Accurate assessment of drought propagation time (PT) and probability (PB) from meteorological to soil moisture drought is crucial for mitigating natural and socio-economic losses. However, inconsistencies among datasets and drought indices (DIs) hinder reliable early warning. Here, we evaluated multiple meteorological and soil moisture datasets against in-situ observations to establish a benchmark. Four DIs-SPI, SPEI, PA, and MI-were employed to estimate PT and PB using maximum correlation coefficient and Copula function. We further quantified uncertainties arising from datasets and DIs and proposed a framework for selecting optimal DIs under varying dataset scenarios. The results show that: (i) Benchmark-based PT ranges from 3.10 months (for SPEI) to 5.37 months (for MI) and PB increases with the regional humidity. (ii) ERA5-Land exhibits the highest spatial consistency, matching benchmark PT in 48.47 % (MI) to 61.62 % (SPEI) of pixels, with no significant monthly bias. In contrast, MERRA-2 yields prolonged PT in over 80 % of pixels and shows substantial overestimations (4-10 months) in humid regions. For PB, more than 80 % of pixels from ERA5-Land, GLDAS-2, and MERRA-2 show significant overestimations. (iii) On average, 67.63 % of pixels display greater PT uncertainty from dataset differences than from DI differences, and 68.77 % show higher PB uncertainty from datasets. Compared to the other indices, SPEI can minimize the assessment uncertainties in drought PT/PB across different dataset scenarios. These findings provide a quantitative basis for selecting DIs and datasets, supporting more reliable drought propagation assessment in China.

Amidst the global transition toward renewable energy, China has emerged as the world leader in solar photovoltaic (PV) capacity and generation. However, the climatic risks and operational stability of this extensively deployed PV infrastructure under future climate change remain insufficiently assessed. Previous studies have primarily focused on the theoretical PV power-generation potential (PsolarPV) across terrestrial areas, overlooking the specific climatic risks of existing operational PV facilities. This study addresses this critical gap through a comprehensive, multi-dimensional risk assessment for China's deployed PV systems. We developed a high-resolution hourly PsolarPV model driven by a multi-model ensemble from the NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP-CMIP6) under three greenhouse gas (GHG) emission scenarios from 2015 to 2060. Focusing on China’s existing deployed PV infrastructure and seven representative regions, we quantified future changes in annual PsolarPV and their driving factors, the frequency of extreme PV power events (energy "surplus" and energy “deficit” days), and intra-annual variability (short-term fluctuations and seasonal variations). Our results reveal that future trends in PsolarPV across China’s PV deployments are shaped by the opposing effects of increasing solar radiation (positive effect) and rising surface temperatures (negative effect). Under the low-emission scenario (SSP1-2.6), enhanced solar radiation dominates, leading to a nationwide increase in annual PsolarPV of 3.4%±0.4% (multi-model mean ± standard error). In contrast, under the high-emission scenario (SSP5-8.5), thermal-induced efficiency losses offset these gains, resulting in a slight increase of 0.6%±0.4% in PsolarPV and a rise in the frequency of poor-power days by 0.1 d per decade. Moreover, climate-induced impacts exhibited pronounced spatial heterogeneity. With increasing GHG emissions, deployed PV systems in northwestern, northern, and eastern China are projected to be the most climate-sensitive, experiencing greater changes in power-generation potential and more frequent extreme power-generation events. Northwest China, where PV deployments are concentrated, is projected to experience a decline of -0.5%±0.2% in PsolarPV and an increase of 1.0 d per decade in extreme poor-power days under the high-emission scenario. Conversely, the deployed PV systems in South and Southwest China exhibited stronger climate resilience. Furthermore, higher GHG-emission scenarios are expected to intensify seasonal and short-term PsolarPV fluctuations, especially in northern regions (e.g., Northeast, North, and Northwest China), posing greater challenges to grid stability and power dispatch management. In conclusion, this study provides the first location-specific, forward-looking climate risk assessment of China's existing PV infrastructure. These findings highlight that stringent GHG mitigation is critical for safeguarding solar energy assets and ensuring the long-term sustainability of PV power generation. They also emphasize the need for spatially differentiated climate adaptation strategies, including optimizing future deployment in climate-resilient regions, strengthening grid capacity with advanced energy storage, and enacting policies that enhance the climate resilience of China’s solar power system.

