The morphological evolution of degraded patches and their sensitive response ranges in alpine meadows are key scientific issues in grassland ecosystem management. Based on a two-factor, three-gradient controlled experiment conducted on the Qinghai-Tibetan Plateau (QTP) from 2018 to 2022, this study extracted landscape metrics of bare patches in alpine meadows using UAV imagery. By integrating K-means clustering, landscape ecological indices, linear mixed models, and the adjacent gradient change rate method, we systematically analyzed the spatiotemporal dynamics of landscape fragmentation and its sensitive response ranges in alpine meadows. The results showed that: (1) Several area-related landscape indices, particularly AREA, MNA, and PLAND, exhibited a pronounced "V"-shaped temporal pattern, with 2020 as the critical turning point. Thereafter, driven by the significant interactions among mowing, pika density, and year (Year & times; Mowing & times; Pika, P < 0.01), meadow degradation was characterized by an increase in patch number, expansion of patch area, and enhanced landscape connectivity, reflecting a two-stage process of patch initiation, expansion, and coalescence; (2) The K2 area class (28.63 m(2)) represents a key potential transitional form in the degradation process and is highly sensitive to disturbances; (3) Among the two disturbance factors, mowing intensity plays a decisive role in determining patch geometry and edge expansion, whereas pika density primarily influences the degree of spatial isolation among patches; (4) Adjacent gradient change rate analysis identifies that the sensitive disturbance ranges associated with nonlinear transitions in landscape patterns occur under medium-high pika densities and medium-high mowing intensities. Therefore, adaptive management of alpine meadows should prioritize monitoring the dynamics of K2 patches to prevent their transition into large patches, while strictly controlling mowing intensity and pika density below the moderate level. Early intervention (within three years of disturbance onset) is also recommended to prevent irreversible nonlinear degradation of landscape patterns. These results will provide a theoretical reference for the early warning and disturbance regulation of patchy degradation of alpine meadows.

Accurately assessing spatiotemporal variations in terrestrial gross primary productivity (GPP) is crucial for understanding the interactions between the terrestrial carbon cycle and climate change. Environmental factors influence annual GPP (AGPP) either directly or indirectly through plant phenology and physiology. However, it remains unclear how environment, plant phenology, and physiology interact to influence the spatial patterns of global AGPP. In this study, we analyzed the geographic patterns and primary controls of the phenological and physiological properties of GPP using 827 site-years of eddy covariance data from 101 sites in the Northern Hemisphere. Specifically, the cascading relationships among environmental, phenological, and physiological factors that contribute to the spatial patterns of AGPP were tested. While the majority of ecosystems across different biomes displayed unimodal GPP seasonal patterns, significant geographical variations were observed in their phenological and physiological properties. The growing season length (GSL) decreased with increasing latitude (P < 0.001), while the maximum photosynthetic capacity (GPPmax) increased from 20°N to 70°N (P < 0.001). The foremost drivers of the spatial variation in the start date of the growing season (SGS), the end date of the growing season (EGS), and GPPmax were winter air temperature, summer precipitation, and spring solar radiation, respectively, which in turn influenced the spatial variation in AGPP. The cascade effects (0.95) of environmental factors on AGPP were larger than the direct effects (0.28). The cascading relationships among environmental factors, SGS, EGS, and GPPmax explained 93 % of the spatial pattern in AGPP. GPPmax exerted the strongest direct influence (0.60) on AGPP, followed by SGS (0.33). Environmental factors influenced the spatial variability of AGPP through cascading effects mediated by plant phenology and physiology. These findings not only provide fundamental parameters for model validation but also enhance our understanding of the intricate environmental and biotic controls governing the spatial pattern of AGPP.

