forest in Ebinur Lake Basin, Northwest China

A persistent problem in surface flux research is that turbulent fluxes observed by eddy covariance methods tend to be lower than the available energy. Using 7 years of eddy covariance flux observations in the Ebinur Lake National Wetland Nature Reserve (ELNWNR) in Xinjiang, Northwest China, this study analyzes the surface–atmosphere energy transfer characteristics at the station to explore variation characteristics of the energy flux and the energy balance closure (EBC), and the factors that influence EBC. The results show that: (1) diurnal and seasonal variations are observed in turbulent flux, available energy, and the partitioning of sensible and latent fluxes affected by environmental factors; (2) the degree of EBC varies significantly diurnally and seasonally, with EBC during the growing season significantly higher than during the dormant season; (3) due to the surface heterogeneity, EBC exhibits significant variations with wind direction that differ between the growing and dormant seasons; (4) environmental factors (e.g., vapor pressure deficit and air temperature) are important in limiting near-surface EBC, but they play a secondary role compared with the state of atmospheric motion. This study provides a basis for accurately assessing the material and energy exchanges between the desert Tugai forest ecosystem and the atmosphere.

Gap-Filling of Surface Fluxes Using Machine Learning Algorithms in Various Ecosystems

Five machine learning (ML) algorithms were employed for gap-filling surface fluxes of CO2, water vapor, and sensible heat above three different ecosystems: grassland, rice paddy field, and forest. The performance and limitations of these ML models, which are support vector machine, random forest, multi-layer perception, deep neural network, and long short-term memory, were investigated. Firstly, the accuracy of gap-filling to time and hysteresis input factors of ML algorithms for different ecosystems is discussed. Secondly, the optimal ML model selected in the first stage is compared with the classic method—the Penman–Monteith (P–M) equation for water vapor flux gap-filling. Thirdly, with different gap lengths (from one hour to one week), we explored the data length required for an ML model to perform the optimal gap-filling. Our results demonstrate the following: (1) for ecosystems with a strong hysteresis between surface fluxes and net radiation, adding proceeding meteorological data into the model inputs could improve the model performance; (2) the five ML models gave similar gap-filling performance; (3) for gap-filling water vapor flux, the ML model is better than the P–M equation; and (4) for a gap with length of half day, one day, or one week, an ML model with training data length greater than 1300 h would provide a better gap-filling accuracy.

Combining eddy covariance measurements with process-based modelling to enhance understanding of carbon exchange rates of dairy pastures

Many temperate grasslands are used for dairying, and ongoing research aims to better understand these systems in order to increase animal production and soil organic carbon (SOC) stocks. However, it is difficult to fully understand management effects on SOC because most changes are slow and difficult to distinguish from natural variability, even if changes are important over years to decades. Eddy covariance (EC) measurements can overcome this problem by continuously measuring net carbon exchange from pastures, but net balances are very sensitive to even small systematic measurement errors. Combining EC measurements with detailed process-based modelling can reduce the risks inherent in total reliance on EC measurements. Modelling can also reveal information about the underlying processes that drive observed fluxes. Here, we describe carbon exchange patterns of five paddocks situated at four different locations in New Zealand and France where EC data and detailed physiological modelling were available. The work showed that respiration by grazing animals was often only incompletely captured in EC measurements. This was most problematic when fluxes were based on gap-filling, which could have estimated incorrect fluxes during grazing periods based on observations from periods without grazing. We then aimed to extract plant physiological insights from these studies. We found appreciable carbon uptake rates even at temperatures below 0 °C. After grazing, carbon uptake was reduced for up to 2 weeks. This reduction was larger than expected from reduced leaf area after grazing, but the factors contributing to that difference have not yet been identified. Detailed physiological models can also extrapolate findings to new management regimes, environmental conditions or plant attributes. This overcomes the limitation of experimental studies, which are necessarily restricted to actual site and weather conditions allowing models to make further progress on predicting management effects on SOC.