Influenced by the rapid increase in labor costs and the decline in the comparative benefits of grain planting, the phenomenon of Non-Grain Use of Cultivated Land (NGUCL) in China has become increasingly prominent. Firstly, from the perspective of cultivated land marginalization, this study combines the theory of cultivated land marginalization, the theory of land rent, and the theory of farmers' behavior to jointly analyze the theoretical basis for the occurrence of NGUCL. Secondly, it systematically reviews the research progress regarding NGUCL, and finally presents prospects for future research. The study shows that: (1) At the level of theoretical analysis, the theory of cultivated land marginalization clarifies the core driving force and the realistic background of NGUCL. In the context of marginalization, the theory of land rent can explain the logic of choosing the location of NGUCL, and the theory of farmers' behavior can explain how differences in farmers' characteristics affect the occurrence of NGUCL. (2) The definition of NGUCL has been evolving and deepening, and at the present stage, the "food-crop ratio" is still the main indicator, but there are certain limitations in this way of measurement. (3) Under the constraints of production factors and policy incentives, the degree of NGUCL shows a fluctuating increase and is characterized by significant spatial differentiation. Among them, mountainous areas, food production and marketing zones, production and marketing balance zones, urban and peri-urban areas are among the areas in which NGUCL happens all the time. (4) While cultivated land marginalization is the main driving force of NGUCL, the occurrence of NGUCL is also affected by a combination of factors, such as natural endowment, which affects the appropriateness of cultivation, the characteristics of farmers, which affects the degree of farmers' demand for NGUCL, and national policies, which gradually slow down the process of NGUCL. (5) NGUCL has complex implications for ecosystems, food security and farmers' livelihoods. 6. The use control of cultivated land is the main measure in China to regulate NGUCL, but the sustainability of this measure is open to question. In the face of the rapid expansion of the cultivated land marginalization in China and the new requirements for the construction of a diversified food supply system, it is urgent to reconstruct the traditional cognition and research paradigm of NGUCL. In the future, we need to focus on the synergistic analysis of multi-stage, multi-scale and multi-subjects, and explore the evolution process, occurrence mechanism and governance mode of NGUCL.

Severe seepage presents a significant challenge to the sustainable management of water resources, and a lack of seepage data from the upper, middle, and lower reaches of the Hotan River hinders effective resource management. This study assessed the water infiltration rate in the riverbed using the double-ring method and evaluated the performance of four commonly used infiltration models. Results showed that infiltration rates were highest in the upper section, with permeability decreasing towards the banks. Water consumption, seepage volume, and seepage per unit river length decreased from upstream to downstream. Specifically, seepage volumes were greatest in the upstream section, followed by midstream and downstream. The seepage rate per unit riverbed was highest in the upstream section, followed by the midstream, and lowest in the downstream section. The mean sediment volume fractal dimension was 1.34, positively correlated with sand content, while higher clay and silt content resulted in finer textures and smaller fractal dimensions. These findings fill critical gaps in understanding water infiltration patterns and sediment characteristics in the Hotan River basin, providing essential data for water resource management and ecological protection. Among the models tested, the Kostiakov equation outperformed the Philip, Green-Ampt and Horton models in terms of accuracy and applicability.

