Search Results (218)

Ecological security pattern (ESP) planning typically emphasizes ecological structure and connectivity, but may provide limited information on long-term functional degradation occurring within ecologically important areas. To address this gap, this study develops a baseline-referenced framework for diagnosing ecological resilience degradation (ERD) by integrating ecosystem service value (ESV) dynamics, minimum cumulative resistance (MCR) modeling, and explainable machine learning (XGBoost–SHAP). Using the Guangdong–Hong Kong–Macao Greater Bay Area (GBA) as a case study, ERD was operationally defined as long-term functional degradation within ecologically important components of the 2000 baseline network, with net ESV decline from 2000 to 2020 used as the functional-degradation signal. Two complementary ERD patterns were distinguished: source erosion and corridor interruption. The results showed that ERD exhibited a pronounced core–periphery pattern, with higher degradation intensity concentrated along the Guangzhou–Foshan–Dongguan–Shenzhen urban development corridor. Integrated ERD covered 5452.69 km², of which source erosion accounted for 4238.32 km² (77.73%) and corridor interruption for 1214.37 km² (22.27%). Source erosion represented the dominant ERD pattern in terms of spatial extent. The XGBoost model showed moderate predictive performance under spatial block cross-validation (mean validation R² = 0.638 ± 0.043), and SHAP analysis indicated that vegetation condition, proximity to water bodies, nighttime light, and elevation were among the most influential factors associated with spatial variation in ERD intensity. NDVI contributions shifted from positive to negative around 0.65, while the distance-to-water response changed most rapidly within 200–300 m. These values are interpreted as empirical transition ranges in the model response. Overall, the proposed framework links long-term ecosystem functional degradation with baseline ecological network position and provides a spatially explicit basis for identifying functionally degraded ecological areas and supporting differentiated spatial prioritization and ecological management. Full article

Surface urban heat island (SUHI) behavior in dryland cities can reverse sign when hot, bare peripheral surfaces exceed urban-core temperatures, yet long monthly records across contrasting climates remain scarce. This study reconstructs land surface temperature (LST) and standardized urban-core–periphery thermal contrasts for five Moroccan cities from 1995 to 2024 using Landsat, ERA5-Land, NDVI, and the annual MODIS MCD12Q1 land-cover product. The diagnostic analysis of SUHI and Urban Heat Sink (UHS) occurrence is explicitly separated from the forecasting component: SARIMA, Random Forest, XGBoost, and LSTM models predict monthly LST rather than UHI intensity. Tangier exhibits a persistent positive SUHI (mean: 4.6 °C; UHS frequency: 3.0%), whereas Béni Mellal, Ifrane, Laayoune, and Taza have negative mean contrasts of −1.4, −2.4, −1.0, and −0.7 °C, respectively; Ifrane records the highest UHS frequency (90.5%). No city shows a statistically significant monotonic UHI trend, and Sen’s slopes remain close to zero. Forecasting skill is city-dependent: SARIMA performs best in Ifrane and Tangier (R² = 0.94 and 0.93), while Random Forest performs best in Taza and Laayoune (R² = 0.90 and 0.79). Approximate 95% empirical uncertainty half-widths derived from held-out RMSE range from ±3.78 to ±15.48 °C, indicating substantial model- and city-specific uncertainty. The results support the hypothesis that local climate and peripheral land-cover context can outweigh urban fraction as controls on SUHI sign and amplitude. Generalization is limited by fixed reference distances, possible urbanization of the outer ring, clear-sky satellite sampling, the distinction between LST and air temperature, and the 36-month recursive forecasting chain used to display the 2026–2027 outlook. Full article