Evaporative Fluxes and Surface Soil Moisture Retrievals in a Mediterranean Setting from Sentinel-3 and the “Simplified Triangle”

Earth Observation (EO) makes it possible to obtain information on key parameters characterizing interactions among Earth’s system components, such as evaporative fraction (EF) and surface soil moisture (SSM). Notably, techniques utilizing EO data of land surface temperature (Ts) and vegetation index (VI) have shown promise in this regard. The present study investigates, for the first time, the accuracy of one such technique, known as the “simplified triangle”, using Sentinel-3 EO data, acquired for 44 days in 2018 at three savannah FLUXNET sites in Spain. The technique was found to be able to predict both EF and SSM with reasonable accuracy when compared to collocated ground measurements. Comparisons performed for all days together showed relatively low Root Mean square Difference (RMSD) for both EF (0.191) and SSM (0.012 cm3 cm−3) and good correlation coefficients (R) of 0.721 and 0.577, respectively. Both EF and SSM were also largely in agreement with land cover and seasonal variability. The present study comprises the first detailed assessment of the “simplified triangle”, in this case, using Sentinel-3 data and in a Mediterranean setting. Findings, albeit preliminary, are of significant value regarding the use of the investigated technique as a tool of environmental management, and towards ongoing, worldwide efforts aiming at developing operationally relevant products based on the Ts/VI feature space and EO data based on new satellites such as Sentinel-3.

Non-stomatal processes reduce gross primary productivity in temperate forest ecosystems during severe edaphic drought

Severe drought events are known to cause important reductions of gross primary productivity (GPP) in forest ecosystems. However, it is still unclear whether this reduction originates from stomatal closure (Stomatal Origin Limitation) and/or non-stomatal limitations (Non-SOL). In this study, we investigated the impact of edaphic drought in 2018 on GPP and its origin (SOL, NSOL) using a dataset of 10 European forest ecosystem flux towers. In all stations where GPP reductions were observed during the drought, these were largely explained by declines in the maximum apparent canopy scale carboxylation rate V_CMAX,APP (NSOL) when the soil relative extractable water content dropped below around 0.4. Concurrently, we found that the stomatal slope parameter (G₁, related to SOL) of the Medlyn et al. unified optimization model linking vegetation conductance and GPP remained relatively constant. These results strengthen the increasing evidence that NSOL should be included in stomatal conductance/photosynthesis models to faithfully simulate both GPP and water fluxes in forest ecosystems during severe drought. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Applicability of a gas analyzer with dual quantum cascade lasers for simultaneous measurements of N2O, CH4 and CO2 fluxes from cropland using the eddy covariance technique

We evaluated the applicability of a closed-path gas analyzer with two mid-infrared quantum cascade lasers (QCLs) for simultaneous measurement of nitrous oxide (N₂O), methane (CH₄) and carbon dioxide (CO₂) fluxes from a cropland using the eddy covariance (EC) technique. The measurements were carried out in a typical vegetable field in the subtropical China during the wintertime, when the gas fluxes are at their lowest level in the year. A new approach was proposed to optimize the determination of lag times between the wind and gas concentration data, which was proven efficient to increase the reliability of the measured fluxes when the gas exchanges are weak. The dual-QCL analyzer showed a median precision (1σ) of 0.14 nmol mol^-1 for N₂O, 3.3 nmol mol^-1 for CH₄ and 0.36 μmol mol^-1 for CO₂ at sampling frequency of 10 Hz under the field conditions. Such precisions are better than, or comparable with, those of other commonly used closed-path or open-path gas analyzers, which are capable of measuring ony one or two ot the three gases. The detection limit of the EC system for measuring half-hourly fluxes were 0.05 nmol m^-2 s^-1 for N₂O, 1.12 nmol m^-2 s^-1 for CH₄ and 0.14 μmol m^-2 s^-1 for CO₂. The results showed that 100% of the N₂O, 85% of the CH₄ and 96% of the CO₂ fluxes were larger than the above detection limits. This study suggests that the EC technique using a closed-path gas analyzer with two quantum cascade lasers is qualified for reliable and simultaneous measurements of N₂O, CH₄ and CO₂ fluxes from a subtropical cropland throughout the year. Moreover, EC method based on this type of gas analyzer provides an additional option for long-term and simultaneous flux measurements of the three greenhouse gases in a wide range of agricultural and natural ecosystems.

The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

The FLUXNET2015 dataset provides ecosystem-scale data on CO₂, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-filled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the first time in this paper. In addition, 206 of these sites are for the first time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible.

