Search Results (307)

The Maowusu Desert is still suffering from serious ecological and environmental security issues such as wind erosion and desertification, influenced by both natural and human factors. The amendment of aeolian sandy soil with soft rock material presents an effective erosion control strategy, leveraging the complementary structural and compositional properties of both materials to enhance soil stability and rehabilitate degraded environments. However, there are few studies that investigate the effect of soil surface electrochemical properties and particle interaction forces on the structural stability of compound soils with soft rock and sandy soil. This decade-long field study quantified the electrochemical properties and interparticle forces and their synergistic effects on structural stability across five soft rock-to-aeolian sandy soil blend volume ratios (0:1, 1:5, 1:2, 1:1, 1:0) within the 0–30 cm soil profile. The results showed that the soil organic matter (SOM), specific surface area (SSA), and cation exchange capacity (CEC) significantly increased with the incorporation of soft rock material. For five different proportions, with the addition of soft rock and the extension of planting years, the content of SOM increased from 5.65 g·kg⁻¹ to 11.36 g·kg⁻¹, the CEC varied from 4.68 cmol kg⁻¹ to 17.91 cmol kg⁻¹, while the σ₀ importantly decreased from 1.8 to 0.47 c m⁻² (p < 0.05). For the interaction force at 2.4 nm between soil particles, the absolute value of van der Waals attractive force increased from 0.10 atm to 0.38 atm, and the net force decreased from 0.09 atm to −0.30 atm after the incorporation ratios of soft rock from 0:1 to 1:1. There was a significant negative correlation between the resultant net force between the particles of compound soil and the SSA and CEC. These results indicate that the addition of soft rock material positively improves the surface electrochemical properties and internal forces between aeolian sandy soil particles, further enhancing its structural stability. This study establishes a foundational theoretical framework for advancing our mechanistic understanding of aeolian sand stabilization and ecosystem rehabilitation in the Mu Us Desert. Full article

Land desertification represents a significant and sensitive global ecological issue. In the Inner Mongolia region of China, soil desertification and salinization are widespread, resulting from the combined effects of extreme drought conditions and human activities. Using Gaofen 5B AHSI imagery as our data source, we collected spectral data for seven distinct land cover types: lush vegetation, yellow sand, white sand, saline soil, saline shell, saline soil with saline vegetation, and sandy soil. We applied Particle Swarm Optimization (PSO) to fine-tune the Wavelet Packet (WP) decomposition levels, thresholds, and wavelet basis function, ensuring optimal spectral decomposition and reconstruction. Subsequently, PSO was deployed to optimize key hyperparameters of the Random Forest algorithm and compare its performance with the ResNet-Transformer model. Our results indicate that PSO effectively automates the search for optimal WP decomposition parameters, preserving essential spectral information while efficiently reducing high-frequency spectral noise. The Genetic Algorithm (GA) was also found to be effective in extracting feature bands relevant to land desertification, which enhances the classification accuracy of the model. Among all the models, integrating wavelet packet denoising, genetic algorithm feature selection, the first-order differential (FD), and the hybrid architecture of the ResNet-Transformer, the WP-GA-FD-ResNet-Transformer model achieved the highest accuracy in extracting soil sandification and salinization, with Kappa coefficients and validation set accuracies of 0.9746 and 97.82%, respectively. This study contributes to the field by advancing hyperspectral desertification monitoring techniques and suggests that the approach could be valuable for broader ecological conservation and land management efforts. Full article

