The evolution of China’s traditional village protection policies reflects established processes of systemic change, from initial exploration and gradual construction to continuous optimization and deepening. Currently, within a critical period of economic transition from high-speed growth to high-quality development, China is seeking to define rules and internal logic regarding its policy evolution for the protection of traditional villages. This is important for promoting high-quality protection and sustainable development of traditional villages. Based on the theory of “attention allocation,” this study analyzed 107 laws, regulations, departmental rules, and other important policy documents formulated, promulgated, and implemented by the national legislative body (Central Committee of the Communist Party of China) or the highest state administrative organs from 1950 to 2023. By applying the three-dimensional analytical framework of “situation–attention–behavior,” this study investigated the stage characteristics and internal mechanisms of the evolution of China’s traditional village protection policies, which are jointly driven by policy situation, government attention allocation and policy behavior. The results showed that: (1) policy evolution is driven by specific situations and attention allocation, while the external manifestations of policy evolution include alterations in policy subjects, effectiveness levels, and policy tools triggered by policy behavior choices; (2) China’s traditional village protection policies have gone through four stages: (i) the policy incipience stage (1950-2001), (ii) the initial institutionalization stage (2002-2011), (iii) the upscaling and integration stage (2012-2019), and (iv) the paradigm transformation stage (2020-present). In the policy incipience stage, policy as a concept was primarily materialistic, with government attention focused on protecting cultural relics within villages. During the initial institutionalization stage, this concept remained materialistic, but government attention shifted to mainly focus on the preservation of cultural relics, historic and cultural villages, and intangible cultural heritage. As policies entered the upscaling and integration stage, the concept shifted to humanism, with government attention prioritizing both the protection of cultural relics and the preservation and utilization of traditional villages. In the paradigm transformation stage, policy evolved further into ecologism, where government attention expanded to include the protection of cultural relics, the preservation and utilization of traditional villages, and the demonstration of concentrated and contiguous preservation and utilization of traditional villages. The intensity and scope of government attention allocation followed an inverted U-shaped trend that peaked during the upscaling and integration phases. Driven by policy concepts and government attention allocation, the scope of policy issues has continuously expanded, and the relationships among issues have shifted from simple to complex; (3) during the evolution of traditional village protection policies, the number of policy entities and the degree of their cooperation gradually increased, peaking during the upscaling and integration stages, before declining during the paradigm transformation stage. Concurrently, the level of policy effectiveness continuously decreased, while policy tools evolved from reliance on environmental-type tools toward a diversified mix that combined environmental, supply-side, and demand-side tools. These findings contribute to understanding the internal mechanisms of the formulation and evolution of traditional village protection policies, identify the characteristics and shortcomings of current policies, and provide valuable references for future policy formulation and improvement.
Cities, especially megacities, are the destinations for new urban residents and young people in rapidly developing China. They are also the main areas where the child population is growing against a backdrop of population decline. The concept of child-friendly is gradually being noticed and valued. In this study, Changsha was chosen as an example of one of the first child-friendly construction demonstration cities in China based on the Child-Friendly Cities Initiative (CFCI) jointly launched by the United Nations Children’s Fund (UNICEF) and the United Nations Human Settlements Programme (UN-Habitat) in 1996. We constructed an evaluation index system for “child-friendly residential areas” using five aspects that meet the most basic needs of children: safety, accessibility, interest, growth, and sharing. The projection pursuit method, differentiation measure index, geographical detector, and other methods were used to calculate the child-friendliness of 1,131 residential communities in the urban area of Changsa, and the spatial differentiation characteristics of child-friendliness in these residential areas as well as their influencing factors were explored. The aim was to guide the planning and implementation of child-friendly cities in China at the residential space level, thereby forming a scientific and systematic local model. The following results were found: 1) The comprehensive child-friendliness of residential areas in Changsha varied significantly in different housing areas, showing an overall spatial pattern of “one center-multiple highland-low edge.” The central urban area in the eastern part of Changsha, the 2-kilometer area along the Xiangjiang River, and the newly developed urban subcenter had the highest child-friendliness, whereas the urban fringe areas and industrial zones were relatively less child-friendly. However, significant differences were observed within the central urban and old urban areas in the eastern part of Changsha, whereas new urban areas such as the Meixi Lake District showed a relatively balanced performance. 2) The spatial differentiation of each sub-dimension index of child-friendliness in residential areas had its own characteristics: safety was higher in the south and lower in the north; the distribution of interest was relatively balanced; the pattern of growth was obviously “high in the center and low at the edge”; and the sharing and accessibility aspects were positively correlated with the overall friendliness. The sub-dimensional indicators were closely related to the sequence of urban development, level of urban construction, supporting facilities of public services, and policy planning. 3) The child-friendliness of residential areas in Changsha was significantly influenced by both internal (e.g., housing prices, construction era, self-governance level, and property management grade) and external factors (e.g., demonstration effect and planning level). Additionally, an interaction enhancement effect among the factors was evident. High-quality housing and effective community management had a synergistic effect in improving child-friendliness. 4) Based on the analysis findings, the following policy suggestions are given: to build child-friendly living spaces, the top-level design of child-friendliness should be strengthened, child-friendly residential areas should be planned and constructed in accordance with local conditions, and the leading role of child-friendly demonstration communities must be enhanced.
