Climate change is reshaping plant growth dynamics, particularly in cold regions experiencing intensified warming and increased precipitation. However, due to limited long-term field evidence, how climatic drivers regulate species-specific growth patterns and thereby influence community growth and biomass production remains poorly understood. Here, based on a 24-year field experiment in alpine meadow on the Qinghai-Tibet Plateau, we systematically analyzed the shifts in plant phenology, growth rates, and biomass trajectories under long-term warming and increased precipitation. We further examined how climate-driven changes in plant growth influenced biomass dynamics at both species and community levels. Our results showed that sustained warming and increased precipitation significantly enhanced plant growth rates, while the start of the growth period remained unchanged. In contrast, the end of the growth period varied markedly among the six observed species. Growth-rate responses were strongly species dependent. K. humilis and A. laxmannii exhibited significantly accelerated growth and increased biomass, largely influenced by increased precipitation under warming. Other species showed weaker or contrasting biomass responses, leading to directional shifts in relative species abundance and dominance structure. Collectively, species-level growth acceleration and compositional shifts enhanced overall community growth and biomass production. Our findings provide long-term in situ evidence that biomass enhancement in alpine meadow under warming and increased precipitation is primarily regulated by species-dependent growth rate responses and associated compositional shifts, rather than by changes in spring phenology. This highlights the importance of integrating species-level growth processes and community reorganization to improve future predictions of grassland productivity.

Alpine grasslands on the Tibetan Plateau constitute a pivotal component of the global carbon cycle. As the dominant CO₂ flux pathway, soil respiration demonstrates marked sensitivity to both climate warming and anthropogenic disturbances. Based on a long-term experiment combining warming (open-top chambers) and mowing (annual clipping), we systematically monitored soil respiration rates, concurrently with soil temperature and moisture, plant community traits, and soil nutrient, to elucidate the responses patterns of alpine meadow soil respiration to warming and mowing and identify their dominant drivers. Soil respiration was significantly affected by the main effects of warming and mowing (P < 0.05) and was strongly correlated with soil temperature and moisture. Q₁₀ decreased by 5.04

Landscape Ecological Risk Assessment is a core component of spatial governance and regional ecological protection, as well as a fundamental task in ecosystem management. This study uses the Qilian Mountains ecosystem as a case study, innovatively integrating the Geo-Detector model, XGBoost-SHAP model, and constraint line method to explore the spatiotemporal dynamics and driving mechanisms of Landscape Ecological Risk (LER) from a nonlinear perspective between 2000 and 2023. The main findings are as follows: (1) Temporal Evolution Characteristics: The annual variation rate of the Landscape Ecological Risk Index (LERI) was 0.0011 yr(-1) (R-2 = 0.0861, p = 0.1641), showing weak fluctuations. The proportion of Extremely Low-Ecological Risk Areas and Low Ecological Risk Areas remained stable within the range of 50.56 % to 64.07 %, and the ecological security pattern remained relatively stable. The area of Extremely High Ecological Risk Areas decreased significantly, with an annual reduction rate of -0.0791 x 10(4) km(2) yr(-1) (R-2 = 0.5655, p < 0.001), indicating continuous improvement in regional ecological quality. (2) Driving Mechanism Analysis: The Geo-Detector model showed that the primary driving factors, ranked by explanatory power, were Grazing Intensity (GI) (Q = 0.2472), Land Surface Temperature (LST) (Q = 0.2145), Elevation (Q = 0.1605), Annual Precipitation (Q = 0.1546), Downward Shortwave Radiation (DSR) (Q = 0.1032), and Annual Mean Temperature (Q = 0.0942), with a total explanatory power of 80.83 %. The XGBoost-SHAP model identified the top six significant factors as GI (SHAP = 0.0918), Specific Humidity (SH) (SHAP = 0.0454), Annual Precipitation (SHAP = 0.0452), DSR (SHAP = 0.0344), Wind Speed (WS) (SHAP = 0.0259), and Elevation (SHAP = 0.0251), with a total contribution rate of 87.46 %. Interaction analysis revealed that the nonlinear synergistic effect between GI and climate factors was the most significant, particularly the interactions between GI and Annual Precipitation (Q = 0.434) and GI and Elevation (Q = 0.419). (3) Threshold Response Characteristics: Elevation exhibited a concave-downward constraint effect (R-2 = 0.7867), with a critical threshold at 4200 m. Beyond this threshold, the constraint intensity on LER increased. A significant threshold inflection point for DSR was found at 2502 W/m(2). Climate constraint thresholds revealed that when Annual Precipitation < 200 mm, Mean Temperature < -6 degrees C, and Specific Humidity < 2.8068 g/kg, the constraint effect on landscape risk was enhanced. Grazing Intensity exhibited a dual-threshold response: 3.35 SU/ha was the critical point for rapid increases in landscape risk, while 14.36 SU/ha marked the threshold for abrupt ecological stability loss. Beyond this threshold, the fragmentation of landscape structure sharply increased, significantly raising the risk of ecological collapse. The nonlinear constraint mechanism model of "driving factors - Landscape Ecological Risk" proposed in this study overcomes the limitations of traditional threshold determination methods and provides an accurate and quantitative tool for mountain ecosystem restoration and spatial planning. The findings offer significant practical value for balancing regional ecological protection with sustainable development.

