Search Results (333)

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

As the world’s largest loess deposit region, the Loess Plateau’s vegetation dynamics are crucial for its regional water–heat balance and ecosystem functioning. Leaf Area Index (LAI) serves as a key indicator bridging canopy architecture and plant physiological activities. Existing studies have made significant advancements in simulating LAI, yet accurate LAI simulation remains challenging. To address this challenge and gain deeper insights into the environmental controls of LAI, this study aims to accurately simulate LAI in the Loess Plateau using deep learning models and to elucidate the spatiotemporal influence of soil moisture and temperature on LAI dynamics. For this purpose, we used three deep learning models, namely Artificial Neural Network (ANN), Long Short-Term Memory (LSTM), and Interpretable Multivariable (IMV)-LSTM, to simulate LAI in the Loess Plateau, only using soil moisture and temperature as inputs. Results indicated that our approach outperformed traditional models and effectively captured LAI variations across different vegetation types. The attention analysis revealed that soil moisture mainly influenced LAI in the arid northwest and temperature was the predominant effect in the humid southeast. Seasonally, soil moisture was crucial in spring and summer, notably in grasslands and croplands, whereas temperature dominated in autumn and winter. Notably, forests had the longest temperature-sensitive periods. As LAI increased, soil moisture became more influential, and at peak LAI, both factors exerted varying controls on different vegetation types. These findings demonstrated the strength of deep learning for simulating vegetation–climate interactions and provided insights into hydrothermal regulation mechanisms in semiarid regions. Full article

Grazing affects soil organic carbon (SOC) through plant removal, livestock trampling, and manure deposition. However, the impact of grazing on SOC is also influenced by multiple factors such as climate, soil properties, and management approaches. Despite extensive research, the mechanisms by which grazing intensity influences SOC density in grasslands remain incompletely understood. This study examines the effects of varying grazing intensities on SOC density (0–30 cm) dynamics in temperate grasslands of northern China using field surveys and experimental analyses in a typical steppe ecosystem of Inner Mongolia. Results show that moderate grazing (3.8 sheep units/ha/yr) led to substantial consumption of aboveground plant biomass. Relative to the ungrazed control (0 sheep units/ha/yr), aboveground plant biomass was reduced by 40.5%, 36.2%, and 50.6% in the years 2016, 2019, and 2020, respectively. Compensatory growth failed to fully offset biomass loss, and there were significant reductions in vegetation carbon storage and cover (p < 0.05). Reduced vegetation cover increased bare soil exposure and accelerated topsoil drying and erosion. This degradation promoted the downward migration of SOC from surface layers. Quantitative analysis revealed that moderate grazing significantly reduced surface soil (0–10 cm) organic carbon density by 13.4% compared to the ungrazed control while significantly increasing SOC density in the subsurface layer (10–30 cm). Increased precipitation could mitigate the SOC transfer and enhance overall SOC accumulation. However, it might negatively affect certain labile SOC fractions. Elucidating the mechanisms of SOC variation under different grazing intensities and precipitation regimes in semi-arid grasslands could improve our understanding of carbon dynamics in response to environmental stressors. These insights will aid in predicting how grazing systems influence grassland carbon cycling under global climate change. Full article

The Inner Mongolia Plateau (IMP), situated in the arid and semi-arid ecological transition zone of northern China, is particularly vulnerable to both climate change and human activities. Understanding the spatiotemporal vegetation dynamics and their driving forces is essential for regional ecological management. This study employs Sen’s slope estimation, BFAST analysis, residual trend method and Geodetector to analyze the spatial patterns of Normalized Difference Vegetation Index (NDVI) variability and distinguish between climatic and anthropogenic influences. Key findings include the following: (1) From 1982 to 2022, vegetation cover across the IMP exhibited a significant greening trend. Zonal analysis showed that this spatial heterogeneity was strongly regulated by regional hydrothermal conditions, with varied responses across land cover types and pronounced recovery observed in high-altitude areas. (2) In the western arid regions, vegetation trends were unstable, often marked by interruptions and reversals, contrasting with the sustained greening observed in the eastern zones. (3) Vegetation growth was primarily temperature-driven in the eastern forested areas, precipitation-driven in the central grasslands, and severely limited in the western deserts due to warming-induced drought. (4) Human activities exerted dual effects: significant positive residual trends were observed in the Hetao Plain and southern Horqin Sandy Land, while widespread negative residuals emerged across the southern deserts and central grasslands. (5) Vegetation change was driven by climate and human factors, with recovery mainly due to climate improvement and degradation linked to their combined impact. These findings highlight the interactive mechanisms of climate change and human disturbance in regulating terrestrial vegetation dynamics, offering insights for sustainable development and ecosystem education in climate-sensitive systems. Full article