Taking the repair of prefabricated hole defects in 2024 aluminum alloy thin-walled components
by friction stir spot welding (FSSW) as the research object, the evolution laws
of microstructure and mechanical properties of FSSW-repaired joints of thin-walled components
were clarified through process experiments and numerical simulations. The
collaborative effect of the temperature field and material flow field during the FSSW repair
process and their regulation laws on the microstructure and properties were revealed. The
results show that as the repair speed increases, the macroscopic surface quality of the FSSW
joint improves. When the repair speed reaches 2000 r/min, a high-quality repaired joint
with a smooth and flat surface and no porosity defects can be obtained. Meanwhile, within
the repair speed range of 800 to 2000 r/min, the grains undergo dynamic recrystallization
(DRX) due to the combined effect of heat and mechanical forces, eventually forming a
uniform equiaxed grain structure in the weld core area. ABAQUS 2023 simulation verifies
the temperature distribution during the FSSW repair process. When the repair speed is
2000 r/min, the maximum temperature obtained from the simulation is 431.1 ◦C, which
agrees with the measured value from the experiment. The simulation results further reveal
that when the repair speed increases from 1200 r/min to 2000 r/min, the material fluidity
significantly enhances, and the flow velocity on the advancing side is always higher than
that in other areas. At the rotational speed of 2000 r/min, the plastic material flows continuously
from the periphery and eventually fills the defect area completely. The fracture
mode of the FSSW-repaired joint is mainly ductile fracture. With the increase in the repair
speed, the number of dimples at the fracture surface increases significantly. When the
rotational speed reaches 2000 r/min, the joint achieves the best mechanical properties, and
the FSSW-repaired joint reaches the maximum tensile strength of 169 MPa. Full article

We developed Tactule, a compact tactile display module that can be attached to host hardware ranging from PCs to game controllers, and characterized its frequency response under controlled, finger-pad-like loading. Tactule uses a $6\times 6$ matrix of multilayer-bimorph piezoelectric pins (with the four corner pins removed; 32 channels at 2 mm pitch), together with an $8\times 8$ variant, that delivers more than 60 $\mathrm{\mu }$m of free displacement at AC 5 V, a regime accessible from a standard USB power supply. We measured per-pin peak-to-peak rear-face displacement at 50–800 Hz across a graded series of five silicone loads (Shore A 10 to 90) and an unloaded reference, using sinusoidal and rectangular driving signals. The unloaded response peaks at 600 Hz; Shore A 10 loading shifts the peak to 750 Hz; and above 700 Hz, the Shore A 10 amplitude exceeds the unloaded amplitude. Coupling the measured waveforms to published models of the tactile periphery shows that the module drives the Pacinian channel with a wide margin throughout the band while reaching the non-Pacinian channels only at its low-frequency edge, providing engineering knowledge for designing receptor-specific stimulation patterns in assistive applications. Full article

As global warming intensifies and extreme heat events occur frequently, the human thermal environment is under severe threat. In this study, the thermal environment risk and spatial equity issues in residential areas of humid and hot summer cities have become increasingly prominent. This study assesses summer thermal environment risk in Wuhan’s central urban area—one of China’s four “Furnace Cities”—from a spatial equity perspective, using the factors from the IPCC Hazard–Exposure–Vulnerability framework. Factor weights were determined through questionnaire surveys and the entropy weight method. Calculation and analysis were conducted on the Open Geospatial Engine (OGE) based on weighted scores. Results show that Wuhan’s main urban area faces considerable thermal stress, with high-temperature zones highly overlapping with densely populated old residential neighborhoods. Building height follows a concentric “high-center, low-periphery” pattern, while housing prices decline along a center-edge gradient; mid-to-low price ranges exceed 90%, indicating limited thermal adaptive capacity among most residents. Although high-density areas account for only approximately 2.7%, they concentrate in high-risk zones such as core Hankou. Comprehensive assessment reveals a “central aggregation, riverside mitigation” risk pattern. Located in Hankou, Hanzheng Street, suffering from extreme heat, dense buildings, crowded residents, and low-quality housing, has the highest heat risk and the worst unequal spatial environment across the city. This study reveals thermal risk disparities in Wuhan’s central urban area and provides a scientific basis for formulating equitable and effective thermal environment risk mitigation strategies. Full article

