Search Results (166)

Gross primary productivity (GPP) is a key carbon flux in the global carbon cycle, and understanding the inhibitory effects of drought on GPP and its underlying mechanisms is crucial for understanding carbon–climate feedback. However, current research has not sufficiently addressed the threshold dynamics and regional differentiation of GPP responses to the synergistic effects of meteorological drought (MD) and soil moisture drought (SD), particularly in the drought-sensitive Mongolian Plateau. This study focuses on the Mongolian Plateau from 1982 to 2021, using the standardized precipitation index (SPI) and standardized soil moisture index (SSI) to characterize MD and SD, respectively. The study combines the three-threshold run theory, cross-wavelet analysis, Spearman correlation analysis, and copula models to systematically investigate the variation characteristics, propagation patterns, and the probability and thresholds for triggering GPP loss under different time scales (monthly, seasonal, semi-annual, and annual). The results show that (1) both types of droughts exhibited significant intensification trends, with SD intensifying at a faster rate (annual scale SSI12 trend: −0.34/10a). The intensification trend strengthened with increasing time scales. MD exhibited high frequency, short duration, and low intensity, while SD showed the opposite characteristics. The most significant aridification occurred in the central region. (2) The average propagation time from MD to SD was 11.22 months. The average response time of GPP to MD was 10.46 months, while the response time to SD was significantly shorter (approximately 2 months on average); the correlation between SSI and GPP was significantly higher than that between SPI and GPP. (3) The conditional probability of triggering mild GPP loss (e.g., <40^th percentile) was relatively high for both drought types, and the probability of loss increased as the time scales extended. Compared to MD, SD was more likely to induce severe GPP loss. Additionally, the drought intensity threshold for triggering mild loss was lower (i.e., mild drought could trigger it), while higher drought intensity was required to trigger severe and extreme losses. Therefore, this study provides practical guidance for regional drought early-warning systems and ecosystem adaptive management, while laying an important theoretical foundation for a deeper understanding of drought response mechanisms. Full article

With the rising concerns about climate change and continuous increase in the salinity of soil, it is essential to understand the C-cycling functioning of saline soil to better predict the ecological functions and health of soil. Microbes play critical roles in C-cycling. However, limited research has been conducted to understand the impact of soil salinity on the microbial functional genes involved in C-cycling. In this study, effects of varying soil salinity levels in wetlands on the C-cycling functions and diversity of soil microbes were investigated by metagenomic sequencing. The results showed a higher relative abundance of genes related to decomposition of easily degradable organic C at low salinity. On the other hand, higher abundance of genes participating in the decomposition of recalcitrant organic C were observed at high salinity. These findings indicate distinct metabolic bias of soil microbes based on the salinity levels. Proteobacteria and Actinobacteria were dominant in soils with low to medium salinity levels, while Bacteroidetes phyla was prominent in highly saline soils. Furthermore, partial least squares path modeling (PLS-PM) identified electrical conductivity, total nitrogen, and total phosphorus as key regulators of C-cycling gene expression. Overall, the present study highlights the intricate connections between salinity, microbial attributes, and carbon metabolism in soil, suggesting that the soil microbes adapt to saline stress through divergent eco-adaptations. The findings of this study highlight the significance of exploring these microbial interactions for effective management and conservation of saline wetlands. Full article

Leaf loss caused by pest infestations poses a serious threat to forest health. The leaf loss rate (LLR) refers to the percentage of the overall tree-crown leaf loss per unit area and is an important indicator for evaluating forest health. Therefore, rapid and accurate acquisition of the LLR via remote sensing monitoring is crucial. This study is based on drone hyperspectral and LiDAR data as well as ground survey data, calculating hyperspectral indices (HSI), multispectral indices (MSI), and LiDAR indices (LI). It employs Savitzky–Golay (S–G) smoothing with different window sizes (W) and polynomial orders (P) combined with recursive feature elimination (RFE) to select sensitive features. Using Random Forest Regression (RFR) and Convolutional Neural Network Regression (CNNR) to construct a multidimensional (horizontal and vertical) estimation model for LLR, combined with LiDAR point cloud data, achieved a three-dimensional visualization of the leaf loss rate of trees. The results of the study showed: (1) The optimal combination of HSI and MSI was determined to be W11P3, and the LI was W5P2. (2) The optimal combination of the number of sensitive features extracted by the RFE algorithm was 13 HSI, 16 MSI, and hierarchical LI (2 in layer I, 9 in layer II, and 11 in layer III). (3) In terms of the horizontal estimation of the defoliation rate, the model performance index of the CNNR_HSI model (MPI = 0.9383) was significantly better than that of RFR_MSI (MPI = 0.8817), indicating that the continuous bands of hyperspectral could better monitor the subtle changes of LLR. (4) The I-CNNR_HSI+LI, II-CNNR_HSI+LI, and III-CNNR_HSI+LI vertical estimation models were constructed by combining the CNNR_HSI model with the best accuracy and the LI sensitive to different vertical levels, respectively, and their MPIs reached more than 0.8, indicating that the LLR estimation of different vertical levels had high accuracy. According to the model, the pixel-level LLR of the sample tree was estimated, and the three-dimensional display of the LLR for forest trees under the pest stress of larch caterpillars was generated, providing a high-precision research scheme for LLR estimation under pest stress. Full article

