Search Results (74)

Forest fires in Yanyuan County, a typical dry-hot valley region, pose serious threats to ecological security and public safety. Conventional fire warning methods rely heavily on manual surveys, making them time-consuming, labor-intensive, and prone to missing the critical window for effective intervention. This paper presents a 3D visualization decision support system for fire prevention, developed on a Web-GIS platform using the Cesium engine. The system integrates multi-source data, including a 12.5 m DEM, remote sensing imagery, and real-time video streams. It employs a YOLO11 model for automated fire and smoke detection, achieving a precision of 82.4%. Compared to conventional 2D systems, the platform enhances emergency response speed by 37% while significantly improving spatial awareness and operational coordination. This cross-platform tool facilitates sustainable forest management through efficient resource allocation and real-time monitoring, offering a scalable and practical solution for fire prevention in complex terrains. Full article

Unmanned Aerial Vehicle (UAV) photogrammetry technique offers significant potential for generating highly detailed digital surface models (DSM) of gullies. However, different flight schemes can considerably influence measurement accuracy. The objectives were (i) to evaluate the influences of flight altitude, photo overlap, Ground Control Points (GCPs), and other environmental factors on the accuracy of the UAV-derived DSMs and (ii) to analyze the main factors affecting the accuracy of UAV gully monitoring and explore flight schemes that balance accuracy and efficiency. The results indicated that DSM accuracy improved markedly as the number of GCPs increased from 0 to 3, with consideration given to both horizontal and vertical distribution. However, further increases in the number of GCPs did not lead to significant improvements. The accuracy of DSMs increased with a decrease in the flight altitude, but was not substantially affected by photo overlap when it exceeded 50%/40% The accuracy of DSM was significantly reduced by shadows, and flight altitude rather than slope gradient was identified as the key factor leading to high-error checkpoints (error > 0.1 m). The proportion of point clouds penetrating tree canopies decreased when the flight altitude was 150 m or higher, which could help reduce the influence of vegetation on the accuracy of DSMs. In general, with a reasonable spatial distribution of GCPs, flight altitude is the primary factor affecting monitoring accuracy. However, when balancing accuracy and efficiency, the optimal flight scheme was determined to be a flight altitude of 70 m, photo overlap of 80%/70%, and nine GCPs. Full article

Investigating the properties of red clay under the action of dry–wet cycles is crucial for mitigating geological disasters and promoting the sustainable development of geotechnical engineering infrastructure. In this paper, red clay from the Yuanmou dry-hot valley in Yunnan Province was selected as the research subject. The investigation focused on examining the effects of dry–wet cycles on its permeability and shear strength. Samples were prepared by controlling the initial moisture content (8%, 11%, 14%, 17%, and 20% for permeability tests; 11%, 14%, and 17% for strength tests) and initial dry density (1.65 g/cm³, 1.70 g/cm³, 1.75 g/cm³, and 1.80 g/cm³). We conducted variable-head permeability tests and direct shear tests on samples undergoing 1–5 dry–wet cycles. The results demonstrated that (1) the saturated moisture content decreased with the increasing number of dry–wet cycles, with the first cycle showing the most significant decrease (decreasing by approximately 15–25% depending on initial conditions). (2) The permeability coefficient decreased continuously with the number of cycles, exhibiting a transition behavior around the optimum moisture content (14%). Samples with lower initial moisture content (8–14%) showed higher permeability reduction (up to 40% decrease) compared to those with higher initial moisture content (14–20%). (3) The dry–wet cycles lead to a significant attenuation of the shear strength, and the first cycle has the largest reduction. The shear strength parameters of red clay exhibit distinct attenuation patterns. The cohesion decreased exponentially with the number of cycles (total attenuation ≈55–60%), and the internal friction angle decreased linearly (total attenuation ≈20–25%). The total attenuation of cohesion was much larger than the internal friction angle. (4) The degradation mechanism is essentially a multi-scale coupling process of cementation dissolution, pore collapse, and fracture expansion of red clay internal structure. These findings provide critical insights for sustainable engineering design and disaster prevention in regions with similar soil conditions, contributing to the resilience and longevity of infrastructure under changing climatic conditions. Full article

