Annual Net Ecosystem CO2 Exchange Research Articles

Capturing the net ecosystem CO2 exchange dynamics of tidal wetlands with high spatiotemporal resolution by integrating process-based and machine learning estimations

Accurate estimation of the net ecosystem CO2 exchange (NEE) at regional scales is of great significance for studying the carbon sink potential of coastal wetland ecosystems and their responses to global climate change. However, current NEE estimation methods are mainly developed for terrestrial ecosystems and are therefore unsuitable for NEE estimation with high spatiotemporal resolution estimation in coastal wetlands subjected to sub-daily tidal flooding. In this study, we proposed a high spatiotemporal resolution NEE estimation method for coastal marsh wetlands that properly considered tidal influence by combining the advantages of process-based modeling and machine learning. This method was verified and applied in the Changjiang estuary and Liaohe estuary marsh wetlands based on eddy covariance and environmental measurements, climate reanalysis data, and satellite images. The proposed method had good performance in the NEE estimation of tidal marsh wetlands, with Phragmites australis, Spartina alterniflora, and Suaeda salsa having coefficients of determination (R2) of 0.850, 0.676, and 0.658, respectively, and root mean square error (RMSE) values of 7.211 μmol m−2 s−1, 8.105 μmol m−2 s−1, and 0.109 μmol m−2 s−1, respectively. By integrating the tide level and salinity, the NEE estimation accuracy for each vegetation type was improved. The total annual NEE values of the Changjiang estuary and Liaohe estuary marsh wetlands in 2022 were estimated to be −0.297 and −0.444 Tg C yr−1, respectively. This study demonstrated that integrating process-based model and machine learning estimation can reliably capture the NEE dynamics of coastal wetlands, providing a useful tool to quantify coastal blue carbon potential with high spatiotemporal resolution at large scales.

Enhanced ecosystem carbon sink in shrub-grassland ecotone under grazing exclusion on Tibetan plateau

Grassland degradation is a prevalent issue at the interface of shrubland and grassland ecosystems, particularly susceptible to environmental changes. To counteract the degradation, grazing exclusion has been proposed as a dominant restoration strategy on the Tibetan plateau, the world's largest and highest plateau. However, the impact of degradation and subsequent restoration on the carbon dynamics consist of carbon sink / source capacity of shrub-grassland ecotones remain unclear. Therefore, in this study, using a transparent chamber (0.8 m in length × 0.8 m in width × 0.6 m in height) attached to an infrared gas analyzer, the in situ field investigation was performed to measure the gross ecosystem primary productivity (GEP), ecosystem respiration (Re), net ecosystem CO2 exchange (NEE), and environmental factors over a four-year continuous period in lightly and heavily degraded shrub-grassland ecotones during recover process on the Tibetan Plateau. Our result showed that: 1). Shrub-grassland ecotone acts as a net CO2 sink, with the maximum NEE occurring in July during the growing season. 2). Ecotone degradation diminishes the carbon sequestration capacity. Specifically, the annual GEP, Re, and NEE rates decrease by 14.1 %, 7.3 %, and 27.2 %, respectively, in the heavily degraded ecotone compared to the lightly degraded counterpart. 3). Grazing exclusion positively influenced the carbon sequestration capacity, particularly in heavily degraded ecotone, which leads to a substantial increase in the annual GEP, Re, and NEE rates of 15.4 % and 33.4 %, 12.3 % and 20.9 %, 22.25 % and 64.9 % for lightly and heavily degraded ecotones, respectively. 4). A piecewise structural equation model reveals that soil moisture and soil temperature are pivotal drivers influencing NEE. 5) Correlation analysis shows that NEE was negatively correlated with soil temperature during April to June and September to October but was positively correlated with soil temperature during July to August. In contrast, NEE displays a consistent negative correlation with soil moisture throughout the growing season. This research provides new insights on grassland degradation and restoration for carbon sequestration in alpine shrub-grassland ecotones and highlights their implications for sustainable management of alpine ecosystems.