Driven by climate change and stringent ecological conservation policies, arid and semi-arid pastoral areas face acute grassland degradation and forage–livestock imbalances. In Sunan County (Gansu Province, China), herders have increasingly turned to off-site grazing—leasing crop fields in adjacent oases during autumn and winter—to alleviate local grassland pressure and adapt their livelihoods. However, the interplay between the evolving land use system (L) and this emergent borrowed pasture system (B) remains under-explored. This study introduces a coupled analytical framework linking L and B. We employ multi-temporal remote sensing imagery (2018–2023) and official statistical data to derive land use dynamic degree (LUDD) metrics and 14 indicators for the borrowed pasture system. Through entropy weighting and a coupling coordination degree model (CCDM), we quantify subsystem performance, interaction intensity, and coordination over time. The results show that 2017 was a turning point in grassland–bare land dynamics: grassland trends shifted from positive to negative, whereas bare land trends turned from negative to positive; strong coupling but low early coordination (C > 0.95; D < 0.54) were present due to institutional lags, infrastructural gaps, and rising rental costs; resilient grassroots networks bolstered coordination during COVID-19 (D ≈ 0.78 in 2023); and institutional voids limited scalability, highlighting the need for integrated subsidy, insurance, and management frameworks. In addition, among those interviewed, 75% (15/20) observed significant grassland degradation before adopting off-site grazing, and 40% (8/20) perceived improvements afterward, indicating its potential role in ecological regulation under climate stress. By fusing remote sensing quantification with local stakeholder insights, this study advances social–ecological coupling theory and offers actionable guidance for optimizing cross-regional forage allocation and adaptive governance in arid pastoral zones. Full article

Inner Mongolia, a typical arid and semi-arid region in northern China, has undergone significant ecological transformation over the past two decades through climate shifts and large-scale ecological restoration projects. However, the relative contributions of climate and anthropogenic drivers to these ecological changes have not been sufficiently quantified. This study presents a comprehensive quantitative evaluation of the relative contributions of climate change, land conversion, and ecological management to changes in four critical ecosystem services—carbon sequestration, hydrological regulation, soil and water conservation, and windbreak and sand fixation—between 2001 and 2020. Using the residual trend method—a technique to separate climate-driven from human-induced effects—we further decomposed human influence into land conversion and management components. The results show that climate change was the primary driver, enhancing carbon sequestration and hydrological regulation but negatively impacting erosion control, with contributions often over 90%. In contrast, human activities had more spatially variable effects; while land conversion improved several services, it also heightened the vulnerability of sand fixation functions. The analysis further revealed ecosystem-type-specific responses, where grasslands and deserts responded better to management measures and forests and croplands showed greater improvements from land conversion. These findings offer crucial insights into the differentiated mechanisms and outcomes of ecological interventions, providing a scientific basis for optimizing restoration strategies and achieving sustainable ecosystem governance in climate-sensitive regions. Full article

Wind erosion poses a major threat to ecosystem stability and land productivity in arid and semi-arid regions. Accurate identification of its spatiotemporal dynamics and underlying driving mechanisms is a critical prerequisite for effective risk forecasting and targeted erosion control. This study applied the Revised Wind Erosion Equation (RWEQ) model to assess the spatial distribution, interannual variation, and seasonal dynamics of the Soil Wind Erosion Modulus (SWEM) across Inner Mongolia from 1990 to 2022. The GeoDetector model was further employed to quantify dominant drivers, key interactions, and high-risk zones via factor, interaction, and risk detection. The results showed that the average SWEM across the study period was 35.65 t·ha⁻¹·yr⁻¹ and showed a decreasing trend over time. However, localised increases were observed in the Horqin and Hulun Buir sandy lands and central grasslands. Wind erosion was most intense in spring (17.64 t·ha⁻¹·yr⁻¹) and weakest in summer (5.57 t·ha⁻¹·yr⁻¹). Gale days, NDVI, precipitation, and wind speed were identified as dominant drivers. Interaction detection revealed non-linear synergies between gale days and temperature (q = 0.40) and wind speed and temperature (q = 0.36), alongside a two-factor interaction between NDVI and precipitation (q = 0.19). Risk detection indicated that areas with gale days > 58, wind speed > 3.01 m/s, NDVI < 0.2, precipitation of 30.17–135.59 mm, and temperatures of 3.01–4.23 °C are highly erosion-prone. Management should prioritise these sensitive and intensifying areas by implementing site-specific strategies to enhance ecosystem resilience. Full article