Aeolian landforms are scarce in subtropical regions due to limited sediment availability, high vegetation coverage, and low wind energy. The Houtian Sandy Land (HSL) in southern China represents the largest such system in the subtropical zone, yet its chronostratigraphy and driving mechanisms remain poorly understood. Through integrated field investigations and laboratory analyses-including morphological measurements, sediment sampling, grain-size analysis, total organic carbon (TOC) determination, and optically stimulated luminescence (OSL) dating-this study reconstructs the multi-temporal evolution of the HSL. On seasonal timescales, climate variability drove nebkha formation around 0.3-0.4 ka by regulating sediment supply, transport, and stabilization. Winter declines in the water level of the Ganjiang River exposed fluvial sediments, which were then transported landward by the topographically enhanced East Asian winter monsoon. In summer, favorable hydrothermal conditions promoted vegetation growth, which trapped aeolian sand and stabilized the nebkhas. Over ten-thousand-year timescales during the Late Pleistocene, the interplay between the East Asian summer and winter monsoons resulted in alternating deposition of dune sands and sandy paleosols. Periods of increased aridity and wind intensity promoted dune formation, whereas intervals of greater vegetation cover and landscape stability favored paleosol development. This study underscores the roles of sediment availability, wind energy, and vegetation cover in shaping subtropical aeolian landscapes across seasonal to orbital timescales, offering new perspectives on the complex drivers of aeolian activity in humid regions.

The interactions between vegetation and morphology on coastal dunes are essential for understanding and managing biogeomorphological processes. While these interactions have been studied at dune field or transect scales over weekly, annual, and decadal timescales, the coupling of individual dunes across several types at seasonal scales remains poorly understood. We selected nine coastal dunes of three types along Tannan Bay on Pingtan Island, China. Seasonal investigations combining unmanned aerial vehicle-based LiDAR monitoring and vegetation surveys were conducted to evaluate vegetation and dune morphology dynamics and analyze their interactions. The results revealed that (1) sediment accumulation increased from the beach to the windward slope but decreased near the dune crest and leeward slope. This accumulation was significant in winter and was controlled by spatiotemporal vegetation dynamics, typhoons, and topographic variations. (2) Coastal dune morphology influenced vegetation distribution, with vegetation on incipient foredunes and nebkhas concentrated on windward slopes and in interdunal areas. Blowouts are primarily found near the inlet and depositional zones. (3) Vegetation and dune elevation were significantly correlated along the across-shore gradient. Results indicate that a 1 % increase in coverage leads to a rise in dune elevation of 0.029-0.067 m, most pronounced in spring and weakest in summer. Additionally, vegetation cover was significantly associated with erosion-deposition in most dunes. Our findings demonstrate the impact of vegetation on dune morphological dynamics and their responses. These results enhance our understanding of eco-geomorphic feedback in coastal dune evolution, facilitating more effective coastal management and restoration.

Comprehensive vegetation surveys are crucial for species selection and layout during the restoration of degraded island ecosystems. However, due to the poor accessibility of uninhabited islands, traditional quadrat surveys are time-consuming and labor-intensive, and it is challenging to fully identify the specific species and their spatial distributions. With miniaturized sensors and strong accessibility, high spatial and temporal resolution, Unmanned Aerial Vehicles (UAVs) have been extensively implemented for vegetation surveys. By collecting UAVs multispectral images and conducting field quadrat surveys on Anyu Island, we employ four machine learning models, namely Gradient Boosting Decision Tree (GBDT), Support Vector Machine (SVM), Random Forest (RF) and Multiple Classifier Systems (MCS). We aim to identify the dominant species and analyze their spatial distributions according to spectral characteristics, vegetation index, topographic factors, texture features, and canopy heights. The results indicate that SVM model achieves the highest (88.55%) overall accuracy (OA) (kappa coefficient = 0.87), while MCS model does not significantly improve it as expected. Acacia confusa has the highest OA among 7 dominant species, reaching 97.67%. Besides the spectral characteristics, the inclusion of topographic factors and texture features in the SVM model can significantly improve the OA of dominant species. By contrast, the vegetation index, particularly the canopy height even reduces it. The dominant species exhibit significant zonal distributions with distance from the coastline on the Anyu Island (p < 0.001). Our study provides an effective and universal path to identify and map the dominant species and is helpful to manage and restore the degraded vegetation on uninhabited islands.

