High-elevation Areas Research Articles

An invasive pathogen generally contracts species to their niche cores, not margins

Quantifying how species' distributions contract in response to threats can reveal pathways of decline and the role of environmental conditions in moderating threat impacts. Two general patterns of niche contraction have been described: ecological marginalization, where species contract away from threat impacts to peripheral, sub‐optimal areas of their niche, and; contraction to the core, where species contract toward their niche center where their fitness and capacity to withstand threat impacts is highest. Recent work has described widespread ecological marginalization in declining mammal species, for which land use change and overexploitation are key threats. Different threatening processes could result in contrasting patterns of niche contraction, although this has not been well‐studied. Here, we examine patterns of realized niche contraction in Australian frog species impacted by the emergence of chytrid fungus Batrachochytrium dendrobatidis, a pathogen that has driven catastrophic amphibian declines globally. We quantified changes in species' environmental niche space following chytrid emergence and documented a pattern of contraction toward the niche core in declining species. We develop and apply a novel approach to show that these niche contractions are driven by losses in a subset of niche space, suggesting population extinctions due to chytrid are driven by factors shaping both pathogen fitness (threat impact) and host fitness (threat tolerance). Species declines have been concentrated in high elevation areas with cooler temperatures, which are more physiologically suitable for the pathogen and constrain the resilience of frog hosts at both individual and population levels. Given the contrast between our results and widespread ecological marginalization in mammals, we propose that while a given threat may result in common patterns of decline among affected species, patterns of decline may vary considerably between threatening processes and among taxa.

Satellite-Based Assessment of Snow Dynamics and Climatic Drivers in the Changbai Mountain Region (2001–2022)

Changbai Mountain is located in China’s northeastern seasonal stable snow zone and is a high-latitude water tower. The changes in snow cover have a great influence on the hydrological process and ecological balance. This study quantitatively analyzed the spatio-temporal variation in snow cover in the Changbai Mountain region and its driving factors based on Moderate Resolution Imaging Spectroradiometer (MODIS) data. To improve the accuracy of snow cover analysis, a simple cloud removal algorithm was applied, and the locally optimal NDSI threshold was investigated. The results showed that the snow-covered area (SCA) in the Changbai Mountain region exhibited strong seasonality, with the largest SCA found in January. The SCA during the winter season showed an insignificant increasing trend (83.88km2) from 2001 to 2022. The variability in SCA observed from November to the following March has progressively decreased in recent years. The snow cover days (SCD) showed high spatial variation, with areas with decreased and increased SCD mainly found in the southern and northern regions, respectively. It was also revealed that temperature is the primary hydrometeorological factor influencing the snow variation in the study domain, particularly during the spring season or in high-elevation areas. The examined large-scale teleconnection indices showed a relatively weak correlation with SCA, but they may partially explain the abnormally low snow cover phenomenon in the winter of 2018–2019.

A roadmap to sustainable management of commercial medicinal and aromatic plants, fungi, and lichens in Nepal.

Thousands of plants, fungi, and lichen species are traded every year. Although sustainable use is critical for livelihoods and biodiversity conservation, insufficient data prevent detailed sustainability assessments for most species. How can the sustainability of trade in such data-deficient species be enhanced? We considered a country-level example of 300 medicinal and aromatic plant, fungus, and lichen species traded in tens of thousands of tons worth tens of millions of US dollars in and from Nepal annually. Past interventions have not ensured sustainable trade, leaving species vulnerable to commercial harvesting and threatening rural household incomes, the processing industry, and government revenues. Building on documented evidence and stakeholder involvement, we used a theory of change approach to develop a sustainable management approach. We produced a draft plan (roadmap) by combining interventions proposed at annual key stakeholder dialogue meetings with recommendations extracted from a literature review on the trade and conservation of commercial medicinal and aromatic plants, fungi, and lichens in Nepal. The draft roadmap was discussed at a national workshop with sector-wide stakeholder representation to derive the final roadmap. The literature review showed the 41 causal assumptions and theoretical explanations for actions and outcomes. Feedback mechanisms included 6 bundles of mutually reinforcing actions, such as the relationship between increased cultivation and decreased wild harvesting. The roadmap has 5 pathways: increase cultivation, strengthen local management, support domestic businesses, improve sector governance, and increase international collaboration. Each pathway is associated with 2-5 actions (e.g., hand over high-elevation areas to local communities) that lead to outputs (2-5) (e.g., an increased area under local management) and outcomes (2-6) (e.g., less overharvesting). Accordingly, the roadmap offers stakeholders a structured approach to implement future activities and investments to enhance sustainable trade. The approach can be replicated for other countries and products.

