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Alpine wetlands sequester large amounts of soil carbon, so it is vital to gain a full understanding of their land-atmospheric CO2 exchanges and how they contribute to regional carbon neutrality; such an understanding is currently lacking for the Qinghai—Tibet Plateau (QTP), which is undergoing unprecedented climate warming. We analyzed two-year (2018–2019) continuous CO2 flux data, measured by eddy covariance techniques, to quantify the carbon budgets of two alpine wetlands (Luanhaizi peatland (LHZ) and Xiaobohu swamp (XBH)) on the northeastern QTP. At an 8-day scale, boosted regression tree model-based analysis showed that variations in growing season CO2 fluxes were predominantly determined by atmospheric water vapor, having a relative contribution of more than 65%. Variations in nongrowing season CO2 fluxes were mainly controlled by site (categorical variable) and topsoil temperature (Ts), with cumulative relative contributions of 81.8%. At a monthly scale, structural equation models revealed that net ecosystem CO2 exchange (NEE) at both sites was regulated more by gross primary productivity (GPP), than by ecosystem respiration (RES), which were both in turn directly controlled by atmospheric water vapor. The general linear model showed that variations in nongrowing season CO2 fluxes were significantly (p < 0.001) driven by the main effect of site and Ts. Annually, LHZ acted as a net carbon source, and NEE, GPP, and RES were 41.5 ± 17.8, 631.5 ± 19.4, and 673.0 ± 37.2 g C/(m2 year), respectively. XBH behaved as a net carbon sink, and NEE, GPP, and RES were –40.9 ± 7.5, 595.1 ± 15.4, and 554.2 ± 7.9 g C/(m2 year), respectively. These distinctly different carbon budgets were primarily caused by the nongrowing season RES being approximately twice as large at LHZ (p < 0.001), rather than by other equivalent growing season CO2 fluxes (p > 0.10). Overall, variations in growing season CO2 fluxes were mainly controlled by atmospheric water vapor, while those of the nongrowing season were jointly determined by site attributes and soil temperatures. Our results highlight the different carbon functions of alpine peatland and alpine swampland, and show that nongrowing season CO2 emissions should be taken into full consideration when upscaling regional carbon budgets. Current and predicted marked winter warming will directly stimulate increased CO2 emissions from alpine wetlands, which will positively feedback to climate change. [ABSTRACT FROM AUTHOR]

High-resolution sampling, measurements of organic carbon contents and 14C signatures of selected four soil profiles in the Haibei Station situated on the northeast Tibetan Plateau, and application of 14C tracing technology were conducted in an attempt to investigate the turnover times of soil organic carbon and the soil-CO2 flux in the alpine meadow ecosystem. The results show that the organic carbon stored in the soils varies from 22.12×104 kg C hm−2 to 30.75×104 kg C hm−2 in the alpine meadow ecosystems, with an average of 26.86×104 kg C hm−2. Turnover times of organic carbon pools increase with depth from 45 a to 73 a in the surface soil horizon to hundreds of years or millennia or even longer at the deep soil horizons in the alpine meadow ecosystems. The soil-CO2 flux ranges from 103.24 g C m−2 a−1 to 254.93 gC m−2 a−1, with an average of 191.23 g C m−2 a−1. The CO2 efflux produced from microbial decomposition of organic matter varies from 73.3 g C m−2 a−1 to 181 g C m−2 a−1. More than 30% of total soil organic carbon resides in the active carbon pool and 72.8%281.23% of total CO2 emitted from organic matter decomposition results from the topsoil horizon (from 0 cm to 10 cm) for the Kobresia meadow. Responding to global warming, the storage, volume of flow and fate of the soil organic carbon in the alpine meadow ecosystem of the Tibetan Plateau will be changed, which needs further research. [ABSTRACT FROM AUTHOR]

The study by the eddy covariance technique in the alpine shrub meadow of the Qinghai-Tibet Plateau in 2003 and 2004 showed that the net ecosystem carbon dioxide exchange (NEE) exhibited noticeable diurnal and annual variations, with more distinct daily changes during the warmer seasons. The CO2 emission of the shrub ecosystem culminated in April and September while the CO2 absorption capacity reached a maximum in July and August. The absorbed carbon dioxide during the two consecutive years was 231.4 and 274.8 g CO2·m−2 respectively, yielding an average of 253.1 gCO2·m−2 per year: that accounts for a large proportion of absorbed CO2 in the region. Obviously, the diurnal carbon flux was negatively related to temperature, radiation and other atmospheric factors. Still, minute discrepancies in kurtosis and duration of carbon emission/absorption were detected between 2003 and 2004. It was found that the CO2 flux in the daytime was similarly affected by photosynthetic photon flux density in both years. Temperature appears to be the most important determinant of CO2 flux: specifically, the high temperature during the plant growing season inhibits the carbon absorption capacity. One potential explanation is that soil respiration is enhanced under such condition. Analysis of biomass revealed that the annual net carbon fixed capacity of aboveground and belowground biomass was 544.0 in 2003 and 559.4 g C·m−2 in 2004, which coincided with the NEE absorption capacity (63.1 g C·m−2 in 2003 and 74.9 g C·m−2 in 2004) in the corresponding plant growing season. [ABSTRACT FROM AUTHOR]

