Search Results (3,111)

The Upper Minjiang River Basin is a critical ecological barrier in the upper Yangtze River, where forest ecosystems play a vital role in carbon sequestration, water conservation, and soil retention. Given that different forest types exhibit significant variations in community structure, species composition, and ecological processes, their ecosystem service (ES) supplies and trade-off/synergy relationships are also expected to show distinct heterogeneity. However, systematic research on the trade-offs and synergies of ESs across different forest types remains limited, constraining the development of precision forest management and differentiated management strategies. To deal with this, we used the InVEST model and calculated five key services across the basin: carbon stock (CS), water yield (WY), soil conservation (SC), habitat quality (HQ), and forest stock volume (FSV). We then applied Spearman’s correlation, root mean square deviation (RMSD), and the GeoDetector model to analyze trade-offs and uncover driving mechanisms. Finally, we used spatially constrained K-means clustering to map different management zones. The results indicate that the Upper Minjiang River Basin stored 1.78 × 10⁸ t of carbon, retained 2.98 × 10⁸ t of soil, produced 6.48 × 10⁹ m³ of water yield, maintained a mean habitat quality of 0.78, and supported a forest stock volume of 1.20 × 10⁸ m³. Coniferous forests exhibited the highest CS (181.07 t ha⁻¹) and FSV (176.37 m³ ha⁻¹), whereas shrublands contributed the largest share (52.17%) of regional water yield. At the regional scale, CS and FSV showed the strongest synergy (r = 0.71, p < 0.01), while WY displayed significant trade-offs with most other services. GeoDetector analysis revealed that forest type acts as the primary driver shaping the relationships among services, while elevation and precipitation play supporting roles. Based on the ES bundles identified via spatially constrained K-means clustering, the Upper Minjiang River Basin was divided into four distinct management zones: a carbon sequestration core zone, an ecological balance zone, an ecologically fragile zone, and a multifunctional conservation zone. Therefore, findings from the Upper Minjiang River Basin may provide insights applicable to other mountain forest ecosystems facing similar environmental and management challenges. Full article

The large-scale integration of wind and solar power has significantly intensified peak-shaving pressure and operational risk in provincial power grids. Effectively leveraging the flexible regulation capability of hydropower to mitigate the uncertainty of wind and solar output is a promising approach to enhancing grid security and stability. To simultaneously improve the peak-shaving performance and risk resilience of hydro-wind-solar systems for a provincial power grid, this paper proposes a multi-objective short-term scheduling model that jointly minimizes the peak value of net load and the Conditional Value-at-Risk (CVaR) of flexibility shortage. Specifically, the residual peak load is used to quantify the system’s peak-shaving burden, while the average CVaR of upward/downward ramping deficits across all time periods characterizes the tail risk associated with insufficient flexibility. Historical wind and solar forecast error data are employed to generate representative uncertainty scenarios via Gaussian mixture model, and the Rockafellar–Uryasev formulation is adopted to accurately embed CVaR into a mixed-integer linear programming (MILP) framework. Furthermore, the normalized normal constraint (NNC) method is introduced to compute a well-distributed Pareto front. Numerical simulations based on a real-world hydro-wind-solar system in a provincial grid in Southwest China demonstrate that the proposed model can significantly reduce the peak load while effectively mitigating flexibility shortfall risk. The resulting Pareto front clearly reveals the trade-off between peak-shaving effectiveness and risk control, providing a scientific basis for day-ahead generation scheduling and coordinated dispatch of flexible resources. Full article

Teacher attrition in rural China is commonly framed as exit from schools or the profession. This framing obscures a more consequential form of mobility: the stepwise internal movement of teachers from remote village schools to township and county-seat schools within county governance systems. This study conceptualizes such patterned movement as semi-attrition and examines its mechanisms and consequences in a formerly poverty-designated county in southwest China. Drawing on semi-structured interviews with 14 participants and county-level administrative records, and integrating teacher labor market theory, spatial inequality theory, and life-course theory, we find that semi-attrition is directional, normalized, and invisible in official statistics, yet produces cumulative staffing instability in remote schools. Geographic isolation, subject mismatch, and unequal access to career advancement create structural push–pull dynamics, while marriage, childcare, and strategic title-accumulation strategies intensify individual mobility pressures. Together, these mechanisms reproduce spatial inequality through a Matthew effect: county-seat schools accumulate experienced teachers while remote schools cycle through successive early-career cohorts. We propose the County-Based Mobility Ecology Framework (CMEF) to explain how internal redistribution—rather than outright exit—drives staffing inequality in county-based governance systems. Findings call for policies that track internal mobility, address structural root causes, and equalize career advancement opportunities across school types. Full article