Temporal and spatial variability of landscape ecological risk in the Yangtze River Midstream Urban Agglomeration in the context of climate change

The Yangtze River Midstream Urban Agglomeration is a pivotal economic zone in China. Over the past 35 years, climate change has increased ecosystem vulnerability and instability in this area. Therefore, assessing landscape ecological risk (LER) is vital for this region. This study analyzed LER variations from 1985 to 2020 using statistical methods and landscape indices, and forecasted LER changes from 2025 to 2050 with multi-model meteorological data. Results show the following: (1) LER indices have decreased over the last 35 years, with a notable shift from high-risk to medium-risk areas. High LER areas remained concentrated in low-elevation, densely urbanized central regions, indicating severe ecological damage compared to high-elevation areas. (2) Climate change significantly impacts the LER index, with temperature exerting a stronger influence than precipitation. Overall, LER decreases with rising temperatures and precipitation, though some cities exhibit opposite trends. (3) Future multi-Shared Socioeconomic Pathway scenarios suggest a general decrease in LER with increased temperature and decreased precipitation, predominantly resulting in low- and medium-risk zones. High LER areas will persist in low-elevation zones, particularly in the southern and central plains. Given the high LER in the plains, the timely governmental regulation and control measures are essential for ensuring ecologically sustainable development.

Drivers of Anuran Assemblage Structure in a Subtropical Montane Region.

Elevation gradients provide excellent semi-experimental conditions to investigate how the spatial distribution of biodiversity is shaped by the environment. Here, we investigate how temperature, productivity, and elevation are related to the diversity of anuran assemblages in a montane region of the southern Brazilian Atlantic Forest. We sampled 20 half-hectare plots between 2020 and 2021, distributed along a sharp elevation gradient. Anuran species richness and abundance decreased with increasing elevation. We show a positive relationship between ambient temperature and frog species richness and abundance, highlighting the importance of temperature in shaping assemblages along the elevation gradient. In contrast, productivity did not affect species richness and abundance, suggesting that available energy via resources does not limit local frog diversity. We further observed marked differences in the composition of anuran assemblages between low and high elevation areas, which were related to temperature. Beta diversity is mainly driven by species replacements among assemblages, which were likely related to environmental conditions. These findings highlight the importance of incorporating protected areas that encompass the entire range of elevations to capture the full complement of landscape-scale diversity. This is crucial as species showed limited distributions, and the marked effects of temperature should be explicitly considered under future scenarios of elevated upslope warming.

Inter-basin groundwater flow in the Ordos Basin: Evidence of environmental isotope and hydrological investigations

The Ordos Basin, located in arid and semi-arid region of China, is famous for its abundant groundwater resources and artesian features. The source of groundwater recharge, whether from local precipitation or external sources, has been debated. This study aims to elucidate the groundwater circulation mechanism in the Ordos Basin through scientific expedition, environmental isotope method, and hydrological drilling exploration, providing valuable insights for other artesian basins. Comprehensive analysis indicates that groundwater in the Ordos Basin is recharged by modern precipitation, primarily from high-elevation areas outside the basin. Deep groundwater from these external sources ascends to the aquifer through basement fault zones. Evidence from hydrogen and oxygen isotopes, hydraulic gradients, and water quantities suggests that the Tibetan Plateau is the most potential recharge source. Based on the distribution of Cenozoic basalt and data from seismic observation wells, we propose that leakage water from the Tibetan Plateau rift valley is transported to the Ordos Basin through fast channels, possibly lava tubes, and then upwelling through basement fault zones. This work provides a new perspective on the mechanism of inter-basin groundwater circulation.

A new species of the genus Scincella (Squamata: Scincidae) from Mount Fansipan, Hoang Lien Son Range, northwestern Vietnam.

We describe a new species of the genus Scincella Mittleman, 1950 from northwestern Vietnam, based on a new collection of ground skinks from Mount Fansipan of the Hoang Lien Son Range in Lao Cai Province. Scincella fansipanensis sp. nov. is distinguished from other Scincella species in the Indochina region and southern China by body size (SVL), separation of prefrontals, number of midbody scale rows, paravertebral scale rows, nuchals and subdigital lamellae on toe IV, separation of toe from finger when limbs are adpressed along the body, and dorsal color pattern. The new species is further distinguished from its congeners by uncorrected genetic distances of 14.60-21.41% (COI gene). The new species is currently known only from high elevation areas of Mt. Fansipan in Vietnam.