The Integrated Environmental Monitoring (IEM) project, part of the Asia-Pacific Environmental Innovation Strategy (APEIS) project, developed an integrated environmental monitoring system that can be used to detect, monitor, and assess environmental disasters, degradation, and their impacts in the Asia-Pacific region. The system primarily employs data from the moderate resolution imaging spectrometer (MODIS) sensor on the Earth Observation System-(EOS-) Terra/Aqua satellite, as well as those from ground observations at five sites in different ecological systems in China. From the preliminary data analysis on both annual and daily variations of water, heat and CO2 fluxes, we can confirm that this system basically has been working well. The results show that both latent flux and CO2 flux are much greater in the crop field than those in the grassland and the saline desert, whereas the sensible heat flux shows the opposite trend. Different data products from MODIS have very different correspondence, e.g. MODIS-derived land surface temperature has a close correlation with measured ones, but LAI and NPP are quite different from ground measurements, which suggests that the algorithms used to process MODIS data need to be revised by using the local dataset. We are now using the APEIS-FLUX data to develop an integrated model, which can simulate the regional water, heat, and carbon fluxes. Finally, we are expected to use this model to develop more precise high-order MODIS products in Asia-Pacific region. [ABSTRACT FROM AUTHOR]

Abstract: Accurate quantification of the spatio-temporal variation of gross primary production (GPP) for terrestrial ecosystems is significant for ecosystem management and the study of the global carbon cycle. In this study, we propose a MODIS-based Photosynthetic Capacity Model (PCM) to estimate GPP in Northern China and the Tibetan Plateau. The PCM follows the logic of the light use efficiency model and is only driven by the Enhanced Vegetation Index (EVI) and the Land Surface Water Index (LSWI). Multi-year eddy CO2 flux data from five vegetation types in North China (temperate mixed forest, temperate steppe) and the Tibetan Plateau (alpine shrubland, alpine marsh and alpine meadow-steppe) were used for model parameterization and validation. In most cases, the seasonal and interannual variation in the simulated GPP agreed well with the observed GPP. Model comparisons showed that the predictive accuracy of the PCM was higher than that of the MODIS GPP products and was comparable with that of the Vegetation Photosynthesis Model (VPM) and the potential PAR-based GPP models. The model parameter (PC max) of the PCM represents the maximum photosynthetic capacity, which showed a good linear relationship with the mean annual nighttime Land Surface Temperature (LSTan). With this linear function, the PCM-simulated GPP can explain approximately 93% of the variation in the flux-observed GPP across all five vegetation types. These analyses demonstrated the potential of the PCM as an alternative tool for regional GPP estimation. [Copyright &y& Elsevier]

Abstract: It is crucial to understand the effects of enhanced nitrogen (N) deposition on soil methane (CH4) uptake to develop a better comprehension of carbon (C) dynamics in terrestrial ecosystems. A two-year field study was conducted to assess the effects of various forms of N (NH4 + and NO3 −) and associated N deposition rates (0, 10, 20 and 40kgNha−1 yr−1) on alpine meadow soil CH4 fluxes on the Qinghai–Tibetan Plateau, China. Soil CH4 fluxes, soil temperature, and soil moisture were monitored weekly using the static chamber technique and gas chromatography. Soil inorganic N pools, soil pH and aboveground biomass were measured monthly to examine the key controlling factors of soil CH4 flux. Our results showed that N addition significantly promoted plant growth and changed soil water-filled pore space (WFPS), but did not alter soil inorganic N storages over the short term. Low rates of N addition significantly decreased the seasonal amount of CH4 uptake by 8.6% compared with the control. Soil CH4 fluxes were mainly determined by soil WFPS, followed by inorganic N availability. N addition increased the contribution of soil WFPS, pH and soil NO3 − storage. The observed reduction in CH4 uptake caused by N addition may be largely due to a decrease in physical diffusion, as the biochemical inhibition effects on methanotrophic bacteria are minor. These results suggest that soil inorganic N is a regulatory factor of soil CH4 uptake, and its promotion or inhibition to soil CH4 uptake depends on the N status in terrestrial ecosystems. [Copyright &y& Elsevier]

Highlights: [•] A new version of evapotranspiration model was proposed. [•] A canopy conductance model was used in the new model. [•] Both GPP and ET was estimated in the model. [•] The model illustrated good agreement with observations at two ecosystems. [•] The model has the potential to be used at regional scale. [ABSTRACT FROM AUTHOR]