Ecological civilization education has become an important component of environmental education and sustainable development strategies in China. Field-based learning in real ecological environments is essential for helping students understand ecological processes and human–environment relationships. However, limited attention has been paid to whether schools can spatially access ecological learning sites within feasible travel-time ranges, especially in plateau and mountainous regions where transportation constraints are strong. From the perspective of ecosystem service flow, forest parks can be regarded as supply sites of ecological learning services, secondary schools as demand sites, and road networks as the pathways through which such services are transformed into actual educational opportunities. To address this gap, this study evaluates the accessibility of forest-park-based ecological learning resources for secondary schools in the Tibet Autonomous Region, China. Taking 11 national forest parks and 137 secondary schools as research objects, a network-based travel-time model was constructed using road network data, and 1 h, 3 h, and 6 h service areas were generated to assess forest park service capacity and school accessibility. The results show that forest park educational service capacity is highly uneven. Nimu, Jiedexiu, and Caina Forest Parks have the highest service capacity, each covering more than 60 secondary schools within 6 h, while nearly half of the parks show relatively limited coverage. School accessibility also presents a clear core–periphery pattern, with high-accessibility schools concentrated around Lhasa and nearby transport corridors, whereas many schools in western and northern Tibet remain outside the 6 h service range. Based on the accessibility levels, differentiated field education strategies are proposed, including short field observation, one-day field trips, cross-regional fieldwork, and virtual or school-based alternatives. This study provides a spatial analytical framework for understanding the flow of ecological learning services from forest parks to schools and offers evidence for optimizing geography field education and improving equitable access to ecological civilization education in mountainous regions. Full article

Spatiotemporal differentiation and coupled driving mechanisms of urban ecological resilience in transboundary composite economic belts remain an understudied niche within human–land coupling system research. Taking 29 prefecture-level and county-level units of the Huaihe River Eco-Economic Belt from 2014 to 2023 as research samples, this study constructs an ecological resilience evaluation framework tailored to the pollution disturbance characteristics of the Huaihe River Basin under a three-dimensional theoretical framework encompassing resistance, adaptability, and recoverability. The entropy weight method is adopted to calculate comprehensive ecological resilience values, while the geographically and temporally weighted regression (GTWR) model is applied to identify spatiotemporal heterogeneous correlations among multiple influencing factors. This paper further characterizes the spatiotemporal evolutionary patterns of urban ecological resilience across the study area and unpacks the coupled associative effects of natural, economic, and social driving factors. The empirical results reveal three key findings: (1) Temporally, the overall comprehensive ecological resilience of the study region rose from 0.318 to 0.416, with a total growth rate of 30.91%. Its evolutionary trajectory follows three successive phases: rapid growth, steady improvement, and slow saturation. Adaptability, which is predominantly boosted by anthropogenic environmental governance, constitutes the primary contributor to resilience growth. The range of urban resilience values narrowed by 9.97%, indicating continuous advancement in balanced regional development. (2) Spatially, ecological resilience presents a prominent core-periphery pattern, with high-resilience zones concentrated in mountainous southwestern areas and low-resilience zones distributed across northeastern plains. All low-resilience county-level units were eliminated by 2023. (3) In terms of driving associations, topographic relief and environmental governance investment maintain persistent positive correlations with ecological resilience, while per capita GDP acts as the core economic supportive factor. The proportion of secondary industry and population density exhibit significant negative correlations with resilience. The normalized difference vegetation index (NDVI) shifts from a negative correlation to a weak positive correlation alongside progressive ecological restoration, whereas river network variables exert negligible long-term associative impacts. Collectively, the spatiotemporally heterogeneous coupling of natural endowments, industrial-economic conditions, and social governance factors shapes the evolutionary patterns of regional ecological resilience. This study fills the research gap regarding long-timescale resilience driving mechanisms for transprovincial composite river basins covering five provinces. It identifies novel human–land coupling mechanisms, including the temporal reversal of vegetation’s ecological benefits and the dual stress imposed by industrial agglomeration and dense human settlements in plain regions. The quantitative outputs of this research can provide data-based references for differentiated coordinated ecological governance across the Huaihe Ecological Economic Belt. Full article

