Search Results (127)

The transportation sector significantly contributes to greenhouse gas (GHG) emissions and remains a key research focus on emission quantification and mitigation. Although numerous models exist for estimating vehicle-based emissions, most lack accuracy at regional scales, particularly in remote or underdeveloped areas, including backcountry national parks and mountainous regions lacking basic infrastructure. This study addresses that gap by developing and applying a terrain-adjusted, segment-based methodology to estimate GHG emissions from tourist vehicles in Altai Tavan Bogd National Park, one of Mongolia’s most remote protected areas. The proposed method uses Tier 1 IPCC emission factors but incorporates field-segmented route analysis, vehicle categorization, and terrain-based fuel adjustments to achieve a spatially disaggregated Tier 1 approach. Results show that carbon dioxide (CO₂) emissions increased from 118.7 tons in 2018 to 2239 tons in 2024. Tourist vehicle entries increased from 712 in 2018 to 13,192 in 2024, with 99.1% of entries occurring between May and October. Over the same period, cumulative methane (CH₄) and nitrous oxide (N₂O) emissions were estimated at 300.9 kg and 45.75 kg, respectively. This modular approach is especially suitable for high-altitude, infrastructure-limited regions where real-time emissions monitoring is not feasible. By integrating localized travel patterns with global frameworks such as the IPCC 2006 Guidelines, this model enables more precise and context-sensitive GHG estimates from vehicles in national parks and similar environments. Full article

The spatiotemporal changes and driving mechanisms of rain-on-snow (ROS) events and their intensities are crucial for responding to disasters triggered by such events. However, there is currently a lack of detailed assessment of the seasonal variations and driving mechanisms of ROS events and their intensities in China. Therefore, this study utilized daily meteorological data and daily snow depth data from 513 stations in China during 1978–2020 to investigate spatiotemporal variations of ROS events and their intensities. Also, based on the detrend and partial correlation analysis model, the driving factors of ROS events and their intensity were explored. The results showed that ROS events primarily occurred in northern Xinjiang, the Qinghai–Tibet Plateau, Northeast China, and central and eastern China. ROS events frequently occurred in the middle and lower Yangtze River Plain in winter but were easily overlooked. The number and intensity of ROS events increased significantly (p < 0.05) in the Changbai Mountains in spring and the Altay Mountains and the southeast part of the Qinghai–Tibet Plateau in winter, leading to heightened ROS flood risks. However, the number and intensity of ROS events decreased significantly (p < 0.05) in the middle and lower Yangtze River Plain in winter. The driving mechanisms of the changes for ROS events and their intensities were different. Changes in the number of ROS events and their intensities in snow-rich regions were driven by rainfall days and quantity of rainfall, respectively. In regions with more rainfall, these changes were driven by snow cover days and snow water equivalent, respectively. Air temperature had no direct impact on ROS events and their intensities. These findings provide reliable evidence for responding to disasters and changes triggered by ROS events. Full article

The assessment of the hydrological functions of landscapes and the landscape–hydrological background is an important instrument for minimizing damage from rivers and preventing water conflicts under conditions of data scarcity for hydrological modeling. To assess the climate–hydrological background of the East Kazakhstan region, the Selyaninov Hydro-thermal Coefficient and the Vysotsky–Ivanov Moisture Coefficient were used. The East Kazakhstan region is a typical continental arid and semi-arid region. The presence of mountain ranges, such as the Altai, makes the climate and environment in the region highly varied. A dataset from 30 weather stations for the period 1961–2023 was used for calculations. Three interpolation methods and landscape extrapolation were used to construct maps of the coefficients. Over the observation period, the values of the moisture indices at the weather stations in the region fluctuated within a wide range. Both coefficients are in the range from extra arid to extra humid climates. Full article