The intensity and frequency of drought are increasing in the tropical zone of China under global warming, and accurate assessment of drought severity and duration is critical for sustainable ecosystem management. Previous studies usually rely on one or more drought indices calculated from meteorological station or reanalysis data. However, the assessment results based on these drought indices are not consistent, which can be due to the differences in data sources and index parameters. In this study, we aim to identify the optimal dataset and drought index, and accurately evaluate the drought severity and drought duration in the tropical zone of China. We assessed the accuracy of five drought indices, namely Precipitation Anomaly in Percentage (PA), Relative Moisture Index (MI), Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Meteorological Drought Composite Index (MCI), calculated from meteorological station data and the China Meteorological Forcing Dataset (CMFD) with respect to drought records compiled by local government. Results indicate that the drought index calculated based on meteorological station data can better match the government-compiled drought records than CMFD. MI is the optimal index for drought severity and duration assessment in study area, especially for winter-spring drought and severe drought, followed by PA. The normalized bell-shaped line of fitted precipitation in winter and spring is biased towards the less rainy side in SPI calculations, which leads to more underestimation even for officially recommended MCI, and actual water supply are also misrepresented in SPEI calculations. This study offers valuable insights for policymakers to use optimal dataset and drought index to accurately assess the drought events, and take effective measures to alleviate its impact on tropical ecosystems in China.

Mangroves are typical ecosystems located in the intertidal zone of tropical and subtropical coasts that protect the area against wave action, promote accretion in river estuaries, and act as an important global carbon sink. However, several natural mangroves have recently degraded due to climate change and human activities, increasing the risk to coastal areas' ecological environments. The mangroves on Qi'ao Island in Zhuhai, China, have been destroyed by human activities and the invasion of the exotic species Spartina alterniflora. In 1999, the Zhuhai municipal government imported pioneer species, such as Sonneratia apetala, to Qi'ao Island to restore the degraded mangroves, which have now evolved into a sufficiently continuous community with a stable area since 2015 with S. apetala as the dominant species. However, because the intensity and frequency of typhoon landfalls are increasing under global warming, dominant species in the mangroves of Qi'ao Island, S. apetala, is more vulnerable to typhoon disturbance due to its height and low trunk density, leading to greater uncertainty regarding their ecological functions on Qi'ao Island. Existing studies have mainly focused on the damage and recovery patterns of mangroves by a single typhoon, having seldom analyzed the response process of mangroves to consecutive disturbances by multiple typhoons; thus, these studies cannot be used to predict the succession process of mangroves with increasing typhoon frequency. In this study, the damage and recovery patterns of mangroves on Qi'ao Island were studied under the disturbance of three consecutive typhoons (2016 NIDA, 2017 Hugo, and 2018 Mangkhut), and their influencing factors were discussed based on the Normalized Difference Vegetation Index (NDVI) using Sentinel-2 remote sensing images. The results showed that (1) the NDVI of mangroves on Qi'ao Island decreased after the typhoon, and the damage levels could be classified as mild or mild to moderate. Moreover, the severity of the damage was relatively small. (2) An annual legacy effect existed across multiple typhoons. The recovery process of mangroves generally followed a circulating succession mode after typhoon disturbances in the order of more severe damage→slow recovery→milder damage→rapid recovery→ more severe damage pattern. (3) The damage levels of mangroves on Qi'ao Island increased with typhoon intensity. However, they decreased if S. apetala recovered slowly before the typhoon. Thus, the recovery pattern was mainly influenced by the damage levels of S. apetala after the typhoon landing and was not largely dependent on the hydrothermal conditions at regional scales. The results suggest that mangroves on Qi'ao Island, mainly consisting of S. apetala, have evolved to adapt to the consecutive typhoon disturbances, which has promoted their succession from plantations to near natural forests and the formation of a stable typhoon-resistant ecosystem.