Based on a nonlinear theoretical framework, this study systematically reveals the spatiotemporal evolution characteristics of fractional vegetation cover (FVC) in the Qilian Mountains and its environmental constraints, providing scientific support for mountain ecosystem restoration and territorial spatial management. By integrating remote sensing inversion, GIS spatial analysis, and the constraint line model, the following key findings were obtained: (1) Spatiotemporal Evolution Characteristics: From 2000 to 2023, the FVC in the study area exhibited a fluctuating upward trend (annual growth rate of 0.26 %, R-2 = 0.5654, p < 0.001), forming a significant longitudinal gradient pattern. A sharp contrast was observed between the high-coverage areas (FVC > 60 %) in the southeast and the lowcoverage areas in the northwest, where bare land and extremely low to low-coverage regions accounted for 56.25 %. Notably, 54.84 % of the region experienced significant vegetation improvement, with the "greening" effect particularly pronounced in the central and western regions. (2) Topographic Vertical Constraint Mechanism: The altitudinal gradient shaped a four-stage response pattern: in the 2000-2900 m range, vegetation cover increased at a rate of + 1.56 %/100 m, mainly driven by water-heat synergy; in the 2900-4000 m range, accumulated environmental stress reversed the growth trend, leading to a decline of -1.32 %/100 m; in the 4000-4800 m range, thermal constraints intensified sharply, accelerating the decline to -8.01 %/100 m; in the 4800-5800 m range, vegetation approached its survival limit, with the decline rate slowing to -0.57 %/100 m. (3) Climatic Regulation Threshold Effects: Temperature control exhibited a biphasic hump-shaped pattern (R-2 = 0.9449). In the -15 degrees C to -7 degrees C range, the FVC gain rate reached 14.22 %/degrees C; between -7 degrees C and 0 degrees C, the gain rate decreased to 3.07 %/degrees C, with 0 degrees C identified as a critical threshold. Above 0 degrees C, increasing competition pressure led to a decline in FVC (-0.68 %/degrees C). Moisture regulation showed a diminishing marginal effect: in the 20-300 mm range, each additional 10 mm of precipitation increased FVC by 2.97 %; in the 300-450 mm range, the marginal gain decreased to 0.88 %; above 450 mm, moisture constraints were lifted, and light-heat conditions became the primary limiting factors. This study identifies critical ecological thresholds of 4000 m altitude, an annual mean temperature of 0 degrees C, and 300 mm annual precipitation, elucidating the nonlinear response mechanisms of mountain ecosystems. Furthermore, it establishes a multidimensional "topography-climate-management" adaptive regulation framework, providing a scientific paradigm for transitioning ecological restoration from "maximum greenness" to "optimal resilience."