Vermipsyllid parasitize the body surface of sheep, feeding on blood and transmitting diseases, causing severe economic losses to the livestock industry. An outbreak of sheep Vermipsyllid fleas in the mountain pastures of Xinjiang’s Altai region showed that several commonly used commercial anthelmintic drugs had poor therapeutic effects on the prevalent flea species. This study first conducted species identification of Vermipsyllid through morphological analysis of 200 female and 40 male specimens collected from the Altai region, followed by molecular biological identification of 6 randomly selected fleas (3 females and 3 males). Finally, pharmacodynamic experiments were performed to screen for highly effective anthelmintic drugs. Ninety Altai multiparous ewes infected with Vermipsyllid were divided into six groups (fifteen sheep per group): an untreated control group (Ctr), avermectin injection group (Group I), ivermectin injection group (Group II), moxidectin pour-on group (Group III), cypermethrin pour-on group (Group IV), and dichlorvos pour-on group (Group V), with a 14-day trial period. On Day 0, each group received a single treatment according to drug instructions and specified dosages. The number of fleas, flea population reduction rates, and cure rates were measured on Day 0, Day 3, Day 7, and Day 14 to screen for effective anthelmintic drugs. Results showed that unfed female and male fleas were grayish-brown. Engorged females reached 14.15 mm in size, appearing pale white or yellow, with their sterna maintaining the original size and shape despite abdominal distension. Female fleas had 20–21 segments on the labium, while males had 16–19 segments. The hind tibiae featured four notches, and each side of the tergite had 13 ± 1 cup-like indentations. Molecular biological identification indicated that the identified fleas belonged to D. ioffi (Vermipsyllidae, Dorcadia Ioff), showing 99.13% sequence similarity with D. ioffi from Xinjiang, China. In pharmacodynamic experiments, the number of D. ioffi in Groups IV and V decreased to zero on both Day 7 and Day 14, which was extremely significantly lower than other groups (p < 0.01). The flea population reduction rates in Groups IV and V reached 100% on both days. By Day 14, the cure rates of Groups I, II, and III were 0%, while those of Groups IV and V were 100%. Avermectin injection, ivermectin injection, and moxidectin pour-on showed poor anthelmintic effects, whereas cypermethrin and dichlorvos pour-on exhibited high anthelmintic activity against this flea species. Full article

This article presents the results of a comprehensive study on Rosa acicularis Lindl., Rosa laxa Retz., and Rosa spinosissima L. growing in the sharply continental climate of the Kazakhstan Altai under diverse ecological and phytocenotic conditions. All three wild rose species show notable ecological plasticity, allowing them to thrive in heterogeneous environments. A total of 41 populations were recorded: 12 of R. acicularis, 13 of R. laxa, and 16 of R. spinosissima, with vertical distribution ranging from 404 to 1837 m a.s.l. Nine populations where each species dominates its plant community were selected as model sites to assess ecological, biological, and economic traits. For each population, the floristic composition and structure were described, and morphometric, resource, and physiological indicators were evaluated. Significant phenotypic variation was noted in plant height, bush diameter, leaf traits, and fruit morphology and taste. Under natural conditions, industrial thickets are mainly formed by R. laxa in the Southern Altai and by R. spinosissima in the Southwestern Altai due to their wide distribution and high plant density. Fruit weight ranged from 2.23 to 2.47 g (R. acicularis), 2.28 to 2.68 g (R. laxa), and 2.17 to 2.55 g (R. spinosissima), values generally lower than those previously reported. Based on coefficients of variation for intra-population diversity in morphological and quantitative traits, several promising populations were identified. These populations hold potential for selecting valuable forms for breeding programs and for establishing a regionally adapted gene pool. Full article