Spatial heterogeneity of soil nutrients in the dry-hot valleys of Southwest China is strongly shaped by topography, yet quantitative evidence remains limited. In this study, we assessed the effects of slope gradient, slope position, and slope aspect on nine soil nutrient indicators in a representative mango orchard in Yanbian County, Panzhihua City, China. Stratified soil samples were collected from two depths (0–10 cm and 10–20 cm) across contrasting topographic conditions. The results showed that: (1) total nitrogen (TN) and organic matter (OM) declined with increasing slope gradient, while available phosphorus (AP) accumulated in the 10–20 cm layer of gentle slopes (0°, 20°). The N:P ratio peaked at 0° slope (0–10 cm), whereas the C:N ratio peaked at 80° slope (10–20 cm). (2) Soil OM and available potassium (AK) increased with higher slope position, while total phosphorus (TP) decreased. TN and AP reached maximum values on hillslope terraces, and total potassium (TK) was highest on piedmont alluvial fans. Summit platforms exhibited the highest C:N, C:P, and N:P ratios (0–10 cm). (3) Sunny slopes had higher TN, OM, and TP, whereas shady slopes had higher TK and AK. The C:N and C:P ratios (0–10 cm) were greater on sunny slopes, while N:P was higher on shady slopes. Principal component analysis indicated that slope gradient, position, and aspect accounted for 60.6%, 68.2%, and 59.6% of the variance in soil nutrients, respectively. Overall, this study highlights the quantitative influence of topography on soil nutrient distribution, providing a scientific basis for more site specific nutrient management in mango orchards of dry-hot valley regions. Full article

The Hengduan Mountains, a global biodiversity hotspot, harbor numerous endemic plant species shaped by complex topography and microclimatic variation. However, increasing habitat fragmentation due to human activities threatens narrowly distributed species such as Cycas panzhihuaensis. To investigate its habitat suitability and inform conservation, we applied the MaxEnt model, Geodetector, and Zonation to predict potential distribution, identify key environmental drivers, and delineate priority conservation areas. Our results show that only 18.36% of the region constitutes suitable and highly fragmented habitat, primarily concentrated along the dry–hot valleys of the Jinsha and Yalong Rivers, and it is shrinking while shifting southward and southeastward under climate change. Elevation emerged as the dominant driver (q = 0.45), with strong interaction effects among topographic, climatic, soil, and anthropogenic factors, highlighting the role of environmental synergies in shaping habitat heterogeneity. Priority conservation areas covered 32% of suitable habitat and overlapped only 6.17% with existing protected areas, indicating a spatial conservation gap. These findings emphasize the need to incorporate microhabitat heterogeneity and environmental interactions in conservation planning and support the adoption of micro-reserve strategies to complement existing reserves. Our study provides a practical framework for protecting vulnerable montane species and offers insights into plant distribution dynamics in topographically complex regions. Full article

The vegetation cover in the Red River Basin (RRB) has undergone considerable changes over the past 20 years. Identifying vegetation cover and its transboundary differences is crucial for assessing the ecological health of the region. This study utilized normalized difference vegetation index (NDVI) data (2000–2023) to analyze the spatiotemporal dynamics of fractional vegetation cover (FVC) and its transboundary differences within the RRB. The results revealed the following: (1) From 2000 to 2023, overall FVC in the basin increased, with a mean value of 0.64, indicating favorable vegetation conditions. (2) In terms of spatial distribution, the RRB in China (RRBC) generally exhibited higher FVC in the west and lower FVC in the east, whereas the RRB in Vietnam and Laos (RRBVL) exhibited higher FVC in the east and lower FVC in the west. Regarding spatiotemporal changes, in RRBC, the changes were primarily characterized by both non-significant improvement (56.01%) and extremely significant improvement (21.45%). Conversely, RRBVL exhibited both areas of extremely significant improvement (25.4%) and areas of extremely significant degradation (18%). (3) Anthropogenic activities exerted a stronger influence than precipitation on both spatiotemporal changes and transboundary differences in FVC. In conclusion, an overall increase in FVC is observed throughout the RRB, with notable transboundary variations. Full article