Habitat quality functions as a critical metric for evaluating regional ecological health and the capacity of ecosystem services. Understanding its temporal dynamics is critical for advancing ecological civilization sustainability. Focusing on the Tacheng region, this study analyzes the evolution characteristics of land use based on long-term sequential land use data from 2003 to 2023. By coupling the PLUS and InVEST models, it predicts land use change trends under three distinct scenarios for the year 2033 and assesses the spatiotemporal evolution characteristics of habitat quality in the Tacheng region from 2003 to 2033. Findings reveal: (1) The land use types in the Tacheng region are dominated by grassland and unutilized land. During 2003–2023, the area of grassland and water showed a decreasing trend, while the areas of cultivated land and unutilized land significantly increased. Among them, NDVI was identified as the primary driver influencing the expansion of cultivated land, grassland, and unutilized land in the Tacheng region, addressing the gap in quantitative contribution analysis of specific drivers in arid region studies. (2) Overall, habitat quality in the Tacheng region significantly deteriorated during 2003–2023, with areas of high habitat quality continuously decreasing and transitioning to medium and relatively low habitat quality zones. This degradation is primarily attributed to the unidirectional conversion of grassland and water into cultivated land and unutilized land. (3) Under different scenario simulations, land use and habitat quality in the Tacheng region exhibit marked differences, with habitat quality showing significant improvement, particularly under the ecological protection scenario. Compared to existing research, this study pioneers the coupling of PLUS and InVEST models in the typical arid region of the Tacheng region, implements localization of model parameters, quantifies future evolution trends of land use and habitat quality under multiple scenarios, and reveals core drivers of land use change in arid regions. This work addresses the research gap regarding habitat quality simulation and driving mechanisms in the Central Asian arid-semiarid transition zone. Full article

The carbon metabolism activity of rhizosphere soil microbial communities is an essential indicator for assessing soil ecosystem health, as it directly affects soil nutrient cycling and the stability of organic matter. However, there is a limited understanding of the carbon metabolism characteristics of rhizosphere soil microorganisms in alfalfa (Medicago sativa L.) of different ages and their relationships with soil physicochemical properties. This study used Biolog EcoPlates to evaluate the carbon metabolism activity, functional diversity, and carbon-source utilization preferences of rhizosphere soil microbial communities in 5-, 7-, and 9-year-old alfalfa grasslands on the semi-arid Loess Plateau of western China. We analyzed the relationships between soil physicochemical properties and microbial carbon metabolism characteristics, considering their potential covariation. The results showed that, with the extension of alfalfa planting years, the rhizosphere soil water content decreased significantly, pH decreased slightly, but soil organic carbon, total nitrogen, and total phosphorus contents increased significantly. The rhizosphere soil microbial community of 9-year-old alfalfa exhibited the highest carbon metabolism activity, Shannon diversity index, and carbon-source utilization. Rhizosphere soil microorganisms from different-aged alfalfa showed significantly different preferences for carbon-source utilization, with microorganisms from 9-year-old alfalfa preferentially utilizing carbon sources such as N-acetyl-D-glucosamine, D-mannitol, and D-cellobiose. Redundancy analysis revealed that soil water content was among the most important factors influencing the carbon metabolism activity of rhizosphere soil microbial communities while acknowledging that the relative contributions of soil water content, organic carbon, and nitrogen require careful interpretation, owing to their potential collinearity. This study demonstrates that, under rain-fed conditions in the semi-arid Loess Plateau, the continuous cultivation of alfalfa for nine years led to a significant decrease in soil water content but enhanced the rhizosphere soil nutrient status and microbial carbon metabolism activity, with no apparent signs of microbial functional degradation, although soil water depletion was observed. These findings highlight the complex interactions among multiple soil factors in influencing microbial carbon metabolism, providing valuable microbiological insights for understanding the sustainability of alfalfa grasslands and a theoretical basis for the scientific management of alfalfa grasslands in the semi-arid Loess Plateau region. Future research should consider longer planting periods to determine the critical age of alfalfa grassland degradation under semi-arid conditions and its associated microbial mechanisms. Full article