Previous studies have established an association between green spaces and the mental health of residents. However, existing research predominantly relies on mean regression models predicated on the assumption of linear relationships, which may overlook potential nonlinear associations between these two variables. Furthermore, the impact of green spaces on mental health might vary across the upper, central, and lower quantiles of the response variable and could be modulated by other environmental and individual factors. In this study, the nonlinear relationship between green spaces and the mental health of residents across different quantiles (i.e., low, medium, and high mental health levels) was explored using questionnaire survey data collected in Guangzhou in 2021 and a Bayesian geoadditive quantile regression model to control for other individual and environmental characteristics. The effects of individual socioeconomic attributes, green space quality, and green space use behavior of the residents on mental health at varying levels were further analyzed. Additionally, spatial correlation was incorporated to capture unexplained geographical associations. The following results were found: (1) Gender showed a significant positive correlation with the low level of mental health. Educational attainment showed a significant negative association with mental health across all three quantiles. Age was positively correlated with mental health at the low, medium and high levels. Income showed a positive association with low and medium levels of mental health.The duration of green space use showed a significant positive correlation at the low mental health level. The frequency of green space use correlated significantly with mental health across different levels. (2) Among the green space quality factors, cleanliness was positively correlated with a low mental health status, whereas security showed positive associations across all mental health levels, with a stronger correlation at the high level. (3) A nonlinear relationship between green spaces and mental well-being was evident. At moderate greenness values (0.36~0.6), green spaces demonstrated a weak positive trend in their impact on mental health, whereas a certain negative trend in this effect was observed at high greenness values. The mean curve suggested an implicit threshold (0.6) at which the health benefits of green spaces become apparent. (4) The low mental health group exhibited a significant negative spatial effect, indicating the presence of unobserved regional risk factors. By contrast, no significant spatial effects were detected in the medium and high mental health groups, suggesting that the model covariates sufficiently explained the observed associations. Overall, BQR enables researchers to integrate prior knowledge via prior distributions and provides comprehensive probabilistic interpretations of model parameters. This allows for posterior distributions of parameters to be obtained, thereby enhancing our understanding of parameter uncertainty and complexity. Second, the method offers valuable insights into the alternative distributional characteristics of the response variable, information that mean regression fails to capture, thus enabling exploration of the impact of green spaces on different mental health levels beyond the average effect. This facilitates the identification of populations who will be the most adversely and favorably affected by green spaces in terms of mental health. The findings of this study have significant implications for promoting public green space utilization and formulating community-level health planning policies.
