Understanding the interactions among ecosystem services (ESs) and their spatiotemporal dynamics is pivotal for sustainable ecosystem management, particularly in arid regions where water scarcity imposes significant constraints. This study focuses on the Ili River Valley, a representative arid region, to investigate the evolution of ESs, their trade-offs and synergies, and the underlying driving mechanisms from a water-resource-constrained perspective. We assessed five key ESs—soil retention (SR), habitat quality (HQ), water purification (WP), carbon sequestration (CS), and water yield (WY)—utilizing multi-source remote sensing and statistical data spanning 2000 to 2020. Employing the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model, Spearman correlation analysis, Geographically Weighted Regression (GWR), and the Geodetector method, we conducted a comprehensive analysis at both sub-watershed and 500 m grid scales. Our findings reveal that, except for SR and WP, the remaining three ESs exhibited an overall increasing trend over the two-decade period. Trade-off relationships predominantly characterize the ESs in the Ili River Valley; however, these interactions vary temporally and across spatial scales. Natural factors, including precipitation, temperature, and soil moisture, primarily drive WY, CS, and SR, whereas anthropogenic factors significantly influence HQ and WP. Moreover, the impact of these driving factors exhibits notable differences across spatial scales. The study underscores the necessity for ES management strategies tailored to specific regional characteristics, accounting for scale-dependent variations and the dual influences of natural and human factors. Such strategies are essential for formulating region-specific conservation and restoration policies, providing a scientific foundation for sustainable development in ecologically vulnerable arid regions.

The growing tension between economic development and ecological preservation in the Ili River Valley underscores the need for advanced analytical methods to effectively balance these interests. In this study, we utilized the InVEST model to quantify ecosystem services, combined with an analysis of ecological sensitivity, to comprehensively assess the ecological health of the region. By applying circuit theory, the research identified key ecological components such as sources, corridors, and critical nodes, alongside barriers; thus, mapping an ecological security pattern tailored specifically for the wetland oasis of the Ili River Valley. The analysis identified 15 ecological source sites covering 43,221.17 km2, 31 ecological corridors totaling 782 km in length, and 32 vital ecological nodes each exceeding 1 km2. Notably, 81.8% of these ecological source areas exhibited high ecological resilience, thus emphasizing their crucial role in maintaining the region’s ecological balance. The findings provide essential guidance for the ecological stewardship and management of the Ili River Valley and underscore the importance of incorporating ecological considerations within economic planning frameworks in arid regions.

Changes in precipitation variability not only have a significant impact on water cycle processes, but also pose an additional challenge to society's climate resilience. Extreme precipitation is more severe, more abrupt, and more sensitive to temperature changes than mean-state precipitation. However, our understanding of the features of extreme precipitation variability over a broad range of temporal scales, as well as the differences between wet and dry seasons, is limited. In this study, we perform filtering on a daily (2-5 days) to an interannual (2-8 years) scale, using daily precipitation data from detrended APHRODITE and bias-corrected CMIP6 based on zero-phase Butterworth filters. We then analyze the changes in climatological extreme precipitation variability at different time scales, looking at the features along geographical gradients and in wet and dry seasons. At various warming levels, extreme precipitation variability is projected. The findings reveal that the longer the time scale, the higher the overall variability of both extreme and mean-state precipitation, with extreme precipitation showing greater variability. From daily to interannual scales, the variability of R95p increases from 142.79 mm to 875.05 mm, representing a 6.13-fold increase in volatility, but the variability in mean precipitation increases just 1.43-fold, from 2.27 mm to 3.24 mm. The variability in the eastern Tienshan Mountains (80 degrees E - 95 degrees E) is greater than that in the western Tienshan Mountains (66 degrees E - 80 degrees E). Furthermore, along longitudinal and latitudinal gradients, extreme precipitation variability exhibits considerable time-scale differences, with the more extreme the event, the greater the variability. R10mm variability increases from 15.28 d to 76.74 d on a daily to interannual scale. The variability increase (61.46 d) is roughly twice that for R5mm. Seasonally, the wet season is more variable than the dry. The total variability of R10mm was 4.57 days in the wet season and 1.78 days in the dry season. Compared with the reference period (1976-2005), there is an overall increase in extreme precipitation variability at different warming levels, along with an increasing sensitivity to temperature. With the exception of consecutive dry days, the degree of response of filtered extreme precipitation variability to temperature (absolute value of response rate) shows obvious increases with time scale and accounts for a greater proportion of the total variability response rate.