Carbon budgets and environmental controls in alpine ecosystems on the Qinghai-Tibet Plateau

Rapid warming in alpine regions exerts important effects on carbon cycling in alpine ecosystem, which are sensitive to environmental changes. So far, little is known about the spatial and temporal variation in carbon budgets and the main influencing factors over different ecosystems. Here, we examined the monthly and annual gross primary production (GPP), net ecosystem CO2 exchange (NEE) and ecosystem respiration (ER) during 2004–2017 in four types of ecosystems (i.e., alpine meadow, steppe, forest and cropland) on the Tibetan Plateau. We explored the relationships between carbon fluxes and environmental factors. The results show that forest, cropland and alpine meadow ecosystems acted as carbon sinks, with NEE values ranging from −21.25 ± 3.54 to −308.75 ± 21.65 g C m-2a-1, while alpine steppe and overmature forest ecosystems serve as carbon sources (mean annual NEE: 23.12 ± 15.88 g C m-2a-1). The temperature sensitivity values (Q10) of ER in the forest (9.39) and alpine steppe (7.47) ecosystems were greater than those in the alpine meadow ecosystems (Q10 = 4.20), indicating that the carbon emissions in the forest and alpine steppe ecosystems were more sensitive to warming. Multiple linear regression analysis indicated that the carbon fluxes (GPP, NEE, ER) of alpine steppe and alpine meadow in the permafrost regions were more sensitive to water forcing (precipitation, soil water content), while in the forest and cropland ecosystems temperature forcing (air and soil temperature) were strong predictors of all the carbon flux indices. Our results showed differential responses of carbon budgets among ecosystems, which could be considered in the future modeling of carbon cycle in alpine regions.

Extreme temperature events reduced carbon uptake of a boreal forest ecosystem in Northeast China: Evidence from an 11-year eddy covariance observation.

Boreal forests, the second continental biome on Earth, are known for their massive carbon storage capacity and important role in the global carbon cycle. Comprehending the temporal dynamics and controlling factors of net ecosystem CO2 exchange (NEE) is critical for predicting how the carbon exchange in boreal forests will change in response to climate change. Therefore, based on long-term eddy covariance observations from 2008 to 2018, we evaluated the diurnal, seasonal, and interannual variations in the boreal forest ecosystem NEE in Northeast China and explored its environmental regulation. It was found that the boreal forest was a minor CO2 sink with an annual average NEE of -64.01 (± 24.23) g CO2 m-2 yr-1. The diurnal variation in the NEE of boreal forest during the growing season was considerably larger than that during the non-growing season, and carbon uptake peaked between 8:30 and 9:30 in the morning. The seasonal variation in NEE demonstrated a "U" shaped curve, and the carbon uptake peaked in July. On a half-hourly scale, photosynthetically active radiation and vapor pressure deficit had larger impacts on daytime NEE during the growing season. However, temperature had major control on NEE during the growing season at night and during the non-growing season. On a daily scale, temperature was the dominant factor controlling seasonal variation in NEE. Occurrence of extreme temperature days, especially extreme temperature events, would reduce boreal forest carbon uptake; interannual variation in NEE was substantially associated with the maximum CO2 uptake rate during the growing season. This study deepens our understanding of environmental controls on NEE at multiple timescales and provides a data basis for evaluating the global carbon budget.

Interannual characteristics and driving mechanism of CO2 fluxes during the growing season in an alpine wetland ecosystem at the southern foot of the Qilian Mountains.