Precipitation use efficiency (PUE) links ecosystem carbon uptake to precipitation input, but endpoint ratios alone cannot show where carbon–water coupling differs along ecohydrological pathways. This limitation is especially relevant in karst landscapes, where thin soils and heterogeneous hydrological pathways can decouple rainfall, soil moisture, evapotranspiration, and plant carbon gain. Here, we developed a PUE chain decomposition framework based on gross primary productivity (GPP), transpiration (T), evapotranspiration (ET), soil moisture (SM), and precipitation (PRE): PUE = GPP/T × T/ET × ET/SM × SM/PRE. In this framework, GPP/T represents carbon fixation per unit transpiration, T/ET the transpiration fraction of evapotranspiration, ET/SM evapotranspiration output relative to soil moisture, and SM/PRE soil moisture status relative to precipitation input. We used multi-source remote-sensing and reanalysis data from 2003 to 2022 to compare karst and non-karst landscapes in Southwest China, applied variance decomposition to quantify the contributions of chain terms and their interactions, and used Stacking ensemble learning with Shapley additive explanations (SHAP) to interpret model-inferred environmental associations. Mean PUE was 1.16 g C m⁻² mm⁻¹ in non-karst areas and 1.08 g C m⁻² mm⁻¹ in karst areas, and all four chain components differed significantly between landform types. Variance decomposition identified SM/PRE and its interaction terms as the largest contributors to PUE variability, mainly reflecting a precipitation-sensitive diagnostic signal and soil moisture status relative to precipitation input. Machine learning interpretation showed that solar radiation, leaf area index, aridity, and groundwater storage were associated with different chain components; karst areas showed stronger groundwater-storage signals and lower model-inferred response thresholds. These findings indicate that PUE differences in Southwest China arise from multiple linked diagnostic stages rather than from endpoint carbon uptake or precipitation alone. The framework can help locate water-use constraints and support landform-specific ecological restoration and water management. Full article

Existing target sorting methods suffer severe performance degradation or even failure under inherent severe spectrum overlap, homogeneous protocol parameters, and scarce single-source points in Synchronous Non-Orthogonal Frequency Hopping (SNOFH) scenarios. To address this challenge, this paper proposes a passive sorting framework for SNOFH UAV swarm signals based on multi-station relative hopping time difference. The proposed framework constructs a spatial-location-driven sorting feature system, designs a kernel joint distribution adaptation module to eliminate inter-station measurement discrepancies, and develops a multi-scale wavelet-based method to achieve sub-sampling level hopping time extraction, reducing the dependence on prior FH parameters and hardware radio frequency fingerprints. Experimental comparisons between the proposed and reference sorting methods are conducted on a simulated SNOFH dataset to validate the performance of the proposed sorting framework. The experimental results show that the proposed method achieves the highest sorting accuracy of 98%, outperforming adopted baselines in most SNOFH cases. The proposed method exhibits favorable robustness with noise interference, clock-synchronization error, carrier-frequency offset and multipath influence. It is a suitable choice for UAV swarm sorting under regular and slow-varying UAV formations. Full article

The Yellow River Basin is a vital ecological security barrier for China, as well as a region rich in cultural and tourism resources. Tourism has emerged as a core industry underpinning both ecological conservation and sustainable, high-quality regional development within the basin. As the tourism industry transitions toward sustainable and high-quality development, tourism efficiency serves not only as a core indicator for measuring the quality of tourism development but also as a critical basis for assessing regional tourism sustainability. Taking 68 Outstanding Tourism Cities in the Yellow River Basin from 2009 to 2023 as research samples, this study employs the Super-Slack-Based Measure (Super-SBM) model to measure tourism efficiency. It depicts the spatiotemporal evolution through trend surface analysis, spatial autocorrelation analysis, hotspot analysis, and standard deviation ellipses and utilizes the Geographically and Temporally Weighted Regression (GTWR) model to identify the determinants of spatiotemporal heterogeneity. Tourism efficiency in the basin’s Outstanding Tourism Cities is generally low but has a variably increasing trend with a pronounced spatial gradient of upstream > midstream > downstream. The efficiency of tourism is highly interdependent spatially and highly clustered, as the regional high and low values are mostly situated up- and downstream, respectively. In general, the center of tourism efficiency has changed to the southwest instead of the northeast. The infrastructure, industrial structure and human capital characterize the efficiency of tourism, but the openness to the external world is the most significant factor, and the impact of these factors also varies sharply in terms of their strength. This study systematically reveals the spatiotemporal evolution patterns and heterogeneous driving mechanisms of tourism efficiency in Outstanding Tourism Cities within the Yellow River Basin. It not only expands the research perspectives and empirical analytical frameworks for sustainable tourism development at the basin scale but also provides a precise decision-making basis for the coordinated advancement of sustainable and high-quality tourism development in the region. Full article