In ecological restoration of arid/semi-arid sandy lands, micro-topographic variations and artificial shrub arrangement synergistically drive vegetation recovery and soil quality improvement. As a typical fragile ecosystem in northern China, the Mu Us Sandy Land has long suffered wind erosion, desertification, soil infertility, and vegetation degradation, demanding precise vegetation configuration for ecological rehabilitation. This study analyzed soil nutrients, plant diversity, and their correlations under various micro-topographic conditions across different types of artificial shrub plantations in the Mu Us Sandy Land. Employing one-way and two-way ANOVA, we compared the significant differences in soil nutrients and plant diversity indices among different micro-topographic conditions and shrub species. Additionally, redundancy analysis (RDA) was conducted to explore the direct and indirect relationships between micro-topography, shrub species, soil nutrients, and plant diversity. The results show the following: 1. The interdune depressions have the highest plant diversity and optimal soil nutrients, with relatively suitable pH values; the windward slopes and slope tops, due to severe wind erosion, have poor soil nutrients, high pH values, and the lowest plant diversity. Both micro-topography and vegetation can significantly affect soil nutrients and plant diversity (p < 0.05), and vegetation has a greater impact on soil nutrients. 2. The correlation between surface soil nutrients and plant diversity is the strongest, and the correlation weakens with increasing soil depth; under different micro-topographic conditions, the influence of soil nutrients on plant diversity varies. 3. In sandy land ecological restoration, a “vegetation type + terrain matching” strategy should be implemented, combining the characteristics of micro-topography and the ecological functions of shrubs for precise configuration, such as planting Corethrodendron fruticosum on windward slopes and slope tops to rapidly replenish nutrients, promoting Salix psammophila and mixed plantation in interdune depressions and leeward slopes to accumulate organic matter, and prioritizing Amorpha fruticosa in areas requiring soil pH adjustment. This study provides a scientific basis and management insights for the ecological restoration and vegetation configuration of the Mu Us Sandy Land. Full article

Monoculture and legume–grass mixed cropping are the two most common planting methods, with mixed cropping generally demonstrating higher hay yield and superior nutritional quality compared to monoculture. However, research on legume–grass mixed cropping for establishing cultivated pastures in typical sand-fixing vegetation areas of the Mu Us Sandy Land remains scarce. These knowledge gaps have hindered the synergistic integration of forage production and ecological restoration in the region. This study conducted mixed cropping trials in the sand-fixing vegetation zone of the Mu Us Sandy Land using Dahurian wildrye (Elymus dahuricus), Mongolian wheatgrass (Agropyron mongolicum), and Standing milkvetch (Astragalus adsurgens) to investigate the effects of species combinations and planting ratios on forage productivity and nutritional quality, aiming to determine the optimal planting strategy. Results showed that in the first establishment year, the yield of all mixed cropping systems significantly exceeded that of monocultured Dahurian wildrye and Mongolian wheatgrass. All mixed cropping combinations exhibited land equivalent ratios (LER) and relative yield totals (RYT) below 1, indicating varying degrees of interspecific competition during the first year, with grass species generally demonstrating stronger competitive abilities than legumes. Mixed-cropped forages showed higher crude protein, crude fat, and crude ash content compared to monocultures, alongside lower neutral detergent fiber (NDF) and acid detergent fiber (ADF) levels, suggesting improved relative feed value (RFV). Among the combinations, E₅A₅ and E₆A₄ (5:5 and 6:4 ratio of Dahurian wildrye to Standing milkvetch) achieved higher RFV, with RFV gradually declining as the legume proportion decreased. In conclusion, both monoculture and legume–grass mixed cropping are viable in the Mu Us Sandy Land’s sand-fixing vegetation areas and the E₅A₅ combination (5:5 ratio of Dahurian wildrye to Standing milkvetch) as having the highest overall score, demonstrating that this mixed cropping ratio optimally balances yield and nutritional quality, making it the recommended planting protocol for the region. This mixed cropping system offers a theoretical foundation for efficiently establishing artificial pastures in the Mu Us Sandy Land, supporting regional pastoral industry development and desertification mitigation. Full article