Abstract: Gross primary productivity (GPP) is a key component of land–atmospheric carbon exchange. Reliable calculation of regional/global GPP is crucial for understanding the response of terrestrial ecosystems to climate change and human activity. In recent years, many light use efficiency (LUE) models driven by remote sensing data have been developed for calculating GPP at various spatial and temporal scales. However, some studies show that GPP calculated by LUE models was biased by different degrees depending on sky clearness conditions. In this study, a two-leaf light use efficiency (TL-LUE) model is developed based on the MOD17 algorithm to improve the calculation of GPP. This TL-LUE model separates the canopy into sunlit and shaded leaf groups and calculates GPP separately for them with different maximum light use efficiencies. Different algorithms are developed to calculate the absorbed photosynthetically active radiation for these two groups. GPP measured at 6 typical ecosystems in China was used to calibrate and validate the model. The results show that with the calibration using tower measurements of GPP, the MOD17 algorithm was able to capture the variations of measured GPP in different seasons and sites. But it tends to understate and overestimate GPP under the conditions of low and high sky clearness, respectively. The new TL-LUE model outperforms the MOD17 algorithm in reproducing measured GPP at daily and 8-day scales, especially at forest sites. The calibrated LUE of shaded leaves is 2.5–3.8 times larger than that of sunlit leaves. The newly developed TL-LUE model shows lower sensitivity to sky conditions than the MOD17 algorithm. This study demonstrates the potential of the TL-LUE model in improving GPP calculation due to proper description of differences in the LUE of sunlit and shaded leaves and in the transfer of direct and diffuse light beams within the canopy. [Copyright &y& Elsevier]

Aims: To assess the effects of atmospheric N deposition on the C budget of an alpine meadow ecosystem on the Qinghai-Tibetan Plateau, it is necessary to explore the responses of soil-atmosphere carbon dioxide (CO) exchange to N addition. Methods: Based on a multi-form, low-level N addition experiment, soil CO effluxes were monitored weekly using the static chamber and gas chromatograph technique. Soil variables and aboveground biomass were measured monthly to examine the key driving factors of soil CO efflux. Results: The results showed that low-level N input tended to decrease soil moisture, whereas medium-level N input maintained soil moisture. Three-year N additions slightly increased soil inorganic N pools, especially the soil NH-N pool. N applications significantly increased aboveground biomass and soil CO efflux; moreover, this effect was more significant from NH-N than from NO-N fertilizer. In addition, the soil CO efflux was mainly driven by soil temperature, followed by aboveground biomass and NH-N pool. Conclusions: These results suggest that chronic atmospheric N deposition will stimulate soil CO efflux in the alpine meadow on the Qinghai-Tibetan Plateau by increasing available N content and promoting plant growth. [ABSTRACT FROM AUTHOR]

Abstract: An increasing nitrogen deposition experiment (2 g N m−2 year−1) was initiated in an alpine meadow on the Qinghai-Tibetan Plateau in May 2007. The greenhouse gases (GHGs), including CO2, CH4 and N2O, was observed in the growing season (from May to September) of 2008 using static chamber and gas chromatography techniques. The CO2 emission and CH4 uptake rate showed a seasonal fluctuation, reaching the maximum in the middle of July. We found soil temperature and water-filled pore space (WFPS) were the dominant factors that controlled seasonal variation of CO2 and CH4 respectively and lacks of correlation between N2O fluxes and environmental variables. The temperature sensitivity (Q 10) of CO2 emission and CH4 uptake were relatively higher (3.79 for CO2, 3.29 for CH4) than that of warmer region ecosystems, indicating the increase of temperature in the future will exert great impacts on CO2 emission and CH4 uptake in the alpine meadow. In the entire growing season, nitrogen deposition tended to increase N2O emission, to reduce CH4 uptake and to decrease CO2 emission, and the differences caused by nitrogen deposition were all not significant (p < 0.05). However, we still found significant difference (p < 0.05) between the control and nitrogen deposition treatment at some observation dates for CH4 rather than for CO2 and N2O, implying CH4 is most susceptible in response to increased nitrogen availability among the three greenhouse gases. In addition, we found short-term nitrogen deposition treatment had very limited impacts on net global warming potential (GWP) of the three GHGs together in term of CO2-equivalents. Overall, the research suggests that longer study periods are needed to verify the cumulative effects of increasing nitrogen deposition on GHG fluxes in the alpine meadow. [Copyright &y& Elsevier]