To clarify the transformation patterns and driving mechanisms of the explicit and implicit morphology of rural settlements in peri-urban areas of large mountainous cities in Southwest China, this study examines the central urban area of Chongqing. Using land-use, point-of-interest (POI), socio-economic and digital elevation model (DEM) data from 2008 to 2024, we constructed an evaluation system for explicit and implicit rural settlement morphology. Kernel density estimation, the Mann–Kendall test and the moving t-test were used to identify morphological evolution, while the coupling coordination degree model and structural equation modeling (SEM) were applied to examine coordination relationships and driving mechanisms. The results show that: (1) during the study period, explicit morphology showed continuous contraction, whereas implicit morphology exhibited fluctuating improvement and polarized differentiation, indicating an overall gradual transformation; (2) no statistically significant abrupt changes were detected in either morphology, while temporal changes in coupling coordination divided the process into three stages—stable coordination, intensified imbalance and weak recovery—reflecting structural adjustment; (3) the coupling coordination degree declined overall, shifting from primary coordination towards near imbalance and indicating an uncoordinated transformation characterized by advanced contraction of explicit morphology and lagged improvement of implicit morphology; and (4) SEM results indicate that transportation infrastructure is the core driver of morphological transformation, with a significant positive effect on explicit morphology and a significant negative effect on implicit morphology. Natural factors positively support both morphologies, socio-economic factors exert negative or weak effects, and public services and real estate negatively affect explicit morphology but significantly promote implicit morphology. These findings provide a scientific basis for optimizing the layout and improving the functions of rural settlements in mountainous cities. Full article

Objective: To analyze the evolving epidemiological characteristics of pediatric poisoning from 2019 to 2024 in Southwest China, explore the changing patterns of pediatric poisoning in the post-pandemic era, and provide a reference for poisoning prevention and the development of effective prevention and treatment strategies. Methods: This study included 3923 cases of pediatric poisoning treated at the Emergency Department of West China Second University Hospital, Sichuan University. Clinical data such as gender, age, poisonous substance, and cause of poisoning were described. The chi-square trend test was used to analyze annual changes, and multivariate Poisson regression was employed to identify risk factors for hospitalization and for intentional poisoning in children. Results: The total number of cases increased significantly from 544 in 2019 to 1006 in 2024. A marked “polarization” pattern was observed: among children aged 1–3 years, unintentional ingestion of household chemicals predominated (n = 2332), whereas among adolescents aged 12–14 years, intentional self-poisoning cases surged by 580%, with the toxic agents shifting mainly to psychotropic prescription drugs. From 2019 to 2024, the proportions of intentional poisoning, psychotropic drug poisoning, psychiatric comorbidity, and delayed presentation all increased significantly. Poisson regression indicated that the post-pandemic period, psychiatric comorbidity, and exposure to psychotropic drugs were risk factors for intentional poisoning. Conclusions: Following the COVID-19 pandemic, mental health problems among adolescents have become increasingly prominent, and pediatric poisoning has exhibited a bipolarization pattern. Clinical prevention and control strategies should shift from simple emergency treatment to early intervention, psychological screening, and comprehensive prevention, so as to reduce health damage to children and the societal disease burden. Full article

Understanding the spatiotemporal relationship between agricultural inputs and crop production is essential for sustainable agricultural management. Using provincial panel data from China from 2000 to 2022, this study integrates spatiotemporal analysis with the XGBoost-SHAP model to examine the nonlinear effects of agricultural machinery, fertilizers, pesticides, and plastic films on soybean, cereal, and tuber yields. The results show that China’s agricultural input system shifted around 2015 from input-intensive growth toward green transformation, with fertilizer, pesticide, and plastic-film use declining after this inflection point. Spatially, agricultural inputs and crop production show clear agglomeration and path dependence: machinery is concentrated in northern China, fertilizers and pesticides in eastern intensive farming regions, and plastic-film use in arid and cold regions, while soybean, cereal, and tuber production are mainly concentrated in Northeast China, the Northeast-Huang-Huai-Hai region, and Southwest China, respectively. The SHAP results reveal distinct crop-specific importance rankings and nonlinear threshold patterns. For soybean yield prediction, agricultural plastic film use contributes most strongly to the model output, followed by fertilizer application, pesticide use, and machinery power; its SHAP contribution turns negative beyond approximately 112.4 thousand tons. For cereal yield prediction, machinery power ranks first, followed by fertilizer application, pesticide use, and plastic-film use; its contribution becomes positive beyond approximately 28.34 million kW and then gradually levels off. For tuber yield prediction, fertilizer application is the dominant predictor, followed by pesticide use, machinery power, and plastic-film use; its contribution turns negative beyond approximately 1.35 million tons. These findings indicate that agricultural inputs have crop-specific nonlinear effects, and that input regulation should prioritize the most influential factors for each crop while considering their threshold ranges. The study provides a scientific basis for differentiated, crop-specific, and regionally adaptive agricultural input management. Full article