To explore the mechanisms by which water, fertilizers, and dissolved oxygen affect the physiological growth and yield quality of custard apple, this study aims to optimize water–fertilizer–oxygen coupling regulation schemes for custard apple in dry hot valley regions through a multi-level fuzzy evaluation method, thereby addressing issues such as soil compaction and reduced aeration caused by long-term water and fertilizer drip irrigation. The experiment was conducted on custard apple in a dry, hot valley area, employing orthogonal and quadratic regression-orthogonal designs. Three factors were set at multiple levels: irrigation amount (60–100% ETc), fertilization rate (1500–1900 kg·ha⁻¹), and dissolved oxygen concentration (6–10 mg·L⁻¹). Custard apple development, production, and attributes were assessed. The two-year trial from 2023 to 2024 demonstrated that the new shoots, leaf area, and net photosynthetic rate of plants treated with W3F2O1 (100% ETc, 1700 kg·ha⁻¹ fertilization rate, and high oxygen 6 mg·L⁻¹) and W3F3O2 (100% ETC, 1500 kg·ha⁻¹ fertilization rate, and high oxygen 8 mg·L⁻¹) were significantly superior to those of W1F1O1 (60% ETc, 1900 kg·ha⁻¹ fertilization rate, and high oxygen 6 mg·L⁻¹), with a single-plant yield of 10.31 kg, and increases in diameter and length of 31.6% and 27.6%, respectively (p < 0.05); quality indicators were also optimal under W3F3O2 (100% ETC, 1500 kg·ha⁻¹ fertilization rate, and high oxygen 8 mg·L⁻¹) treatment, with soluble sugar and vitamin C levels increasing by 17.3% and 29.9%, respectively, compared to the control. Using a multi-level fuzzy evaluation to comprehensively evaluate the water–fertilizer–oxygen coupling, the comprehensive productivity of custard apples was significantly improved by optimizing the root zone microenvironment. It is recommended that dry hot valleys adopt an optimized range of 82.5–100% ETc irrigation, 1650–1847.86 kg·ha⁻¹ fertilization, and 7.4–9.25 mg·L⁻¹ dissolved oxygen, providing a theoretical basis for precise irrigation and sustainable cultivation of tropical fruit trees. Full article

Forest disturbance is a major driver shaping the structure and function of plantation ecosystems. Current research predominantly focuses on single forest types or landscape scales. However, species-level fine-scale assessments of disturbance dynamics are still scarce. In this study, we investigated Chinese fir (Cunninghamia lanceolata), Armand pine (Pinus armandii), and Yunnan pine (Pinus yunnanensis) plantations in the mountainous eastern Yunnan Plateau. We developed a Spatial Coupling Framework of Disturbance Legacy (SC-DL) to systematically elucidate the spatial associations between contemporary species distribution patterns and historical disturbance regimes. Using the Google Earth Engine (GEE) platform, we reconstructed pixel-level disturbance trajectories by integrating long-term Landsat time series (1993–2024) and applying the LandTrendr algorithm. By fusing multi-source remote sensing features (Sentinel-1/2) with terrain factors, employing RFE, and performing a multi-model comparison, we generated 10 m-resolution species distribution maps for 2024. Spatial overlay analysis quantified the cumulative proportion of the historically disturbed area and the spatial aggregation patterns of historical disturbances within current species ranges. Key results include the following: (1) The model predicting disturbance year achieved high accuracy (R² = 0.95, RMSE = 2.02 years, MAE = 1.15 years). The total disturbed area from 1993 to 2024 was 872.7 km², exhibiting three distinct phases. (2) The random forest (RF) model outperformed other classifiers, achieving an overall accuracy (OA) of 95.17% and a Kappa coefficient (K) of 0.93. Elevation was identified as the most discriminative feature. (3) Significant spatial differentiation in disturbance types emerged: anthropogenic disturbances (e.g., logging and reforestation/afforestation) dominated (63.1% of total disturbed area), primarily concentrated within Chinese fir zones (constituting 70.2% of disturbances within this species’ range). Natural disturbances accounted for 36.9% of the total, with fire dominating within the Yunnan pine range (79.3% of natural disturbances in this zone) and drought prevailing in the Armand pine range (71.3% of natural disturbances in this zone). (4) Cumulative disturbance characteristics differed markedly among species zones: Chinese fir zones exhibited the highest cumulative proportion of disturbed area (42.6%), with strong spatial aggregation. Yunnan pine zones followed (36.5%), exhibiting disturbances linearly distributed along dry–hot valleys. Armand pine zones showed the lowest proportion (20.9%), characterized by sparse disturbances within fragmented, high-altitude habitats. These spatial patterns reflect the combined controls of topographic adaptation, management intensity, and environmental stress. Our findings establish a scientific basis for identifying disturbance-prone areas and inform the development of differentiated precision management strategies for plantations. Full article