Maintaining the ecological security of arid Central Asia (CA) is essential for the sustainable development of arid CA. Based on the moderate-resolution imaging spectroradiometer (MODIS) data stored on the Google Earth Engine (GEE), this paper investigated the spatiotemporal changes and factors related to ecological environment quality (EEQ) in CA from 2000 to 2020 using the remote sensing ecological index (RSEI). The RSEI values in CA during 2000, 2005, 2010, 2015, and 2020 were 0.379, 0.376, 0.349, 0.360, and 0.327, respectively; the unchanged/improved/deteriorated areas during 2000–2005, 2005–2010, 2010–2015, and 2015–2020 were about 83.21/7.66%/9.13%, 77.28/6.68%/16.04%, 79.03/11.99%/8.98%, and 81.29/2.16%/16.55%, respectively, which indicated that the EEQ of CA was poor and presented a trend of gradual deterioration. Consistent with the RSEI trend, Moran’s I index values in 2000, 2005, 2010, 2015, and 2020 were 0.905, 0.893, 0.901, 0.898, and 0.884, respectively, revealing that the spatial distribution of the EEQ was clustered rather than random. The high–high (H-H) areas were mainly located in mountainous areas, and the low–low (L-L) areas were mainly distributed in deserts. Significant regions were mainly located in H-H and L-L, and most reached the significance level of 0.01, indicating that EEQ exhibited strong correlation. The EEQ in CA is affected by both natural and human factors. Among the natural factors, greenness and wetness promoted the EEQ, while heat and dryness reduced the EEQ, and heat had greater effects than the other three indexes. Human factors such as population growth, overgrazing, and hydropower development are important factors affecting the EEQ. This study provides important data for environmental protection and regional planning in arid and semi-arid regions.

The current study evaluates consistency among three Normalized Difference Vegetation Index (NDVI) datasets, namely GIMMS, MODIS and SPOT, to characterize alpine vegetation dynamics (greening and browning) across High Mountain Asia (HMA) in 2001-2015. The utility of these datasets is explored to evaluate the vegetation's variability at different spatial-temporal scales and, elevation, and to compare their spatial trends and distribution patterns. In addition to the Pearson correlation coefficients performed to quantitatively analyze the consistency and inconsistency of each dataset, an NDVI quality control (QC) layer and Landsat NDVI are also used to evaluate the findings. The results indicate that the GIMMS has the highest NDVI mean, while SPOT has the lowest. However, GIMMS also showed a browning trend for both Tianshan (TS) and the Qinghai Tibet Plateau (TP) at a rate of -0.3 x 10(-3) per year, whereas MODIS and SPOT exhibit a greening trend (TSMODIS = 0.5 x 10(-3) per year, TSSPOT = 0.6 x 10(-3) per year, TPMODIS = 0.9 x 10(-3) per year, TPSPOT = 1.6 x 10(-3) per year). Furthermore, MODIS-SPOT shows the highest correlation (R-GREEN = 0.73; R-BROWN = 0.47), followed by MODIS-GIMMS, and GIMMS-SPOT. The overall, NDVI trend consistency appears to be higher in TS. Finally, the consistent greening pixels mainly distributed in central TP stretching to the northeastern part, and in western stretching to eastern TS, account for 32.14%, while 8.32% of consistent browning pixels are concentrated in southwestern TP and central TS. The inconsistent pixels account for 59.54%, with 39.21% of inconsistent greening pixels being widely distributed across HMA, and 20.58% of inconsistent browning pixels being relatively pronounced in central TS and southern TP. This study provides baseline inferences for the selection and reconstruction of data in follow-up studies on vegetation dynamics.