Alpine grassland soils accumulate massive stocks of organic carbon and function as important carbon sinks on the Qinghai-Tibetan Plateau. Substantial uncertainties prevent a full understanding of ecosystems’ carbon pools and their responses to environmental factors, mainly because of limited observations and inconsistent up-scaling algorithms. This study compiled data since 2000 for 422 alpine grassland sites in Qinghai Province, China, to investigate vegetation and organic carbon densities in the topsoil (at 0–30 cm depth) and their spatial variations. The site-averaged below-ground biomass carbon density (BOD) and topsoil organic carbon density (SOD) were both highest in alpine meadows with values of 0.43 ± 0.34 (Mean ± S.D.) and 12.52 ± 5.74 kg C/m2, respectively. They are about five times the lowest corresponding values of alpine desert steppes. The above-ground biomass carbon density (AOD) is not significantly different between alpine steppes and alpine desert steppes, and averaged 32.66 ± 22.02 g C/m2, around twice that for alpine meadows. Boosted regression tree models and a structural equation model consistently show that mean annual precipitation, rather than mean annual air temperature, was the predominant factor influencing the spatial variability of site-level AOD, BOD, and SOD across the alpine grasslands. The boosted regression tree models, integrated with spatial datasets of topographic attributes, mean annual air temperature and precipitation, and mean annual maximal normalized difference vegetation index, yielded area-averaged AOD, BOD, and SOD values of 22.67 ± 4.48 g C/m2, 0.37 ± 0.074 kg C/m2, and 9.53 ± 4.48 kg C/m2, respectively. Modeling results indicate that ecosystem carbon densities increase from northwest to southeast, mainly following the spatial patterns of vegetation greenness and precipitation. The size of the total terrestrial ecosystem carbon pool in Qinghai province is estimated to be 3.65 Pg C, of which 96.02

Alpine grasslands store vast amounts of organic carbon and are susceptible to global change. However, the responses of ecosystem carbon storage to synchronous atmospheric nitrogen deposition and altered precipitation regimes, along with the potential environmental mechanisms, remain uncertain. Here, we investigated the responses of aboveground and belowground biomass (AGB and BGB, respectively) and surface (0 -10 cm) soil organic carbon content (SOCC) to nitrogen addition (slow-release urea, 10 g m-2 year-1) and changing precipitation (50 % increases and decreases, respectively) via a coordinated experiment distributed across three alpine grasslands (dense alpine meadow from 2017 to 2022, alpine meadow from 2017 to 2020, and alpine steppe from 2017 to 2020) on the Qinghai-Tibetan Plateau. Nitrogen-related treatments increased AGB significantly (by 20.9 %-25.1 %) in the dense alpine meadow, and the treatment of nitrogen addition plus a 50 % decrease in precipitation (N - 50 %) increased AGB by 59.8 % in the alpine steppe, when compared with the control. The N - 50 % treatment increased BGB (by 29.8 %) only in the dense alpine meadow. The SOCC of alpine grasslands exhibited an undetectable response to all treatments. Random forest model analysis showed that the spatiotemporal variations of the response ratio (RR) of AGB, BGB, and SOCC were jointly controlled by air temperature and their context (the mean values of the respective controls). Piecewise structural equation modeling confirmed the effects of context and further revealed that the RR of SOCC was balanced by the negative effects of SOCC context and positive effects of the RR of AGB. Variation partitioning analysis consistently showed that the RR of ecosystem carbon storage was regulated by the intersections of context combined with climate and treatment, rather than by individual effects. Our findings reveal a higher stabilization of belowground properties than aboveground biomass to short-term nitrogen addition and precipitation change within alpine grasslands. These results highlight the importance of context and temperature in terms of future climate impacts on alpine grassland ecosystem carbon storage.

Elucidating the response mechanisms of soil microorganisms and enzyme activities to nitrogen(N)deposition and altered precipitation regimes is crucial for understanding carbon cycle processes in alpine meadows under global change.Based on a manipulative platform involving N addition(10 g/(m2 a))and precipitation alteration(±50％)established in 2017 on the northeastern Tibetan Plateau,we analyzed the responses of soil microbial biomass carbon and nitrogen(MBC,MBN),phospholipid fatty acids(PLFAs),enzyme activities,and soil organic carbon(SOC)chemical fractions in surface(0-10 cm)and deep(30-40 cm)soil layers in 2024.Results showed that N addition enhanced aboveground biomass,surface SOC,and total nitrogen while inducing surface soil acidification,with no significant effects on belowground biomass(BGB)and soil phosphorus/potassium content.MBC,MBN,and PLFAs remained stable in surface layers but declined in deep layers.N addition increased surface urease activity but suppressed hydrolytic enzymes and deep-layer oxidative enzymes.Surface slow labile SOC increased whereas deep-layer labile and recalcitrant SOC decreased.pH and BGB jointly regulated SOC dynamics by mediating microbes and enzyme activities.These findings highlight that nitrogen and precipitation alteration drive soil carbon stability through dual pathways of environmental filtering and metabolic substrate availability.