The carbon process of the alpine ecosystem is complex and sensitive in the face of continuous global warming. However, the long-term dynamics of carbon budget and its driving mechanism of alpine ecosystem remain unclear. Using the eddy covariance (EC) technique-a fast and direct method of measuring carbon dioxide (CO2) fluxes, we analyzed the dynamics of CO2 fluxes and their driving mechanism in an alpine wetland in the northeastern Qinghai-Tibet Plateau (QTP) during the growing season (May-September) from 2004-2016. The results show that the monthly gross primary productivity (GPP) and ecosystem respiration (Re) showed a unimodal pattern, and the monthly net ecosystem CO2 exchange (NEE) showed a V-shaped trend. With the alpine wetland ecosystem being a carbon sink during the growing season, that is, a reservoir that absorbs more atmospheric carbon than it releases, the annual NEE, GPP, and Re reached -67.5 ± 10.2, 473.4 ± 19.1, and 405.9 ± 8.9 gCm-2, respectively. At the monthly scale, the classification and regression tree (CART) analysis revealed air temperature (Ta) to be the main determinant of variations in the monthly NEE and GPP. Soil temperature (Ts) largely determined the changes in the monthly Re. The linear regression analysis confirmed that thermal conditions (Ta, Ts) were crucial determinants of the dynamics of monthly CO2 fluxes during the growing season. At the interannual scale, the variations of CO2 fluxes were affected mainly by precipitation and thermal conditions. The annual GPP and Re were positively correlated with Ta and Ts, and were negatively correlated with precipitation. However, hydrothermal conditions (Ta, Ts, and precipitation) had no significant effect on annual NEE. Our results indicated that climate warming would be beneficial to the improvement of GPP and Re in the alpine wetland, while the increase of precipitation can weaken this effect.

Evapotranspiration and carbon exchange of the main agroecosystems and their responses to agricultural land use change in North China Plain

The North China Plain (NCP) plays an important role in food production while there is serious groundwater overexploitation in this area. The quantified relationship between the variation in evapotranspiration (ET) and net ecosystem CO2 exchange (NEE) and agricultural land use change in NCP remains unclear. In this study, based on the eddy covariance method, water balance method, and remote sensing data, ET and NEE variations were quantified and the impacts of agricultural land use change from 2002 to 2012 on regional ET and NEE variation were analyzed. The average ET and NEE of the winter wheat – summer maize cropland ecosystem were 714.2 mm yr-1 and − 534.3 gC m-2 yr-1, respectively. Correspondingly, the above values were 786.2 mm yr-1 and 667.5 gC m-2 yr-1 for the pear orchard ecosystem, and 778.6 mm yr-1 and 814.8 gC m-2 yr-1 for the vegetable field ecosystem, which had relatively high ET and ecosystem productivity. The average annual ET and NEE of the cotton field ecosystem were only 592.0 mm and − 351.3 gC m-2, respectively. Agricultural land area increased by 331.2 × 103 ha over 2002–2012, which was caused by the increasing land area of spring maize, forest/fruit trees, and vegetables. As a result, the ET and NEE of the agroecosystems in NCP increased by 25.6 × 108 m3 and − 257.9 × 104 tonC from 2002 to 2012, which are beneficial for carbon sequestration. However, the increase in carbon sink was at the cost of greater groundwater overexploitation due to increased regional water consumption. The planting of crops with high water consumption should be reduced as the surpluses of these agricultural products compared to the food demand in this region. These results are meaningful for reasonable planting structure adjustment of water-adaptive sustainable agricultural development in the NCP.

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.

Evaluation of forest carbon uptake in South Korea using the national flux tower network, remote sensing, and data-driven technology

Forests provide most of the carbon sequestration of atmospheric carbon dioxide (CO2); however, accurately quantifying the uptake amount over a region remains challenging. For reginal or national estimates, the forest productivity model and forest inventories are used which provide information for national greenhouse gas inventories. However, it has some limitations, such as not considering below-ground biomass, its lack of species-specific allometric models, the restrictions it places during fieldwork, and the long period it takes to complete the survey. In contrast to inventory-based biomass estimates, the eddy covariance (EC) method can assess net CO2 exchange of a whole ecosystem continuously and automatically with a high temporal resolution. Since, these measurements only represent a site-level observation scale (∼ 1 km2), upscaling via linkages with observation data, remote sensing, and modeling methods has been used to estimate regional or national land-atmosphere carbon fluxes. In this study, we employ a data-driven method to estimate the national-scale gross primary production (GPP) and net ecosystem CO2 exchange (NEE) by combining EC flux data from 10 sites in South Korea with remote sensing data through a machine learning algorithm based on support vector regression (SVR) for the period 2000–2018. Site-level evaluation of estimated GPP and NEE from the SVR-based model shows equivalent performance compared to other continental and global upscaled models. The mean estimated annual GPP and NEE of the South Korea forests region over the period 2000–2018 were 1465 ± 37 and −243 ± 32 g C m2 year−1, respectively. The SVR-based net primary production (NPP) was consistent with the biometric-based NPP (r2 = 0.46, p < 0.05). This study shows that combining data from a national flux network and remote sensing using a data-driven approach can be used to estimate forest CO2 fluxes on a national scale.