Modern residential balconies have the potential to function as passive solar buffer spaces, yet their thermal performance in cold-region high-rise apartments remains insufficiently explored. This study proposes a stepwise glazing–phase change material (PCM) integrated balcony sunspace strategy for a typical high-rise residential apartment in Xi’an, China. Dynamic simulations were conducted to evaluate the effects of balcony orientation, glazing system, PCM melting temperature, and PCM thickness on indoor thermal comfort and annual heating and cooling demand. First, an open living room-connected balcony was used as the benchmark case, and five glazing systems were compared under southwest-, south-, and southeast-facing orientations. Then, based on the optimal glazing system, a 9C–PCM–9C partition wall was introduced between the enclosed balcony sunspace and the living room. The results showed that the optimal glazing system increased the annual thermal comfort ratio by 4.15–5.24 percentage points and reduced annual heating and cooling demand by 13.78–15.80 kWh/m² and 6.16–7.21 kWh/m², respectively. Further PCM integration achieved additional improvements, with 21 °C + 30 mm identified as the optimal configuration for all orientations. Compared with the glazing-only case, it increased thermal comfort by 2.05–2.50 percentage points and reduced heating and cooling demand by 4.80–5.10 kWh/m² and 1.64–1.76 kWh/m², respectively. The findings provide a practical passive design strategy for climate-responsive balcony sunspaces in cold-region residential buildings. Full article

Spaceborne imaging spectroscopy has created new opportunities for monitoring soil properties at regional scales. Its use for predicting soil heavy metal concentrations in mountainous environments, however, remains insufficiently tested, especially when EMIT hyperspectral data are used. In this study, EMIT Level-2A surface reflectance data were integrated with DEM-derived terrain variables to estimate soil arsenic (As), copper (Cu), and zinc (Zn) concentrations in Renhuai, Guizhou Province, Southwest China. Only soil samples falling within valid EMIT coverage were used for element-specific modeling, resulting in 139 samples for As, 136 for Cu, and 130 for Zn. To reduce redundancy among predictors, EMIT spectral variables and terrain factors were screened before model construction. Random forest and XGBoost models were then tested using repeated spatial cross-validation. The best-performing model for As combined EMIT predictors with elevation and achieved a validation R² of 0.460. Model performance was considerably weaker for Cu, with a validation R² of 0.188. For Zn, the model failed to outperform the mean-based benchmark, producing a negative validation R² of −0.028. The spatial prediction maps and residual patterns suggested that the EMIT-based prediction showed moderate potential for As, limited predictive value for Cu, and exploratory rather than reliable mapping capability for Zn under the current sample and predictor conditions. Full article

Fire occurrence in Southwest China is jointly shaped by meteorological conditions, topography, vegetation status, and human activities. To improve the interpretability and validation rigor of regional fire susceptibility assessment, this study developed a grid-day-based susceptibility assessment framework for Yunnan, Sichuan, Guizhou, and Chongqing using MODIS active-fire detections and multi-source environmental data from 2015 to 2024 at a 5 km grid resolution. A sensitivity analysis was conducted to determine the training sample configuration, and a 1:2 positive-to-negative sampling ratio was adopted. Random Forest (RF), Support Vector Machine (SVM), and Logistic Regression (LR) were compared, and SHapley Additive exPlanations (SHAP), together with partial dependence plots (PDP), were used to interpret key drivers and their interactions. Data from 2015 to 2018 were used for model training, while data from 2019 to 2024 were used to evaluate the model’s cross-year transferability within the same study domain, rather than full spatiotemporal independence. The results show that the 1:2 sampling ratio achieved a favorable balance between fire detection and false-alarm control. In five-fold stratified cross-validation, RF outperformed LR and SVM (AUC = 0.9167; F1-score = 76.70%). In the cross-year transferability test, areas classified as high and very high susceptibility captured 62.04–68.95% of the observed fire points while accounting for less than 32% of the total area. Soil moisture and maximum temperature contributed most strongly to the model output, and their interaction revealed a pronounced dry-hot statistical response pattern associated with elevated susceptibility. Fire susceptibility also exhibited stable positive spatial autocorrelation, with hotspot areas concentrated in the dry-hot valleys near the Sichuan-Yunnan border and in central-southern Yunnan. Because the model was built with under-sampled negatives and same-day environmental matching, the output should be interpreted as a relative fire susceptibility index for spatial assessment and statistical attribution rather than as a calibrated occurrence probability or a forward-looking daily forecast. Full article