Study region: Alpine shrubland on the northeastern Qinghai-Tibetan Plateau. Study focus: Water provision ability is a pivotal ecological service of high-altitude alpine regions and is controlled by precipitation, evapotranspiration (ET), and soil water storage whereas the underlying ecohydrological processes remain highly unquantified. Here, we investigated continuous 19-year flux measurements to quantify the temporal patterns of ET and water budget (precipitation minus ET, P-ET), as well as 0-20 cm soil water storage change (Delta SWS). New hydrological insights for the region: At a monthly scale, ET peaked in July (96.7 f 26.4 mm, Mean f S.D.) and averaged 41.7 f 31.9 mm, whose variations were determined by the slope of the saturation vapor pressure curve at air temperature, air and soil temperatures, regardless of vegetation growth stage. P-ET averaged 18.3 f 26.3 mm in August and September while stayed deficit during the other months. The variations in P-ET were controlled by precipitation in the May-October growing season whereas by ET in the non-growing season from November to April. Delta SWS peaked in May (28.8 f 11.2 mm) and September (3.0 f 2.7 mm) and almost accumulated to zero over the whole season. At annual scales, none of ET, P-ET, and Delta SWS changed significantly. ET averaged 512.2 f 68.4 mm and exceeded precipitation (459.1 f 58.4 mm), likely due to the lateral flow supply of uphill locations. The variations in ET were regulated directly by bulk canopy resistance and indirectly by net radiation. P-ET averaged -53.2 f 95.4 mm and demonstrated a clear water deficit (-51.6 f 21.0 mm) during the non-growing season. The variations of P-ET were driven jointly by precipitation and ET, with opposite but equivalent effects. The dominance of thermal conditions and energy availability on ET variability manifested an energy-limited feature of water loss in the alpine shrubland. The temporal patterns in P-ET elucidated that the alpine shrubland plays the water retention rather than water provision function through transforming variable precipitation input into stable ET loss.

Temperate grassland (TG) and alpine grassland (AG) are two distinct grassland types with different climatic backgrounds and adaptation patterns. Little is known about the universal and divergent responses of TGs and AGs to climate change, particularly with regard to the carbon (C) fluxes. The large-scale responses of the C fluxes in different grasslands to climate change remain unclear, with only a few comparative studies of distinct responses of the C fluxes in TGs and AGs to climate change hinders our understanding of this subject. In this study, we conducted a large-scale transect study across the Mongolian, Loess, and Tibetan Plateaus in China to reveal the similarities and differences in the responses of the C fluxes in TGs and AGs to climate change. We used C flux data measured by eddy covariance from ChinaFLUX and published literature, covering the period from 2003 to 2020. The results showed that TGs and AGs in China were weak C sinks. Net ecosystem productivity in TGs and AGs exhibited opposite trends with increasing latitude, longitude, and altitude. Elevated water (mean annual precipitation and soil water content) consistently increased the C fluxes. Conversely, increased temperature (mean annual temperature and mean annual soil temperature) reduced the C fluxes in TGs and increased the C fluxes in AGs. The water factors promoted the C fluxes in both TGs and AGs by improving the leaf area indices. Conversely, the temperature factors had a strong direct, negative effect on the C fluxes in TGs and a weak direct, positive effect on the C fluxes in AGs, emphasizing the divergent patterns of the C fluxes in TGs and AGs and their responses to climate change. Overall, this study enhances our knowledge on C sinks and various grassland hydrothermal sensitivities.