Abstract: Quantifying the partitioning of evapotranspiration (ET) and its controls are particularly important for accurate prediction of the climatic response of ecosystem carbon, water, and energy budgets. In this study, we employed the Shuttleworth–Wallace model to partition ET into soil water evaporation (E) and vegetation transpiration (T) at four grassland ecosystems in China. Two to three years (2003–2005) of continuous measurements of ET with the eddy covariance technique were used to test the long-term performance of the model. Monte Carlo simulations were performed to estimate the key parameters in the model and to evaluate the accuracy in model partitioning (i.e. E/ET). Results indicated that the simulated ET at the four ecosystems was in good agreement with the measurements at both the diurnal and seasonal timescales, but the model tended to underestimate ET by 3–11% on rainy days, probably due to the lack of model representation of rainfall interception. In general, E accounted for a large proportion of ET at these grasslands. The monthly E/ET ranged from 12% to 56% in the peak growing seasons and the annual E/ET ranged from 51% to 67% across the four ecosystems. Canopy stomatal conductance controlled E/ET at the diurnal timescale, and the variations and magnitude of leaf area index (LAI) explained most of the seasonal, annual, and site-to-site variations in E/ET. A simple linear relationship between growing season LAI and E/ET explained ca. 80% of the variation observed at the four sites for the 10 modeled site-years. Our work indicated that the daily E/ET decreased to a minimum value of ca. 10% for values of LAI greater than 3m2 m−2 at the ecosystem with a dense canopy. The sensitivities of E/ET to changes in LAI increased with the decline in water and vegetation conditions at both the seasonal and the annual time scales, i.e., the variations in LAI could cause stronger effects on E/ET in the sparse-canopy ecosystems than in the dense-canopy ecosystems. It implies that the hydrological processes and vegetation productivity for ecosystems in arid environments might be more vulnerable to projected climate change than those in humid environments. [Copyright &y& Elsevier]

Abstract: To assess the impacts of yak excreta patches on greenhouse gas (GHG) fluxes in the alpine meadow of the Qinghai-Tibetan plateau, methane (CH4), carbon dioxide (CO2), and nitrous oxide (N2O) fluxes were measured for the first time from experimental excreta patches placed on the meadow during the summer grazing seasons in 2005 and 2006. Dung patches were CH4 sources (average 586μgm−2 h−1 in 2005 and 199μgm−2 h−1 in 2006) during the investigation period of two years, while urine patches (average −31μgm−2 h−1 in 2005 and −33μgm−2 h−1 in 2006) and control plots (average −28μgm−2 h−1 in 2005 and −30μgm−2 h−1 in 2006) consumed CH4. The cumulative CO2 emission for dung patches was about 36–50% higher than control plots during the experimental period in 2005 and 2006. The cumulative N2O emissions for both urine and dung patches were 2.1–3.7 and 1.8–3.5 times greater than control plots in 2005 and 2006, respectively. Soil water-filled pore space (WFPS) explained 35% and 36% of CH4 flux variation for urine patches and control plots, respectively. Soil temperature explained 40–75% of temporal variation of CO2 emissions for all treatments. Temporal N2O flux variation in urine patches (34%), dung patches (48%), and control (56%) plots was mainly driven by the simultaneous effect of soil temperature and WFPS. Although yak excreta patches significantly affected GHG fluxes, their contributions to the whole grazing alpine meadow in terms of CO2 equivalents are limited under the moderate grazing intensity (1.45yakha−1). However, the contributions of excreta patches to N2O emissions are not negligible when estimating N2O emissions in the grazing meadow. In this study, the N2O emission factor of yak excreta patches varied with year (about 0.9–1.0%, and 0.1–0.2% in 2005 and 2006, respectively), which was lower than IPCC default value of 2%. [Copyright &y& Elsevier]

• The CO 2 sink was strong in the alpine meadows located in east of the plateau (∼200 g cm−2 y−1). • The carbon fluxes of the water-adequate ecosystems were mainly controlled by soil temperature. • Surface soil moisture explained 48% of the variations in spatial variations NEE. The magnitude and spatial patterns of carbon fluxes in alpine grasslands determine the regional terrestrial carbon balance of the Tibetan Plateau. However, the patterns and controlling factors of carbon fluxes on the plateau remain unclear, hampering the understanding of the carbon cycle of these vulnerable ecosystems. In this study, we compared the spatial variations of carbon fluxes of ten alpine ecosystems with diverse grassland types and explored their environmental controls across these different ecosystems. Our results show that the mean annual net ecosystem exchange (NEE) of carbon dioxide (CO 2) varied from -284 to 31 g C m−2 across sites. The alpine meadow ecosystems in the northeast and east of the plateau were strong CO 2 sinks (∼200 g C m−2 y−1), while the western alpine grasslands were weak CO 2 sinks or even sources. During the growing season, soil temperature generally played the dominant role in regulating the daily variations of the carbon fluxes for the alpine meadow ecosystems in the cold and humid northeastern areas, while soil moisture was the main con-trolling factor for the alpine grassland ecosystems in the dry western areas. Annual gross primary productivity (GPP), ecosystem respiration (Re) and the carbon sink capacity linearly increased with the increasing longitude but linearly decreased with elevation. The spatial pattern of annual NEE was primarily controlled by surface soil moisture, and higher soil water content (SWC) led to greater carbon sink capacity. SWC, vapor pressure deficit (VPD) also had favorable effects on the annual GPP and Re. The spatial variations of carbon fluxes resulted primarily from the longitudinal or altitudinal variations of the dominant environmental factors. This study provides guidance for the assessment of carbon fluxes on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