Alpine meadows,alpine wetlands,and alpine desert steppes are the three typical vegetation types on the Qinghai-Tibet Plateau.The complex terrain and harsh climatic conditions across this region lead to considerable diversification in the vegetation growth environment,resulting in substantial spatial heterogeneity in ecosystem carbon flux and its controlling mechanisms.Using eddy covariance data collected from March to August 2019,this study examined the responses of carbon and water fluxes in different ecosystems on the Tibetan Plateau to typical hydrometeorological factors,focusing on Net Ecosystem CO 2 Exchange(NEE)and Evapotranspiration(ET).The results indicate that:1)The Longbao alpine wetland primarily acted as a carbon sink from May to August,while serving as a carbon source from March to April.In the Maqin alpine meadow,it functioned as a carbon sink during June and July but acted as a carbon source in March,April,May,and August.The Tuotuohe alpine desert strppe was predominantly a net carbon sink from March to August.Overall,after the entire growing season(March to August),the Longbao alpine wetlands,Maqin alpine meadow,and Tuotuohe alpine desert steppe all showed net carbon sink properties,with net CO2 uptakes of 236.12 g/m2,291.45 g/m2,and 290.28 g/m2,respectively.2)The importance of meteorological factors to NEE varies with scale and ecosystem type,with global radiation(Rg)being the most critical factor influencing NEE variation.Volumetric soil water content(Soil_VWC)and soil temperature(Soil_T)had a positive effect on NEE at Maqin alpine meadow and Tuotuohe alpine desert steppe,while higher values of these variables showed a negative contribution.Furthermore,the sensitivity of NEE to Soil_T at Longbao alpine wetland and Tuotuohe alpine desert steppe was greater than its sensitivity to air temperature(Tair).3)The effect of Gross Primary Productivity(GPP)on NEE in alpine desert steppes is significantly greater than in alpine meadows.Both Ecosystem Respiration(Reco)and NEE were substantially limited by GPP,with 84％of GPP in alpine wetlands contributing to Reco and 16％to NEE;92％of GPP in alpine meadows contributing to Reco and 8％to NEE;and 40％of GPP in high-altitude desert grasslands contributing to Reco and 60％to NEE.4)The strong correlation between NEE and evapotranspiration suggests that water availability is the primary factor controlling changes in the carbon and water budgets of alpine ecosystems.

Quantitative exploration of shifts in regional vegetation net primary productivity (NPP) and their driving factors holds immense importance in unraveling the mechanisms steering vegetation alterations, comprehending the impact of climate variations and human interventions on NPP, and guiding ecological management. Despite this significance, there is a scarcity of research reports on Qinghai Province. The aim is to dissect the influences of climate change and human activities on Qinghai’s vegetation NPP and to estimate the growth potential of livestock carrying capacity. This study addresses the gap by juxtaposing the characteristics of climate-induced potential NPP changes, computed using the Zhou Guangsheng model, with actual NPP changes, calculated via the CASA model. Our findings underscore climate factors as the predominant drivers of Qinghai’s vegetation NPP, accounting for 64.6% of the total area. Regions influenced by human activities contribute 34.3%, while unchanged areas constitute 2%. Climate emerges as the primary catalyst for increased vegetation NPP in Qinghai, encompassing 87% of the total area, with 73% attributed to climate factors across all counties. Conversely, human activities predominantly lead to decreased NPP, affecting 11% of the total area. Notably, 99% of the reduced NPP is attributable to human activities, concentrated in Golmud, Mangya, and Dulan counties in the northwest. Examining the growth potential of livestock carrying capacity from 1982 to 2018 reveals a consistent upward trajectory in Qinghai Province. The average annual growth potential per unit area escalates from 0.38 SHU/ha in 1982 to 0.56 SHU/ha in 2018. By 2018, regions exhibiting positive growth potential encompass 95% of the province, with areas exceeding 1 SHU/ha constituting 9%, primarily situated in the eastern part of Qinghai Province.

Understanding the effects of climate change on plant phenological dynamics and growth patterns is critical for predicting climatic changes on the Qinghai-Tibetan Plateau (QTP). We used data over 21 years (1997 to 2017) for four dominant species on the QTP, namely Astragalus laxmannii (legume), Artemisia scoparia (forb), Kobresia humilis (sedge), Stipa purpurea (grass), and examined the relationships among climatic changes, plant phenology, growth pattern, and biomass. Most phenological periods in Stipa purpurea and Artemisia scoparia were delayed, whereas in Astragalus laxmannii, they were advanced. Soil temperature and maximum air temperature were the most important drivers. There were trade-offs between reproductive phenology and vegetative phenology, as well as between the length of the rapid growth period and the intrinsic growth rate. The impacts of the phenological or growth processes were species-specific. Our findings provide evidence of long-term changes and are of great significance for improving the accuracy of models.