Excessive fertilization is a widespread issue in onion (Allium cepa L.) production in Southwest China. This practice not only leads to environmental pollution but also decreases the marketable yield and fertilizer productivity of onions. Identifying an optimal fertilization rate is crucial for promoting high-yield and highly efficient onion cultivation. The objective of this research is to determine the appropriate amount of fertilizer by investigating the effects of different fertilization rates on the growth characteristics and bulb yield of onion. The study was conducted over two consecutive growing seasons utilizing a randomized complete block design, which included six treatments: local routine fertilizer application (F1), a 20% reduction from F1 (F2), a 40% reduction from F1 (F3), a 60% reduction from F1 (F4), an 80% reduction from F1 (F5), and no fertilizer application (F0). The results show that, at the mature stage, aboveground dry matter quantity and its accumulation rate of onion under treatment F2 were found to be the highest among all other treatments across both growing seasons. Following the onset of bulbing, dry matter accumulation initially increased but subsequently decreased with reduced fertilizer supply; notably, it was greater under treatment F2 compared to other treatments. Compared with F1, the PFPN (partial factor productivity of nitrogen fertilizer) under treatment F2 increased by 35.2% and 32.0%, and the marketable bulb yield under treatment F2 increased by 8.4% and 5.8% during the 2022–2023 and 2023–2024 growing seasons, respectively. The marketable bulb yield demonstrated extremely significant positive correlations with aboveground dry matter and the dry matter accumulation rate throughout all growth periods in both growing seasons. Furthermore, marketable bulb yield exhibited extremely significant positive correlations with dry matter translocation before the onset of bulbing and dry matter accumulation following bulbing initiation. It was concluded that the appropriate fertilizer application (F2), characterized by a fertilization rate of 339-216-318 kg ha⁻¹ for N-P₂O₅-K₂O, enhanced onion bulb yield and nitrogen fertilizer productivity by promoting post-bulbing dry matter accumulation. This study emphasizes the significance of optimizing the fertilization rate as a crucial factor in achieving high-yield and highly efficient onion cultivation by enhancing dry matter accumulation. Full article

A clear understanding of drought perceptions and adaptation behaviors adopted by farmers is an important way to cope with climate change and achieve sustainable agricultural development. Karst is a type of landscape where the dissolving of the bedrock has created sinkholes, sinking streams, caves, springs, and other characteristic features. The study took the Huajiang karst dry-hot river valley area located in the southwestern part of Guizhou as the study area and used questionnaire survey method, the index of perception and the diversity index of adaptation strategy to explore the risk perception, adaptation perception and adaptation behavior of farmers to non-climatic droughts in the subtropical karst dry-hot valleys. A total of 530 questionnaires were distributed and 520 were returned. The results show that (1) the farmers’ risk perception of drought is stronger than adaptation perception, which shows that although farmers are well aware of the possible risks posed by drought, their subjective initiative and motivation to adapt to drought are weaker; (2) in the face of drought, farmers prioritize selected non-farm measures for adaptation, followed by crop management and finally water resource management; and (3) compared to farmers in arid and semi-arid regions, those in karst hot-dry river valleys exhibit distinct adaptive behaviors in response to drought, particularly in water resource management. Full article