• The CO 2 sink was strong in the alpine meadows located in east of the plateau (∼x223C 200 g C m-2 y-1). • The carbon fluxes of the water-adequate ecosystems were mainly controlled by soil temperature. • Surface soil moisture explained 48% of the variations in spatial variations NEE. The magnitude and spatial patterns of carbon fluxes in alpine grasslands determine the regional terrestrial carbon balance of the Tibetan Plateau. However, the patterns and controlling factors of carbon fluxes on the plateau remain unclear, hampering the understanding of the carbon cycle of these vulnerable ecosystems. In this study, we compared the spatial variations of carbon fluxes of ten alpine ecosystems with diverse grassland types and explored their environmental controls across these different ecosystems. Our results show that the mean annual net ecosystem exchange (NEE) of carbon dioxide (CO 2) varied from -284 to 31 g C m−2 across sites. The alpine meadow ecosystems in the northeast and east of the plateau were strong CO 2 sinks (∼x223C 200 g C m−2 y−1), while the western alpine grasslands were weak CO 2 sinks or even sources. During the growing season, soil temperature generally played the dominant role in regulating the daily variations of the carbon fluxes for the alpine meadow ecosystems in the cold and humid northeastern areas, while soil moisture was the main controlling factor for the alpine grassland ecosystems in the dry western areas. Annual gross primary productivity (GPP), ecosystem respiration (Re) and the carbon sink capacity linearly increased with the increasing longitude but linearly decreased with elevation. The spatial pattern of annual NEE was primarily controlled by surface soil moisture, and higher soil water content (SWC) led to greater carbon sink capacity. SWC, vapor pressure deficit (VPD) also had favorable effects on the annual GPP and Re. The spatial variations of carbon fluxes resulted primarily from the longitudinal or altitudinal variations of the dominant environmental factors. This study provides guidance for the assessment of carbon fluxes on the Tibetan Plateau. [ABSTRACT FROM AUTHOR]

The eddy covariance technique provides measurements of net ecosystem exchange (NEE) of CO2 between the atmosphere and terrestrial ecosystems, which is widely used to estimate ecosystem respiration and gross primary production (GPP) at a number of CO2 eddy flux tower sites. In this paper, canopy-level maximum light use efficiency, a key parameter in the satellite-based Vegetation Photosynthesis Model (VPM), was estimated by using the observed CO2 flux data and photosynthetically active radiation (PAR) data from eddy flux tower sites in an alpine swamp ecosystem, an alpine shrub ecosystem and an alpine meadow ecosystem in Qinghai–Tibetan Plateau, China. The VPM model uses two improved vegetation indices (Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI)) derived from the Moderate Resolution Imaging Spectral radiometer (MODIS) data and climate data at the flux tower sites, and estimated the seasonal dynamics of GPP of the three alpine grassland ecosystems in Qinghai–Tibetan Plateau. The seasonal dynamics of GPP predicted by the VPM model agreed well with estimated GPP from eddy flux towers. These results demonstrated the potential of the satellite-driven VPM model for scaling-up GPP of alpine grassland ecosystems, a key component for the study of the carbon cycle at regional and global scales. [Copyright &y& Elsevier]

Abstract: We examined the CO2 exchange of a Kobresia meadow ecosystem on the Qinghai–Tibetan plateau using a chamber system. CO2 efflux from the ecosystem was strongly dependence on soil surface temperature. The CO2 efflux–temperature relationship was identical under both light and dark conditions, indicating that no photosynthesis could be detected under light conditions during the measurement period. The temperature sensitivity (Q 10) of the CO2 efflux showed a marked transition around −1.0°C; Q 10 was 2.14 at soil surface temperatures above and equal to −1.0°C but was 15.3 at temperatures below −1.0°C. Our findings suggest that soil surface temperature was the major factor controlling winter CO2 flux for the alpine meadow ecosystem and that freeze–thaw cycles at the soil surface layer play an important role in the temperature dependence of winter CO2 flux. [Copyright &y& Elsevier]