Mountain treelines are thought to be sensitive to climate change. However, how climate impacts mountain treelines is not yet fully understood as treelines may also be affected by other human activities. Here, we focus on "closed-loop" mountain treelines (CLMT) that completely encircle a mountain and are less likely to have been influenced by human land-use change. We detect a total length of similar to 916,425 km of CLMT across 243 mountain ranges globally and reveal a bimodal latitudinal distribution of treeline elevations with higher treeline elevations occurring at greater distances from the coast. Spatially, we find that temperature is the main climatic driver of treeline elevation in boreal and tropical regions, whereas precipitation drives CLMT position in temperate zones. Temporally, we show that 70% of CLMT have moved upward, with a mean shift rate of 1.2 m/year over the first decade of the 21st century. CLMT are shifting fastest in the tropics (mean of 3.1 m/year), but with greater variability. Our work provides a new mountain treeline database that isolates climate impacts from other anthropogenic pressures, and has important implications for biodiversity, natural resources, and ecosystem adaptation in a changing climate.

[目的]构建科学完善的水资源法律体系是破除我国水资源困境的重要途径,对我国水资源法律颁布的时空分布特征进行分析,以期为我国水资源的高效利用与保护提供基础依据.[方法]对我国1980-2019年水资源法律颁布的时空分布特征进行分析,并在计算水资源综合协调度,同时考虑区域GDP的基础上,采用地理探测器对胡焕庸线两侧地区水资源立法的驱动因素及其差异进行探讨.[结果]结果显示:截至2019年,水资源国家性法律、行政法规和部门规章的有效立法数分别为4部、14部和40部,而其更新速率则表现出相反趋势,分别为3.25次/部、0.73次/部和0.37次/部.水资源地方性法规的有效立法数为864部,而地方政府规章仅有421部,但二者在胡线东西两侧的比值均为87∶13.前者在胡线东西两侧的更新速率分别为1.23次/部和0.69次/部,而后者仅有0.74次/部和0.26次/部.[结论]结果表明:在时间上,水资源国家性法律的立法数变化主要与其法律效力有关,表现为法律效力越高,更新速率越快,但其立法数相应越少,且变化也更稳定.水资源地方性法规因其效力比地方部门规章高,在2005年后逐渐成为地方水资源立法的首选,特别是2015年后《立法法》赋予市级地方政府立法权,其立法数迎来爆发式增长.在空间上,胡焕庸线东侧地区的水资源立法数显著大于西侧,且更新速率也更快,但二者的比值随着立法基数的增加已趋于稳定.区域GDP和水资源综合协调度的交互作用是我国水资源地方立法的主要驱动力,其中胡焕庸线东侧立法主要与区域GDP有关,表现为"法律助推经济";而其西侧立法主要与水资源综合协调度有关,表现为"问题催生法律".

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绿地对于缓解城市洪涝灾害具有非常重要的作用,对其土壤入渗的定量化研究是评价城市绿地雨洪调蓄能力的关键.受城市土壤空间异质性的影响,不同功能区绿地土壤水分入渗速率的差异较大.采用双环入渗仪对广州海珠国家湿地公园典型乔草和灌草绿地的土壤水分入渗特征进行测定,并对其影响因素进行分析,结果表明:(1)广州海珠国家湿地公园的绿地土壤水分入渗性能处于中等至较高水平,但受机械和人为压实作用,绿地土壤容重偏大,总孔隙率偏低,加上外来客土影响,土壤物理性黏粒含量高,且有人为侵入体混入等,从而抑制了绿地表层土壤的水分入渗;(2)灌草相对于乔草对绿地表层土壤水分入渗的改善更为明显,这主要与前者的根系分布较浅有关,此外灌草绿地的凋落物更易留存,且其细根分解较快,这均有助于表层土壤有机质的及时返还,从而促进了绿地表层土壤的水分入渗;(3)广州海珠国家湿地公园绿地土壤的水分累积入渗量随时间变化更符合Kostiakov模型.未来广州市绿地的建设及管理应减少土壤压实及外来客土混入,适当增加灌草比例,使其兼顾旅游休闲和雨洪蓄积功能,从而有助于海绵城市的高效建设.