Prolonged impacts of extreme precipitation events weakened annual ecosystem CO2 sink strength in a coastal wetland

It remains unclear whether coastal wetlands could maintain the expected carbon sink role since extreme climate events are predicted to occur more frequently under future climate change. Among these extreme events, extreme precipitation may cause significant changes in ecosystem carbon stocks in coastal wetlands. However, the impacts of extreme precipitation events on carbon cycle processes and the mechanisms responsible for associated changes in the ecosystem carbon balance remain uncertain. To address this issue, we investigated the effects of extreme precipitation events on the ecosystem carbon dioxide (CO2) budget based on a 10-year eddy covariance dataset (2010-2019) at a coastal wetland in the Yellow River Delta. Results showed that this coastal wetland was a stable sink for CO2, with the annual net ecosystem CO2 exchange (NEE) ranged between -94.49 and -240.70 g C m−2 yr−1. Meanwhile, the interannual variability of the ecosystem CO2 sink strength in the dry stage was linked to the vegetation condition, and it was strongly affected by extreme precipitation events in the wet stage. During the wet stage, there was a clear trend of less negative daily NEE (i.e., lower CO2 uptake rate) in the years with extreme precipitation events occurring (extreme years) than in normal years, leading to the wet stage cumulative CO2 uptake being 56% lower in extreme years. Eventually, the coastal wetland became a weaker annual CO2 sink due to the prolonged impact of the extreme precipitation event. This research provides a timely study of the effect of extreme precipitation on ecosystem CO2 budget in coastal wetlands and should be of value to researchers attempting to assess the future impact of climate change on coastal ecosystems.

Altered albedo dominates the radiative forcing changes in a subtropical forest following an extreme snow event.

Subtropical forests are important ecosystems globally due to their extensive role in carbon sequestration. Extreme climate events are known to introduce disturbances in the ecosystem that cause long-term changes in carbon balance and radiation reflectance. However, how these ecosystem function changes contribute to global warming in terms of radiative forcing (RF), especially in the years following a disturbance, still needs to be investigated. We studied an extreme snow event that occurred in a subtropical evergreen broadleaved forest in south-western China in 2015 and used 9years (2011-2019) of net ecosystem CO2 exchange (NEE) and surface albedo (α) data to investigate the effect of the event on the ecosystem RF changes. In the year of the disturbance, leaf area index (LAI) declined by 40% and α by 32%. The annual NEE was -718 ± 128gCm-2 as a sink in the pre-disturbance years (2011-2014), but after the event, the sink strength dropped significantly by 76% (2015). Both the vegetation, indicated by LAI, and α recovered to pre-disturbance levels in the fourth post-disturbance year (2018). However, the NEE recovery lagged and occurred a year later in 2019, suggesting a more severe and lasting impact on the ecosystem carbon balance. Overall, the extreme event caused a positive (warming effect) net RF which was predominantly caused by changes in α (90%-93%) rather than those in NEE. This result suggests that, compared to the climate effect caused by forest carbon sequestration changes, the climate effect of α alterations can be more sensitive to vegetation damage induced by natural disturbances. Moreover, this study demonstrates the important role of vegetation recovery in driving canopy reflectance and ecosystem carbon balance during the post-disturbance period, which determines the ecosystem feedbacks to the climate change.