Desert plants in arid regions are facing escalating challenges from global warming, underscoring the urgent need to predict shifts in the distribution and habitats of dominant species under future climate scenarios. This study employed the Maximum Entropy (MaxEnt) model to project changes in the potential suitable habitats of three keystone desert species in Xinjiang—Halostachys capsica (M. Bieb.) C. A. Mey (Caryophyllales: Amaranthaceae), Haloxylon ammodendron (C. A. Mey.) Bunge (Caryophyllales: Amaranthaceae), and Karelinia caspia (Pall.) Less (Asterales: Asteraceae)—under varying climatic conditions. The area under the Receiver Operating Characteristic curve (AUC) exceeded 0.9 for all three species training datasets, indicating high predictive accuracy. Currently, Halos. caspica predominantly occupies mid-to-low elevation alluvial plains along the Tarim Basin and Tianshan Mountains, with a suitable area of 145.88 × 10⁴ km², while Halox. ammodendrum is primarily distributed across the Junggar Basin, Tarim Basin, and mid-elevation alluvial plains and aeolian landforms at the convergence zones of the Altai, Tianshan, and Kunlun Mountains, covering 109.55 × 10⁴ km². K. caspia thrives in mid-to-low elevation alluvial plains and low-elevation alluvial fans in the Tarim Basin, western Taklamakan Desert, and Junggar–Tianshan transition regions, with a suitable area of 95.75 × 10⁴ km². Among the key bioclimatic drivers, annual mean temperature was the most critical factor for Halos. caspica, precipitation of the coldest quarter for Halox. ammodendrum, and precipitation of the wettest month for K. caspia. Future projections revealed that under climate warming and increased humidity, suitable habitats for Halos. caspica would expand in all of the 2050s scenarios but decline by the 2070s, whereas Halox. ammodendrum habitats would decrease consistently across all scenarios over the next 40 years. In contrast, the suitable habitat area of K. caspia would remain nearly stable. These projections provide critical insights for formulating climate adaptation strategies to enhance soil–water conservation and sustainable desertification control in Xinjiang. Full article

The China–Mongolia arid region adjacent to the Altai Mountain (CMA) has a sensitive ecosystem that relies heavily on both terrestrial water (TWS) and groundwater storage (GWS). However, during the 2003–2016 period, the CMA experienced significant glacier retreat, lake shrinkage, and grassland degradation. To illuminate the TWS and GWS dynamics in the CMA and the dominant driving factors, we employed high-resolution (0.1°) GRACE (Gravity Recovery and Climate Experiment) data generated through random forest (RF) combined with residual correction. The downscaled data at a 0.1° resolution illustrate the spatial heterogeneity of TWS and GWS depletion. The highest TWS and GWS decline rates were both on the north slope of the Tianshan River Basin (NTRB) of the Junggar Basin of Northwestern China (JBNWC) (27.96 mm/yr and −32.98 mm/yr, respectively). Human impact played a primary role in TWS decreases in the JBNWC, with a relative contribution rate of 62.22% compared to the climatic contribution (37.78%). A notable shift—from climatic (2002–2010) to anthropogenic factors (2011–2020)—was observed as the primary driver of TWS decline in the Great Lakes Depression region of western Mongolia (GLDWM). To maintain ecological stability and promote sustainable regional development, effective action is urgently required to save essential TWS from further depletion. Full article

Xinjiang larch (Larix sibirica Ledeb.) is a keystone species in the Altay Mountains, playing a vital role in maintaining ecosystem stability. This study investigates how different soil preparation techniques (ring, strip, and burrow) influence seed germination and seedling establishment by mitigating apomictic allelopathy. Experimental plots were established using artificial seeding and natural seed dispersal at soil depths of 5 cm, 10 cm, and 15 cm. Seedling survival and development were monitored in June, July, and August 2023. The results demonstrated that sod removal significantly enhanced seed germination by reducing allelopathic inhibition, improving seed–soil contact, and increasing moisture retention. Among the techniques, the ring method yielded the highest rates of seedling establishment, particularly when artificial seeding was combined with natural seed dispersal. Although seedling numbers tended to increase with soil depth, the differences were not statistically significant. Temporal dynamics revealed a peak in seedling survival in July, followed by a subsequent decline. These findings highlight the critical role of optimized soil preparation techniques in promoting successful seedling development. The study offers practical guidance for ecological restoration and sustainable forest management in degraded larch ecosystems of the Altay Mountains. Full article