Aim: Chronic directional climate changes in temperature and precipitation are predicted to increase the frequency of extreme climatic events (ECEs); however, their co-occurring effects on the temporal stability of community productivity (i.e. ANPP stability) are still unclear. Here, we evaluate whether the increased frequency of ECEs reduces ANPP stability, and how it modulates the effects of chronic directional climate factors on ANPP stability in natural grassland. Location: Twenty-two sites in Asia and 14 sites in North America. Time period: 1980s-2010s. Major taxa studied: Herbaceous plant. Methods: We collected 36 long-term observational and consecutive ANPP data (at least 10 years) and resampled yearly ANPP via a consecutive resampling method of nested time windows for each field. We used linear mixed-effect models, partial regression analysis and structure equation models to explore the interactive effects of three climatic factors on ANPP stability and their associated intermediate processes of sensitivity, asymmetry, resistance and resilience. Results: The increased frequency of ECEs was observed within the long-term rising temperature and elevating precipitation trend across sites in the past several decades. Elevating precipitation rather than rising temperature was the primary driver influencing ANPP stability. Elevating precipitation increased ANPP stability through increasing mean ANPP and decreasing the standard deviation (i.e. SD) of ANPP due to a decrease in sensitivity of ANPP to precipitation. The increased frequency of ECEs decreased ANPP stability mainly by increasing the SD of ANPP, and it reduced the positive effect of elevated precipitation on ANPP stability via a decrease in resilience. Main conclusion: Our results demonstrated that recurrent and discrete ECEs had cumulatively negative effects on ANPP stability, and the decreased resilience was identified as the primary factor reducing the grassland community stability under long-term climate change. This highlighted the potential risks of increased frequency of ECEs for grassland ecosystem functions.

Quantifying the elevation dependency of radiation partitioning in high-altitude mountains is crucial for projecting regional energy balance while remains highly uncertain. We compared the surface radiation partitioning parameters across a meadow (3,200 m), shrub (3,400 m), and forb (3,600 m) along a southern slope of the Qilian Mountains. At a daily scale, the downward shortwave radiation (Rs) fluctuated minimally among the grassland types probably induced by similar site orientations. The greatest downward and upward longwave radiation (Ld and Lu) happened at the lowest meadow while the largest net shortwave (Sn) and longwave (Ln) radiation occurred at the deciduous shrub. The net all-wave radiation (Rn) of the meadow and shrub was similar and exceeded that of the forb by similar to 20%. The differences in Rn between the sites were jointly explained by those of upward shortwave radiation (Ru) and Lu, more than by Rs and Ld, suggesting the importance of surface attributes. The monthly normalized effective terrestrial radiation (lambda, the ratio of Ln to Rs) varied insignificantly among the sites and averaged 0.25 +/- 0.05, which was comparable to the global mean value (0.26). The smallest surface albedo (alpha, the ratio of Ru to Rs) and largest radiation efficiency (eta, the ratio of Rn to Rs) were 0.13 +/- 0.02 and 0.64 +/- 0.09, respectively, both at the shrub. Grassland type dominated the spatial variations of monthly alpha and eta. These findings highlighted the importance of grassland types to explain the spatiotemporal variations of radiation partitioning parameters in high-altitude alpine grasslands. An accurate understanding of the radiation budget and partitioning of high-altitude mountainous regions played a pivotal role in projecting the global climate system. This is especially true in the Qinghai-Tibetan Plateau, the so-called "roof of the world", where there is a large scarcity of high-quality field observations from different vegetation types. We compared the four-component radiation measurements of alpine grasslands along an altitudinal gradient (a meadow at 3,200 m, a shrub at 3,400 m, and a forb at 3,600 m) of a southern slope of the Qilian Mountains. We found that the incoming shortwave radiation changed little across the three sites. However, the lowest meadow had the largest incoming and outgoing longwave radiation. The net all-wave radiation of the meadow and shrub exceeded that of the highest forb. The shrub had the lowest annual surface albedo and the biggest annual radiation efficiency. The annual normalized effective terrestrial radiation fluctuated minimally across the three sites and was comparable to the global mean value. Grassland type was the most important variable responsible for the variations of surface albedo and radiation efficiency. Our findings underscored the importance of taking surface attributes into account when projecting radiation budget and partitioning in high-altitude alpine grasslands. The differences in net all-wave radiation were jointly explained by the differences in upward shortwave and longwave radiation The normalized effective terrestrial radiation was conservative among these grasslands and comparable to the global mean value Grassland type, more than environmental variables explained the spatiotemporal variations of surface albedo and radiation efficiency