This paper investigates the performance of bias-corrected Flexible Global Ocean-Atmosphere-Land System-g3 (FGOALS-g3) model products and then detects changes in extreme precipitation (EP) in the Tienshan Mountains, Central Asia (TMCA), as reflected by 25 EP indices. The reliability of the FGOALS-g3 model outputs is assessed systematically based on multiple statistical indicators against multi-source precipitation datasets and the bias -corrected FGOALS-g3 model products are applied to project EP variations under different global warming levels. Using the geographical detector method, a novel statistical method for detecting spatial heterogeneity and elucidating the underlying causes, the explanatory power of 20 atmospheric circulation factors related to EP is examined. The findings indicate that while the FGOALS-g3 products can detect the spatial pattern of multi-year average precipitation in the TMCA, there is an obvious overestimation in magnitude, especially in the West and Middle Tienshan Mountains. These biases are significantly reduced, however, after downscaling and bias correction. Compared with the Asian Precipitation Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) data, the grid-by-grid error in bias-corrected FGOALS-g3 simulated mean precipitation is between-7.64% and 10.95%. In terms of EP, the corrected FGOALS-g3 products not only reproduce the spatial distribution, but also reasonably simulate their magnitudes, with some overestimation in light EP and underestimation in heavy EP. Overall, across the historical period, EP has increased. The intensity and frequency of EP are projected to generally increase under different scenarios. At 1.5 degrees C warming levels, annual total pre-cipitation in wet days (PRCP) increases by 5.74% (7.74%) under the SSP245 (SSP585). Additionally, as an EP becomes rarer, its rate of change rises. The main driving factors in EP are detected to be 30 hPa zonal wind (30ZW), relative number of sunspots (SF), south Asian summer monsoon (SAM), sea surface temperature anomaly in the region of 5 degrees S-5 degrees N, 170 degrees-120 degrees W (NINO 3.4), and mean surface temperature (T).

The Tienshan Mountains is the main water source and ecological barrier in the central portion of the Silk Road Economic Belt, a new economic development zone with the Asia-Pacific Economic Circle to the east and the European Economic Circle to the west. Production-living-ecological activities in the arid Central Asia region are heavily dependent on water resources mainly recharged from melt and alpine precipitation. Hence, reliable projections of changes in extreme precipitation under global warming are particularly important for the utilization and management of water resources. Based on the downscaled and bias-corrected state-of-art global climate models from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we investigate changes in extreme precipitation over the Tienshan Mountains, Central Asia (TMCA) under different levels of global warming (1.5 degrees C, 2.0 degrees C, 3.0 degrees C, and 4.0 degrees C). We specifically assess the robustness of changes and the benefits of limiting warming to 2.0 degrees C as opposed to 3.0 degrees C. Compared with the reference period (1976-2005), a robust change in extreme precipitation across the TMCA is expected for all warming levels. And the fraction of land faced a robust change also increases with warming levels. Furthermore, there would be a substantial rise in extreme impacts in the TMCA when shifting from increases of 2.0 degrees C to 3.0 degrees C. In a scenario involving a 1.0 degrees C rise (i.e., from 2.0 degrees C to 3.0 degrees C), nearly 85.70 % and 60.19 % of the land in the TMCA will be affected by a robust increase in annual total wet-day precipitation (PRCPTOT) and number of light rain days (RSmm), respectively. In the same scenario, areas affected by robust changes in duration indices (consecutive dry days [CDD] and consecutive wet days [CWD]) will likely be less than 11.59 %. Limiting warming to 2.0 degrees C instead of 3.0 degrees C can avoid a marked increased impacts of about 62.84 %similar to 153.77 % of the change in frequency, intensity, and duration of extreme precipitation.