Carbon dioxide and water vapor fluxes of multi-purpose winter wheat production systems in the U.S. Southern Great Plains

• We synthesized CO 2 fluxes and ET from differently managed eight winter wheat fields. • Wheat fields, including graze-out, were large sinks of CO 2 during growing seasons. • Wheat fields were from near CO 2 neutral to large sinks of CO 2 at annual scales. • In general, evapotranspiration (ET) was smaller under no-till than tilled fields. • CO 2 fluxes and ET were poorly correlated with biometric variables in grazed fields. Eddy fluxes collected during 2016 to 2019 from eight production-scale multi-purpose winter wheat fields (grain only, graze-grain, and graze-out), managed under conventional till (CT) and no-till (NT), were synthesized to determine seasonality, daily magnitudes, seasonal, and annual budgets of carbon dioxide (CO 2 ) fluxes and evapotranspiration (ET), and to investigate spatio-temporal variability of the fluxes. Maximum daily net ecosystem CO 2 exchange (NEE), gross primary production (GPP), and ecosystem respiration (ER) approximated -11, 19, and 12 g C m −2 , respectively, and daily ET approximated 7 mm. Wheat fields, including graze-out, were large sinks of CO 2 (ranged from -149 ± 8 to -564 ± 9 g C m −2 ) during growing seasons (October–May). Wheat fields, left fallow during summer, were from near neutral to large sinks of CO 2 at annual (calendar year) scales. Cumulative annual NEE was up to -242 ± 12 g C m −2 in a NT and -183 ± 12 g C m −2 in a CT field, which had grain-only wheat in spring followed by graze-grain wheat in fall. Cumulative seasonal ET ranged from 260 mm to 521 mm, and maximum annual ET approximated 800 mm. In general, ET was smaller under NT than CT. Eddy fluxes showed stronger relationships with remotely-sensed enhanced vegetation index and in-situ biometric variables in grain-only fields than grazed fields. Across-site analysis for grain-only wheat showed biomass and leaf area index alone explained >80% of variations in NEE, GPP, and ET, and ∼70% of variations in ER. Similarly, Canopy coverage explained >80% of variations in NEE and GPP, and ∼60% of variations in ER and ET. Strong relationships of biometric observations with the fluxes demonstrated their potential to model and explain spatio-temporal variability of CO 2 fluxes and ET. Results also indicated huge implications of management practices on carbon and water budgets by altering vegetative properties.

Seasonal not annual precipitation drives 8-year variability of interannual net CO2 exchange in a salt marsh

Salt marshes are significant contributors to global “blue carbon” resources, and these habitats are sensitive to precipitation events due to periodically dry-wet alternation induced by tides. However, whether annual marsh-atmospheric CO2 flux responds more to annual or seasonal precipitation remains unclear. Here, eight years (2012-2019) of eddy covariance data were evaluated to determine typical CO2 budgets, and we assessed the effect of annual and seasonal precipitation on interannual net ecosystem CO2 exchange (NEE) in a salt marsh of the Yellow River Delta, China. The salt marsh was a sink for atmospheric CO2 in each of the eight study years, with an 8-year average NEE of -51.7 ± 9.7 g C m−2 a−1 varying from -8 to -85 g C m−2 a−1. Annual NEE was mainly regulated by precipitation levels during the early growth stage of plants, which modulated maximal plant biomass accumulation via water-salt transport. Besides, a spring precipitation distribution experiment showed that wetter early growth stage of plants enhanced carbon assimilation capacity in the salt marsh by decreasing soil salinity and promoting plant biomass accumulation. These findings suggest that soil water-salt conditions induced by precipitation during the onset of the growing season are crucial for interannual variations of NEE in salt marshes.

Simulating shrubs and their energy and carbon dioxide fluxes in Canada's Low Arctic with the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC)