Forest disturbance shapes habitat selection but not migratory tendency for partially migratory ungulates

AbstractIn forest management settings, disturbance resets forests to earlier successional stages, typically improving forage conditions for mule deer. Examining how forest disturbance influences mule deer behavior is important for guiding forest and wildlife management. We used GPS collar data collected between 2017 and 2019 from 136 adult female mule deer in three populations throughout western Montana, United States, to investigate how disturbance from burns (wildfire and prescribed fire) and timber harvest influenced three aspects of space‐use behaviors: (1) probability of migration from winter range to summer range, (2) home range (second‐order) selection by migrants on summer range, and (3) within‐home range (third‐order) selection. We hypothesized that deer would maximize use of disturbances during summer for nutritional benefits, predicting that deer with higher proportionate disturbance in their winter home range would be less likely to migrate away from those disturbances during summer. We predicted that migrants would select disturbances at the second and third orders. We found that proportionate disturbance in winter home ranges had no effect on the probability of migration. Among migrants, deer generally selected burns, timber harvests, and open‐canopy habitat at the second order in all study areas, with particularly strong selection for 6‐ to 15‐year‐old disturbances. At population levels, selection for disturbances ceased at the third order. At individual levels, however, third‐order selection for burns increased with availability, whereas selection for harvests decreased, suggesting burns may satisfy more resource needs than harvests. Our results emphasize how space‐use fidelity constrains mule deer habitat selection. During summer, adherence to migratory strategies constrains the habitat available for second‐order selection, preventing deer from exploiting disturbances that would otherwise be available had they remained resident in wintering areas. Second‐order selection then determines disturbance availability within home ranges, affecting third‐order behaviors. Although variance in selection behaviors among individuals was high, population‐level patterns were remarkably similar among study areas, suggesting these responses may be generalizable to mule deer throughout the northern Rocky Mountains. Forest management practices like timber harvest, prescribed burns, and wildfire management within higher elevation areas of summer range used by migrants could yield the greatest nutritional benefits for mule deer.

Discovering the Ecosystem Service Value Growth Characteristics of a Subtropical Soil Erosion Area Using a Remote-Sensing-Driven Mountainous Equivalent Factor Method

Evaluation ecosystem service value (ESV) is critical, as “lucid waters and lush mountains are invaluable assets”. To assess the incremental effects of ecological assets on soil and water conservation in subtropical mountains, we developed a remote-sensing-driven mountainous equivalent factor (RS-MEF) method to estimate the ESV of Changting County, China. This method is a hybrid of a conventional equivalent factor framework and remote sensing techniques for mountains, achieving several advancements, including spatial adjustment using vegetation activity merged with productivity, improved spatial resolution, and the removal of topographic effects. Using the RS-MEF method, we estimated that the ESV of Changting County was approximately CNY 15.80 billion in 2010 and CNY 34.83 billion in 2022. Specifically, the ESV per unit area of the major soil erosion area (MSEA) in the county was less than that of the non-major soil erosion area (n-MSEA); however, the ESV growth rate of the MSEA from 2010 to 2022 was faster than that of the n-MSEA. Therefore, the ESV gap between the two areas was reduced from 28.99% in 2010 to 15.83% in 2022. Topographic gradient analysis illustrates that areas with elevations of 385 to 658 m and steep slopes achieved a high ESV, while high-elevation areas with gentle slopes will be a focus of control in the next phase. Our study demonstrates that significant achievements have been made in ecological restoration from an ESV perspective, with a notable reduction in low-ESV areas in the MSEA; the insights gained into ESV growth and its underlying factors are valuable and instructive for future soil and water conservation efforts.