Based on the high relevance of climate change issues and the extent of their investigation at global and regional levels, this study aims to quantify current changes in average annual air temperature, relative humidity, and precipitation within the Chu River watershed, and to identify patterns of their spatiotemporal variability under conditions of intensifying global warming. The study is based on long-term observational data from 18 meteorological stations collected during the period 1940–2024 under diverse physical and geographical conditions across the basin. The analysis of climatic dynamics within the Chu River basin catchment during the period 1940–2024, conventionally divided into four physiographic-altitudinal zones (high-mountain, mid-mountain, low-mountain, and plain regions), and conducted using a linear trend assessment approach with the application of statistical criteria, revealed the presence of multidirectional trends in climatic variables. It was established that the spatial and temporal variability of the trend coefficients for mean annual air temperature ranged from −2.50 to 2.45, for mean annual relative humidity from 0.93 to 1.03, and for annual atmospheric precipitation from 0.59 to 1.42. The identified positive trend in mean annual air temperature, occurring simultaneously with negative trends in relative humidity and atmospheric precipitation, is characterized not only by a stochastic component but also by a pronounced deterministic component manifested in the form of persistent positive and negative trends. These observed patterns are associated with the complex nature of climatic responses occurring in the northern part of the Tien Shan mountain system and along the eastern periphery of the Turan Lowland. Full article

Ecological security is fundamental to achieving the United Nations Sustainable Development Goals (SDGs) and maintaining ecosystem stability in ecologically sensitive regions. Mountainous protected areas, where ecological fragility and human pressure coexist, require dynamic evaluation frameworks that go beyond static pattern description. This study proposes an extended SPMOR (State–Pressure–Modelling–Optimization–Response) framework to assess the spatiotemporal evolution of ecological security in the Fanjingshan Mountain Region, a UNESCO World Heritage Site in Southwest China. Multi-source environmental and socio-economic datasets were standardized, objectively weighted using the CRITIC method, and integrated to construct a grid-based Ecological Security Index (ESI) for 2002, 2007, 2012, 2017, and 2022. Spatial autocorrelation analysis with global and local Moran’s I was employed to identify clustering patterns and temporal shifts. Results show that the average ESI increased from 0.4983 in 2002 to a peak of 0.5238 in 2012, before declining to 0.4945 in 2022. Global Moran’s I remained consistently high, ranging from 0.6516 to 0.6862, indicating persistent spatial clustering of ecological security. Spatially, the region exhibited a stable core–periphery structure, with high-security zones concentrated in the core reserve and low-security clusters distributed along human activity corridors. These findings suggest the coexistence of ecological restoration effects and renewed development pressures in mountainous protected areas. The proposed SPMOR framework provides a structured and potentially applicable approach for ecological security evaluation and offers practical insights for sustainable management of mountainous protected regions. Full article

Cropland and rural settlements are core components of rural human–environment systems, and their coordinated development is crucial for regional sustainability, particularly in China’s major agricultural production regions. Taking the Huang-Huai-Hai region as the study area, this study systematically investigates the spatiotemporal evolution of cropland and its coupling relationship with rural settlements using land use data from 1990 to 2020. Grid-based analysis and multiple spatial modeling methods were employed. The results show that: (1) From 1990 to 2020, the cropland in the region decreased by a net total of 21,021.94 km², with annual dynamic degrees ranging from −0.13% to −0.28%. Cropland conversion to other land uses far exceeded conversion from others, with construction land being the primary destination. Among these, rural settlements and urban construction land accounted for 43.75% and 55.58% of the total cropland loss, respectively. (2) The spatial distribution of cropland exhibited a distinct pattern of “hot in the center and south, cold in the periphery and north” (Moran’s I = 0.232, p < 0.001), indicating significant positive spatial autocorrelation. Hot spot areas clustered in the North China Plain and the Huang-Huai Plain, while cold spot areas were distributed in the Yanshan–Taihang mountains and the hilly regions of the Shandong Peninsula, clearly controlled by topography. (3) Cropland change exhibited stage-specific characteristics. The pattern was relatively stable during 1990–2000. During 2000–2010, cropland conversion to other uses intensified, with high-value conversion areas concentrated around urban agglomerations. In the 2010–2020 period, these high-value conversion areas diffused from the core plain areas to urban fringe zones. (4) The spatial coupling between cropland and rural settlements was predominantly characterized by the Moderately Coordinated Type (MCT), accounting for 48.38–58.44% of the area. However, the proportion of Rural Settlement-Dominant Type (RC) increased from 15.51% to 21.58%, indicating a trend toward intensifying human–environment conflicts. Overall, the Huang-Huai-Hai region experienced significant cropland changes. While its spatial pattern remains relatively stable, the coupling relationship between cropland and rural settlements is deteriorating, posing challenges to regional food security and rural sustainable development. Full article