High Mountain Asia (HMA), known as Earth’s “third pole” and “Asia’s water tower,” is the largest glacier and snow reservoir on Earth except for the polar ice sheets. Snow is an important component of the HMA cryosphere, and its variability directly affects the water and energy balances in the region. Identifying long-term changes in snow cover in the HMA region is important for the development of downstream water resources, prevention of water disasters, and survival and social stability of the “Third Pole” region.We had developed a long-term, high-quality, daily High Mountain Asia Snow Cover (HMASCE) product to systematically study the snow cover indicators (SCA and snow cover phenology (SCP)) in different sub-regions and altitudes in HMA over the past 40 years in the context of global climate change. The results show that (1) the accuracy of the HMASCE product was validated using station snow depth data, with OA, PA, and UA values of 81.99%, 84.20%, and 76.39%, respectively. (2) the SCA shows a significant trend of shrinkage (-0.56% a-1), snow cover days (SCD) shortens by 15.5 days, and snow cover start date (SOD) is delayed by about 5.6 daysand snow cover end date (SED) has advanced by 10 d in HMA over the last 40 years. (3) Another important finding is the altitudinal dependence of SCD, where, below 5000 m, higher altitudes experience lead to greater SCD reduction than lower altitudes. The possible mechanisms underlying this phenomenon related to the region's own characteristics, the elevation dependence of warming (EDW), and the increased black carbon.

Reservoirs play a vital role in agricultural irrigation, food security, and ecological protection in arid and semi–arid areas where water resources are scarce. In the Tarim Basin (TB) in northwestern China, a large number of reservoirs have been built or are being built, resulting in significant evaporation losses. However, information about the distribution, area and evaporation rate of the reservoirs in TB is limited. To contribute, we present an inventory of reservoirs and calculate their monthly surface area and evaporation rate during the study period of 1990–2019, using the TerraClimate dataset, Google Earth Engine (GEE) platform, Landtrendr algorithm, Penman method, and Landsat images. The results suggest: (1) The inventory of 167 reservoirs in TB consists of 142 existing reservoirs (built before 1990), 5 new reservoirs (mountain reservoirs, built during 1990–2019), and 20 dried–up reservoirs (plain reservoirs that went extinct during 1990–2019). (2) The reservoir types in TB are mainly plain reservoirs with an altitude of less than 1500 m and an area of less than 10 km2, accounting for about 88% of the total number of reservoirs. (3) The surface area of the reservoirs increased at a significant rate (p < 0.05) of 12.45 km2/y from 401 km2 in 1990 to 766 km2 in 2019. (4) The evaporation rate of the reservoirs increased at a slight trend of 0.004 mm/d/a and varied from 2.57 mm/d in 1990 to 2.39 mm/d in 2019. Lastly, (5) The evaporation losses of reservoirs in TB significantly increased (p < 0.05) from 4.72 × 108 m3 to 4.92 × 108 m3 due to the significant increase in reservoir surface area (p < 0.05) and the slight increase in evaporation rate from 1990 to 2019. This study provides essentials of the reservoir inventory, surface area, and evaporation rate with considerable baseline inferences for TB that may be beneficial for long–term investigations and assist in local water resources decision support and sustainable management in arid regions.

基于博格达山北坡68个表土样品花粉组合特征,对比植物群落样方调查结果,借助聚类分析、主成分分析方法,探讨了表土花粉组合与现代植被分布的关系.研究表明,(1)博格达山北坡表土花粉可划归5个不同植被带,湿度是影响其分布的主要因素,藜科(Chenopodiaceae)、蒿属(Artemisia)、云杉属(Picea)花粉分布受气流影响显著,忽略它们对其他植被带花粉组合的干扰,表土花粉与现代植被分布对应良好.各植被带均有其特有的花粉组合方式,山地荒漠带藜科-蒿属组合占绝对优势,山地草原带演替为蒿属-藜科-禾本科(Poaceae)-蔷薇科(Rosaceae)组合,山地森林带以云杉属-桦木属(Betula)-蒿属-藜科-禾本科为主,高山草甸带以蒿属-云杉属-藜科-莎草科(Cyperaceae)组合为特征,高山垫状植被带表现为蒿属-藜科-蔷薇科-云杉属组合.(2)草本植物花粉含量(62.7％)优势明显,乔、灌木(37.3％)次之.蒿属(23.1％)、藜科(21.5％)、云杉属(18.1％)、莎草科(9.4％)、禾本科(8.6％)、桦木属(5.7％)、蔷薇科(5.3％)等科(属)含量高、变幅大,为最主要的花粉类型,可作为古气候研究的重要依据,藜科、蒿属产量大、易传播,表现出超代表性,云杉属代表性较好,莎草科则受自身结构及保存条件等多重因素影响呈低代表性.(3)蒿属/藜科(A/C)比值不仅能将山地荒漠带、山地草原带区分开,还能指示研究区域湿度变化,古环境重建时可作为区域有效湿度的代用指标.