With the intensification of global climate change and human activities, coniferous species as the main components of natural forests in the Altay Mountains are facing the challenges of aging and regeneration. This study systematically analyzed structural heterogeneity and regeneration of three coniferous stand groups, Larix sibirica Ledeb. stand group, Abies sibirica Ledeb.-Picea obovata Ledeb.-Larix sibirica mixed stand group, and Picea obovata stand group, respectively, across western, central, and eastern forest areas of the Altay Mountains in Northwest China based on field surveys in 2023. Methodologically, we integrated Kruskal–Wallis/Dunn’s post hoc tests, nonlinear power-law modeling (diameter at breast height (DBH)–age relationships, validated via R², root mean square error (RMSE), and F-tests), static life tables (age class mortality and survival curves), and dynamic indices. Key findings revealed structural divergence: the L. sibirica stand group exhibited dominance of large-diameter trees (>30 cm DBH) with sparse seedlings/saplings and limited regeneration; the mixed stand group was dominated by small DBH individuals (<10 cm), showing young age structures and vigorous regeneration; while the P. obovata stand group displayed uniform DBH/height distributions and slow regeneration capacity. Radial growth rates differed significantly—highest in the mixed stand group (average of 0.315 cm/a), intermediate in the P. obovata stand group (0.216 cm/a), and lowest in the L. sibirica stand group (0.180 cm/a). Age–density trends varied among stand groups: unimodal in the L. sibirica and P. obovata stand groups while declining in the mixed stand group. All stand groups followed a Deevey-II survival curve (constant mortality across ages). The mixed stand group showed the highest growth potential but maximum disturbance risk, the L. sibirica stand group exhibited complex variation with lowest risk probability, while the P. obovata stand group had weaker adaptive capacity. These results underscore the need for differentiated management: promoting L. sibirica regeneration via gap-based interventions, enhancing disturbance resistance in the mixed stand group through structural diversification, and prioritizing P. obovata conservation to maintain ecosystem stability. This multi-method framework bridges stand-scale heterogeneity with demographic mechanisms, offering actionable insights for climate-resilient forestry. Full article

Background/Objectives: This study explores the biochemical diversity of Hippophae rhamnoides, Viburnum opulus, and Lonicera caerulea subsp. altaica to identify genotypes rich in bioactive compounds for breeding nutritionally valuable cultivars. Methods: Selected forms and cultivars of each species were evaluated for key biochemical traits. Analyses included quantification of vitamins (C, B9, B12), sugars, organic acids, carotenoids, and flavonoids using HPLC and TLC. Results: In H. rhamnoides, vitamin C content ranged widely, with ‘Pamyati Baytulina Sh-9-81’ reaching 156.0 mg/%, while ‘Shetlastinka No. 7’ showed the most favorable sugar-to-vitamin C ratio. ‘Krasnoplodnaya K-14-81’ had the highest carotenoids (55.3 mg/100 g), and ‘Dolgozhdannaya No. 5’ was notable for flavonoid richness. In V. opulus, considerable variation was observed in vitamin content, sugars, and dry matter; ‘Zhemchuzhnoe Ozhele’ and ‘Shtambovaya’ were rich in rutin and robinin. In L. caerulea subsp. altaica, forms No. 5, 7, and 9 stood out for vitamin C, sugar, and flavonoid content. Hyperoside, isorhamnetin, and myricetin were common, while kaempferol and hypolaetin were form-specific. Conclusions: H. rhamnoides demonstrated the highest variability in biochemical composition, while L. caerulea subsp. altaica showed a particularly rich flavonoid profile. These species offer valuable genetic resources for developing biofortified cultivars suited to both nutritional and adaptive breeding goals. Full article