The Bowen ratio (beta), which is the ratio of sensible heat (H) to latent heat (LE), reflects the energy balance and partitioning processes among soil, vegetation, and the atmosphere. Although the spatial patterns of beta have been clearly delineated, the importance of vegetation in the spatial variation of beta is frequently underestimated. Revealing the spatial patterns of beta would improve the understanding of the variation in energy partitioning in terrestrial ecosystems and its reciprocal relationship with environmental change. Here, we calculated beta by integrating H and LE flux values from 80 flux observation sites based on the eddy -covariance method in ChinaFLUX to analyze the spatial pattern and mechanism of beta in China. Terrestrial ecosystems in China had an average beta of 0.64 +/- 0.47. beta varied significantly among ecosystem types. Deserts had the highest beta (2.08 +/- 0.17), while wetlands had the lowest beta (0.37 +/- 0.11). The beta values of terrestrial ecosystems exhibited a significant latitudinal pattern, increasing linearly with latitude. This pattern also existed in forest and cropland ecosystems. The spatial pattern of beta was dominated by climate -shaped vegetation factors, including leaf area index (LAI) and fractional vegetation cover (FVC). Nevertheless, as water and thermal conditions decline, the contribution of vegetation factors gradually wanes. These findings demonstrated the spatial variations and driving mechanisms of terrestrial ecosystem beta and provided insights into the mitigation of future climate change by vegetation.

Grazing exclusion is one of the primary management practices used to restore degraded grasslands on the Tibetan Plateau. However, to date, the effects of long-term grazing exclusion measures on the process of restoring degraded alpine meadows have not been evaluated. In this study, moderately degraded plots, in which the vegetation coverage was approximately 65% and the dominant plant species was Potentilla anserina L, with grazing exclusion for 2 to 23 years, were selected in alpine meadows of Haibei in Qinghai-Tibet Plateau. Plant coverage, plant height, biomass, soil bulk density, saturated water content, soil organic carbon (SOC) and total nitrogen (TN) were evaluated. The results were as follows: (1) With increased grazing exclusion duration, aboveground biomass and total saturated water content at 0–40 cm depth, the average SOC and TN contents in moderately degraded alpine meadows increased as a power function, and the plant height increased as a log function. (2) The average soil bulk density at 0–40 cm depth first decreased and then increased with increasing grazing exclusion duration, and the minimum value of 0.90 g·cm−3 was reached at 15.23 years. The plant coverage, total belowground biomass at 0–40 cm depth, total aboveground and belowground biomass first increased and then decreased, their maximum values (80.49%, 2452.92 g·m−2, 2891.06 g·m−2) were reached at 9.41, 9.46 and 10.25 years, respectively. Long-term grazing exclusion is apparently harmful for the sustainable restoration of degraded alpine meadows. The optimal duration of grazing exclusion for the restoration of moderately degraded alpine meadows was 10 years. This research suggests that moderate disturbance should be allowed in moderately degraded alpine meadows after 10 years of grazing exclusion.

青藏高原草甸草原是生态系统中重要的植被类型，准确评估高寒草甸草原生态系统碳源汇状况及碳储量变化尤为重要。基于涡度相关系统观测，分析了2009年至2016年8年期间青海湖北岸草甸草原环境因子以及碳通量的变化特征，运用结构方程模型（SEM）分析环境因子对总初级生产力（GPP）、净生态系统CO 2 交换量（NEE）、生态系统呼吸（Re）的调控机制。结果表明：2009—2016年8年NEE日均值在-2.02—0.88 gC m -2 d -1 之间，5—9月NEE为负值，表现为碳吸收，雨热同期的6、7、8月是CO 2 净吸收最强的时期，平均每月吸收CO 2 39.85 gC m -2 month -1 ,NEE负值日数约占全年的48%,10月—翌年4月为正值，表现为碳释放，初春3月和秋末11月是CO 2 净释放最强的时期；Re日均值为1.69 gC m -2 d -1 ,受季节温度的影响，呈夏季强，冬季弱的态势，夏季的生态系统呼吸强度大约是冬季的8倍，秋季较春季呼吸强度更大；GPP日均值为3.15 gC m -2 d -1 ,随着光照辐射强度不断增大，生长季的光合生产能力显著强于非生长季，夏季最强，秋季较春季更强。从年际尺度分析可得研究区为一碳汇区，8年平均碳吸收强度为63.51 gC m -2 a -1 ,2015年碳吸收最强NEE为-95.80 gC m -2 a -1 ,2016年碳吸收最弱NEE为-30.60 gC m -2 a -1 。通过SEM分析可得：气温（Ta）对Re和GPP有显著提高的作用，GPP对NEE有极显著负响应，而Re对NEE有极显著提高作用。暗示在气候变暖的背景下，未来气温升高，青海湖北岸草甸草原生态系统碳汇功能可能会加强。