Bike-sharing is an important component of urban short-distance mobility systems, offering a flexible, low-carbon alternative to motorized travel while addressing “last-mile” connectivity in metropolitan areas. Despite its rapid expansion, bike-sharing usage exhibits pronounced spatiotemporal variability and spatial heterogeneity, which complicates system management, infrastructure provision, and policy design. Studies have predominantly relied on global statistical models or localized spatial methods, making it difficult to simultaneously identify the dominant influencing factors and reveal their spatially varying effects. To address this limitation, this study proposes an integrated analytical framework combining Random Forest (RF) with Multiscale Geographically Weighted Regression (MGWR) to explore the mechanisms through which the built environment influences bike-sharing usage from global and local perspectives. Using large-scale bike-sharing trip data from central urban Shenzhen, China, a comprehensive set of built environment indicators was constructed, covering the road network structure, population and building density, land-use characteristics, points of interest, and public transport accessibility. First, RF was employed to capture complex nonlinear relationships between bike-sharing usage and the built environment, and SHapley Additive exPlanations (SHAP) values were used to quantify the global importance and marginal effects of each variable. Based on the RF-SHAP results, road network, population, work–life POI, and metro station densities within a 1 km buffer were identified as the most influential predictors of bike-sharing demand. Subsequently, these key variables were incorporated into the MGWR model to examine their spatially varying effects and scale-dependent influence mechanisms. The results revealed substantial differences in the magnitude and spatial scale of the built environment effects. Road network density exhibited strong local-scale effects, indicating pronounced spatial heterogeneity that is closely associated with micro-level street connectivity and cycling infrastructure conditions. Its positive influence on bike-sharing demand was notable in major commuting corridors and high-connectivity areas. Conversely, population density demonstrated near-global-scale effects with relatively stable coefficients across space, suggesting that overall demand intensity provides a consistent baseline for bike-sharing usage throughout the study area. Work-life POI density showed context-dependent effects, with negative associations observed in highly mixed-use urban cores, particularly on non-workdays. This pattern suggests a substitution effect in compact, functionally intensive areas where walking may replace short-distance cycling. Metro station density within a 1-km buffer exerted a robust and spatially stable positive influence on bike-sharing usage, highlighting the importance of bike-sharing as a feeder mode for rail transit. The effect was pronounced in areas with weaker bus service coverage, underscoring the importance of “metro-bike” integration in enhancing multimodal accessibility. Overall, built environment factors influenced bike-sharing usage through distinct spatial scales and heterogeneous mechanisms that cannot be fully captured by single-model approaches. By integrating global importance identification with local-scale spatial heterogeneity analysis, the proposed RF-MGWR framework provides a more comprehensive understanding of bike-sharing behaviors. This study combines machine learning and spatial econometric methods and offers empirical evidence on the scale-dependent effects of the built environment on active travel. These findings are important for differentiated bike-sharing management, cycling infrastructure investment, and integrated public transport planning, thereby supporting more efficient and sustainable urban mobility strategies.
National image represents the comprehensive power and influence of a country across multiple dimensions in the global arena. How a nation can simultaneously expand its overseas economic activities while gaining broad international recognition and cultivating a favorable national image has long been a central concern in both international political theory and practice. In this study, ten ASEAN countries were used in a regional case study of how China’s Outward Foreign Direct Investment (OFDI) affects its national image in the region. Using data from multiple sources, we constructed a 2003–2022 panel dataset covering China and the ten ASEAN countries and used a two-way fixed-effects model to empirically analyze the OFDI effects, underlying mechanisms, and nonlinear processes. The following results were found: 1) China’s OFDI significantly enhanced its national image in the ASEAN countries, indicating that Chinese firms abroad not only pursued economic gains but also played a crucial role in shaping evaluations of China by host countries. 2) The effect of China’s OFDI on national image varied with the host country income level, industrial structure, and religious-cultural context. The image-enhancing effect of OFDI was more pronounced in countries with lower–middle incomes. With regard to industrial structures, the positive effect diminished in highly industrialized economies. Culturally, Buddhist-majority countries generally exhibited a more favorable response to Chinese OFDI. 3) The mechanism through which China’s OFDI shaped national image operated at macro, meso, and micro levels. At the macro level, OFDI promoted green development and environmental improvement, enhancing institutional recognition of China’s development model. At the meso level, OFDI strengthened recognitions of China’s capabilities and cooperative value through technology diffusion, skills training, and industrial cooperation. At the micro level, OFDI directly affected individual-level perceptions and attributions by generating employment and alleviating poverty, thereby fostering positive emotional responses. Moreover, the positive image effect of OFDI became more pronounced when the number of inbound tourists from the host country exceeded a certain threshold. This study contributes to the literature in two main ways. First, it theoretically integrates essentialist and constructivist perspectives, addressing both the objective economic and social effects of OFDI and its role in cognitive construction through cross-national interactions, thereby systematically revealing the multidimensional mechanisms through which investment influences national image. Second, in terms of regional selection, the ten ASEAN countries constitute a distinctive “small yet comprehensive” setting for examining the impact of OFDI on national image. On the one hand, the region features a complex geopolitical landscape in which major powers such as China, the USA, and Japan interact and compete closely, providing a multifaceted real-world context for assessing how China’s OFDI contributes to building national image. On the other hand, ASEAN exhibits pronounced internal heterogeneity in levels of economic development, industrial structures, and cultural traditions, ranging from high-income service-oriented economies (e.g., Singapore) to low-income agriculture-based countries that retain strong traditional cultural characteristics (e.g., Laos). This diversity offers a rich empirical basis for investigating the heterogeneous effects of OFDI under different economic and cultural conditions and unpacking the macro-, meso-, and micro-level mechanisms through which these effects operate.