• ET was primarily radiatively driven at the two humid alpine sites. • Water supply was both controlled by precipitation with a unity slope. • Higher bulk surface resistance accounted for lower ET and higher water yields at the upper shrub. Alpine regions are generally referred to as water towers for the lowlands, yet the water balance has not been quantified for alpine catchments with different vegetation types. This paper presented a multi-year time series of evapotranspiration (ET) and water supply (precipitation minus ET) during the warm-season (June to September), measured using eddy covariance techniques for an upper alpine shrub (3400 m) and for a lower alpine meadow (3200 m), on the northeastern Qinghai-Tibetan Plateau. The monthly ET for the shrub averaged 71.8 ± 10.1 mm (Mean ± SD), which was 22.7% lower than for the meadow. ET peaked at 89.0 ± 3.0 mm for the shrub and at 113.9 ± 2.6 mm for the meadow both in July. The monthly water supply was nearly neutral from June to July and represented a surplus in August and September at both sites. The mean warm-season ET and water supply were 287.0 ± 17.6 mm and 59.6 ± 16.3 mm for the shrub, and 352.2 ± 15.7 mm and 22.5 ± 32.5 mm for the meadow, respectively. Piecewise structural equation models showed that variability of daily ET was dominated more by net radiation (R n) than by vapor pressure deficit (VPD) at both sites. However, net radiation was 32.6% higher for the shrub than for the meadow, but this did not drive higher ET for the shrub. This was explained by the difference in the energy partitioning strategy (Bowen ratio), which was attributable to the difference in the bulk surface resistance, rather than the difference in the climatological resistance (which is proportional to VPD/ R n). The seasonal and annual variability of water supply was determined by precipitation rather than by ET. The linear slopes of water supply with precipitation were all close to one, regardless of vegetation type. This suggested that the water yield efficiency was consistent at the two sites. Our results highlighted the different effects of vegetation type on ET and water supply for humid alpine regions. The lower ET loss and consequent higher water yield, but with less digestible forage in the shrub, would present a dilemma for the balance between water supply and forage production under current shrub expansion in alpine rangeland. [ABSTRACT FROM AUTHOR]

• Forests and wetlands buffer thermal fluctuation better than non-forests • Forest degradation reduces thermal buffer ability, especially at high latitudes • Canopy height is the primary impact factor influencing TBA of forests • Energy partitioning, water and CO 2 exchange are the main drivers of non-forests TBA • Protecting mature forests mitigates thermal fluctuation under extreme events With the increase in intensity and frequency of extreme climate events, interactions between vegetation and local climate are gaining more and more attention. Both the mean temperature and the temperature fluctuations of vegetation will exert thermal influence on local climate and the life of plants and animals. Many studies have focused on the pattern in the mean canopy surface temperature of vegetation, whereas there is still no systematic study of thermal buffer ability (TBA) of different vegetation types across global biomes. We developed a new method to measure TBA based on the rate of temperature increase, requiring only one radiometer. With this method, we compared TBA of ten vegetation types with contrasting structures, e.g. from grasslands to forests, using data from 133 sites globally. TBA ranged from 5.2 to 21.2 across these sites and biomes. Forests and wetlands buffer thermal fluctuation better than non-forests (grasslands, savannas, and croplands), and the TBA boundary between forests and non-forests was typically around 10. Notably, seriously disturbed and young planted forests displayed a greatly reduced TBA as low as that of non-forests at high latitudes. Canopy height was a primary controller of TBA of forests, while the TBA of grasslands and savannas were mainly determined by energy partition, water availability, and carbon sequestration rates. Our research suggests that both mean values and fluctuations in canopy surface temperature should be considered to predict the risk for plants under extreme events. Protecting mature forests, both at high and low latitudes, is critical to mitigate thermal fluctuation under extreme events. Image, graphical abstract [ABSTRACT FROM AUTHOR]

• α GPP , integrated index of GPP seasonality, was ratio of mean to maximum daily GPP. • α GPP in Northern Hemisphere ranged from 0.47 to 0.85 with an average of 0.62. • α GPP decreased as latitude increased, and was stable between years. • Spatial pattern of astronomical radiation seasonality affected that of α GPP. • Spatiotemporal variation of α GPP provided a new approach to assess annual GPP. The seasonal dynamic of gross primary productivity (GPP) has influences on the annual GPP (AGPP) of the terrestrial ecosystem. However, the spatiotemporal variation of the seasonal dynamic of GPP and its effects on spatial and temporal variations of AGPP are still poorly addressed. In this study, we developed a parameter, α GPP , defined as the ratio of mean daily GPP (GPP mean) to the maximum daily GPP (GPP max) during the growing season, to analyze the seasonal dynamic of GPP based on Weibull function. The α GPP was a comprehensive parameter characterizing the shape, scale, and location of the seasonal dynamic curve of GPP. We calculated α GPP based on the data of GPP for 942 site-years from 115 flux sites in the Northern Hemisphere, and analyzed the spatiotemporal variation and influencing factors of the α GPP. We found that the α GPP of terrestrial ecosystems in the Northern Hemisphere ranged from 0.47 to 0.85, with an average of 0.62 ± 0.06. The α GPP varied significantly both among different climatic zones and different ecosystem types. The α GPP was stable on the interannual scale, while decreased as latitude increased, which was consistent across different ecosystem types. The spatial pattern of the seasonal dynamic of astronomical radiation was the dominating factor of the spatial pattern of α GPP , that was, the spatial pattern of the seasonal dynamic of astronomical radiation determined that of the seasonal dynamic of GPP by controlling that of seasonal dynamics of total radiation and temperature. In addition, we assessed the spatial variation of AGPP preliminarily based on α GPP and other seasonal dynamic parameters of GPP, indicating that the understanding of the spatiotemporal variation of α GPP could provide a new approach for studying the spatial and temporal variations of AGPP and estimating AGPP based on the seasonal dynamic of GPP. [ABSTRACT FROM AUTHOR]