为探究亚热带湿润地区河湖周边发育的灌丛沙堆形态与沉积特征,以南昌市厚田沙地为研究区,对其优势种蔓荆(Vitex trifolia)所形成的灌丛沙堆开展野外调查,通过对不同部位的沉积物进行采样与分析,研究沙堆形态、沉积特征及其与植被特性之间的关系.结果 表明:蔓荆灌丛沙堆形态大多为盾形,水平尺度大,高度矮,坡度缓.沙堆沉积物以中沙为主,分选性较差,呈正偏和窄峰态分布,沙源来自附近平沙地和丘间地,为近源沉积.平均粒径从迎风坡底部至背风坡底部呈现为先变细后变粗的趋势,体现了灌丛沙堆的防风滞沙功能和对沙粒的重新分选作用.灌丛与沙堆的各形态参数(灌丛高度除外)均存在高度的正相关性(P＜0.01),说明各形态参数在沙堆发育过程中得以协调发展.受植被类型和区域环境的影响,与干旱-半干旱地区直立生长且分支少的灌丛形成的椭球形或圆锥形沙堆形态不同,蔓荆匍匐生长且高度较矮的形态常形成低矮且范围较大的灌丛沙堆.亚热带湿润地区风力资源不丰富及厚田沙地沙源不足使沉积物主要来源于附近平沙地与丘间地,但不同坡位沉积规律与干旱-半干旱地区相同.

The adaptive capacity of psammophytes to sand burial is crucial for the ecological restoration of coastal dune systems. The responses of Spinifex littoreus to different sand burial depths and levels were examined on the coast of Pingtan Island, Fujian Province, South China. The results indicated that, compared with the control group (CG), sand burial on the S. littoreus stolons had no signi?cant impact on the vertical growth of its conjoint ramets. However, the horizontal growth of S. littoreus stolons was stimulated and signi?cantly increased in half-intense (HI) and complete-intense (CI) sand burial treatments by 24.56% and 40.79%, respectively. Throughout the experiment, about 96% of adventitious roots were observed on the base section of stolons, while no roots in the control group (CG). After 20-day arti?cial sand burial treatments, the dry weight ratio between stem and leaf of S. littoreus was decreased in all three sections of stolons, especially for the top sections. Overall, S. littoreus can adapt to the complete and intense sand burial in growing season by rapid growth of stolons, abundant production of adventitious roots on the stolon base, and more germination of leaves on the stolon top.

非结构性碳水化合物（non-structural carbonhydrate,NSC）作为光合作用的主要产物,其含量多少可反映植物整体的碳收支平衡关系及对外界环境胁迫的适应策略。该研究采用改进的苯酚-浓硫酸法对福建省平潭岛海岸处于生长旺盛期的3种典型沙生植物木麻黄、单叶蔓荆和老鼠艻茎叶的NSC及其组分含量进行测定。结果表明:（1）单叶蔓荆叶片、茎干可溶性糖含量均最大,分别为（137.83±3.75）、（90.74±2.65）mg·g -1 ,老鼠艻叶片、茎干淀粉含量均最大,分别为（105.41±2.49）、（120.48±7.67） mg·g -1 ,二者茎叶NSC含量均大于木麻黄,且全部达到显著水平（P＜0.05）。（2）沙堆表面老鼠艻叶片NSC及组分含量从雏形、发育到稳定阶段变化不明显,但茎干NSC及组分含量在雏形阶段沙堆表面显著大于其他两个演替阶段（P＜0.05）,且依次呈现下降趋势。（3）从幼龄林、中龄林到成龄林阶段,木麻黄NSC含量呈现先上升后下降趋势,其中成龄林叶片可溶性糖、淀粉和NSC含量、茎干可溶性糖和NSC含量均显著低于其他两个生长阶段（P＜0.05）。（4）不同沙生植物对环境胁迫的适应策略各异,海岸沙丘表面植被恢复应充分考虑物种特性及其更新。