Alpine shrubland is one of the important vegetation types on the Qinghai-Tibet Plateau, which mainly lies in the shady or semi-shady slope of snowpack mountains or the high-altitude alluvium and diluvium on plains. It plays a crucial role in carbon sequestration, water conservation and climate regulation. Since 2002, Haibei National Field Research Station for Alpine Grassland (Haibei Station) has been using eddy covariance techniques to continuously observe the carbon, water and heat exchange between an alpine Potentilla fruticosa shrubland ecosystem and the atmosphere and has accumulated nearly 20-year data. On the basis of the previous publication of relevant data from 2003 to 2010, the carbon, we further released water and heat fluxes of the alpine shrubland and supplementary meteorological data from 2011 to 2020. This dataset consists of the subsets of meteorological factors, covering air temperature, air relative humidity, water vapor pressure, wind speed, wind direction, ambient pressure, total solar radiation, net radiation, photosynthetically active radiation, precipitation, soil temperature, and soil moisture, as well as net ecosystem CO2 exchange, ecosystem respiration, gross ecosystem CO2 exchange, latent heat flux, and sensible heat flux. The temporal resolutions of the dataset include half-hourly, daily, monthly, and yearly scales. This dataset can not only be used to scientifically evaluate the environmental drivers and evolution trends of the ecological functions of carbon, water and heat in alpine shrub ecosystems, but also provide ground data support for parameter validation and optimization of remote sensing-based ecological process models.

Understanding the long-term variation in evapotranspiration (ET) for the spatially distributed grasslands is crucial for the accurate prediction of ET response to climate change. In this study, we analyzed the interannual variability (IAV) of ET and its responses to environmental conditions at four grassland ecosystems across a wide range of climatic and biome conditions based on the long-term (9-11 years) eddy-covariance measurements. The four ecosystems encompassed the most prevalent grassland vegetations in China, containing a typical temperate steppe, an alpine meadow-steppe, an alpine shrubland meadow, and an alpine marsh meadow. The IAVs of annual ET at the typical temperate steppe and the alpine meadow-steppe were primarily affected by either change in precipitation (P) or relative humidity (RH). Leaf area index (LAI) was the dominant factor controlling the IAVs of annual and growing-season ET at the alpine shrubland meadow, and the IAV of LAI was significantly correlated with P variation. As to the alpine marsh meadow, net radiation turned to be the dominant factor for the IAV of annual ET, additionally with significant effects from water supply condition (P and RH) on the IAV of growing-season ET. Similar environmental responses were also found for the IAVs of mean surface conductance (g(s)) across the sites. Specifically, annual and growing-season mean gs significantly increased with increases in LAI at the alpine shrubland meadow, and appeared to be more sensitive to changes in water availability and VPD at the typical temperate steppe and the alpine meadow-steppe. Significant linear relationships were also observed among the IAVs of mean Priestley-Taylor coefficient (alpha = ET/ETeq, where ETeq is the equilibrium evaporation), decoupling coefficient (Omega), and g(s) on both the annual and growing-season basis in this study. Moreover, the variabilities of annual mean g(s), Omega, and alpha further demonstrated the energy-limited conditions at the alpine marsh meadow, and the overall water-limited conditions at the other three grasslands. This study reveals the divergent environmental responses of long-term ET variations over grassland ecosystems, and contributes to the comprehensive understanding on the ET process and modeling efforts as well.