Selective inhibition of the transcription elongation factor (P-TEFb) complex represents a promising approach in cancer therapy, yet CDK9 inhibitors (CDK9i) are currently limited primarily to certain hematological malignancies. Herein, while initial responses to CDK9-targeted therapies are observed in vitro across various KRAS-mutant cancer types, their efficacy is far from satisfactory in nude mouse xenograft models. Mechanistically, CDK9 inhibition leads to compensatory activation of ERK-MYC signaling, accompanied by the recovery of proto-oncogenes, upregulation of immediate early genes (IEGs), stimulation of the complement C1r-C3-C3a cascade, and induction of tumor immunosuppression. The "paradoxical" regulation of PP2Ac activity involving the CDK9/Src interplay contributes to ERK phosphorylation and pause-release of RNA polymerase II (Pol II). Co-targeting of CDK9 and KRAS/MAPK signaling pathways eliminates ERK-MYC activation and prevents feedback activation mediated by receptor tyrosine kinases, leading to more effective control of KRAS-mutant cancers and overcoming KRASi resistance. Moreover, modulating the tumor microenvironment (TME) by complement system intervention enhances the response to CDK9i and potently suppresses tumor growth. Overall, the preclinical investigations establish a robust framework for conducting clinical trials employing KRASi/SOS1i/MEKi or immunomodifiers in combination with CDK9i to simultaneously target cancer cells and their crosstalk with the TME, thereby yielding improved responses in KRAS-mutant patients., (© 2024 The Author(s). Advanced Science published by Wiley‐VCH GmbH.)

Discrete extreme heat events, deluges, and droughts will become more frequent and disproportionately affect the processes and functions of grassland ecosystems. Here, we compared the responses of CO 2 and heat fluxes to natural extreme events in 2016 in a lower alpine meadow and neighboring upper shrubland on the northeastern Qinghai-Tibetan Plateau. Unlike insensitive sensible heat flux, latent heat flux (LE) increased by 21.8 % in the meadow and by 56.4 % in the shrubland during a dry period and subsequent compound hot-dry period in August. Changes (Δ, data for 2016 minus the corresponding means from other years) in the heat flux at both sites were determined by changes in solar radiation (ΔSwin), as sufficient soil moisture was available. ΔLE was more sensitive to ΔSwin in the open-canopy shrubland, reflecting its greater capacity for evaporative cooling to buffer climate anomalies. CO 2 fluxes responded weakly to extreme wet or dry events but strongly when those events were accompanied by exceptional heat. During single or compound hot events, the mean changes in total ecosystem respiration (ΔTER) increased by about 30 % in both grasslands, although ΔTER was more sensitive to changes in the topsoil temperature in the more productive meadow than in the shrubland. The mean changes in gross primary productivity (ΔGPP) fluctuated by <10 % in the warmer meadow but increased by 29.3 % in the cooler shrubland relative to the respective baseline, probably because of the differences in canopy structure and root depth and the consequent high-temperature stress on vegetation photosynthesis. The changes in net ecosystem CO 2 exchange (ΔNEE) were significantly related to ΔTER in the meadow and increased by 55.8 %, whereas ΔNEE was controlled mainly by ΔGPP in the shrubland and decreased by 22.4 %. Overall, both alpine grasslands were resistant to rainfall anomalies but susceptible to exceptional warmth, with the differential responses being ascribed to canopy structure and root depth. Our results provide helpful insights based on which the carbon sequestration and water-holding functions of alpine grasslands during future climate change can be predicted., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R 2 ), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics., (© 2023. Springer Nature Limited.)

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 (CO 2 ) fluxes, we analyzed the dynamics of CO 2 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 CO 2 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 CO 2 fluxes during the growing season. At the interannual scale, the variations of CO 2 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., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Zhu, Li, He, Zhang, Yang and Li.)