Climate warming and human disturbance are supposed to have significantly impacted the alpine grasslands. However, it is still unclear how human activity affects the community composition and niche characteristics in response to warming. We conducted a two-factorial experiment in an alpine meadow, and set up four treatments: warming, mowing, warming with mowing, and control. Based on the investigation of community composition and niche characteristics, we evaluated the impacts of soil carbon, nitrogen, and phosphorus on species niche overlap. The results showed that mowing significantly increased species richness of Grass, Sedge, Forbs and the importance value of Sedge compared to warming (P < 0.05). The niche breadth of species (>50 %) was reduced by warming, but increased under mowing. The niche overlap mainly occurred between Grass and Forbs in warming, while it was evenly distributed among species after mowing, which alleviated the negative effects of warming on interspecific competitiveness. Warming increased the number of species pairs with a niche overlap value >0.9 by 24.15 %, while warming with mowing decreased it by 2.7 %. The number of species pairs with niche overlap was significantly correlated with soil total nitrogen and soil available nitrogen (P < 0.05). In particular, the species pairs with highly competitive showed a greater dependency on soil nitrogen. Our work highlights that moderate utilization and soil nitrogen are two crucial factors influencing the response of community structure in alpine meadows to future climate change. The study provides an important reference for predicting and addressing the impact of global climate change on adaptive management and grassland protection.

Based on the 20%,40%,60%and 80%quantiles of the daily cumulative energy of downward short-wave radiation,the four-component radiation observation data observed by the Haibei Animal Husbandry Experi-mental Station of China Meteorological Administration from September 2014 to December 2020 were divided in-to five groups.The influence of difference in downward shortwave radiation on the radiation balance of meadow grassland has been analyzed,which provided a basis for clarifying the changes and causes of radiation balance under different sunlight conditions.The results show that the downward shortwave radiation energy in the whole year is 8192.9 MJ·m-2·a-1,which can be theoretically received under the condition of abundant sunlight.Under normal sunlight,it is only 80%of that in the condition of abundant sunlight,while this proportion is only 40%under the condition of less sunlight.The downward shortwave radiation received by the surface under different sunlight conditions showes a very significant logarithmic increase trend in the same month,and the difference be-tween the groups exceeds the difference between different season.There are also large differences between the groups of upward shortwave radiation and atmospheric longwave radiation.However,the upward shortwave radi-ation increases with the increase of solar radiation,due to the change of air humidity and cloudiness,while the atmospheric longwave radiation decreases with the increase of solar radiation.The variation of surface longwave radiation under different sunlight conditions is small,and does not exceed 3%.Although the difference in surface longwave radiation is not significant between the three sunlight conditions,due to the small amount of down-ward shortwave radiation received under the condition of less sunlight,the surface longwave radiation is 3.4 times more than the downward shortwave radiation,while it is only 1.4 and 1.7 times under the other two light-ing conditions.As the increase of sunlight,the net shortwave radiation received by the surface increases,and the net longwave radiation also increases.Therefore,the energy absorbed by the radiation under different sunlight conditions accounts for 36%to 39%of the downward shortwave radiation energy received in each case.In addi-tion,the difference of sunlight conditions also affect the linear regression model between downward shortwave radiation and net total radiation.The coefficient of determination and slope of the relationship model are the smallest under the condition of less sunlight.The coefficient of determination of the relationship model are above 0.85 for both normal and abundant sunlight.However,the slope is 1 when the sunlight is normal,while the slope is 0.87 when the sunlight is abundant.