: In the Tarim Basin, the Taklimakan Desert is the second largest shifting dune globally. Holocene relic sites in the desert hinterland suggested ancient rivers flowing, oasis occupation, and human activities. The Keriya River is one of the rivers that originated from the glacier mountains of south Tarim Basin. The Yuansha Site is the earliest city in the Taklimakan Desert, located in the delta area of the Keriya River and provided an ideal case for illustrating the relationship between the natural environment and human activities. To better understand this area ’ s past environment, we selected the KYN22 section (22 km from north of the Yuansha Site) and 134 grain size samples in the section from each depth for particle size distribution measurement and grain size parameter calculation. We collected four OSL chronology samples from the depth of 230 cm, 490 cm, 590 cm, and 1070 cm, respectively. The measurement results showed the following. (1) The main components of sediment samples are silt and very fine sand. (2) The grain size median diameter, sorting coefficient, skewness, and kurtosis changed at approximately 3.27 - 6.86 Φ , 0.54 - 2.50 Φ , - 0.30 - 1.48 Φ , and 0.71 - 1.71 Φ , respectively. (3) The OSL age measurement results are 6.4±0.4 ka, 9.8±0.6 ka, 10.1±0.5 ka, and 13.8±0.6 ka from the upper part to the bottom of the section, respectively. (4) The very fine sand content variation is consistent with that of fine sand and opposite with silt sand with depth increase, whereas the silty sand variation content is consistent with mild clay samples. (5) The sediment grains in the 0 to 550 cm depth composed mainly of silt, followed by very fine sand. In contrast, the sediment grains in the 550 to 1070 cm depth composed of very fine sand as the main content, and silt is the minor content. A reported OSL age (2.3 ka) at the upper layer of the section suggests that the KYN22 section recorded past environmental and landform changes of the Yuansha Delta in 13.8 - 2.3 ka. The section is mainly for fluvial activities, indicating that the Keriya River dominated this area most of the Holocene. The sediment sequence indicates the domination of aeolian activity at approximately 13.8 ka in earlier Holocene and the fluvial and aeolian activity in 9.8 - 10.1 ka; thus, fluvial activity controls from the middle to the late Holocene. The OSL age (13.8 ka) of the aeolian sand section bottom was followed with the formation of a paleochannel section at approximately 50 km east of the Yuansha and the high terrace formed in the upper reaches of the Keriya River, suggesting flooding events frequently occurred in the Tarim Basin ’ s south margin. The fluvial sediment deposited in 9.8 - 10.1 ka was coeval with the increase of northern hemisphere solar radiation and temperature rising, suggesting increasing melt water in the Kunlun Mountains. This study provides a relatively complete Holocene sediment sequence recorded with reliable chronology data at the Keriya River ’ s lower reaches. For oasis ’ prosperity and inhabitants ’ activities depending on the river, this section recorded the natural environment and the rise and fall of ancient civilization in the Keriya River delta.

植被总初级生产力(Gross primary productivity,GPP)是陆地生态系统碳循环的关键环节,对维持全球碳平衡至关重要.基于Google Earth Engine平台,利用NASA LP DAAC发布的MOD17A2H产品,研究分析了塔里木河生态输水期间陆地生态系统生长季的GPP变化.结果表明:(1)生态输水后,塔里木河生态环境整体得到改善.输水前期,塔里木河生长季GPP平均为3675.51 g C·m-2·季-1,输水中期,生长季GPP增加到4024.09 g C·m-2·季-1,输水后期,该值跃升为4896.61 g C·m-2·季-1.2000—2020年塔里木河生长季GPP表现出明显的增加趋势,增长幅度约为每个生长季增加90.25 g C·m-2.2010年后,上、中、下游日GPP增加幅度亦更明显,分别为每10 a增加2.54 g C·m-2、2.17 g C·m-2和1.74 g C·m-2.(2)塔里木河陆地生态系统生长季(5—10月)的日GPP变化在不同区域存在明显差异.上游区日GPP变化总体上表现出先增加后减小的单峰趋势,下游区则以双峰变化趋势为主.(3)塔里木河生态输水工程有益于生长季GPP的变化,其中对6、8月的GPP变化影响更显著.