Peat swamp wetlands, crucial carbon pools in terrestrial ecosystems, significantly impact regional carbon cycling and climate change. In this study, the peat swamp wetland in the Altay Mountains was selected as the research object. In July 2023, soil samples were collected in situ from a depth of 0–80 cm of the peat swamp wetland. Subsequently, the contents of soil organic carbon (SOC), dissolved organic carbon (DOC), particulate organic carbon (POC), and the physicochemical properties of the soil samples were determined. The distribution characteristics of soil organic carbon and its active carbon fractions at different soil depths and their influencing factors were investigated. The results demonstrate that (1) SOC, POC, and DOC concentrations were significantly higher in subsurface layers (20–80 cm) than in those of surface layers (0–20 cm), with SOC and POC peaking at 20–40 cm and DOC predominantly accumulating at 40–80 cm. (2) The concentrations of SOC, POC, and DOC reached minima at 0–10 cm, accounting for 17.25%, 16.91%, and 6.46% of the total 0–80 cm profile, respectively. POC represented 76.46% of SOC throughout the profile. (3) Available phosphorus (AP), total nitrogen (TN), ammonium nitrogen (NH₄⁺N), and soil moisture (SM) accounted for an average of 68.94% of the variation in soil organic carbon and active carbon fractions at a depth of 0–80 cm. Higher levels of soil moisture and total nitrogen content emerged as the primary factors responsible for the reduction in soil organic carbon and active carbon fractions. In shallow soils (0–20 cm), an increase in the content of available phosphorus and ammonium nitrogen contributed to a decline in the soil’s active carbon fraction. Conversely, the situation was reversed in deeper soils. This study thus offers scientific insights into alpine peat bog wetland soil carbon dynamics and environmental responses. Full article

This paper focuses on insect remains found at the Kebezen site (51.93600° N, 87.09665° E) on the Turachak stream, Altai Republic, Russia, in layers ranging in age from 20.1 to 19.3 cal ky BP, corresponding to the onset of the last deglaciation. Coleoptera, represented by 105 species from 21 families, predominate in the sediments, with the families Carabidae, Staphylinidae, Chrysomelidae and Scolytidae being the most numerous. The insect assemblage of Kebezen contrasts sharply with the Late Pleistocene entomofauna of the West Siberian Plain, but it is similar with the assemblages of the geographically close Lebed site (Oldest and Older Dryas). Also, it corresponds well with the modern middle-altitude entomofauna of the mountains of north-eastern Altai. Based on such entomological data, boreal forests with a predominance of Picea and alpine meadows, as well as a cold and humid climate, were reconstructed for the Kebezen site. Changes in the ecological composition of beetles were traced during sedimentation: the most complete spectrum of the basal layer was replaced by a complex with a significant predominance of meadow and water-edge species, after which the proportions of shrub species, bryophilous species, and forest species consistently increased. Such changes correspond to the course of primary succession initiated by a catastrophic factor such as a megaflood. Full article

Landslides frequently occur in the Xinjiang Uygur Autonomous Region of China due to its complex geological environment, posing serious risks to human safety and economic stability. Existing studies widely use machine learning models for landslide susceptibility prediction. However, they often fail to capture the threshold and interaction effects among environmental factors, limiting their ability to accurately identify high-risk zones. To address this gap, this study employed a gradient boosting decision tree (GBDT) model to identify critical thresholds and interaction effects among disaster-causing factors, while mapping the spatial distribution of landslide susceptibility based on 20 covariates. The performance of this model was compared with that of a support vector machine and deep neural network models. Results showed that the GBDT model achieved superior performance, with the highest AUC and recall values among the tested models. After applying clustering algorithms for non-landslide sample selection, the GBDT model maintained a high recall value of 0.963, demonstrating its robustness against imbalanced datasets. The GBDT model identified that 8.86% of Xinjiang’s total area exhibits extremely high or high landslide susceptibility, mainly concentrated in the Tianshan and Altai mountain ranges. Lithology, precipitation, profile curvature, the Modified Normalized Difference Water Index (MNDWI), and vertical deformation were identified as the primary contributing factors. Threshold effects were observed in the relationships between these factors and landslide susceptibility. The probability of landslide occurrence increased sharply when precipitation exceeded 2500 mm, vertical deformation was greater than 0 mm a⁻¹, or the MNDWI values were extreme (<−0.4, >0.2). Additionally, this study confirmed bivariate interaction effects. Most interactions between factors exhibited positive effects, suggesting that combining two factors enhances classification performance compared with using each factor independently. This finding highlights the intricate and interdependent nature of these factors in landslide susceptibility. These findings emphasize the necessity of incorporating threshold and interaction effects in landslide susceptibility assessments, offering practical insights for disaster prevention and mitigation. Full article