The sensitivity of grassland above- (AGB, gC m-2) and below-ground biomass (BGB, gC m-2) to climate has been shown to be significant on the Tibetan Plateau, however, the spatial patterns and sensitivity of biomass with altitudinal change needs to be quantitated. In this study, large data sets of AGB and BGB during the peak growth season, and the corresponding geographical and climate conditions in the grasslands of the Tibetan Plateau between 2001 and 2020 were analyzed, and modelled using a Cubist regression trees algorithm. The mean values for AGB and BGB were 61.3 and 1304.3 gC m-2, respectively, for the whole region over the two decades. There was a significant change in spatial AGB of 64.8 % on the Plateau (P < 0.05, with areas where AGB increased being twice as large as areas where AGB decreased), while BGB did not change significantly in majority the of the region (≥ 90.1 %, P > 0.05). In general, the areas where AGB showed positive partial correlations with precipitation were larger than the areas where AGB had positive correlations with temperature (P < 0.05). However, these trends varied depending on the climatic conditions: in the wetter regions, temperature had a greater effect on the size of the areas with positive AGB responses than precipitation (P < 0.05), while precipitation had a greater effect on the size of areas with positive BGB changes than temperature (P < 0.05). In the drier areas, however, precipitation affected the AGB response significantly compared to temperature (P < 0.05), while temperature influenced the BGB response greater than precipitation (P < 0.05). The response and sensitivity of grassland biomass to temperature and precipitation varied according to the altitude of the Plateau: the response and sensitivity were stronger and more sensitive at medium altitudes, and weak at the higher or lower altitudes. Likely, this phenomenon was resulted from the natural selection of plants to maintain the efficient use of resources during un-favourable and stressed conditions for maximum plant development and growth. These findings will help assess the ecological consequences of global climate change for the grasslands of the Tibetan Plateau, particularly in those regions with highly variable altitudes.

Ground surface heat flux (G0) is a key component of surface energy flux and serves as a reliable parameter for assessing shallow geothermal energy. Using the observations from four sites and a novel method, we investigated the daily, monthly, and diurnal characteristics of G0 across various types of land cover in the Three River Source Region. The contribution of soil heat flux at 5 cm or 7.5 cm (Gsoil) to G0 was found to be only between 1/2 and 2/ 3, with the remaining portion being attributed to changes in heat storage of soil and liquid water (Delta ssoil), heat storage of soil ice (Delta sice) and latent heat of ice phase change (Delta sLH). The characteristics of G0 exhibited significant variations in response to different land-covered vegetation during daily, monthly, and diurnal cycles, as well as two freeze-thaw stages. The alpine marsh-covered soil had the largest annual amplitude in G0 on both daily and monthly averages but showed the smallest diurnal amplitude in G0. In the frozen stage (FS), G0 played a significant role as a supplement to net radiation (Rn) in TRSR, particularly in the alpine marsh region where it accounted for approximately -22 % to -80 % of Rn from November to February.

随着气候变化对牧草生长的影响,牧草栽培已成为当前较为关注的话题之一,阐释气候、土壤和海拔对乡土牧草生长的影响,可为今后牧草栽培提供一定的科学依据.垂穗披碱草(Elymus nutans)、冷地早熟禾(Poa crymophila)、冰草(Agropyron cristatum)和驼绒藜(Ceratoides latens)是较适宜青海省种植的优良牧草,本研究利用MaxEnt模型对当前气候条件下4种乡土牧草在青海省范围内的潜在分布及起主导作用的环境变量进行分析.结果表明:利用MaxEnt模型对当前气候条件下4种乡土牧草的适生区预测均具有极高的准确度;当前气候条件下垂穗披碱草、冷地早熟禾和冰草的地理分布格局具有一定的相似性,均集中分布在青海省东部、东南部和南部地区,而驼绒藜主要分布在柴达木盆地东北部、南部边缘及青海湖流域南部地区.影响青海省4种乡土牧草适生范围的环境变量具有一定的相似性,也存在差异,对垂穗披碱草、冷地早熟禾和冰草影响较大的是地面向下短波辐射、海拔和近地面气温,而对驼绒藜影响较大的环境变量分别是降水量、海拔和近地面气温.本研究对了解青海省多种乡土牧草的地理分布格局及生境条件具有重要意义,以期为开展牧草栽培提供参考.