Widespread concern about ecological degradation has prompted development of concepts and exploration of methods to quantify ecological quality with the aim of measuring ecosystem changes to contribute to future policy-making. This paper proposes a conceptual framework for ecological quality measurement based on current ecosystem functions and biodiverse habitat, compared with pixel-scale historical baselines. The framework was applied to evaluate the changes and driving factors of ecological quality for Chinese terrestrial ecosystems through remote sensing-based and ecosystem process modeled data at 1 km spatial resolution from 2000 to 2018. The results demonstrated the ecological quality index (EQI) had a very different spatial pattern based upon vegetation distribution. An upward trend in EQI was found over most areas, and variability of 46.95% in EQI can be explained well by change in climate, with an additional 10.64% explained by changing human activities, quantified by population density. This study demonstrated a practical and objective approach for quantifying and assessing ecological quality, which has application potential in ecosystem assessments on scales from local to region and nation, yet would provide a new scientific concept and paradigm for macro ecosystems management and decision-making by governments., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Biomass temporal stability plays a key role in maintaining sustainable ecosystem functions and services of grasslands, and climate change has exerted a profound impact on plant biomass. However, it remains unclear how the community biomass stability in alpine meadows responds to changes in some climate factors (e.g., temperature and precipitation). Long-term field aboveground biomass monitoring was conducted in four alpine meadows (Haiyan [HY], Henan [HN], Gande [GD], and Qumalai [QML]) on the Qinghai-Tibet Plateau. We found that climate factors and ecological factors together affected the community biomass stability and only the stability of HY had a significant decrease over the study period. The community biomass stability at each site was positively correlated with both the stability of the dominant functional group and functional groups asynchrony. The effect of dominant functional groups on community stability decreased with the increase of the effect of functional groups asynchrony on community stability and there may be a 'trade-off' relationship between the effects of these two factors on community stability. Climatic factors directly or indirectly affect community biomass stability by influencing the stability of the dominant functional group or functional groups asynchrony. Air temperature and precipitation indirectly affected the community stability of HY and HN, but air temperature in the growing season and nongrowing season had direct negative and direct positive effects on the community stability of GD and QML, respectively. The underlying mechanisms varied between community composition and local climate conditions. Our findings highlighted the role of dominant functional group and functional groups asynchrony in maintaining community biomass stability in alpine meadows and we highlighted the importance of the environmental context when exploring the stability influence mechanism. Studies of community stability in alpine meadows along with different precipitation and temperature gradients are needed to improve our comprehensive understanding of the mechanisms controlling alpine meadow stability., Competing Interests: We declare no conflict of interest., (© 2022 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.)

Changes in ecological processes over time in ambient treatments are often larger than the responses to manipulative treatments in climate change experiments. However, the impacts of human-driven environmental changes on the stability of natural grasslands have been typically assessed by comparing differences between manipulative plots and reference plots. Little is known about whether or how ambient climate regulates the effects of manipulative treatments and their underlying mechanisms. We collected two datasets, one a 36-year long-term observational dataset from 1983 to 2018, and the other a 10-year manipulative asymmetric warming and grazing experiment using infrared heaters with moderate grazing from 2006 to 2015 in an alpine meadow on the Tibetan Plateau. The 36-year observational dataset shows that there was a nonlinear response of community stability to ambient temperature with a positive relationship between them due to an increase in ambient temperature in the first 25 years and then a decrease in ambient temperature thereafter. Warming and grazing decreased community stability with experiment duration through an increase in legume cover and a decrease in species asynchrony, which was due to the decreasing background temperature through time during the 10-year experiment period. Moreover, the temperature sensitivity of community stability was higher under the ambient treatment than under the manipulative treatments. Therefore, our results suggested that ambient climate may control the directional trend of community stability while manipulative treatments may determine the temperature sensitivity of the response of community stability to climate relative to the ambient treatment. Our study emphasizes the importance of the context dependency of the response of community stability to human-driven environmental changes., (© 2021 John Wiley & Sons Ltd.)

The FLUXNET2015 dataset provides ecosystem-scale data on CO 2 , 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.

Tibetan permafrost largely formed during the late Pleistocene glacial period and shrank in the Holocene Thermal Maximum period. Quantifying the impacts of paleoclimatic extremes on soil carbon stock can shed light on the vulnerability of permafrost carbon in the future. Here, we synthesize data from 1114 sites across the Tibetan permafrost region to report that paleoclimate is more important than modern climate in shaping current permafrost carbon distribution, and its importance increases with soil depth, mainly through forming the soil's physiochemical properties. We derive a new estimate of modern soil carbon stock to 3 m depth by including the paleoclimate effects, and find that the stock ([Formula: see text] PgC) is triple that predicted by ecosystem models (11.5 ± 4.2 s.e.m PgC), which use pre-industrial climate to initialize the soil carbon pool. The discrepancy highlights the urgent need to incorporate paleoclimate information into model initialization for simulating permafrost soil carbon stocks.