Measurement(s)	net ecosystem exchange • carbon dioxide • water • energy
Technology Type(s)	eddy covariance • measurement device
Sample Characteristic - Environment	terrestrial biome • atmosphere
Sample Characteristic - Location	Earth (planet)

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12295910

Estimation of Gross Primary Productivity (GPP) Phenology of a Short-Rotation Plantation Using Remotely Sensed Indices Derived from Sentinel-2 Images

This study aimed to understand which vegetation indices (VIs) are an ideal proxy for describing phenology and interannual variability of Gross Primary Productivity (GPP) in short-rotation coppice (SRC) plantations. Canopy structure- and chlorophyll-sensitive VIs derived from Sentinel-2 images were used to estimate the start and end of the growing season (SOS and EOS, respectively) during the period 2016–2018, for an SRC poplar (Populus spp.) plantation in Lochristi (Belgium). Three different filtering methods (Savitzky–Golay (SavGol), polynomial (Polyfit) and Harmonic Analysis of Time Series (HANTS)) and five SOS- and EOS threshold methods (first derivative function, 10% and 20% percentages and 10% and 20% percentiles) were applied to identify the optimal methods for the determination of phenophases. Our results showed that the MEdium Resolution Imaging Spectrometer (MERIS) Terrestrial Chlorophyll Index (MTCI) had the best fit with GPP phenology, as derived from eddy covariance measurements, in identifying SOS- and EOS-dates. For SOS, the performance was only slightly better than for several other indices, whereas for EOS, MTCI performed markedly better. The relationship between SOS/EOS derived from GPP and VIs varied interannually. MTCI described best the seasonal pattern of the SRC plantation’s GPP (R2 = 0.52 when combining all three years). However, during the extreme dry year 2018, the Chlorophyll Red Edge Index performed slightly better in reproducing growing season GPP variability than MTCI (R2 = 0.59; R2 = 0.49, respectively). Regarding smoothing functions, Polyfit and HANTS methods showed the best (and very similar) performances. We further found that defining SOS as the date at which the 10% or 20% percentile occurred, yielded the best agreement between the VIs and the GPP; while for EOS the dates of the 10% percentile threshold came out as the best.

Geographical variations in gross primary production and evapotranspiration of paddy rice in the Korean Peninsula

The quantification of canopy photosynthesis and evapotranspiration of crops (ET_c) is essential to appreciate the effects of environmental changes on CO₂ flux and water availability in agricultural ecosystems and crop productivity. This study simulated the canopy photosynthesis and ET processes of paddy rice (Oryza sativa) based on the development of physiological modules (i.e., gross primary production [GPP] and ET_c) and their incorporation into the GRAMI-rice model that uses remote sensing data. We also projected spatiotemporal variations in the GPP, ET, yield, and biomass of paddy rice at maturity using the updated GRAMI-rice model combined with geostationary satellite images to identify the relationships of canopy photosynthesis and ET_c with crop productivity. GPP and ET data for paddy rice were obtained from three KoFlux sites in South Korea in 2015 and 2016. Vegetation indices were acquired from the Geostationary Ocean Color Imager (GOCI) of the Communication Ocean and Meteorological Satellite (COMS) from 2012 to 2017 and integrated into GRAMI-rice. GPP and ET_c estimates using GRAMI-rice were in close agreement with flux tower estimates with Nash-Sutcliffe efficiency ranges of 0.40-0.79 for GPP and 0.49-0.62 for ET_c. Also, GRAMI-rice was reasonably well incorporated with the COMS GOCI imagery and reproduced spatiotemporal variations in the GPP and ET of rice in the Korean peninsula. The current study results demonstrate that the updated GRAMI-rice model with the canopy photosynthesis and ET_c modules is capable of reproducing spatiotemporal variations in CO₂ assimilation and ET of paddy rice at various geographical scales and for regions of interest that are observable by satellite sensors (e.g., inaccessible North Korea).