景观生态风险评价作为国土资源空间优化配置与生态资源管理决策设计的综合手段,为区域生态安全定量化评估提供了新思路.本研究分析了1980-2020年西宁市土地利用时空演变特征以及景观生态风险时空分异特征.结果表明:(1)草地占西宁市总面积的51％以上,以中/低覆盖度草地为主,1980-2020年耕地面积减少97.42 km2,建设用地增加103.89 km2.(2)2000年以前土地利用结构相对稳定,2000年以来土地利用变化程度活跃.40年间耕地转出面积最大,为109.69 km2,建设用地转入面积最大,为104.44 km2.(3)5个时期西宁市景观生态风险指数均在0.288左右,景观生态安全状况总体稳定,景观生态风险等级以低生态风险等级和较低生态风险等级为主,占西宁市面积的70％以上.(4)5个时期西宁市景观生态风险全局Moran's Ⅰ值分别是0.712、0.720、0.724、0.741、0.764,呈现以低-低聚集和高-高聚集为主的空间分布格局,空间 自相关程度逐渐增加,空间趋同趋势不断增强.土地资源优化配置路径包括:科学估算土地利用结构中生产、生活、生态用地的规模阈值,避免生产、生活用地过度开发利用挤占生态空间,修复和改善草地、耕地资源质量,强化和提升林地资源生态功能和价值溢出效益,合理规划建设用地开发规模和强度,培育水域、建设用地景观生态廊道,适度增加建城区生态用地规模,可以保障西宁市生态安全格局健康稳定.

基于青藏高原61个区域级气象站的气温降水地面观测数据,对CMFD(中国区域高分辨率地区驱动数据集)、CRA(全球大气和陆面再分析资料)以及MERRA-2(大气再分析资料)数据集的日、月、季节以及年气温、降水数据进行精度对比分析,评估3套数据的准确性以及在青藏高原的适用性,结果表明:(1)3 套年平均气温资料 70％的RMSE＜4℃,其中CMFD拟合精度最高,2/3的站点RMSE＜2℃;CMFD和CRA对年降水的拟合精度较高,MERRA-2 低估了高原中部的年降水量.(2)CMFD对季节平均气温整体拟合结果最好,尤其是气温较高的夏季和秋季;CRA在降水较为集中的夏季和秋季拟合结果最接近观测值,而在降水较少的春季和冬季CMFD拟合结果最好.(3)CMFD对月平均气温拟合结果整体上最接近观测值;月降水拟合结果与季节降水结果相似,CMFD对降水偏少月份拟合结果较好,CRA在降水偏多月份最接近观测值.(4)对61个区域站进行日尺度平均气温和降水数据精度评估,发现CMFD和CRA拟合效果最好,CMFD拟合趋势一致性好.

青海省内已建成10个高原地气交换通量观测站,其中三江源区域内7个、柴达木盆地内1个、青海湖流域内1个、祁连山国家公园内1个,观测场下垫面有温性草原、高寒草原、高寒草甸、高寒湿地、荒漠化草原和沙漠.为了保障站网运行和数据有效管理,青海省气象局开发了野外试验数据综汇管理平台.

Plant phenology is the bridge between climate change and ecosystem functions. Time coordination of interspecific and intraspecific phenology changes overlap or separate can be regarded as an important characteristic of species coexistence. To confirm the hypothesis that plant phenological niche promotes species coexistence, three key alpine plants, Kobresia humilis (sedge), Stipa purpurea (grass), and Astragalus laxmannii (forb) were investigated in this study in the Qinghai-Tibet Plateau. Phenological niches represented as the duration of green up-flowering, flowering-fruiting, and fruiting-withering by 2-day intervals for phenological dynamics of three key alpine plants from 1997 to 2016. We found the role of precipitation on regulating the phenological niches of alpine plants was highlighted in the context of climate warming. The response of the intraspecific phenological niche of the three species to temperature and precipitation is different, and the phenological niche of Kobresia humilis and Stipa purpurea was separate, especially in the green up-flowering. But the overlapping degree of interspecific phenological niche of the three species has continued to increase in the past 20 years, reducing possibility of species coexistence. Our findings have profound implications for understanding the adaptation strategies of key alpine plants to climate change in the dimension of phenological niche.