The invasion of alien species has emerged as a global ecological challenge and invasive species can seriously threaten the habitats of native plants and intensify interspecific competition, ultimately exerting significant impacts on local ecosystems. Therefore, it is necessary to implement effective prevention and control strategies to reduce these impacts and maintain ecological stability. Against this backdrop, it is especially critical to analyze the influencing factors of invasive alien species and predict their future trends. Given China’s vast territory, complex natural geography, and diverse climatic conditions, the problem of invasive alien species in China is particularly severe, and scientific countermeasures are urgently required. Up to now, the number of invasive alien plant species in China has exceeded 520. Based on the number of invasive plant species in each province of China, this study analyzes the intrinsic connection between various influencing factors and invasive species, and through correlation analysis identifies the influencing factors, which are then used to analyze and predict the future invasion risks that each region may face. Full article

Snow serves as a crucial water source for vegetation growth on the Mongolian Plateau, and its temporal and spatial variations exert profound influences on terrestrial vegetation phenology. In recent years, global climate change has led to significant changes in snow and vegetation start of growing season (SOS). Therefore, it is necessary to study the mechanism of snow cover on vegetation growth and changes on the Mongolian Plateau. The study found that the spatial snow cover fraction (SCF) of the Mongolian Plateau ranged from 50% to 60%, and the snow melt date (SMD) ranged from day of the year (DOY) 88 to 220, mainly concentrated on the northwest Mongolian Plateau mountainous areas. Using different SOS methods to calculate the vegetation SOS distribution map. Vegetation SOS occurs earlier in the eastern part compared to the western part of the Mongolian Plateau. In this study, we assessed spatiotemporal distribution characteristics of snow on the Mongolian Plateau over the period from 2001 to 2023. The results showed that the SOS of the Mongolian Plateau was mainly concentrated on DOY 71-186. The Cox survival analysis model system established SCF and SMD on vegetation SOS. The SCF standard coefficient is 0.06, and the SMD standard coefficient is 0.02. The SOS_NDVI coefficient is −0.15, and the SOS_NDGI coefficient is −0.096. The results showed that the vegetation SOS process exhibited differential response characteristics to snow driving factors. These research results also highlight the important role of snow in vegetation phenology and emphasize the importance of incorporating the unique effects of vegetation SOS on the Mongolian Plateau. Full article

Desertification presents a significant ecological challenge in arid and semi-arid regions, posing a severe threat to regional ecological security and sustainable development. This study introduces an integrated framework for desertification vulnerability assessment, combining the MEDALUS model with the XGBoost algorithm, to evaluate desertification dynamics across the Mongolian Plateau from 2000 to 2020 and project future trends under four Shared Socioeconomic Pathways (SSPs) for 2030. The findings are as follows: (1) Between 2000 and 2020, desertification vulnerability was most pronounced in the southern and western regions of the plateau, with lower vulnerability observed in the northern and eastern areas. High-vulnerability zones expanded over time, highlighting the need for targeted and prioritized management efforts. (2) Climate factors—particularly temperature, wind speed, and precipitation—emerged as the dominant drivers of desertification, followed by soil characteristics and vegetation (NDVI). The influence of human activities on desertification became increasingly significant, stressing the need for improved land management and sustainable practices. (3) Future risks show that desertification vulnerability in the Mongolian Plateau will intensify under high-emission scenarios (SSP3-7.0, SSP5-8.5), with significant expansion of high vulnerability areas. Lower-emission scenarios (SSP1-2.6, SSP2-4.5) may reduce some impacts, but high vulnerability will persist, highlighting the need for urgent climate mitigation and adaptation efforts. Full article