Comparative analysis of the CO2 emissions of expressway and arterial road traffic: A case in Beijing

Urban traffic is an important source of global CO₂ emissions. Uncovering the temporal and structural characteristics can provide scientific support to identify the variation regulation and main subjects of urban traffic CO₂ emissions. The road class is one of the most important factors influencing the urban traffic CO₂ emissions. Based on the annual traffic field monitoring work in 2014 and the localized MOVES model, this study unravels the temporal variation and structural characteristics of the urban traffic CO₂ emissions and conducts a comparative analysis of expressway (5R) and arterial road (DB), two typical classes of urban roads in Beijing. Obvious differences exist in the temporal variation characteristics of the traffic CO₂ emissions between the expressway and arterial road at the annual, week and daily scales. The annual traffic CO₂ emissions at the expressway (5R, with 47271.15 t) are more than ten times than those of the arterial road (DB, with 4139.19 t). Stronger weekly “rest effect” is observed at the expressway than the arterial road. The daily peak time and duration of the traffic CO₂ emissions between the two classes of urban roads show significant differences particular in the evening peak. The differences of the structural characteristics between the two classes of urban roads are mainly reflected on the contribution of the public and freight transportation. Passenger vehicles play a predominant role at both the two classes of urban roads. The public transportation contributed more at DB (24.76%) than 5R (5.47%), and the freight transportation contributed more at 5R (23.41%) than DB (3.49%). The results suggest that the influence of traffic CO₂ emissions on the CO₂ flux is significant at the residential and commercial mixed underlying urban areas with arterial roads (DB) but not significant at the underlying urban park area with expressway (5R) in this study. The vegetation cover in urban areas have effects on the CO₂ reduction. Increasing the design and construction of the green space along the urban roads with busy traffic flow will be an effective way to mitigate the urban traffic CO₂ emissions and build the low-carbon cities.

East Siberian Arctic inland waters emit mostly contemporary carbon

Inland waters (rivers, lakes and ponds) are important conduits for the emission of terrestrial carbon in Arctic permafrost landscapes. These emissions are driven by turnover of contemporary terrestrial carbon and additional pre-aged (Holocene and late-Pleistocene) carbon released from thawing permafrost soils, but the magnitude of these source contributions to total inland water carbon fluxes remains unknown. Here we present unique simultaneous radiocarbon age measurements of inland water CO2, CH4 and dissolved and particulate organic carbon in northeast Siberia during summer. We show that >80% of total inland water carbon was contemporary in age, but pre-aged carbon contributed >50% at sites strongly affected by permafrost thaw. CO2 and CH4 were younger than dissolved and particulate organic carbon, suggesting emissions were primarily fuelled by contemporary carbon decomposition. Our findings reveal that inland water carbon emissions from permafrost landscapes may be more sensitive to changes in contemporary carbon turnover than the release of pre-aged carbon from thawing permafrost.

Impact of forest plantation on methane emissions from tropical peatland

Tropical peatlands are a known source of methane (CH4 ) to the atmosphere, but their contribution to atmospheric CH4 is poorly constrained. Since the 1980s, extensive areas of the peatlands in Southeast Asia have experienced land-cover change to smallholder agriculture and forest plantations. This land-cover change generally involves lowering of groundwater level (GWL), as well as modification of vegetation type, both of which potentially influence CH4 emissions. We measured CH4 exchanges at the landscape scale using eddy covariance towers over two land-cover types in tropical peatland in Sumatra, Indonesia: (a) a natural forest and (b) an Acacia crassicarpa plantation. Annual CH4 exchanges over the natural forest (9.1 ± 0.9 g CH4  m-2  year-1 ) were around twice as high as those of the Acacia plantation (4.7 ± 1.5 g CH4  m-2  year-1 ). Results highlight that tropical peatlands are significant CH4 sources, and probably have a greater impact on global atmospheric CH4 concentrations than previously thought. Observations showed a clear diurnal variation in CH4 exchange over the natural forest where the GWL was higher than 40 cm below the ground surface. The diurnal variation in CH4 exchanges was strongly correlated with associated changes in the canopy conductance to water vapor, photosynthetic photon flux density, vapor pressure deficit, and air temperature. The absence of a comparable diurnal pattern in CH4 exchange over the Acacia plantation may be the result of the GWL being consistently below the root zone. Our results, which are among the first eddy covariance CH4 exchange data reported for any tropical peatland, should help to reduce the uncertainty in the estimation of CH4 emissions from a globally important ecosystem, provide a more complete estimate of the impact of land-cover change on tropical peat, and develop science-based peatland management practices that help to minimize greenhouse gas emissions.