The capacity to develop resilience to global change, such as nitrogen deposition, is an important topic for the management of key ecological functional zones. In this study, nitrogen enrichment (10 g N m⁻² yr⁻¹, NE) and control plots (0 g N m⁻² yr⁻¹, CL), each with eight replications, were randomly established in the Horqin Sandy Land to investigate how grassland carbon sequestration functions and herdsmen’s livelihoods respond to nitrogen deposition. In addition, three grazing scenarios (non-grazing, light grazing, and moderate grazing) were simulated to determine whether human activities affect the relationships (trade-off vs. synergistic) among forage supply, carbon sequestration, and windbreak and sand-fixing services under nitrogen deposition. The results showed that NE exhibited a significant increase in aboveground carbon storage (99.40 g C m⁻², 117.34%) and the shoot carbon/root carbon ratio (1.90) when compared to the CL (0.95) (p < 0.05). NE significantly decreased soil carbon storage ability, particularly in the 10–30 cm soil layer (p < 0.05). The reduction in soil carbon storage was offset by increases in plant carbon storage, resulting in a neutral effect of the NE treatment on the total grassland carbon storage (p > 0.05). The synergistic effects of NE on grassland forage supply and windbreak and sand-fixing functions were observed under a light grazing scenario, which balanced ecological safety and livelihood more effectively than the non-grazing and moderate grazing scenarios. These findings indicate that the structure of grassland carbon storage is influenced by nitrogen deposition and that light grazing would enhance ecosystem services and promote sustainable grassland development. Full article

Coccidioidomycosis (Valley fever), caused by Coccidioides spp., is a fungal infection endemic to semi-arid regions of the Americas. Despite 80 years of disease recognition in New Mexico, there is limited disease awareness. We incorporated clinical, epidemiological, and ecological datasets to summarize the knowledge of Valley fever in New Mexico. We analyzed 1541 human cases from 2006 to 2023. On average, 86 cases were reported each year (4.1 cases per 100,000 population per year). The highest levels of incidence were in southwestern New Mexico. American Indian or Alaska Natives in New Mexico had a 1.9 times higher incidence rate of coccidioidomycosis than White people, and among age groups, older populations in New Mexico had the highest incidence rates. We analyzed 300 soil samples near Las Cruces, New Mexico, for the presence of Coccidioides and reported the first known positive soil samples collected from the state, the majority of which were from grassland-dominated sites and from animal burrows. Sequence analyses in clinical specimens, wild animals, and soil samples confirmed that Coccidioides posadasii is the main causative species of coccidioidomycosis in New Mexico. Environmental surveillance validated that locally acquired infections could occur in, but are not limited to, Catron, Doña Ana, Sierra, and Socorro Counties. Full article

In this study, we investigate the impact of soil moisture at varying depths on the stability of Chinese ecosystems, with ecosystem stability assessed using the Enhanced Vegetation Index (EVI) and Gross Primary Productivity (GPP). A multi-perspective analysis is conducted across different climatic zones and land cover types. Sen’s Slope Estimation and the Mann–Kendall trend test, combined with linear regression and correlation analyses, are employed to analyze the long-term trends of EVI and GPP in different climatic zones and land cover types and to assess the effects of soil moisture changes on ecosystem stability. The research reveals the following findings: (1) On a national scale, both EVI and GPP exhibit positive growth trends, with more significant increases in humid areas and relatively slower growth in arid areas. In addition, EVI and GPP of different land cover types exhibit positive inter-annual variation trends, reflecting a gradual enhancement in ecosystem productivity. (2) Cluster analysis shows that EVI has strong spatial correlation, with a distribution pattern of low–low (L-L) clusters in the north and high–high (H-H) clusters in the south. L-H clusters are concentrated in the Huaihai, Southwest Rivers, and Pearl River basins, while H-L clusters are scattered along the eastern coast. The spatial correlation of GPP is mainly concentrated in the south and the northeast, with a distribution pattern of L-L in the northeast, L-H in the Yangtze River basin, and H-H in the south. H-L clusters are dispersed in the downstream area of the Yangtze River. Both EVI and GPP show a tendency for high-value aggregation in space, with high-value areas of EVI located in the south and low-value areas in the central and western regions. High-value areas of GPP are in the south, while low-value areas are in the northeast, particularly in the Yangtze River Delta. (3) The correlation between EVI, GPP, and soil moisture varies significantly across different climatic regions. Arid and semi-humid regions show significant correlations between specific soil moisture depths and EVI and GPP, while such correlations are not significant in humid regions. The EVI and GPP values of croplands and grasslands are significantly and negatively correlated with soil moisture at depths of 150–200 cm (SM4). Conversely, wetland GPP values increase significantly with increasing soil moisture. Other vegetation types do not show significant correlations with soil moisture. The results of this study provide an important basis for understanding the impact of climate change on ecosystem stability and offer scientific guidance for ecological protection and water resource management. Full article