天山北坡受西风环流影响,是对气候变化反应最敏感的地区之一.但由于缺乏高分辨率的古气候记录,对该区域2000 cal yr B.P.以来气候演变过程的认识仍存在分歧,尤其是气候演化模式和水热组合方式等问题.为厘清上述问题,以伊犁盆地2400 cal yr B.P.以来的泥炭沉积剖面为研究材料,通过对其进行精确定年和高分辨率孢粉研究,重建了天山北坡2400 cal yr B.P.以来的植被和气候演化历史.结果 表明:1)2400 cal yr B.P.以来天山北坡气候经历了暖干-暖湿-冷湿3个阶段,并可与其他地区研究结果进行良好对比.2429-949 cal yr B.P.期间,喜光、喜暖植物含量丰富,PCA axis l得分指示有效湿度偏低,气候以暖干为主要特征;949-475 cal yr B.P.期间,区域有效湿度明显增加,气温较高,为中世纪暖期;475-301 cal yr B.P.期间的小冰期打断了天山北坡气候向暖湿化发展的趋势,此时段内以冷湿为主.2)天山北坡气候变化过程并不稳定,包含短期的气候突变事件,泥炭沉积物记录了以冷湿为主要特征的小冰期,可能是西风环流加强、西风带南移或北大西洋涛动负异常叠加,温度变低导致水面蒸发、植物蒸腾减少等共同作用的结果.

基于库鲁斯台草原2000～2015年MODIS时间序列数据,反演植被覆盖度及温度植被干旱指数(Temperature Vegetation Dryness Index,TVDI),并借助于趋势检验及相关性分析等方法,对库鲁斯台草原植被覆盖度时空变化及其与TVDI相关性进行了分析,结果表明:1)库鲁斯台草原植被总体属于中覆盖水平,全区中、高、低覆盖草地比例分别为49.57％、25.02％和25.41％;2)近16a库鲁斯台草原植被覆盖度下降趋势明显,全区82.11％草地的覆盖度呈现不同程度下降,其中14.35％达到显著水平,全区62.05％区域变化率介于-0.01～0单位·a-1之间,变化率<-0.01单位·a-1的比例达20.19％;3)近16a库鲁斯台草原90.01％区域干旱程度出现不同程度增加,对植被覆盖度的降低有较大影响,采取有效措施增加水分供给对草地植被恢复与重建具有重要意义.

采用平板稀释法、紫外分光光度法、NaHCO3浸提-钼锑抗显色法等方法对伊犁大小西沟野生樱桃李下发育土壤的速效氮、速效磷、过氧化氢酶、蔗糖酶、微生物个数及土壤粒度进行了研究.结果表明,研究区土壤的速效氮含量约3.87 mg·kg-1,速效磷含量约17.89 mg·kg-1,二者在垂直方向上均呈现随土层深度的增加而逐渐减少的规律.研究区土壤中的微生物数量变化范围在0～5 000个,均值约2 217个.在垂直方向上,微生物个数与土层深度呈现出显著的负相关性.研究区土壤下的过氧化氢酶活性约为8.26 mg·g-1·min-1,蔗糖酶活性约0.22 mg·g-1,二者在垂直方向上均随土层深度的增加呈明显减少趋势.研究区内的土壤粒级以粉粒、砂粒居多,平均粒径约50.01 μm.土粒不均匀,分选性极差,粒度频率曲线很尖锐,呈极正偏.研究区土壤的速效磷与速效氮、蔗糖酶、过氧化氢酶、微生物个数之间呈现显著的正相关关系,相关系数依次为0.983,0.992,0.960,0.917.野生樱桃李下土壤速效氮及粘粒含量的偏少,微生物数量、过氧化氢酶及蔗糖酶的下降可能是导致野生樱桃李退化的一个原因.