Sapindus delavayi is a drought-resistant tree species endemic to the dry–hot valleys of Southwestern China and is of great significance for soil and water conservation and ecological restoration. In this study, we sequenced the transcriptome of its leaves using the Illumina HiSeq 4000 platform and obtained 96.12 Gb of high-quality data (Q20 = 98.68%, Q30 = 95.62%), which were de novo assembled to obtain 89,228 unigenes (N50 = 1538 bp), of which 63,005 (70.61%) were successfully annotated to at least one database (NR, NT, SwissProt, KOG, KEGG, GO, Pfam). Overall, 53.96% of the unigenes in the S. delavayi leaves were annotated to Acer yangbiense, which belongs to the same family as S. delavayi. A total of 42,870 CDSs and 21,488 SSR loci were detected, with the highest mononucleotide repeat rate at 42.72% of the total number. Drought stress experiments identified 669–1203 differentially expressed genes (DEGs). Through our research, the first high-quality transcriptome database of S. delavayi has been constructed and its drought-resistance-related gene features have been analyzed, laying an important foundation for future functional gene mining, molecular marker development, molecular diversity studies, molecular breeding, and ecological adaptation research. Full article

The inherent spatial heterogeneity of land types often leads to a class imbalance in remote sensing-based classification, reducing the accuracy of minority class detection. Consequently, current land use datasets are often inadequate for the specific needs of soil erosion studies. In response to the need for soil conservation in dry–hot valley regions, this study integrated multi-source remote sensing imagery and constructed three high-precision imbalanced sample datasets on the Google Earth Engine (GEE) platform to perform land use classification. The degree of class imbalance was quantified using the imbalance ratio (IR), and the impact of sample imbalance on the classification accuracy of different land use types in a typical dry–hot valley was analyzed. The results show that (1) Feature selection significantly improved both classification accuracy and computational efficiency. The period from February to April each year, between 2018 and 2023, was identified as the optimal time window for land use classification in dry–hot valleys. (2) Constructing composite images over longer time scales enhanced classification performance: using a 2020 annual composite image combined with a Gradient Tree Boosting classifier yielded the highest accuracy, indicating that longer temporal synthesis improves classification results. (3) The effect of class imbalance on classification accuracy varied by land type: woodland (the majority class) was least affected by imbalance, whereas minority classes such as cultivated land, garden plantations, and grassland were highly sensitive to imbalance. In imbalanced scenarios, minority classes are prone to omission errors, leading to notable accuracy declines; producer’s accuracy (PA) decreased by 46%, 42%, and 25% for cultivated land, garden plantations, and grassland, respectively, as IR increased (with PA dropping faster than user’s accuracy, UA). Cultivated land was especially sensitive and frequently overlooked under high imbalance conditions compared to gardens and grasslands. Despite overall accuracy improving with higher IR, the accuracy of these minority classes dropped significantly, underscoring the importance of addressing the class imbalance in land use classification for erosion-prone areas. Full article