Abstract. Climate change in the Arctic is leading to shifts in vegetation communities, permafrost degradation and alteration of tundra surface–atmosphere energy and carbon (C) fluxes, among other changes. However, year-round C and energy flux measurements at high-latitude sites remain rare. This poses a challenge for evaluating the impacts of climate change on Arctic tundra ecosystems and for developing and evaluating process-based models, which may be used to predict regional and global energy and C feedbacks to the climate system. Our study used 14 years of seasonal eddy covariance (EC) measurements of carbon dioxide (CO2), water and energy fluxes, and winter soil chamber CO2 flux measurements at a dwarf-shrub tundra site underlain by continuous permafrost in Canada’s Southern Arctic ecozone to evaluate the incorporation of shrub plant functional types (PFTs) in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC), the land surface component of the Canadian Earth System Model. In addition to new PFTs, a modification of the efficiency with which water evaporates from the ground surface was applied. This modification addressed a high ground evaporation bias that reduced model performance when soils became very dry, limited heat flow into the ground, and reduced plant productivity through water stress effects. Compared to the grass and tree PFTs previously used by CLASSIC to represent the vegetation in Arctic permafrost-affected regions, simulations with the new shrub PFTs better capture the physical and biogeochemical impact of shrubs on the magnitude and seasonality of energy and CO2 fluxes at the dwarf-shrub tundra evaluation site. The revised model, however, tends to overestimate gross primary productivity, particularly in spring, and overestimated late-winter CO2 emissions. On average, annual net ecosystem CO2 exchange was positive for all simulations, suggesting this site was a net CO2 source of 18 ± 4 g C m−2 yr−1 using shrub PFTs, 15 ± 6 g C m−2 yr−1 using grass PFTs, and 25 ± 5 g C m−2 yr−1 using tree PFTs. These results highlight the importance of using appropriate PFTs in process-based models to simulate current and future Arctic surface–atmosphere interactions.

Forest floor fluxes drive differences in the carbon balance of contrasting boreal forest stands

The forest floor provides an important interface of soil-atmosphere CO2 exchanges but their controls and contributions to the ecosystem-scale carbon budget are uncertain due to measurement limitations. In this study, we deployed eddy covariance systems below- and above-canopy to measure the spatially integrated net forest floor CO2 exchange (NFFE) and the entire net ecosystem CO2 exchange (NEE) at two mature contrasting stands located in close vicinity in boreal Sweden. We first developed an improved cospectra model to correct below-canopy flux data. Our empirical below-canopy cospectra models revealed a greater contribution of large- and small-scale eddies in the trunk space compared to their distribution in the above-canopy turbulence cospectra. We found that applying the above-canopy cospectra model did not affect the below-canopy annual CO2 fluxes at the sparse pine forest but significantly underestimated fluxes at the dense mixed spruce-pine stand. At the mixed spruce-pine stand, forest floor respiration (Rff) was higher and photosynthesis (GPPff) was lower, leading to a 1.4 times stronger net CO2 source compared to the pine stand. We further found that drought enhanced Rff more than GPPff, leading to increased NFFE. Averaged across the six site-years, forest floor fluxes contributed 82% to ecosystem-scale respiration (Reco) and 12% to gross primary production (GPP). Since the annual GPP was similar between both stands, the considerable difference in their annual NEE was due to contrasting Reco, the latter being primarily driven by the variations in NFFE. This implies that NFFE acted as the driver for the differences in NEE between these two contrasting stands. This study therefore highlights the important role of forest floor CO2 fluxes in regulating the boreal forest carbon balance. It further calls for extended efforts in acquiring high spatiotemporal resolution data of forest floor fluxes to improve predictions of global change impacts on the forest carbon cycle.

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

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

Seasonal and Interannual Variations of CO2 Fluxes Over 10 Years in an Alpine Wetland on the Qinghai‐Tibetan Plateau

AbstractAlpine wetlands play a sensitive function in global carbon cycle during the ongoing climate warming, yet the temporal patterns of carbon dynamics from in situ ground‐based long‐term observations remain unclear. Here, we analyzed the continuous net ecosystem CO2 exchange (NEE) measured with the eddy covariance technique over an alpine peatland on the northeastern Qinghai‐Tibetan Plateau from 2007 to 2016. The wetland acted as a net CO2 source with a positive NEE (120.4 ± 34.8 gC m−2 year−1, Mean ± SD), with the mean annual gross primary productivity (GPP) of 500.3 ± 59.4 gC m−2 year−1 and annual ecosystem respiration (RES) of 620.7 ± 74.2 gC m−2 year−1. At the seasonal scale, the classification and regression trees (CART) analysis showed that aggregated growing season degree days (GDDs) were the predominant determinant on variations in monthly NEE and monthly GPP. Variations in monthly RES were determined by soil temperature (Ts). Furthermore, nongrowing season Ts had a significant positive correlation with the following year annual GPP (p &lt; 0.05). Nongrowing season RES only accounted for about 25% of annual RES but had significant correlation with annual RES and annual NEE (p &lt; 0.05). The further partial correlation analysis showed that nongrowing season air temperature (Ta, p = 0.05), rather than precipitation (PPT, p = 0.25) was a predominant determinant on variations in annual NEE. Our results highlighted the importance in carbon dynamics of climate fluctuations and CO2 emission from the nongrowing season in alpine wetlands. We speculated that the vast peadlands would positively feedback to climate change on the Tibetan plateau where the nongrowing season warming was significant.