Artemisia absinthium L. contributes to ecological stabilization in arid regions through its deep root system for sand fixation and soil microenvironment modulation, thereby effectively mitigating desertification. Total terpenoids have been extracted from A. absinthium (AATP) and found to have antioxidant and anti-inflammatory activities. Terpenoids are a class of natural products derived from methyl hydroxypropanoic acid, for which their structural units consist of multiple isoprene (C5) units. They are one of the largest and most structurally diverse classes of natural compounds. However, there are still large gaps in knowledge regarding their exact biological activities and effects. Atherosclerosis (AS) is a prevalent cardiovascular disease marked by the chronic inflammation of the vascular system, and lipid metabolism plays a key role in its pathogenesis. This study determined the extraction and purification processes of AATP through single-factor experiments and response surface optimization methods. The purity of AATP was increased from 20.85% ± 0.94 before purification to 52.21% ± 0.75, which is 2.5 times higher than before purification. Studies have shown that the total terpenoids of A. absinthium significantly reduced four indices of serum lipids in atherosclerosis (AS) rats, thereby promoting lipid metabolism, inhibiting inflammatory processes, and hindering aortic wall thickening and hepatic fat accumulation. It is known from network pharmacology studies that AATP regulates the Janus kinase/signal transducer (JAK/STAT) signaling axis. Molecular docking studies have indicated that the active component of AATP effectively binds to Janus kinase (JAK2) and signal transducer (STAT3) target proteins. The results indicate that AATP can inhibit the release of pro-inflammatory mediators (such as reactive oxygen species (ROS)) in LPS-induced RAW264.7 macrophages. It also inhibits the M1 polarization of RAW264.7 macrophages. Protein immunoblotting analysis revealed that it significantly reduces the phosphorylation levels of Janus kinase (JAK2) and the signal transducer and activator of transcription 3 (STAT3). Research indicates that the active components in A. absinthium may exert anti-atherosclerotic effects by regulating lipid metabolism and inhibiting inflammatory responses. It holds potential value for development as a functional food or drug for the prevention and treatment of atherosclerosis. Full article

Guangxi is among China’s regions most severely affected by karst rocky desertification (KRD). Over the past two decades, global climate change and human activities have jointly led to significant changes in the extent and intensity of KRD in Guangxi. Given this context, it is crucial to comprehensively analyze the spatiotemporal evolution of KRD in Guangxi and its driving forces. This study proposed a novel three-dimensional feature space model for monitoring KRD in Guangxi. We then applied transition matrices, dynamic degree indices, and landscape metrics to analyze the spatiotemporal evolution of KRD. We also proposed a Spatiotemporal Interaction Intensity Index (STII) to quantify mutual influences among KRD patches. Finally, we used GeoDetector to analyze the driving factors of KRD. The results indicate the following: (1) The three-dimensional model showed high applicability for large-scale KRD monitoring, with an overall accuracy of 92.86%. (2) KRD in Guangxi exhibited an overall recovery–deterioration–recovery trend from 2000 to 2023. The main recovery phases were 2005–2015 and 2020–2023. During these phases, both severe and moderate KRD showed strong signals of recovery, including significant declines in area, number of patches, and Landscape Shape Index, along with persistently low STII values. In contrast, from 2015 to 2020, KRD predominantly deteriorated, primarily characterized by transitions from no KRD to potential KRD and from potential KRD to light KRD. (3) For severe KRD patches, the intensity of interaction required from neighboring patches to promote recovery exceeded that which led to deterioration, indicating the difficulty of reversing severe KRD. (4) Slope, land use, and elevation were the main drivers of KRD in Guangxi from 2000 to 2023. Erosive rainfall exhibited a higher explanatory power for KRD than average precipitation. Two-factor interactions significantly enhanced the driving forces of KRD. These findings provide a scientific basis for KRD management. Full article

Agricultural water resource management is increasingly challenged by climate variability, land degradation, and socio-economic pressures, particularly in the Mediterranean region. This study, conducted in 2023–2024 within the REACT4MED project (PRIMA initiative), addresses sustainable water use through a comparative analysis of organic and conventional farms in the Stornara and Tara area (Puglia, Italy). The research aimed to identify critical indicators for sustainable water management and develop ecosystem restoration strategies that can be replicated across similar Mediterranean agro-ecosystems. An interdisciplinary, participatory approach was adopted, combining technical analyses and stakeholder engagement through three workshops involving 30 participants from diverse sectors. Fieldwork and laboratory assessments included soil sampling and analysis of parameters such as pH, electrical conductivity, soil organic carbon, nutrients, and salinity. Cartographic studies of vegetation, land use, and pedological characterization supplemented the dataset. The key challenges identified were water loss in distribution systems, seawater intrusion, water pumping from unauthorized wells, and inadequate public policies. Soil quality was significantly influenced by salt stress, hence affecting crop productivity, while socio-economic factors affected farm income. Restoration strategies emphasized the need for water-efficient irrigation, less water-intensive crops, and green vegetation in infrastructure channels while incorporating also the native flora. Enhancing plant biodiversity through weed management in drainage channels proved beneficial for pathogen control. Proposed socio-economic measures include increased inclusion of women and youth in agricultural management activities. Integrated technical and participatory approaches are essential for effective water resource governance in Mediterranean agriculture. This study offers scalable, context-specific indicators and solutions for sustainable land and water management in the face of ongoing desertification and climate stress. 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