As a crucial manifestation of ecosystem water regulation and supply functions, water conservation plays a vital role in regional ecosystem development and sustainable water resource management. This study investigates nine major Chinese river basins (Songliao, Haihe, Huaihe, Yellow, Yangtze, Pearl, Southeast Rivers, Southwest Rivers, and Inland Rivers) through integrated application of the InVEST model and geographical detector model. We systematically examine the spatiotemporal heterogeneity of water conservation capacity and its driving mechanisms from 1990 to 2020. The results reveal a distinct northwest–southeast spatial gradient in water conservation across China, with lower values predominating in northwestern regions. Minimum conservation values were recorded in the Inland River Basin (15.88 mm), Haihe River Basin (42.07 mm), and Yellow River Basin (43.55 mm), while maximum capacities occurred in the Pearl River Basin (483.68 mm) and Southeast Rivers Basin (517.21 mm). Temporal analysis showed interannual fluctuations, peaking in 2020 at 130.98 mm and reaching its lowest point in 2015 at 113.04 mm. Precipitation emerged as the dominant factor governing spatial patterns, with higher rainfall correlating strongly with enhanced conservation capacity. Land cover analysis revealed superior water retention in vegetated areas (forests, grasslands, and cultivated land) compared to urbanized and bare land surfaces. Our findings demonstrate that water conservation dynamics result from synergistic interactions among multiple factors rather than single-variable influences. Accordingly, we propose that future water resource policies adopt an integrated management approach addressing climate patterns, land use optimization, and socioeconomic factors to develop targeted conservation strategies. Full article

Drought impacts agricultural production and regional sustainable development. Accordingly, timely and accurate drought monitoring is essential for ensuring food security in rain-fed agricultural regions. Alternating drought and flood events frequently occur in the Heilongjiang River Basin, the largest grain-producing area in Far East Asia. However, spatiotemporal variability in drought is not well understood, in part owing to the limitations of the traditional Temperature Vegetation Dryness Index (TVDI). In this study, an Improved Temperature Vegetation Dryness Index (ITVDI) was developed by incorporating Digital Elevation Model data to correct land surface temperatures and introducing a constraint line method to replace the traditional linear regression for fitting dry–wet boundaries. Based on MODIS (Moderate-resolution Imaging Spectroradiometer) normalized vegetation index and land surface temperature products, the Heilongjiang River Basin, a cross-border basin between China, Mongolia, and Russia, exhibited pronounced spatiotemporal variability in drought conditions of the growing season from 2001 to 2023. Drought severity demonstrated clear geographical zonation, with a higher intensity in the western region and lower intensity in the eastern region. The Mongolian Plateau and grasslands were identified as drought hotspots. The Far East Asia forest belt was relatively humid, with an overall lower drought risk. The central region exhibited variation in drought characteristics. From the perspective of cross-national differences, the drought severity distribution in Northeast China and Inner Mongolia exhibits marked spatial heterogeneity. In Mongolia, regional drought levels exhibited a notable trend toward homogenization, with a higher proportion of extreme drought than in other areas. The overall drought risk in the Russian part of the basin was relatively low. A trend analysis indicated a general pattern of drought alleviation in western regions and intensification in eastern areas. Most regions showed relatively stable patterns, with few areas exhibiting significant changes, mainly surrounding cities such as Qiqihar, Daqing, Harbin, Changchun, and Amur Oblast. Regions with aggravation accounted for 52.29% of the total study area, while regions showing slight alleviation account for 35.58%. This study provides a scientific basis and data infrastructure for drought monitoring in transboundary watersheds and for ensuring agricultural production security. Full article