Carbon dioxide balance of an oil palm plantation established on tropical peat

Oil palm plantations have been expanding in recent decades in Indonesia and Malaysia. Carbon-rich tropical peat swamp forest has not been excluded from this expansion, because it was the last frontier suitable for industrial agriculture and more accessible than other undeveloped areas. Carbon dioxide (CO2) emission through accelerated peat decomposition is one of the main environmental concerns in the conversion of peatlands into plantations, which undergo drainage to increase palm growth rates and production. Changes in aboveground biomass might also significantly alter the CO2 exchange dynamics of the ecosystem. Despite the potential changes in CO2 balance due to land conversion, so far no study has been conducted using the eddy covariance technique about the CO2 balance of oil palm plantations established on peat. We have monitored the eddy CO2 flux above an oil palm plantation on peat in Sarawak, Malaysia since 2011. During the period from 2011 to 2014 (four years), the plantation at 7–10 years of age was a large stable CO2 source with an annual net ecosystem CO2 exchange (NEE) of 994 ± 158 g C m−2 yr−1. The NEE was much more positive than that of a peat swamp forest (-136 ± 51 g C m−2 yr−1) in the same region during the same period. The large positive NEE was caused mainly by its relatively small gross primary production (GPP) (2529 ± 125 g C m−2 yr−1) due to low leaf area index resulting from high palm mortality. In addition, a large amount of plant debris left in the plantation probably contributed to the large NEE through decomposition, especially under the many canopy gaps due to high palm mortality mainly caused by toppling on poorly compacted peat. Adequate peat compaction is essential to reduce the mortality rate.

The response of CO&amp;lt;sub&amp;gt;2&amp;lt;/sub&amp;gt; fluxes to the amplitude of diurnal temperature in alpine meadow during growing season from 2002 to 2016 at the southern foot of Qilian Mountains

Known as the “Third Pole” and “Early-warning region” of the world, the Qinghai-Tibetan Plateau (QTP) had an intense increase in surface temperature and marked change in the amplitude of diurnal temperature (ADT), which could have significant influences on the ecosystem carbon cycle. The increasing rate of the mean daily minimum temperature (MinTa) was about two times higher than that of maximum temperature (MaxTa) in the last five decades, and this asymmetric pattern has resulted in a smaller ADT, which substantially affected the plant phenology and vegetation productivity. The reduction in the ADT caused by global climate change would have a profound impact on the carbon balance of alpine ecosystems. However, the response of carbon budgets to the ADT over the QTP remained unclear. Here, we analyzed the 15-a growing seasonal (June−September) carbon fluxes (measured by the eddy covariance [EC] technique) in alpine meadow at the southern foot of Qilian Mountains, which is one of the most extensive vegetation types on the QTP. This study aimed to clarify how carbon fluxes respond to ADT at different temporal (daily, monthly and annual) scales in alpine meadow and to understand their potential response to future climate change. The results indicated that both the MaxTa and MinTa showed bell-shaped seasonal patterns, whereas the ADT failed to show an obvious trend during the growing season from 2002 to 2016. Besides, there was a non-significant increase in annual MaxTa, MinTa and ADT ( P >0.05). Meanwhile, daily gross primary productivity (GPP) and ecosystem respiration (Re) exhibited a single-peaked trend that increased and then decreased, whereas daily net ecosystem CO2 exchange (NEE) showed a v-shaped trend. The alpine meadow ecosystem is a carbon sink during the growing season, and the annual NEE, GPP, and Re were −230.4±17.3, 668.8±25.5, 438.3±27.5 g C m–2, respectively. Moreover, the annual GPP and Re of alpine meadow in the growing season showed a significant increase trend ( P P >0.05). Annual CO2 fluxes were not related annual ADT. Only annual MaxTa exerted significant influence on variations in annual GPP and Re. Interestingly, the slopes of GPP and Re with respect to MaxTa were similar, also indicating the little impact of MaxTa on annual NEE. On a monthly scale, ADT exerted a negligible influence on CO2 fluxes ( P >0.05), but there were significant correlations between MinTa and MaxTa with CO2 fluxes. On a daily scale, there was a significant quadratic relationship between daily NEE and ADT during the whole growing season ( P P