Spatial Analysis of Chronic Kidney Disease of Unknown Aetiology (CKDu) Prevalence in Badulupura Village, Sri Lanka

This study investigated spatial patterns of chronic kidney disease of unknown aetiology (CKDu) patients in Badulupura village. The analysis utilized published locational data for all households, including households affected by CKDu, and all wells used by CKDu-affected patients (CPA wells). The study employed Average Nearest Neighbour (ANN) and Hot Spot Analysis (Getis-Ord Gi*) tools to assess the spatial clustering of CKDu households and CPA wells. The study also explored the impact of topographical factors such as elevation, slope, and distance to watershed boundaries on the spatial distribution of CKDu patients. The ANN analysis revealed a dispersed pattern for all wells, and a random distribution for all households. However, both CKDu households and CPI wells exhibited a clustered pattern, suggesting a location-specific cause for the spatial distribution of the disease. Additionally, overlaying CKDu-affected households on the digital elevation model revealed a concentration of CKDu hot spots in high-elevation areas, while cold spots were observed in low-elevation regions. Furthermore, the t-test was employed to investigate the significance of elevation, slope, and distance to the watershed boundaries in relation to CKDu distribution. The results indicated a significant (p<0.05) prevalence of CKDu in high-elevation areas, while no significant association was found with slope or distance to watershed boundaries. The study revealed the presence of localized CKDu hot spots and cold spots within a small geographical area, highlighting the importance of considering topographical factors and conducting comprehensive hydrogeological and geological studies to gain valuable insights into the spatial distribution of CKDu.

Phosphorus dynamics in volcanic soils of Weizhou Island, China: implications for environmental and agricultural applications

The dynamics of phosphorus are intricately governed by geological and ecological processes. Examining phosphorus dynamics in volcanic islands can enhance our comprehension of its behavior within such unique geological systems. However, research on phosphorus dynamics in volcanic islands remains limited. We investigated the phosphorus content of volcaniclastic rocks and basalt soils from Weizhou Island, China, to understand the influencing factors on phosphorus dynamics. The results indicate that in the volcaniclastic profile, phosphorus concentrates at 20–40 cm (17 mg/kg), decreases at 40–60 cm (11.9 mg/kg), and increases at 80–200 cm up to 46.4 mg/kg proximate to the bedrock, for the basalt profile, phosphorus content increases from the surface (80.2 mg/kg) towards the bedrock (83.9 mg/kg). The differences in phosphorus distribution between volcaniclastic rocks and basalts reflect the influence of parent material, rock weathering degree, carbonate content, topographic elevation, sea level changes, and geological activities. A strong positive correlation (R = 0.96907) between total and available phosphorus has been observed, suggesting that total phosphorus content effectively predicts available phosphorus content. Volcaniclastic rocks in wharves and high-elevation areas show low total phosphorus, while forest land with dense vegetation and neutral to alkaline soil supports higher total phosphorus due to enhanced bioavailability for plant absorption and utilization. Overall, the basalt soil of the volcanic island Weizhou Island demonstrates superior long-term fertility compared to the volcaniclastic soil. Despite its low total phosphorus content, it mainly exists in a highly bioavailable form, facilitating plant absorption, which is crucial for enhancing agricultural yields and ecosystem restoration on volcanic islands.

Toward the reliable use of reanalysis data as a reference for bias correction in climate models: A multivariate perspective

General circulation models are vital tools in climate change research, profoundly influencing numerous hydroclimatological studies, but often exhibit systematic biases due to limitations in parameterization. To correct these biases, bias correction (BC) methods, which are heavily dependent on the quality of historical reference data, are employed. Ideally, accurate data comes from a dense network of gauges, but due to their limited availability, reanalysis data is frequently used instead. Although reanalysis data provides consistent global and temporal coverage, its assimilated nature can introduce additional biases, potentially increasing error propagation particularly in the multivariate perspective. Thus, this study investigates the reliability of reanalysis data as a reference for multivariate bias correction (MBC) and utilizes a two-stage bias correction approach that integrates both gauge and reanalysis data to leverage their respective strengths. Conducting a case study in South Korea, we utilized gauge data, ERA5 reanalysis data, and outputs from 10 CMIP6 General Circulation Models. We implemented three-nested experiments to test the robustness of this two-stage approach across various dimensions. Results show that using reanalysis data as a reference can lead to bias propagation, especially misrepresenting precipitation and wind dependencies in high elevation areas. However, the two-stage approach has shown an enhancement in mitigating these limitations, even when gauge data is temporally sparse, and across different combinations of MBC methods. Finally, we highlight the current limitations and potential for future research to focus on effectively combining gauge and reanalysis data to compensate for each other’s weaknesses, thereby enhancing the accuracy and reliability in future climate realizations.