Projection of Net Primary Productivity under Global Warming Scenarios of 1.5 °C and 2.0 °C in Northern China Sandy Areas

Empirical evidence suggests that variations in climate affect the net primary productivity (NPP) across sandy areas over time. However, little is known about the relative impacts of climate change on NPP with global warming of 1.5 and 2.0 °C (GW_1.5 °C_2.0 °C) relative to pre-industrial levels. Here, we used a new set of climate simulations from four Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP 2b) datasets, modified the Carnegie-Ames-Stanford approach (CASA) model and assessed the spatio-temporal variation in NPP in sandy areas of northern China (SAONC). Compared with the reference period (RP, 1986–2005), the NPP variation under four emission scenarios showed clear rising trends and increased most significantly under RCP8.5 with an annual average increase of 2.34 g C/m2. The estimated annual NPP under global warming of 1.5 °C (GW_1.5 °C) increased by 14.17, 10.72, 8.57, and 26.68% in different emission scenarios, and under global warming of 2.0 °C (GW_2.0 °C) it increased by 20.87, 24.01, 29.31, and 39.94%, respectively. In terms of seasonal change, the NPP value under the four emission scenarios changed most significantly in the summer relative to RP, exhibiting a growth of 16.48%. Temperature changes (p > 0.614) had a greater impact on NPP growth than precipitation (p > 0.017), but solar radiation showed a certain negative impact in the middle- and low-latitude regions. NPP showed an increasing trend that changed from the southeast to the central and western regions at GW_1.5 to GW_2.0 °C. NPP was consistent with the spatial change in climate factors and had a promoting role in high latitudes in SAONC, but it was characterized by a certain inhibitory effect at middle and low latitudes in SAONC. The uncertainty of NPP under the four models ranged from 16.29 to 26.52%. Our findings suggest that the impact of GW_1.5 °C is relatively high compared with the current conditions, whereas GW_2.0 °C implies significantly lower projected NPP growth in all areas.

How eddy covariance flux measurements have contributed to our understanding of Global Change Biology

A global network of long-term carbon and water flux measurements has existed since the late 1990s. With its representative sampling of the terrestrial biosphere's climate and ecological spaces, this network is providing background information and direct measurements on how ecosystem metabolism responds to environmental and biological forcings and how they may be changing in a warmer world with more carbon dioxide. In this review, I explore how carbon and water fluxes of the world's ecosystem are responding to a suite of covarying environmental factors, like sunlight, temperature, soil moisture, and carbon dioxide. I also report on how coupled carbon and water fluxes are modulated by biological and ecological factors such as phenology and a suite of structural and functional properties. And, I investigate whether long-term trends in carbon and water fluxes are emerging in various ecological and climate spaces and the degree to which they may be driven by physical and biological forcings. As a growing number of time series extend up to 20 years in duration, we are at the verge of capturing ecosystem scale trends in the breathing of a changing biosphere. Consequently, flux measurements need to continue to report on future conditions and responses and assess the efficacy of natural climate solutions.

Carbon fluxes across alpine, oasis, and desert ecosystems in northwestern China: The importance of water availability

Dryland regions cover >40% of the Earth's land surface, making these ecosystems the largest biome in the world. Ecosystems in these areas play an important role in determining the interannual variability of the global terrestrial carbon sink. Examining carbon fluxes of various types of dryland ecosystems and their responses to climatic variability is essential for improving projections of the carbon cycle in these regions. In this study, we made use of observations from a regional flux tower observation network in a typical arid endorheic basin, the Heihe river basin (HRB). As a representative area of both the arid region of China and the entire region of central Asia, the HRB includes the main ecosystems in arid regions. We compared the spatial variations of carbon fluxes of five terrestrial ecosystems (i.e., grassland, cropland, desert, wetland, and forest ecosystems) and explored the responses of ecosystem carbon fluxes to climatic factors across different ecosystems. We found that our region exhibits a carbon sink ranging from 85.9 to 508.7 gC/m²/yr for different ecosystems, and the water availability is critical to the spatial variability of carbon fluxes in arid regions. Carbon fluxes across all sites exhibited weak correlations with temperature and precipitation. Marked differences in precipitation effects were observed between the sites within oases and those outside of oases. Irrigation and groundwater recharge were of great importance to the variations in carbon fluxes for the sites within oases. Evapotranspiration (ET) exhibited strong relationships with carbon fluxes, indicating that ET was a better metric of soil water availability than was precipitation in driving the spatial variability of carbon fluxes in arid regions. This study has implications for better understanding the carbon budget of terrestrial ecosystems and informing ecological management in dryland regions.