Shrub encroachment in grasslands has a major impact on soil carbon storage (SOC_S) and soil total nitrogen (STN_S), which affects nutrient cycling and ecosystem processes. We explored the effects of shrub encroachment on SOC_S and STN_S in five grassland types in the Altai Mountains: mountain meadows, temperate meadow steppe, temperate steppe, temperate steppe desert, and temperate desert steppe. Shrub encroachment considerably improved SOC_S and STN_S, with the greatest increases occurring in locations with high encroachment. The interaction between grassland type and encroachment extent also significantly influenced soil properties, including bulk density, soil water content, and microbial carbon and nitrogen. Specifically, SOC_S increased by 16%, 77%, and 129%, and STN_S increased by 43%, 94%, and 127% under low, medium, and high shrub encroachment, respectively. The soil stoichiometry shifted, with C/N ratios decreasing and C/P and N/P ratios increasing with shrub encroachment. Structural equation modeling (SEM) revealed that shrub encroachment indirectly affected SOC_S and STN_S through changes in soil nutrients and climate. Our findings suggest that shrub encroachment promotes soil C sequestration and alters soil nutrient cycling, with implications for grassland management and ecological restoration in the face of global climate change. Full article

In arid regions, climatic fluctuations significantly affect vegetation structure and function. Sun-induced chlorophyll fluorescence (SIF) can quantify certain physiological parameters of vegetation but has limitations in characterizing responses to climate change. This study analyzed the spatiotemporal differences in response to climate change across various ecological regions and vegetation types from 2000 to 2020 in Xinjiang. According to China’s ecological zoning, R1 (Altai Mountains-Western Junggar Mountains forest-steppe) and R5 (Pamir-Kunlun Mountains-Altyn Tagh high-altitude desert grasslands) represent two ecological extremes, while R2–R4 span desert and forest-steppe ecosystems. We employed the standardized precipitation evapotranspiration index (SPEI) at different timescales to represent drought intensity and frequency in conjunction with global OCO-2 SIF products (GOSIF) and the normalized difference vegetation index (NDVI) to assess vegetation growth conditions. The results show that (1) between 2000 and 2020, the overall drought severity in Xinjiang exhibited a slight deterioration, particularly in northern regions (R1 and R2), with a gradual transition from short-term to long-term drought conditions. The R4 and R5 ecological regions in southern Xinjiang also displayed a slight deterioration trend; however, R5 remained relatively stable on the SPEI24 timescale. (2) The NDVI and SIF values across Xinjiang exhibited an upward trend. However, in densely vegetated areas (R1–R3), both NDVI and SIF declined, with a more pronounced decrease in SIF observed in natural forests. (3) Vegetation in northern Xinjiang showed a significantly stronger response to climate change than that in southern Xinjiang, with physiological parameters (SIF) being more sensitive than structural parameters (NDVI). The R1, R2, and R3 ecological regions were primarily influenced by long-term climate change, whereas the R4 and R5 regions were more affected by short-term climate change. Natural grasslands showed a significantly stronger response than forests, particularly in areas with lower vegetation cover that are more structurally impacted. This study provides an important scientific basis for ecological management and climate adaptation in Xinjiang, emphasizing the need for differentiated strategies across ecological regions to support sustainable development. Full article