Desert ecosystems play a critical role in global climate regulation. Current research reveals a relative lack of research regarding desert ecosystem service (ES) supply and demand. Therefore, we selected the Ulanbuh desert, one of the eight major deserts in China, as study area. Using specialized models, we quantify the supply and demand of four ES, including water yield (Wy), soil conservation (Sc), windbreak and sand fixation (Ws), and carbon sequestration (Cs), from 1985 to 2020. Univariate linear regression analysis and panel data analysis (PDA) were used to examine trends in desert ES supply–demand ratio (ESDR) and its determinants. The findings indicated that ES supply presented increases in Sc and Cs, and decline in Ws from 1985 to 2020. Demand patterns showed a growth trend for Wy and Cs. ESDR revealed that Sc, Ws, and Cs show an excess of supply over demand and are in a decreasing trend, while Wy displays a supply deficit relative to demand with no significant change. The comprehensive ESDR decreased over the study period, with a supply-deficit status emerging in the southwestern area. Natural factors (NDVI and precipitation) and socio-economic factors (GDP and population density) served as the main factors affecting the comprehensive ESDR. This research provides a novel perspective for desert ecosystems management and conservation, emphasizing the necessity of incorporating the ES supply and demand balance into regional development policies to achieve sustainable development in arid regions. Full article

Snow cover phenology (SCP) serves as a critical regulator of hydrological cycles and ecosystem stability across the Mongolian Plateau (MP). Despite its importance, the spatiotemporal patterns of SCP and their climatic drivers remain poorly quantified, constrained by persistent gaps in satellite snow cover observations. Leveraging a high-resolution (500 m) daily gap-filled Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover dataset combined with reanalysis climate datasets, we systematically quantified SCP dynamics and identified the dominant controls during the 2000–2022 hydrological years using trend analysis and ridge regression. Our results reveal a significant divergence in SCP parameters: snow end dates (D_e) advanced markedly across the entire plateau (0.29 days yr⁻¹, p < 0.01), accounting for 90.39% of SCP anomalies. In contrast, snow onset date (D_o) exhibited unnoticeable changes, explaining 9.58% of SCP changes. Attribution analysis demonstrates that 47.72% of D_e variability stems from increased net shortwave radiation (+0.38 Wm⁻² yr⁻¹) and rising temperatures (+0.06 °C yr⁻¹) during the melting season, with net shortwave radiation exerting stronger control (R² = 0.73) than temperature (R² = 0.63). This study establishes the first continuous, high-resolution SCP climatology for the MP, providing mechanistic insights into cryosphere–atmosphere interactions that inform adaptive water resource strategies for climate-vulnerable arid ecosystems in this region. Full article

The escalation in the population of livestock coupled with inadequate precipitation has caused a reduction in pasture biomass, thereby resulting in diminished grassland carrying capacity (GCC) and pasture degradation. In this research, net primary productivity (NPP) data, sourced from the Global Land Surface Satellite (GLASS) and Moderate Resolution Imaging Spectroradiometer (MODIS) datasets from 1982 to 2020, were initially transformed into aboveground biomass (AGB) estimates. These estimates were subsequently utilized to evaluate and assess the long-term trends of GCC across Mongolia. The MODIS data indicated an upward trend in AGB from 2000 to 2020, whereas the GLASS data reflected a downward trend from 1982 to 2018. Between 1982 and 2020, climatic analysis uncovered robust positive correlations between AGB and precipitation (R > 0.80) and negative correlations with temperature (R < −0.60). These climatic alterations have led to a reduction in AGB, further impairing the regenerative capacity of grasslands. Concurrently, livestock numbers have generally increased since 1982, with a decrease in certain years due to dzud and summer drought, leading to the increase in the GCC. GCC assessment found that 37.5% of grasslands experienced severe overgrazing and 31.9–40.7% was within sustainable limits. Spatially, the eastern region of Mongolia could sustainably support current livestock numbers; the western and southern regions, as well as parts of northern Mongolia, have exhibited moderate to critical levels of grassland utilization. A detailed analysis of GCC dynamics and its climatic impacts would offer scientific support for policymakers in managing grasslands in the Mongolian Plateau. Full article

The flood risk of urban buildings has been continuously increasing, owing to the increasing frequency and severity of floods. There is an urgent need to implement precise mitigation strategies to address the unique characteristics of urban residential structures. In this study, an indicator system consisting of 17 indicators in four dimensions (extent of hazard, degree of exposure, vulnerability, and response ability) was developed for the flood risk of residential buildings. The assessment was conducted in Katsushika Ward, Tokyo, and the ANALYTIC HIERARCHY PROCESS(AHP)—Criteria Importance Through Intercriteria Correlation (CRITIC) method was integrated with Geographic Information System(GIS) technology. The spatial distribution of residential flood risk exhibits marked heterogeneity, with ‘extremely high’ and ‘high’ risk areas concentrated in northwestern and southwestern riverine zones. These regions exhibit dense populations, substantial assets, deep immersion depths, prolonged inundation durations, high proportions of wooden houses, and narrow roads impeding rescue operations. The mitigation priorities are the following: Enhance flood-resistant building heights and quality in riverside areas, strengthen vacant house management, widen rescue access routes, promote mid-/high-rise buildings, and optimize subsidies for tenants and single-person households to minimize losses. Full article