Error characterization of methane fluxes and budgets derived from a long-term comparison of open- and closed-path eddy covariance systems

Wetlands represent the dominant natural source of methane (CH₄) to the atmosphere. Thus, substantial effort has been spent examining the CH₄ budgets of global wetlands via continuous ecosystem-scale measurements using the eddy covariance (EC) technique. Robust error characterization for such measurements, however, remains a major challenge. Here, we quantify systematic, random and gap-filling errors and the resulting uncertainty in CH₄ fluxes using a 3.5 year time series of simultaneous open- and closed path CH₄ flux measurements over a sub-boreal wetland. After correcting for high- and low frequency flux attenuation, the magnitude of systematic frequency response errors were negligible relative to other uncertainties. Based on three different random flux error estimations, we found that errors of the CH₄ flux measurement systems were smaller in magnitude than errors associated with the turbulent transport and flux footprint heterogeneity. Errors on individual half-hourly CH₄ fluxes were typically 6%-41%, but not normally distributed (leptokurtic), and thus need to be appropriately characterized when fluxes are compared to chamber-derived or modeled CH₄ fluxes. Integrated annual fluxes were only moderately sensitive to gap-filling, based on an evaluation of 4 different methods. Calculated budgets agreed on average to within 7% (≤ 1.5 g - CH₄ m^-2 yr^-1). Marginal distribution sampling using open source code was among the best-performing of all the evaluated gap-filling approaches and it is therefore recommended given its transparency and reproducibility. Overall, estimates of annual CH₄ emissions for both EC systems were in excellent agreement (within 0.6 g - CH₄ m^-2 yr^-1) and averaged 18 g - CH₄ m^-2 yr^-1. Total uncertainties on the annual fluxes were larger than the uncertainty of the flux measurement systems and estimated between 7-17%. Identifying trends and differences among sites or site years requires that the observed variability exceeds these uncertainties.

Locating and quantifying multiple landfills methane emissions using aircraft data

A mass balance approach to quantify methane (CH4) emission of four co-located landfills by means of airborne measurements and dispersion modelling was proposed and assessed. By flying grids at different heights above the landfills, atmospheric CH4 densities and wind components were measured along the edges and inside the study atmospheric volume, in order to calculate mass flows in the along- and across-wind directions. A steady-state Gaussian dispersion model was applied to build the concentration fields associated to unit emission from each landfill, while the contribution of each one to the total emission was assessed using a General Linear Model approach, minimizing the difference between measured and modeled mass flows. Results showed that wind spatial and temporal variability is the main factor controlling the accuracy of the method, as a good agreement between measured and modeled mass flows was mainly found for flights made in steady wind conditions. CH4 emissions of the entire area ranged from 213.5 ± 33.5 to 317.9 ± 90.4 g s-1 with a mean value of 252.5 ± 54.2 g s-1. Contributions from individual sources varied from 17.5 to 40.1 g m-2 day-1 indicating a substantial heterogeneity of the different landfills, which differed in age and waste composition. The proposed method was validated against tower eddy covariance flux measurements made at one of the landfills, revealing an overall agreement within 20%.