Seasonal changes in altitudinal patterns of bird species richness in a temperate low-elevation mountain

Mountain environments change rapidly over short distances along altitudinal gradients, providing an ideal system for exploring the mechanisms that shape biodiversity gradients. Species richness is the most studied diversity metric in mountains, and altitudinal patterns and their shaping mechanisms have been investigated worldwide. Although the altitudinal patterns of species richness in breeding bird assemblages have been extensively studied, less attention has been paid to seasonal changes in patterns between winter and summer. Furthermore, the effects of severe climate in high-elevation areas on seasonal changes in the altitudinal pattern of species richness in insular mountains remain unclear. We investigated changes in the pattern between the breeding and wintering seasons using field and literature surveys in Mount Tsukuba (877 m a.s.l.), central Japan. Temperatures at the middle elevations of the slope are relatively higher than those at the foot of the mountain in winter. The mountain is covered with forests up to its summit. We found that the altitudinal pattern of species richness was the low-plateau during the wintering season. Low-elevation areas were havens for wintering species, whereas high-elevation areas were impoverished in wintering species. Conversely, there was no association between elevation and species richness during the breeding season. Our study suggests that the relaxation of severe climates in high-elevation areas during winter and verdant forests in the highlands during summer are critical mechanisms driving seasonal changes in the altitudinal pattern of species richness. Furthermore, we highlight that comprehensive monitoring, including wintering seasons, is essential for detecting the changes in the diversity patterns of mountain bird assemblages due to the shift in the peak of wintering species richness under ongoing climate change.

Sparse large trees in secondary and planted forests highlight the need to improve forest conservation and management

Large trees are essential for carbon storage and biodiversity conservation. While an increasing number of studies have focused on large trees in primary forests, little is known about them in secondary and planted forests. We surveyed 86,936 trees in secondary forests and 91,294 trees in planted forests in Zhejiang, China, to investigate the distribution patterns and determinants of large trees in these forests. We found a mean density of large trees (DBH ≥ 30 cm) of 15 ± 13 stems ha−1 in secondary forests and 11 ± 9 stems ha−1 in planted forests. Moreover, the mean density of trees with DBH ≥ 60 cm was 0.36 stems ha−1, indicating that large trees are particularly rare in secondary and planted forests. These large trees were primarily occurred in secondary forests that living in high-elevation area with less human exploitation and colder and wetter climates, and in planted forests with higher species richness and lower tree density. In addition, the density of large trees in these forests significantly increased with tree species richness and decreased with increasing tree density. These results indicate that the sparse large trees were the legacy of historical human activities in the studied area, but currently, the development of large trees is still limited by the improper forest structure characterized by low species diversity and high tree density. To better conserve large trees, there is an urgent need for enhanced conservation policies for secondary forests, such as establishing forest parks for forests with large trees, and implementing near-natural forest management practices for planted forests, which include planting mixed native tree species and maintaining moderate tree density.

The changing geography of wine climates and its implications on adaptation in the Italian Alps

AbstractWine production and quality both strongly depend on suitable climatic conditions. Increasing the climate resilience of wine regions is therefore of critical importance but requires instruments to evaluate shifts in climatic conditions and growing suitability. This evaluation is particularly challenging in mountain viticultural areas due to their complex topoclimatic patterns, yet they offer the possibility to analyze climate change impacts and adaptation strategies across various climatic conditions and cultivated varieties. Here, we assessed historical and future bioclimatic conditions and identified effective adaptation strategies toward more sustainable and climate‐resilient wine production in the mountain winegrowing regions within South Tyrol in the Italian Alps. We found significant changes in climatic conditions under future scenarios, such as an increase in the Huglin index (HI) and cool night index (CNI) as well as a decreased dryness index (DI), causing an expansion of suitable areas for viticulture as well as a spread of unprecedented climatic conditions in traditional vineyards. Impacts and suitable adaptation options varied depending on climate type and grape variety, highlighting the need for targeted solutions that balance the need for high‐quality wine production with environmental protection and sustainability. Higher elevated areas over 1000 m a.s.l. will experience an increased suitability raising the need for restrictions regarding the expansion of vineyards to avoid degradation of natural ecosystems and biodiversity declines. In contrast, many traditional winegrowing areas will need to implement a combination of short‐ and long‐term adaptation measures to maintain traditional wine styles. Our findings provide a framework for the assessment of viticultural suitability and the formulation of appropriate adaptation strategies for the sustainable cultivation of wine grapes in a changing climate that applies to a variety of climates and grape varieties.