Understanding the processes of organic nitrogen (N) mineralization to ammonium (NH₄⁺) and NH₄⁺ oxidation to nitrate (NO₃⁻), which, together, supply soil inorganic N (the sum of NH₄⁺ and NO₃⁻), is of great significance for guiding the restoration of degraded ecosystems. This study used space-for-time substitution to investigate the dynamic changes in the rates of organic N mineralization (M_Norg) and nitrification (O_NH4) in soil at different vegetation restoration stages. Soil samples were collected from grassland (3–5 years), shrub-grassland (7–8 years), early-stage shrubland (15–20 years), late-stage shrubland (30–35 years), early-stage woodland (45–50 years), and late-stage woodland (70–80 years) in the subtropical karst region of China during the dry (December) and rainy (July) seasons. The M_Norg and O_NH4 were determined using the ¹⁵N labeling technique. The soil microbial community was determined using the phospholipid fatty acid method. Soil organic carbon (SOC), total nitrogen (TN), NH₄⁺, NO₃⁻, and inorganic N contents, as well as the soil moisture content (SMC) were also measured. Our results showed that SOC and TN contents, and the SMC, as well as microbial community abundances increased markedly from grassland to the late-stage shrubland. Especially in the late-stage shrubland, the abundance of the total microbial community, bacteria, fungi, actinomycetes, and AMF in soil was significantly higher than other restoration stages. These results indicate that vegetation restoration significantly increased soil nutrient content and microbial community abundance. From grassland to the late-stage shrubland, the soil NH₄⁺, NO₃⁻, and inorganic N contents increased significantly, and the NH₄⁺:NO₃⁻ ratios changed from greater than 1 to less than 1, indicating that vegetation restoration significantly influenced soil inorganic N content and composition. As restoration progressed, the M_Norg and O_NH4 increased significantly, from 0.04 to 3.01 mg N kg⁻¹ d⁻¹ and 0.35 to 2.48 mg N kg⁻¹ d⁻¹ in the dry season, and from 3.26 to 7.20 mg N kg⁻¹ d⁻¹ and 1.47 to 10.7 mg N kg⁻¹ d⁻¹ in the rainy season. At the same vegetation restoration stage, the M_Norg and O_NH4 in the rainy season were markedly higher than those in the dry season. These results indicate that vegetation restoration and seasonal variations could significantly influence M_Norg and O_NH4. Correlation analysis showed that the increase in M_Norg during vegetation restoration was mainly attributed to the increase in SOC and TN contents, as well as the total microbial community, bacterial, fungal, actinomycetes, and AMF abundances, and that the increase in O_NH4 was mainly attributed to the increase in M_Norg and the decrease in the F: B ratio. Moreover, the M_Norg and O_NH4 showed a strong positive correlation with inorganic N content. This study clarifies that vegetation restoration in karst regions could significantly increase M_Norg and O_NH4 through enhancing soil carbon and N contents, as well as microbial community abundances, thereby increasing the available soil N supply, which could provide a theoretical basis for soil fertility regulation in future rocky desertification management. Full article

The Upper Yellow River Region plays an irreplaceable role in water conservation and ecological protection in China. Due to both natural and human-induced factors, this area has experienced significant grassland deterioration, land desertification, and salinization. Consequently, evaluating the region’s environmental status plays a vital role in promoting ecological conservation and sustainable growth in the Upper Yellow River Basin. This study constructed an ecological index based on remote-sensing data and examined its spatiotemporal changes from 1990 to 2020. Future ecological dynamics were predicted using the Hurst index, while key influencing factors were examined through an optimal-parameter-based GeoDetector and geographically weighted regression. The findings revealed the following: (1) RSEI values were generally lower in the north and increased progressively toward the south, indicating a notable spatial disparity. (2) Ecological conditions remained largely stable, with notable improvements observed in 65.47% of the study area. (3) It was anticipated that 52.76% of the region would continue to improve, whereas 24% is expected to experience further degradation. (4) Precipitation, temperature, elevation, and land cover were major factors contributing to ecological variation. Their impact on ecological quality varies across different geographic locations. These research findings provided references for the sustainable development and ecological civilization construction of the Upper Yellow River Region. Full article