Intensified inundation shifts a freshwater wetland from a CO2 sink to a source

Climate change has altered global precipitation patterns and has led to greater variation in hydrological conditions. Wetlands are important globally for their soil carbon storage. Given that wetland carbon processes are primarily driven by hydrology, a comprehensive understanding of the effect of inundation is needed. In this study, we evaluated the effect of water level (WL) and inundation duration (ID) on carbon dioxide (CO₂ ) fluxes by analysing a 10-year (2008-2017) eddy covariance dataset from a seasonally inundated freshwater marl prairie in the Everglades National Park. Both gross primary production (GPP) and ecosystem respiration (ER) rates showed declines under inundation. While GPP rates decreased almost linearly as WL and ID increased, ER rates were less responsive to WL increase beyond 30 cm and extended inundation periods. The unequal responses between GPP and ER caused a weaker net ecosystem CO₂ sink strength as inundation intensity increased. Eventually, the ecosystem tended to become a net CO₂ source on a daily basis when either WL exceeded 46 cm or inundation lasted longer than 7 months. Particularly, with an extended period of high-WLs in 2016 (i.e., WL remained >40 cm for >9 months), the ecosystem became a CO₂ source, as opposed to being a sink or neutral for CO₂ in other years. Furthermore, the extreme inundation in 2016 was followed by a 4-month postinundation period with lower net ecosystem CO₂ uptake compared to other years. Given that inundation plays a key role in controlling ecosystem CO₂ balance, we suggest that a future with more intensive inundation caused by climate change or water management activities can weaken the CO₂ sink strength of the Everglades freshwater marl prairies and similar wetlands globally, creating a positive feedback to climate change.

Evaluation of MOD16 Algorithm over Irrigated Rice Paddy Using Flux Tower Measurements in Southern Brazil

Evapotranspiration (ET) is an important component of the hydrological cycle. Understanding the ET process has become of fundamental importance given the scenario of global change and increasing water use, especially in the agricultural sector. Determining ET over large agricultural areas is a limiting factor due to observational data availability. In this regard, remote sensing data has been used to estimate ET. In this study, we evaluated the Moderate-Resolution Imaging Spectroradiometer (MODIS) land surface ET product estimates (hereafter MOD16 ET – MODIS Global Terrestrial Evapotranspiration Product) over two rice paddy areas in Southern Brazil, through the ET measured using the eddy covariance technique (hereafter EC). The energy balance components were evaluated during fallow and flooded seasons showing latent heat flux dominates in both seasons. The results showed that MOD16 ET underestimated EC measurements. Overall, the RMSE (root mean square error) ranged between 13.40 and 16.35 mm 8-day−1 and percent bias (PBIAS) ranged between −33.7% and −38.7%. We also assessed the ET (measured and estimated) main drivers, with EC yielding higher correlation against observed net radiation (Rn) and global radiation (Rg), followed by air temperature (Temp) and vapor pressure deficit (VPD), whilst MOD16 ET estimates yielded higher correlation against leaf area index (LAI) and fraction of photosynthetically active radiation (fPAR). The MOD16 algorithm was forced with meteorological measurements but the results did not improve as expected, suggesting a low sensitivity to meteorological inputs. Our results indicated when a water layer was present over the soil surface without vegetation (LAI around zero), the largest differences between EC measurements and MOD16 ET were found. In this period, the expected domain of soil evaporation was not observed in MOD16 ET physical processes partition, indicating the algorithm was not able to detect areas with high soil moisture. In general, the MOD16 ET product presented low accuracy when compared against experimental measurements over flooded rice paddy, suggesting more studies are necessary, in order to reduce uncertainties associated to the land cover conditions.

Water vapor flux in tropical lowland rice

A field experiment was conducted at Indian Council of Agricultural Research-National Rice Research Institute, Cuttack, Odisha, India in the dry seasons of 2015 and 2016 to assess the water vapor flux (FH₂O) and its relationship with other climatic variables. The FH₂O and climatic variables were measured by an eddy covariance system and a micrometeorological observatory. Daily mean FH₂O during the dry seasons of 2015 and 2016 were 0.009-0.092 g m^-2 s^-1 and 0.014-0.101 g m^-2 s^-1, respectively. Seasonal average FH₂O was 14.6% higher in 2016 than that in 2015. Diurnal variation for FH₂O showed a bell-shaped curve with its peak at 13:30-14:00 Indian Standard Time (IST) in both the years. Carbon dioxide flux was found higher with rise in FH₂O. This relationship was stronger at higher vapor pressure deficit (VPD) (20 ≤ VPD ≤ 40 and VPD > 40 hPa). The FH₂O showed significant positive correlation with latent heat flux, net radiation flux, photosynthatically active radiation, air, water and soil temperatures, shortwave down and upwell radiations, maximum and minimum temperatures, evaporation, and relative humidity in both the years. Principal component analysis showed that FH₂O was very close to latent heat flux in both the years (Pearson correlation coefficient close to 1). The two-dimensional observation map of the principal component F1 and F2 showed the observations taken during the vegetative stage and panicle initiation stage, and flowering stage and maturity stage were closer to each other. It can be concluded that the most important climatic variables controlling the FH₂O were latent heat of vaporization, net radiation, air temperature, soil temperatures, and water temperature.