Insect antimicrobial peptides (AMPs) are classically viewed as terminal effectors of innate immunity, but emerging evidence suggests that some can also shape defined neural states. In this Review, we argue that insect systems provide a powerful framework for resolving immune–brain communication at the level of individual peptide effectors, because genetically tractable innate-immune pathways allow pathway activation to be distinguished from peptide-specific effector function. Rather than surveying AMP families exhaustively, we focus on representative cases in which peptide identity, source, and timing can be linked to sleep, memory-related plasticity, and responses to acute injury. These studies show that the neural consequences of AMP induction cannot be inferred from pathway activation alone, but require peptide-level analysis of effector identity, cellular context, and exposure logic. This perspective also raises the question of translational potential. At present, direct biomedical development of endogenous insect AMPs in neural contexts remains limited, whereas more tangible applied interest has centered on insect venom peptides that share AMP-like physicochemical features. We therefore discuss insect venoms separately from endogenous AMP physiology. Venom peptides are not physiological equivalents of endogenous insect AMPs, but represent evolutionarily diversified AMP-like templates for scaffold discovery, mechanistic probing, and therapeutic engineering. Together, this review develops a peptide-level perspective on insect neuroimmune biology while highlighting insect venoms as a valuable, but highly constrained, source of templates for biomedical discovery. Full article

Government-funded teacher education in China links financial support, teacher preparation, employment expectations, and post-graduation service obligations. Understanding how pre-service preschool teachers perceive this policy-based pathway is important for explaining their professional identity development; therefore, this study examined how policy satisfaction and perceived teacher support were associated with the professional identity of government-funded pre-service preschool teachers in Chongqing, Southwest China. Based on paper-based questionnaire data from 620 participants, Latent Profile Analysis identified four profiles: Dissatisfied–Low Support, Moderately Satisfied–Moderate Support, Highly Dissatisfied–Low Support, and Highly Satisfied–High Support. Multinomial logistic regression showed that only-child status and age significantly predicted profile membership, and one-way ANOVA and multiple regression further indicated that professional identity differed significantly across profiles, with lower scores observed in the less satisfied and less supported profiles after controlling for demographic covariates. These findings suggest that strengthening policy communication and accessible teacher support may help promote professional identity development among government-funded pre-service preschool teachers. Full article

Coptodon zillii and Oreochromis niloticus are dominant invasive fish species that have successfully established and coexisted in the Jinghong Reservoir of the lower Lancang River, Southwest China. To explore the mechanisms underlying their invasion and coexistence from the perspective of reproductive traits, we conducted monthly sampling from January to December 2025 to compare key reproductive parameters, including size at first sexual maturity, sex ratio, breeding season, spawning pattern and fecundity. The results showed that the predicted sizes at first sexual maturity for females and males of C. zillii (83.4 mm and 81.7 mm, respectively) were significantly smaller than those of O. niloticus (127.7 mm and 125.8 mm, respectively). Both species exhibited early sexual maturation. The sex ratio of C. zillii was approximately 1:1, whereas that of O. niloticus was significantly female-biased. The breeding season of C. zillii lasted from April to September, peaking in May and June, while O. niloticus spawned from May to November, with a peak in August, showing a staggered temporal distribution. Both species were batch spawners; however, O. niloticus had significantly larger egg diameters than C. zillii. Absolute fecundity, length-relative fecundity and weight-relative fecundity were significantly higher in C. zillii than in O. niloticus. Moreover, the absolute fecundity of C. zillii showed stronger correlations with body length, body weight, net weight and gonadal weight. C. zillii adopted a more r-selected strategy, while O. niloticus exhibited a more K-selected strategy. The two species displayed clear divergence in their reproductive strategies, including size at maturity, breeding season, egg diameter and fecundity, which reduced interspecific competition and promoted niche separation and coexistence in the Jinghong Reservoir. Full article