Climate change poses substantial threats to natural ecosystems and human livelihoods, particularly in coastal regions, by intensifying coastal erosion. This process leads to land loss, infrastructure damage, and habitat destruction while amplifying challenges such as sea-level rise, flooding, desertification, and salinization. In Vietnam’s Red River Delta (RRD), the dynamic interplay between erosion and accretion presents a highly complex challenge, necessitating effective risk assessment and management to safeguard communities and resources. Using the principles of natural disaster risk assessment and comprehensive analysis, this study develops a coastal erosion risk assessment framework incorporating hazard, exposure, and vulnerability dimensions. The framework integrates 17 indicators, including human activities, socioeconomic factors, shoreline type, and vegetation cover, with indicator weights determined through expert evaluation and the analytic hierarchy process. The application of this framework reveals that coastal erosion risk in the RRD is relatively high, with greater risk concentrated in the central and northern segments of the coastline compared to the flanking areas. This framework offers valuable insights for coastal erosion prevention, mitigation strategies, and the optimization of coastal spatial planning. The application of coastal erosion risk assessment methods provides a relatively complete foundation for developing comprehensive prevention and adaptation solutions in the future. Through the system of parameters and corresponding weights, it provides an overview of potential responses to future impacts while identifying current high-risk zones specifically and accurately, thereby assessing the importance of each parameter on that impact. Based on specific analysis of assessment results, a reasonable resource use and management policy can be developed to minimize related natural disasters. Therefore, two main groups of solutions proposed under the “Protection—Adaptation” strategy are proposed to prevent natural disasters, minimize risks and sustainably develop the coastal area of the RRD. Full article

Accurate prediction of the Normalized Difference Vegetation Index (NDVI) is crucial for regional ecological management and precision decision-making. Existing methodologies often rely on smoothed NDVI data as ground truth, overlooking uncertainties inherent in data acquisition and processing. Fuzzy time series (FTS) prediction models based on the Fuzzy C-Means (FCM) clustering algorithm address some of these uncertainties by enabling soft partitioning through membership functions. However, the method remains limited by its reliance on expert experience in setting fuzzy parameters, which introduces uncertainty in the definition of fuzzy intervals and negatively affects prediction performance. To overcome these limitations, this study enhances the interval type-2 fuzzy clustering time series (IT2-FCM-FTS) model by developing a pixel-level time series forecasting framework, optimizing fuzzy interval divisions, and extending the model from unidimensional to spatial time series forecasting. Experimental results from 2021 to 2023 demonstrate that the proposed model outperforms both the Autoregressive Integrated Moving Average (ARIMA) and conventional FCM-FTS models, achieving the lowest RMSE (0.0624), MAE (0.0437), and SEM (0.000209) in 2021. Predictive analysis indicates a general ecological improvement in the Aksu region (Xinjiang, China), with persistent growth areas comprising 61.12% of the total and persistent decline areas accounting for 2.6%. In conclusion, this study presents an improved fuzzy model for NDVI time series prediction, providing valuable insights into regional desertification prevention and ecological strategy formulation. Full article