Modification of the moving point test method for nighttime eddy CO2 flux filtering on hilly and complex terrains

The measurement of carbon dioxide (CO₂) fluxes using the eddy covariance technique is difficult in forests in complex terrain because of the horizontal advection of CO₂ at night. This results the under- or overestimation of net ecosystem exchanges of CO₂. We propose a technique for nighttime filtering (and correction) of CO₂ fluxes to eliminate (and replace) those significantly affected by horizontal advection: the modified moving point test method. This was developed by merging the friction velocity filtering and van Gorsel methods. It is based on an approach using moving windows for time and friction velocity, allowing a nighttime CO₂ flux correction that includes an assessment of CO₂ drainage at midnight. We tested the method using datasets from two flux towers in forests in hilly and complex terrains, where the application of generic nighttime filtering methods is difficult because CO₂ drainage is generated earlier than the time assumed by the generic methods. The method produced carbon budgets consistent with previous research results, while showing improved applicability.

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We propose a nighttime CO₂ flux filtering method for hilly and complex terrain that combines the friction velocity filtering and van Gorsel methods.

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This method determines the friction velocity threshold and the significance of CO₂ drainage at midnight based on an approach using moving windows for time and friction velocity.

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The method produced consistent results and shows improved applicability.

Accounting for spectroscopic effects in laser-based open-path eddy covariance flux measurements

A significant portion of the production and consumption of trace gases (e.g. CO₂ , CH₄ , N₂ O, NH₃ , etc.) by world ecosystems occurs in areas without sufficient infrastructure or easily available grid power to run traditional closed-path flux stations. Open-path analyzer design allows such measurements with power consumption 10-150 times below present closed-path technologies, helping to considerably expand the global coverage and improve the estimates of gas emissions and budgets, informing the remote sensing and modeling communities and policy decisions, all the way to IPCC reports. Broad-band nondispersive infrared devices have been used for open-path CO₂ and H₂ O measurements since the late 1970s, but since recently, a growing number of new narrow-band laser-based instruments are being rapidly developed. The new design comes with its own challenges, specifically: (a) mirror contamination, and (b) uncontrolled air temperature, pressure and humidity, affecting both the gas density and the laser spectroscopy of the measurements. While the contamination can be addressed via automated cleaning, and density effects can be addressed via the Webb-Pearman-Leuning approach, the spectroscopic effects of the in situ temperature, pressure and humidity fluctuations on laser-measured densities remain a standing methodological question. Here we propose a concept accounting for such effects in the same manner as Webb et al. proposed to account for respective density effects. Derivations are provided for a general case of flux of any gas, examined using a specific example of CH₄ fluxes from a commercially available analyzer, and then tested using "zero-flux" experiment. The proposed approach helps reduce errors in open-path, enclosed, and temperature- or pressure-uncontrolled closed-path laser-based flux measurements due to the spectroscopic effects from few percents to multiple folds, leading to methodological advancement and geographical expansion of the use of such systems providing reliable and consistent results for process-level studies, remote sensing and Earth modeling applications, and GHG policy decision-making.

Gross Primary Productivity of Four European Ecosystems Constrained by Joint CO2 and COS Flux Measurements

Gross primary productivity (GPP), the gross uptake of carbon dioxide (CO2) by plant photosynthesis, is the primary driver of the land carbon sink, which presently removes around one quarter of the anthropogenic CO2 emissions each year. GPP, however, cannot be measured directly and the resulting uncertainty undermines our ability to project the magnitude of the future land carbon sink. Carbonyl sulfide (COS) has been proposed as an independent proxy for GPP as it diffuses into leaves in a fashion very similar to CO2, but in contrast to the latter is generally not emitted. Here we use concurrent ecosystem-scale flux measurements of CO2 and COS at four European biomes for a joint constraint on CO2 flux partitioning. The resulting GPP estimates generally agree with classical approaches relying exclusively on CO2 fluxes but indicate a systematic underestimation under low light conditions, demonstrating the importance of using multiple approaches for constraining present-day GPP.