Reliable precipitation data are highly necessary for geoscience research in the Third Pole (TP) region but still lacking, due to the complex terrain and high spatial variability of precipitation here. Accordingly, this study produces a long-term (1979–2020) high-resolution (1/30∘, daily) precipitation dataset (TPHiPr) for the TP by merging the atmospheric simulation-based ERA5_CNN with gauge observations from more than 9000 rain gauges, using the climatologically aided interpolation and random forest methods. Validation shows that TPHiPr is generally unbiased and has a root mean square error of 5.0 mm d−1, a correlation of 0.76 and a critical success index of 0.61 with respect to 197 independent rain gauges in the TP, demonstrating that this dataset is remarkably better than the widely used datasets, including the latest generation of reanalysis (ERA5-Land), the state-of-the-art satellite-based dataset (IMERG) and the multi-source merging datasets (MSWEP v2 and AERA5-Asia). Moreover, TPHiPr can better detect precipitation extremes compared with these widely used datasets. Overall, this study provides a new precipitation dataset with high accuracy for the TP, which may have broad applications in meteorological, hydrological and ecological studies. The produced dataset can be accessed via https://doi.org/10.11888/Atmos.tpdc.272763 (Yang and Jiang, 2022).

生态空间分区识别是支撑自然保护地生态资产管理的前提性和基础性工作.以祁连山国家公园青海片区(以下简称为"园区")为例,集成遥感技术、地理信息模型方法、景观生态学方法、GIS格网法,分析了园区1998-2018年土地利用、生态系统服务价值、景观生态风险的时空演变特征,选用Z-score标准化构建了四类生态分区.结果表明:(1)草地占园区面积的55.00％以上,30年间(1998-2018年)园区土地利用之间转移总面积为102.49 km2.(2)3个时期(1998年、2008年、2018年)园区生态系统服务价值(ESV)约为274亿元/a,单位面积ESV为172.94万元/km2.不同ESV等级呈现"大分散、小集聚"的镶嵌交错分布格局,高寒河源湿地区和寒温带针叶林区为ESV的高值区.(3)3个时期园区景观生态风险指数(ERI)分别为0.2287、0.2286和0.2310,生态安全状态整体较好,景观生态风险以低生态风险等级和较低生态风险等级占主导地位,占园区面积的90.00％左右.人工牧草地、旱地、建设用地的景观生态风险等级较高.(4)结合生态系统服务价值和景观生态风险两个维度将园区划分为生态保障型生境修复区(Ⅰ)、生态脆弱型特别保护区(Ⅱ)、生态改良型发展利用区(Ⅲ)和生态预防型保育涵养区(Ⅳ)四类生态分区,并提出差异化管控方案.

青海省地处青藏高原高寒地区核心地带,区域生态环境脆弱又敏感.在全球气候变化背景下,青藏高原高寒生态系统的格局、过程与功能会发生较大的改变,对该区生态安全和稳定带来前所未有的挑战.生态气象服务作为青海省生态文明建设的重要决策支撑,是应对气候变化和保障高原生态安全的内在需求,也是实现"双碳"目标、探索绿色发展模式的具体行动.

以青藏高原玛沁地区高寒草甸和沱沱河地区高寒荒漠草原为观测研究站,利用涡动协方差技术获取高寒生态系统水平上的CO2通量以及水和能量通量,通过REddyProc、随机森林(Random Forest,RF)进行了数据后处理,探究了不同下垫面典型环境因子对净生态系统CO2交换量(Net Ecosystem Exchange,NEE)的影响机制.结果表明:1)玛沁高寒草甸在6-7月以吸收为主,表现为碳汇,吸收峰值出现在11:00-12:00(北京时,下同)之间,而在3、4、5、8月以排放为主,表现为碳源,排放峰值出现在21:00-23:00之间;沱沱河高寒荒漠在3-8月以吸收为主,表现为净碳汇,吸收峰值出现在13:00-14:00之间;整个生长季前后(3-8月),玛沁和沱沱河的累计NEE分别为79.50 g C/m2和79.24 g C/m2,都表现为碳汇.2)不同尺度不同下垫面,气象因子对NEE的重要程度不同,小时尺度上,高寒草甸辐射对NEE的重要性最大,高寒荒漠草原蒸散发对NEE的重要性最大;日尺度上,高寒草甸土壤含水率对NEE的重要性最大,高寒荒漠草原风速对NEE的重要性最大;3)生态系统呼吸(Ecosystem Respiration,Reco)和NEE都受到总初级生产力(Gross Primary Productivity,GPP)的显著限制,高寒荒漠草原GPP对NEE的影响远大于高寒草甸GPP对NEE的影响;4)NEE与蒸散发呈显著相关性,表明水分条件是控制高寒草甸和高寒荒漠草原碳和水收支变化的最重要因素.