Integrating Active and Passive Remote Sensing Data for Forest Age Estimation in Shangri-La City, China

The accurate mapping of age structure and access to spatially explicit information are essential to optimal planning and policy-making for forest ecosystems, including forest management and sustainable economic development. Specifically, surveying and mapping the age structure of forests is crucial for calculating the carbon sequestration capacity of forest ecosystems. However, spatial heterogeneity and limited accessibility make forest age mapping in mountainous areas challenging. Here, we present a new workflow using ICESat-2 LiDAR data integrated with multisource remote sensing imagery to estimate forest age in Shangri-La, China. Two methods—a climate-driven exponential model and a random forest algorithm—are compared to infer the age structure of the five dominant species in Shangri-La. The climate-driven model, with an R2 of 0.67 and an RMSE of 12.79 years, outperforms the random forest model. The derived wall-to-wall forest age map at 30 m resolution reveals that nearly all forests in Shangri-La are mature or overmature, especially among the high-elevation species Abies fabri (Mast.) Craib and Picea asperata Mast., compared with Pinus yunnanensis Franch., Quercus aquifolioides Rehd. and E.H. Wils. and Pinus densata Mast., where the age structure is more evenly distributed across different elevation ranges. Younger forests are frequently found around human settlements and along the Jinsha River valley, whereas older forests are located in remote and high-elevation areas that are less disturbed. The combined use of active and passive remote sensing data has resulted in substantial improvements in the spatial detail and accuracy of wall-to-wall age mapping, which is expected to be a cost-effective approach for supporting forest management and carbon accounting in this important ecological region. The method developed here can be scaled to other mountain areas both to understand the age patterns and structure of mountain forests and to provide critical information for forestation, reforestation and carbon accounting in surface-to-high mountain areas, which are increasingly crucial for climate mitigation.

Season-dependent climate sensitivity of the surface runoff of major rivers in Changbai Mountain

Due to the sensitivity of runoff to changes in seasonal snowpack, the changes in surface runoff within high-latitude and high-elevation areas are more complex than in other areas. However, this sensitivity is often overlooked when correlating changes in runoff with meteorological variables. Here, we analyze changes in surface runoff during snowmelt and snowless periods and their sensitivity to climate change from 1960 to 2019 in the upstream watersheds of the Songhua, Yalu, and Tumen Rivers in Changbai Mountain. Most runoff indices, except for low flow in the Yalu River, exhibited decreasing trends during snowmelt and snowless periods. Precipitation was the primary variable responsible for surface runoff during snowless and snowmelt periods. Notably, rainfall replenished all runoff indices during snowless periods, particularly under high flow conditions. The average and high flows were also primarily supplemented by rainfall during snowmelt periods. However, low flow was positively correlated with snowmelt in the Songhua and Tumen Rivers and with temperature in the Songhua, Yalu and Tumen Rivers during snowmelt periods. Additionally, extreme runoff events were closely associated with extreme precipitation. These findings demonstrate the seasonal and index-dependent climate sensitivity of surface runoff within Changbai Mountain, offering insights into the surface runoff response mechanism to climate change in high-altitude mountainous areas. Under future climate change conditions, frequent and intense extreme precipitation events may increase the risk of flooding, owing to the high sensitivity of high flows to precipitation, posing a serious threat to regional ecological security.

Unveiling the future water pulse of central asia: a comprehensive 21st century hydrological forecast from stochastic water balance modeling

This study uses a new dataset on gauge locations and catchments to assess the impact of 21st-century climate change on the hydrology of 221 high-mountain catchments in Central Asia. A steady-state stochastic soil moisture water balance model was employed to project changes in runoff and evaporation for 2011–2040, 2041–2070, and 2071–2100, compared to the baseline period of 1979–2011. Baseline climate data were sourced from CHELSA V21 climatology, providing daily temperature and precipitation for each subcatchment. Future projections used bias-corrected outputs from four General Circulation Models under four pathways/scenarios (SSP1 RCP 2.6, SSP2 RCP 4.5, SSP3 RCP 7.0, SSP5 RCP 8.5). Global datasets informed soil parameter distribution, and glacier ablation data were integrated to refine discharge modeling and validated against long-term catchment discharge data. The atmospheric models predict an increase in median precipitation between 5.5% to 10.1% and a rise in median temperatures by 1.9 °C to 5.6 °C by the end of the 21st century, depending on the scenario and relative to the baseline. Hydrological model projections for this period indicate increases in actual evaporation between 7.3% to 17.4% and changes in discharge between + 1.1% to –2.7% for the SSP1 RCP 2.6 and SSP5 RCP 8.5 scenarios, respectively. Under the most extreme climate scenario (SSP5-8.5), discharge increases of 3.8% and 5.0% are anticipated during the first and second future periods, followed by a decrease of -2.7% in the third period. Significant glacier wastage is expected in lower-lying runoff zones, with overall discharge reductions in parts of the Tien Shan, including the Naryn catchment. Conversely, high-elevation areas in the Gissar-Alay and Pamir mountains are projected to experience discharge increases, driven by enhanced glacier ablation and delayed peak water, among other things. Shifts in precipitation patterns suggest more extreme but less frequent events, potentially altering the hydroclimate risk landscape in the region. Our findings highlight varied hydrological responses to climate change throughout high-mountain Central Asia. These insights inform strategies for effective and sustainable water management at the national and transboundary levels and help guide local stakeholders.