Understanding the internal spatial structure of widely distributed species is fundamental for biogeographic theory and conservation practice, yet such structure is often masked by extent-based range metrics. We investigated the spatial organisation of Pseudopus apodus (Pallas, 1775), the largest limbless lizard of the Western Palearctic, using 3967 occurrence records spanning 1843–2025. Spatial point pattern analysis revealed a pronounced deviation from complete spatial randomness (Clark–Evans R = 0.105, p < 0.001), with strong fine-scale clustering. Kernel density estimation identified a clear core–periphery organisation: high-density core areas accounted for 30% of records but occupied only 22% of the total extent of occurrence (EOO). The discrepancy between EOO (~8.9 million km²) and area of occupancy (AOO; ~8944 km²) spanned three orders of magnitude, emphasising that only a small fraction of the species’ geographic envelope is actively occupied. Spatial heterogeneity was high (coefficient of variation ≈ 0.99), and core and peripheral occurrences were significantly segregated along both latitudinal and longitudinal gradients. The proportion of core records showed a weak positive temporal trend most plausibly attributable to sampling effort, particularly the recent expansion of citizen-science contributions, rather than to ecological processes. These findings demonstrate that P. apodus exhibits a compact spatial core embedded within a broad, sparsely occupied periphery, underscoring the limitations of EOO-based metrics in the conservation assessment of widely distributed reptiles. We emphasise that this structure is characterised using the density of occurrence records and therefore describes the observed spatial organisation of the available data rather than directly measured population density; ecological interpretations are accordingly framed as hypotheses requiring independent validation. Full article

This study examines the interconnectedness of the Philippine banking system across three contagion channels: interbank loans, interbank deposits, and payment systems. Using network data from 481 banks supervised by the Bangko Sentral ng Pilipinas (BSP), the study applies topology-based measures to assess the structure and strength of interbank linkages. It introduces two metrics: the Overall Interconnectedness Index (OII), which measures the level of connectedness of the network, and the Core Connectivity Index (CCI), which identifies robustly linked banks within the system. The results show that payments are more interconnected than loans and deposits, but the overall interconnectedness remains very low across all channels. For the full banking system, OII values range from 0.06 to 0.65%, indicating a sparse network structure. In the core network of universal and commercial banks, loans and deposits show modestly higher interconnectedness, while payments display a much stronger core–periphery pattern. The CCI results are consistent with these findings, confirming weak connectedness in the loans and deposits networks and relatively stronger connectedness in the payments network. These findings suggest that the Philippine interbank network has limited potential for contagion through small shocks, but its sparse structure may also reduce risk-sharing capacity and weaken the system’s ability to absorb larger shocks. The proposed measures offer a useful framework for monitoring systemic risk and identifying banks that contribute most to interconnectedness. They also provide policy implications for financial regulators, like BSP, in strengthening financial stability through improved market access, payment system participation, and macroprudential surveillance. Full article