Above-ground biomass (AGB) is a core indicator for evaluating grassland ecosystem health and carbon storage. Traditional ground-based AGB measurements are labor-intensive and ill suited for large-scale monitoring. This study addresses this gap by developing a Multilayer Perceptron (MLP) model integrating Landsat 9 OLI/TIRS imagery acquired on 15 August 2024, with ground data from 78 sampling points (62 training, 16 testing). Incorporating fourteen multi-source features (seven vegetation indices, e.g., Modified Vegetation Index (MVI) and Green Chlorophyll Index (CIg); four meteorological variables; three soil properties), all data were standardized via z-score normalization before training. The MLP model, optimized via six-fold cross-validation, achieved an R² of 0.765 and RMSE of 38.066 g/m², outperforming XGBoost (R² = 0.723, RMSE = 41.354 g/m²) with a statistically significant 5.8% accuracy improvement (p < 0.05). Spatial analysis revealed a north-to-south AGB gradient, strongly correlated with precipitation gradients (250–350 mm/year) and soil organic carbon (R = 0.428). These findings provide a robust framework for climate-adaptive grassland management and carbon assessment in semi-arid regions. Full article

Understanding vegetation phenology dynamics is essential for evaluating ecosystem responses to environmental changes. While previous studies have primarily focused on the correlation between vegetation phenology and climate variables, the integrated effects of meteorological factors, topography, and greenhouse gas (GHG) have often been overlooked. This study aims to analyze the spatiotemporal variations in grassland phenology on the southern slopes of the Qilian Mountains from 2002 to 2022, investigating the combined effects of these environmental factors. Our findings reveal significant spatial heterogeneity in vegetation phenology during the study period. Specifically, the start of the growing season (SOS), length of growing season (LOS), and end of the growing season (EOS) advanced, lengthened, and delayed by 0.35, 0.55, and 0.20 days per year, respectively. Climate factors were the primary drivers of phenological changes, with annual precipitation being the main determinant of SOS and LOS, while annual minimum temperature significantly influenced EOS. Topography and GHG had indirect effects on phenology, influencing both annual precipitation and temperature. Additionally, topography affected phenology through its impact on N₂O and CO₂ emissions. This study highlights the complex interactions between climate, topography, and GHG in shaping vegetation phenology, providing new insights into the driving mechanisms behind phenological changes in semi-arid grassland ecosystems. Full article

The extant Patagonian mara Dolichotis patagonum (Zimmermann, 1780) is a cursorial herbivorous rodent that is hare-like in appearance. Nowadays, it occurs in some ecoregions of Argentina (28 °S–50 °S) in lowland habitats, in semi-arid thorn-scrub, in open grasslands and in shrub–land steppe. In this research, we have studied a partially preserved skull (FCDPV-2758), referred to D. patagonum, from the Late Pleistocene (Sopas Formation) in northern Uruguay (Arapey Grande River, Salto Department). Body mass estimates and morphological analyses were performed including contemporary specimens of D. patagonum, the Chaco mara Dolichotis salinicola, and extinct dolichotine species. The body mass estimate using the regression method and geometric similarity suggested a 6–8 kg range for the studied specimen, which is consistent with D. patagonum (7–8 kg) and notably greater than D. salinicola (1–2.3 kg). A comparative analysis, including the extinct D. platycephala and material previously referred to D. major from southwestern Uruguay, suggests that the studied specimen falls within the variation of D. patagonum, differing in part from D. chapalmalense and more clearly from D. salinicola, the extinct D. minor and Prodolichotis prisca. The implications of the wider geographic distributions of the living Patagonian mara at these latitudes in the Late Pleistocene in South America, and the paleoenvironmental significance are discussed. Full article