Land Degradation Neutrality (LDN) is an ambitious initiative by the United Nations Convention to Combat Desertification (UNCCD) to tackle land degradation. Inspired by the “no net loss” concept, LDN seeks to counterbalance unavoidable land degradation—primarily driven by food systems—through targeted regenerative actions at multiple scales—such as regenerative agriculture or grazing practices that simultaneously support production and preserve land fertility. The objective is to ensure that degradation does not surpass the 2015 baseline. While the UNCCD’s Science–Policy Interface provides guidance and the LDN Target Setting Programme has led many countries to define baselines using agreed indicators (soil organic carbon, land use change, and primary productivity), concrete intervention strategies often remain poorly defined. Moreover, the voluntary nature of LDN has limited its effectiveness. A key shortcoming is the lack of integrated planning. LDN should function as a “Plan of Plans”—a coordinating framework to align policies across sectors and scales, reconciling conflicting agendas in areas such as food, energy, and water. To this end, we advocate for a systemic approach to uncover synergies, manage trade-offs, and guide decision-making in complex socio-ecological landscapes. Land degradation is intricately linked to issues such as food insecurity, land acquisitions, and transboundary water stress. Although LDN is implemented at the national level, its success also depends on accounting for global dynamics—particularly “LDN leaks”, where land degradation is outsourced through international trade in food and raw materials. In an increasingly complex world shaped by globalization, resource depletion, and unpredictable system dynamics, effective responses demand an integrated socio-ecological management approach. LDN is not simply a strategy to address desertification. It offers a comprehensive framework for sustainable resource management, enabling the balancing of trade-offs and the promotion of long-term resilience. Full article

It is crucial to clarify the relationship between ecological industry development and ecological civilization construction, as well as their driving forces, to promote high-quality local development. The ecological environment of the karst region is fragile, and it faces a contradiction between ecological preservation and economic advancement. Coordinating the relationship between economic development and ecological protection is crucial for achieving sustainable development in rural karst regions. This study identified karst characteristics in Guizhou province, China, by constructing an index system for ecological industry development and civilization construction. It employed the entropy weight method to calculate a comprehensive score and utilized a coupling coordination model to analyze interactions and symbiotic coordination. Finally, a linear regression analysis model was employed to analyze the impact of ecological industrial development on the construction of ecological civilization. The results indicate the following: (1) The ecological industry and ecological civilization construction levels exhibited a relatively stable growth trajectory across three research areas from 2011 to 2021, with the ecological civilization construction index outperforming the ecological industry development index. (2) The correlation analysis indicated a relationship between the two indices in the research areas, and the divergence trend among the three research areas rose in a uniform direction, indicating a strong positive correlation between the two indices. From the perspective of the coupling degree (C), the degree of coupling between ecological industry and ecological civilization construction in the three research areas exceeded 0.9, indicating a high level of coordination. This suggests that ecological civilization construction and ecological industry in these research areas are effectively coordinated and exist in a state of harmonious co-promotion. There were differences from the coupling coordination degree (D) perspective, but they increased in the three research areas. (3) The regression analysis results indicate that the per capita agricultural output value, per capita forestry output value, per capita forage industry output value, industrial solid waste utilization rate, energy consumption per unit of GDP, tourism income, rocky desertification level, and proportion of the labor force population with a high school education or higher significantly contribute to the development of ecological civilization. The per capita forestry output value greatly advances ecological civilization, significantly enhancing ecological culture and security. The coefficients are 0.0354 and 0.0393, respectively, indicating that a 1% rise in the per capita forestry output value results in increases of 0.0354% and 0.0393% in the ecological culture and security indices. Full article

Rocky desertification is a significant ecological issue in the karst regions of Southwest China, severely affecting both the environment and local livelihoods. Accurate extraction and prediction of rocky desertification are critical for its prevention and control, playing a crucial role in advancing ecological civilization and sustainable land management. This study focuses on the Pearl River source area in Yunnan, analyzing dynamic changes in rocky desertification over eight periods from 1990 to 2023, using long-term remote sensing data and multi-source reference data. It also predicts the intensity and trends of rocky desertification for the next decade. The results indicate that: (1) Rocky desertification is widespread and severe in the study area; however, its further intensification has been effectively mitigated through long-term governance efforts. By 2023, an area of 14,896.19 km² of rocky desertification has been mitigated to varying extents, accounting for 55.77% of the total watershed area. Trend analysis suggests that, under current management conditions, rocky desertification will continue to decline and improve over time. (2) The overall development of rocky desertification in the basin is showing a positive trend, with deep-level rocky desertification gradually transitioning to shallow-level rocky desertification. In future scenarios, the extent of rocky desertification will continue to decrease. (3) The approach of integrating the Google Earth Engine with traditional remote sensing platforms for extracting rocky desertification information has proven to be both fast and efficient. This method retains high extraction accuracy while alleviating the data burden typically associated with exclusive use of local platforms, thereby enhancing processing efficiency. Full article