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 (R2), 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.

The Qinghai-Tibet Plateau (QTP) is a hotspot and sensitive region affected by global climate change. The alpine shrub and alpine Kobresia humilis meadow are the primary types of alpine meadow found in this area, which play an important role in the sustainable development of the QTP and even the global alpine meadow ecosystem. Biomass, as a direct index reflecting the production function of grassland ecosystem, can be used to effectively study the relationship between grassland ecosystem function and other influencing factors. The precise measurement and assessment of the biomass of the alpine shrub and alpine Kobresia humilis meadow are crucial elements for gaining a scientific understanding of the ecological functions of the alpine meadow on the QTP. The National Field Scientific Observation and Research Station of Alpine Grassland Ecosystem located in Haibei Prefecture, Qinghai Province (Haibei Station) has been conducting scientific monitoring of the biomass of alpine Potentilla fruticosa shrub and alpine Kobresia humilis meadow respectively since 2002 and 2003. Haibei Station has continuously accumulated the original data of these two ecosystems for 17 and 18 years respectively. In order to precisely evaluate the carbon sink potential of the alpine shrub and alpine Kobresia humilis meadow ecosystems in the QTP and even the global, and accurately predict the long-term response of the ecosystem to climate change, we published the biomass data of the alpine shrub (2003-2020) and alpine Kobresia humilis meadow (2002-2020) in the Haibei Flux Monitoring Station. This dataset includes aboveground biomass and underground biomass of the alpine shrub and alpine Kobresia humilis meadow. It can provide ground observation data support for scientific cognition, remote sensing inversion and model verification of the spatial and temporal dynamics of ecosystem biomass in alpine meadows, and contribute to the healthy and sustainable development of alpine meadows.

Discrete extreme heat, deluges, and droughts become more frequent and disproportionately affect grassland ecosystem processes and functions. Here, we pair-compared the changes of CO2 and heat fluxes to natural extreme events between an alpine meadow and adjoining shrubland on the northeastern Qinghai-Tibetan Plateau. Unlike insensitive sensible heat fluxes, latent heat fluxes (LE) were promoted by 21.8% in the meadow and by 56.4% in the shrubland during a dry and subsequent compound dry hot period, respectively. The changes (Δ, data in 2016 minus the corresponding mean from the other years) of heat fluxes were both determined by the changes of solar radiation (ΔSwin). And the open-canopy shrubland has a higher sensitivity of ΔLE with ΔSwin, reflecting a stronger evaporative cooling capacity to buffer climate anomalies. CO2 fluxes responded weakly to extreme wet or dry events until those events were accompanied by hot events. During a single or compound hot event, the mean changes of total ecosystem respiration (ΔTER) were both promoted by about 30%, with a higher sensitivity of ΔTER against the changes of topsoil temperature in the more productive meadow. The mean changes of gross primary productivity (ΔGPP) fluctuated by less than 10% in the warmer meadow while were promoted by 29.3% in the cooler shrubland, likely due to different canopy structures and consequent high-temperature stress on vegetation photosynthesis. The changes of net ecosystem CO2 exchanges (ΔNEE) were significantly related to ΔTER and thus increased by 55.8% in the meadow, while it was mainly controlled by ΔGPP and then decreased by 22.4% in the shrubland. Overall, semi-arid alpine grasslands are resistant to rainfall alterations and susceptible to exceptional warmth. And the differential response was probably associated with canopy structures. Our results provide helpful insights into predicting the ecological functions of alpine grasslands in future climate changes.

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 CO2 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 (A, data for 2016 minus the corresponding means from other years) in the heat flux at both sites were determined by changes in solar radiation (ASwin), as sufficient soil moisture was available. ALE was more sensitive to ASwin in the open-canopy shrubland, reflecting its greater capacity for evaporative cooling to buffer climate anomalies. CO2 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 (ATER) increased by about 30 % in both grasslands, although ATER 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 (AGPP) 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 CO2 exchange (ANEE) were significantly related to ATER in the meadow and increased by 55.8 %, whereas ANEE was controlled mainly by AGPP 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 re-sponses 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.