This paper studies the topic that has been rather less explored until now—the internal diversification of trading. Unlike looking at aggregate measures of financial development such as market capitalization and liquidity, the study focuses on trading diversification, defined as the portion of trading volume attributed to firms other than the ten most actively traded (VTX). The empirical analysis is based on the World Bank’s Global Financial Development database. It covers an unbalanced cross-country dataset of 2004–2021. Due to limited data availability, the resulting database became smaller and has an unbalanced panel structure. Four main independent variables in the core regression specification are related to financial structure (bank deposits) and financial integration (remittances, international public debt), as well as external measures of financial development (market capitalization, excluding firms within VTX). A broad range of control variables are introduced into the model to account for macroeconomic conditions, financial development, market size, liquidity, and participation. Lagged regressors are introduced to address persistence, delays, and potential endogeneity issues. The methodology relies on panel data econometrics, hierarchical clustering, and machine learning. The findings show that market structure and remittances positively affect trading diversification, whereas banks’ dominance and international public debt contribute to its concentration. The results persist across alternative specifications and robustness tests. The country-level analysis shows a core–periphery pattern, while machine learning demonstrates the critical importance of market structure. Full article

Despite Mozambique’s substantial natural gas reserves, most households rely on solid biomass for cooking, with serious consequences for public health, livelihoods, and the environment. The domestic use of these resources could improve energy efficiency, security, and sustainable development. This mixed-methods study uses household interviews, descriptive statistics, multinomial, and conditional logit models, analyzing data from a random survey of 434 households in energy-rich peripheries of northern Inhambane and Maputo City to ascertain the determinants of household cooking energy choice. Results reveal that rising income increases the odds of choosing electricity, LPG, and biomass over natural gas. In energy-rich peripheries, the odds of selecting biomass over natural gas are reduced by 96.2% compared to non-energy-rich regions. Educational and urban habitation are positively correlated with the adoption of electricity and liquefied petroleum gas (LPG). Price serves as a significant negative predictor of fuel selection (OR ≈ 0.000001), whereby each unit increase in price per GJ substantially diminishes the likelihood of opting for alternatives over domestic gas. Monthly fuel expenditure positively predicts electricity, LPG, and biomass adoption (OR = 1.0042), with effects accumulating meaningfully across realistic spending ranges. Households that experienced energy system incidents were more than twice as likely to switch away from natural gas (OR = 2.072), reflecting the critical role of infrastructure reliability in fuel choice. Given natural gas’s potential as a clean cooking transition fuel, the government should prioritize investment in gas infrastructure, expand domestic supply, and promote public awareness of the health and environmental benefits of clean cooking energy. Full article

Accurately identifying urban functional zones and revealing their spatial interaction characteristics is crucial for understanding urban operational mechanisms and optimizing spatial layouts. Addressing the limitations of traditional research in simultaneously capturing static functional attributes and dynamic resident travel behaviors, this study takes the central urban area of Lhasa as the research object, integrating ride-hailing trajectory data with Point of Interest (POI) data to conduct research on urban functional zone identification and spatial interaction characteristics. First, Thiessen polygons were used to quantify the spatial influence range of POIs, and an address matching algorithm was employed to associate ride-hailing origins and destinations (ODs) with POIs. A weighted land use intensity index was constructed, and functional zones were precisely identified using information entropy and K-Means clustering. Secondly, with basic research units as nodes and OD flows as edges, a directed weighted spatial interaction network was constructed. Complex-network indicators and the Infomap community detection algorithm were utilized to analyze network characteristics, node importance, and community interaction patterns. The results show that: (1) The functional mixing degree in the study area exhibits a pattern of “highly composite core, relatively differentiated periphery.” Eight functional zone types, including commercial–residential mixed, science–education–culture, and transportation service zones, were ultimately identified. Residential areas form the base, while the core area features multi-functional agglomeration. (2) The spatial interaction network exhibits typical small-world effects, while its degree distribution is better characterized by a lognormal distribution rather than a power law. Node importance is dominated by betweenness centrality, with Lhasa Station, the Potala Palace, and core commercial areas constituting key hubs. (3) The network can be divided into four functionally coupled communities: the core multi-functional area, the western industry–residence integrated area, the eastern science–education-dominated area, and the southern transportation hub area, forming a “core leading, two wings supporting” center–subcenter spatial organization pattern. This study verifies the effectiveness of integrating trajectory and POI data for identifying urban functional zones and provides a new perspective for understanding the spatial structure and planning of plateau cities. Full article