Spatial and Temporal Dynamics in Vegetation Greenness and Its Response to Climate Change in the Tarim River Basin, China

Vegetation in ecologically sensitive regions has experienced significant alterations due to global climate change. The underlying mechanisms remain somewhat obscure owing to the spatial heterogeneity of influencing factors, particularly in the Tarim River Basin (TRB) in China. Therefore, this study targets the TRB, analyzing the spatial and temporal dynamics of vegetation greenness and its climatic determinants across multiple spatial scales. Utilizing Normalized Difference Vegetation Index (NDVI) data, vegetation greenness trends over the past 23 years were assessed, with future projections based on the Hurst exponent. Partial correlation and multiple linear regression analyses were employed to correlate NDVI with temperature (TMP), precipitation (PRE), and potential evapotranspiration (PET), elucidating NDVI’s response to climatic variations. Results revealed that from 2000 to 2022, 90.1% of the TRB exhibited an increase in NDVI, with a significant overall trend of 0.032/decade (p < 0.01). The difference in NDVI change across sub-basins and vegetation types highlighted the spatial disparity in greening. Notable greening predominantly occurred near rivers at lower elevations and in extensive cropland areas, with projections indicating continued greening in some regions. Conversely, future trends mainly suggested a shift towards browning, particularly in higher-elevation areas with minimal human influence. From 2000 to 2022, the TRB experienced a gradual increase in TMP, PRE, and PET. The latter two factors were significantly correlated with NDVI, indicating their substantial role in greening. However, vegetation sensitivity to climate change varied across sub-basins, vegetation types, and elevations, likely due to differences in plant characteristics, hydrothermal conditions, and human disturbances. Despite climate change influencing vegetation dynamics in 51.5% of the TRB, its impact accounted for only 25% of the total NDVI trend. These findings enhance the understanding of vegetation ecosystems in arid regions and provide a scientific basis for developing ecological protection strategies in the TRB.

A global analysis of ice phenology for 3702 lakes and 1028 reservoirs across the Northern Hemisphere using Sentinel-2 imagery

As existing global lake ice studies have predominantly focused on medium to large lakes, and reservoir ice studies have been limited to regional scales, very few studies of ice phenology have combined both lakes and reservoirs of different sizes. This study aims to characterize the freeze-up and break-up dates of 3702 lakes and 1028 reservoirs from 1 to 31,000 km2 across the Northern Hemisphere, and to analyze spatial patterns and relationships between ice phenological dates and driving factors. The freeze-up and break-up dates of these water bodies were retrieved from Sentinel-2 imagery using an ice detection algorithm through the Google Earth Engine platform from 2019 to 2023. The algorithm was verified by comparing phenology dates with an independent database based on observations from passive microwave sensors, with a mean absolute error of 18 days for both freeze-up and break-up dates. This newly established ice phenology database along with various geographic, morphometric, and climatic characteristics of the water bodies, was used to develop a random forest model for predicting ice phenology dates. While the predictive model performance is at a fair level (mean absolute error of 12 days for both freeze-up and break-up), challenges were encountered in certain high-elevation areas where cloudy conditions as well as black ice resulted in delayed freeze-up dates. Among the variables included in the random forest model, latitude and accumulation of freezing degree days were identified as the main drivers of ice phenology dates. Despite the challenges of applying a single, straightforward method on a global scale, this study has allowed the creation of a vast and comprehensive database of lake and reservoir freeze-up and break-up dates that can be used by the community to further analyze ice patterns.