假林线在中国亚热带山地普遍存在,研究其物种组成及优势种的种群特征有助于理解人类活动中止后,该地区森林群落的次生演替过程.对广东石门台假林线典型分布区内的木龙顶样地进行野外植被调查,并对其乔木层优势种的种群特征进行测量及采样分析,结果表明,(1)木龙顶样地的植物群落属于山顶常绿苔藓矮曲林,受物种特性及山顶效应影响,其群落结构简单,总体矮化.依据各层物种重要值,可将该样地群落命名为疏齿木荷-五列木-野古草群丛(Ass.Schima remotiserrata-Pentaphylax euryoides-Arundinella anomala).(2)乔木层优势种疏齿木荷的植株普遍低矮,88.8％的植株高度均小于1 m,总体分布呈现为反"J"型.其胸径大于2.5 cm以上的植株仅占总数的7.7％,以小径级为主.(3)乔木层优势种疏齿木荷的总生物量为9.11 t·hm?2,与同气候区其他森林相比偏低,这主要与疏齿木荷种群中的幼苗占比过大有关.受物种的生物学特性及所在生境影响,研究区假林线的物种组成单一、长势较差.其优势种疏齿木荷的幼苗更新充分,但死亡率较高,从幼苗到幼树的过渡成为疏齿木荷天然更新的障碍,当前整个种群增长仍处于滞缓阶段.

Non-structural carbohydrates (NSC) are essential substances for the tree growth and metabolism, and play an important role in environmental adaptation of trees. At temporal scale, NSC contents in trees have limited inter-annual variation, which could be attributed to the strategy of tree growth and carbon storage. Different factors influence NSC contents of trees in various climatic regions, which change substantially at the seasonal scale. At spatial scale, the variations of NSC content in trees show an insignificantly decreasing trend with the decreases of latitude at global and continental scales, which are mainly related to the hydrothermal gradients. The trend at regional scale is opposite because of the decrease of hydrothermal gradients and lower sample frequency. More sophisticated relations exist between the variations of NSC content in trees and altitudes, which are caused by species-specific characteristics and the variations of micro-habitat conditions. The variations of NSC content in trees at multiple spatial-temporal scales are generally determined by both biotic and abiotic factors, which are mainly dependent on the tradeoff among photosynthate production, respiratory depletion, and tree growth. Furthermore, the methods used for the determination of NSC content are different, which results in great uncertainties in comparing conclusions from different studies. The methods used for sample collection and measurement of NSC should be improved and unified to enhance the comparison among different studies. The NSC contents of trees in different age classes should be measured with all organs collected at multiple spatial-temporal scales. The underlying mechanisms, significance of NSC storage, transformation and allocation on tree growth and survival should be further discussed.

Tree seedlings are one of the important components in alpine treeline ecotone, whose regeneration is crucial to treeline migration in response to climate change. We analyzed the spatial distribution, regeneration of tree seedlings and their responses to climate change in treeline ecotone in recent decades. The spatial distribution of tree seedlings in treeline ecotone is dominated by diffuse and clustered forms, with different indicative significance for spatial dynamics of treeline. At global scale, the altitude distribution limits of tree seedlings are usually related to the length and average temperature of growing season, along with the species characteristics. However, precipita-tion plays an important role at regional scale. The initial stage of seedling recruitment is restricted by seed source, which determines seed distribution and germination to a great extent. Microenvironment facilitates seedling regeneration by providing shelter for establishment and improving their survival rate. The regeneration process is more relevant to multiple biotic, abiotic factors and their interactions. With global warming, rising temperature in treeline ecotone and more precipitation are more suitable for seedling regeneration of treeline species. The expansion of seedlings to higher elevations could be considered as the portent of timberline upwards migration. Due to species-specific adaption strategy, however, some trees only increase seedling density and timberline location is constant. In the future, it is necessary to take precise dating techniques, such as tree-ring and 14C dating, and conduct long-term in-situ monitoring and indoor simulation experiments. To provide scientific basis for mountain ecosystem restoration and conservation, we should strengthen the studies on spatial patterns and regeneration mechanism of seedlings in treeline ecotone at multiple spatio-temporal scales, the adaptation strategies of tree seedlings in different types of treeline ecotone and treeline dynamics prediction.