Soil active nitrogen (N) fractions are essential for plant growth and nutrient cycling in terrestrial ecosystems. While previous studies have primarily focused on the impact of vegetation restoration on soil active nitrogen in karst ecosystems, the role of microclimate variation in rocky desertification areas has not been well explored. This study investigates soil active nitrogen fractions and key biotic and abiotic factors across four grades of rocky desertification—non-rocky desertification (NRD), light rocky desertification (LRD), moderate rocky desertification (MRD), and intense rocky desertification (IRD)—within two distinct microclimates: a dry-hot valley and a humid monsoon zone in the karst region of Guizhou Province, China. We evaluate soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), soil nitrate nitrogen (NO₃⁻-N), ammonium nitrogen (NH₄⁺-N), microbial biomass nitrogen (MBN), soluble organic nitrogen (SON), and plant diversity. Results showed that SOC, TN, and TP were significantly higher in IRD areas. Soil NO₃⁻-N, MBN, and SON initially decreased before increasing, with consistent MBN growth in the dry-hot valley. NH₄⁺-N did not differ significantly under NRD but was higher in the dry-hot valley under LRD, MRD, and IRD. The dry-hot valley had higher MBN and SON across most desertification grades. Microclimate significantly influenced soil active N, with higher levels in the dry-hot valley under LRD and MRD conditions. Plant diversity and regeneration varied markedly between the microclimates. In the dry-hot valley, Artemisia dominated herbaceous regeneration, especially in MRD areas. Conversely, the humid monsoon zone showed more diverse regeneration, with Artemisia and Bidens prevalent in MRD and NRD grades. Despite declining plant diversity with desertification, the humid monsoon zone displayed greater resilience. These findings highlight the role of microclimate in influencing soil nitrogen dynamics and plant regeneration across rocky desertification gradients, offering insights for restoration strategies in karst ecosystems. Full article

This study investigates the hydrological processes and water body transformation mechanisms in the Yuanmou dry–hot valley, focusing on precipitation, well water, spring water, river water, and reservoir water, during both wet and dry seasons. The spatiotemporal characteristics and significance of the hydrogen and oxygen stable isotopes across these water bodies were analyzed. Key findings included the following: (i) Seasonal variations in precipitation, river water, and shallow groundwater were minimal, and were primarily driven by differences in water vapor sources and transport distances during wet and dry seasons. The seasonal effects of mid-deep groundwater and reservoir water were influenced by leakage recharge from deep aquifers and temperature variations, respectively. (ii) The groundwater line-conditioned excess (lc-excess) deviated significantly from the Local Meteoric Water Line, indicating that precipitation recharge occurred primarily through slow infiltration piston flow with significant isotopic fractionation. (iii) River water was recharged by precipitation, deep groundwater, and spring water; well water by precipitation and lateral groundwater inflow; spring water by deep groundwater; and reservoir water by precipitation, groundwater, and water transfer, with strong evaporation effects. (iv) Using a binary isotope mass balance model, the recharge ratios of precipitation and groundwater to surface water were calculated to be 40% and 60%, respectively. Additionally, during the wet season, the proportion of groundwater recharge to river water increased. This study provides valuable insights into hydrological cycle processes in dry–hot valleys and offers a scientific basis for the sustainable development and management of water resources in arid regions. Full article

Trunk sap flow is essential for assessing plant water use efficiency and adaptation, yet the mechanisms underlying drought resistance and water utilization strategies in dry and hot valleys remain poorly understood. This study investigates the sap flow dynamics of four tree species (Albizia kalkora, Diospyros dumetorum, Terminalia franchetii, and Acacia auriculiformis) in a dry and hot valley using Granier’s thermal diffusion probe method. The aims were to analyze interspecific differences and their response mechanisms to environmental factors using a fitted model of sap flow density and transpiration variables, supplemented by Pearson’s and Mantel’s tests. The results showed that (1) the trunk sap flow of each tree species is significantly higher in the wet season than in the dry season. (2) In the dry and wet seasons, the average trunk sap flow rates were in the order Albizia kalkora > Diospyros dumetorum > Terminalia franchetii > Acacia auriculiformis. (3) The correlation between environmental factors and trunk sap flow was in the order photosynthetically active radiation > atmospheric temperature > saturated water vapor pressure difference > relative humidity > wind speed. (4) Deciduous plants demonstrated stronger water-conducting capacities than evergreen plants and native plants exhibited better drought resistance than introduced plants. (5) Acacia auriculiformis and Albizia kalkora were identified as rainfall-sensitive plants, while Diospyros dumetorum and Terminalia franchetii were rainfall-insensitive. By optimizing species selection based on water use efficiency, rainfall sensitivity, and environmental conditions such as light and temperature, this research contributes to enhancing the stability and resilience of ecosystem restoration in arid regions. Full article