The swnR gene was cloned in the endophytic fungus Alternaria oxytropis OW 7.8 isolated from Oxytropis glabra, and the gene knockout mutant ΔswnR was first constructed in this study. Compared with A. oxytropis OW 7.8, the ΔswnR exhibited distinct morphological alterations in both colony and mycelial structure, a slower growth rate, and significant reductions in swainsonine (SW) levels, indicating that the function of the swnR gene promoted SW biosynthesis. Six differentially expressed genes (DEGs) closely associated with SW synthesis were identified by transcriptomic analysis of A. oxytropis OW 7.8 and ΔswnR, with P5CR, swnR, swnK, swnH2, and swnH1 downregulating, and sac upregulating. The expression levels of the six genes were consistent with the transcriptomic analysis results. Five differential metabolites (DEMs) closely associated with SW synthesis were identified by metabolomic analysis, with L-Lys, L-Glutamic acid, Saccharopine, and L-Proline upregulating, and L-PA downregulating. The results lay the foundation for the in-depth elucidation of molecular mechanisms and SW synthesis pathways in fungi, and are also of importance for the prevention of locoism in livestock, the control and utilization of locoweeds, and the protection and sustainable development of grassland ecosystems. Full article

The Mongolian Plateau, a region where nomadic and agrarian civilizations intersect, exemplifies regional sustainable development and natural resource utilization through the spatiotemporal distribution of cultivated land. However, large-scale, long-term, high-precision extraction of cultivated land has not been systematically conducted in this area. This study integrated remote sensing technology with machine learning methodologies to develop an automated extraction process based on spectral, textural, and topographical features. We monitored changes in cultivated land across eight time periods from 1990 to 2023 within the Selenge River Basin, utilizing Google Earth Engine and 3527 scenes derived from Landsat and Sentinel satellite imagery. The area of cultivated land fluctuated between 6332.78 km² and 14,799.22 km², representing 2.26% to 5.29% of the total area. Cultivated land exhibited a significant decline prior to 2005 and gradually increased after 2010, largely influenced by agricultural policy reforms. Traditional nomadic areas showed a spatial pattern of reconstruction, characterized by a significant transformation to agricultural land. The overall accuracy exceeded 90%, and kappa coefficients remained above 0.83. Consistency checks and comparisons of different integration methods further validate the feasibility and reliability of the research methods and results. This approach holds promise for application across the entire Mongolian Plateau and other arid and semi-arid regions for monitoring cultivated land dynamics. Full article

Midlatitude westerly and East Asian summer monsoon (EASM) are crucial circulation systems in the upper and lower troposphere of East Asia that significantly influence mid-summer precipitation pattern. However, their synergistic effect on mid-summer precipitation in North China (NC) remains unclear. In this study, the concurrent variations of mid-summer westerly and EASM are categorized into two configurations: strong westerly–strong EASM (SS) and weak westerly–weak EASM (WW). At the synoptic timescale, the SS configuration significantly enhances precipitation in NC, whereas the WW configuration suppresses mid-summer rainfall. The underlying mechanism is that the SS pattern stimulates an anomalous quasi-barotropic cyclone–anticyclone pair over the Mongolian Plateau–Yellow Sea region. Two anomalous water vapor channels (westerly-driven and EASM-driven water vapor transport) are established in the southern and western peripheries of this cyclone–anticyclone pair, ensuring abundant moisture supply over NC. Meanwhile, frequently occurring westerly jet cores in northern NC form a jet entrance region, favoring strong upper-level divergent pumping and deep accents in its southern flank. This synergy between strong westerlies and EASM enhances both the moisture transports and ascending movements, thereby increasing precipitation over NC. Conversely, the atmospheric circulation associated with the WW pattern exhibits opposite characteristics, resulting in decreased NC rainfall. Our findings elucidate the synoptic-scale influences of westerly–monsoon synergy on mid-summer rainfall, through regulating moisture transports and westerly jet-induced dynamic uplift, potentially improving predictive capabilities for mid-summer precipitation forecasting. Full article