Biometeorological effects on carbon dioxide and water-use efficiency within a semiarid grassland in the Chinese Loess Plateau

Semiarid grassland ecosystems play a crucial role in global carbon and water cycles. Considerable attention has been devoted to the effect of biometeorological parameters on ecosystem carbon exchanges in semiarid regions. However, a gap remains regarding carbon and water flux in the Chinese Loess Plateau. In this study, we describe 6 years (2007–2012) of eddy-covariance carbon fluxes (CO2) and water-use efficiency (WUE) over a semiarid grassland site and their biometeorological controls. Interannual CO2 flux variations were analyzed based on a correlation analysis with measured biometeorological factors. The annual net ecosystem CO2 exchange (NEE) was negative (mean net carbon sink) across the entire period, varying from −236.3 (2012) to − 114.2 g C m−2 year−1 (2011), with a mean value of − 168.9 g C m−2 year −1. The normalized differential vegetation index is the most highly correlated with gross primary production (GPP) and evapotranspiration (ET) across several timescales. The effective precipitation frequency is an important factor influencing CO2 fluxes on an annual timescale, and soil water content was the second most important factor affecting CO2 fluxes on a monthly timescale. On an annual timescale, the semiarid grassland ecosystem WUE increased with the soil drought stress index, with ET decreasing more than GPP as soil drought increased. The monthly mean WUE varied from 0.44 to 2.51 g C kg−1 H2O, and the monthly WUE plateaued in October. Summer drought-induced leaf senescence caused GPP reduction in weaker summer monsoon years, leading to a notable reduction in WUE. We found obvious transitional characteristics in the response of WUE to soil water stress. We also found a strong positive relationship between the annual NEE and the annual effective precipitation frequency at the study site.

Methane emissions reduce the radiative cooling effect of a subtropical estuarine mangrove wetland by half.

The role of coastal mangrove wetlands in sequestering atmospheric carbon dioxide (CO2 ) and mitigating climate change has received increasing attention in recent years. While recent studies have shown that methane (CH4 ) emissions can potentially offset the carbon burial rates in low-salinity coastal wetlands, there is hitherto a paucity of direct and year-round measurements of ecosystem-scale CH4 flux (FCH4 ) from mangrove ecosystems. In this study, we examined the temporal variations and biophysical drivers of ecosystem-scale FCH4 in a subtropical estuarine mangrove wetland based on 3years of eddy covariance measurements. Our results showed that daily mangrove FCH4 reached a peak of over 0.1gCH4 -Cm-2 day-1 during the summertime owing to a combination of high temperature and low salinity, while the wintertime FCH4 was negligible. In this mangrove, the mean annual CH4 emission was 11.7±0.4gCH4 -Cm-2 year-1 while the annual net ecosystem CO2 exchange ranged between -891 and -690gCO2 -Cm-2 year-1 , indicating a net cooling effect on climate over decadal to centurial timescales. Meanwhile, we showed that mangrove FCH4 could offset the negative radiative forcing caused by CO2 uptake by 52% and 24% over a time horizon of 20 and 100years, respectively, based on the corresponding sustained-flux global warming potentials. Moreover, we found that 87% and 69% of the total variance of daily FCH4 could be explained by the random forest machine learning algorithm and traditional linear regression model, respectively, with soil temperature and salinity being the most dominant controls. This study was the first of its kind to characterize ecosystem-scale FCH4 in a mangrove wetland with long-term eddy covariance measurements. Our findings implied that future environmental changes such as climate warming and increasing river discharge might increase CH4 emissions and hence reduce the net radiative cooling effect of estuarine mangrove forests.