Rubber plantations in Southeast Asia and China’s Hainan Island face the threat of increasingly frequent compound drought and hot events (CDHEs). To overcome the biases of traditional meteorological indicators in reflecting ecological stress, we propose herein a method for quantifying environmental stress on the basis of the optimal growth threshold of gross primary productivity (GPP). By constructing three CDHE identification patterns for soil compound drought and hot events (SCDHEs), atmospheric compound drought and hot events (ACDHEs), and ecological compound drought and hot events (ECDHEs), we aimed to quantify the impact of such events on the GPP of rubber plantations on the basis of the degree of deviation from the optimal threshold. The following results were found: (1) The optimal growth threshold of rubber plantations exhibited significant latitudinal gradients and seasonality, with soil moisture thresholds throughout the year being higher and more stable in areas near the equator than in high-latitude regions, the latter of which showed obvious seasonal fluctuations. (2) Both the frequency and intensity of CDHEs showed increasing trends from 1982 to 2018, with ACDHEs exhibiting the highest growth rate (
Against the background of deepening integration within the China-ASEAN Free Trade Area, which has significantly intensified near-long-range coupling effects within the regional ecological economy, existing research remains insufficient in providing a quantitative exploration of large-scale cross-border energy metabolism and factor coupling under an adapted analytical framework. This study aims to systematically elucidate the evolutionary characteristics of regional energy metabolism pressure and the internal driving mechanisms of sustainable development, thereby providing critical, quantified scientific evidence for regional collaborative governance and green transformation. In terms of methodology, this study utilizes material flow panel data from 11 China-ASEAN countries spanning the period from 2005 to 2020. Based on sustainable development theory and the near-long-range coupling framework, this study integrates energy-value metabolism analysis with the logarithmic mean Divisia index (LMDI) decomposition method. This facilitates the construction of a multidimensional evaluation system comprising total annual metabolism (U), external factor dependence (EER), local and transboundary environmental load ratios (LELR, TELR), and the ecological sustainability index (ESI). The research findings indicate that total regional energy utilization exhibited a steady upward trend. Vietnam and Cambodia demonstrated the most pronounced growth rates of 146.32% and 168.08%, respectively; meanwhile China recorded the largest total energy volume (3.03×1025 Sej) and Laos the smallest (7.32×1022 Sej). Furthermore, regional energy externality generally increased, with Singapore exhibiting the highest dependence on remote factor flows through global value chains, thus indicating that most nations are continuously strengthening their reliance on external factors. In terms of metabolic pressure assessment, environmental load rates for both near and remote factors continued to increase, with remote pressures consistently exceeding local pressures. Specifically, Brunei faced the highest local environmental pressure due to its oil- and gas-dependent economic structure, whereas Singapore’s limited resource endowment resulted in the highest remote environmental pressure. Meanwhile, countries such as China and Thailand maintained relatively high levels across both categories. Sustainability assessments revealed that the overall level of regional sustainable development declined during the study period. Nevertheless, Laos and Cambodia maintained superior system vitality and sustainability (ESI > 2), whereas Singapore exhibited typical consumption-driven system characteristics with the weakest sustainability performance. The analysis of the driving forces demonstrates that renewable resource utilization and economic growth serve as the primary positive drivers of sustainability enhancement. Conversely, high energy intensity and a heavy dependence on externally imported resources act as principal negative constraints. Notably, the overall driving mechanism evolved through three distinct stages: the "extensive growth-resource consumption" mode, the "trade deepening-efficiency differentiation" mechanism, and the "resource constraint-equity adaptation" phase. This study contributes to the academic field by integrating near-long-range coupling perspectives with energy-value theory to address the gap in large-scale, quantitative, cross-regional research. Furthermore, it achieves a differentiated measurement of factor impacts, and reveals the phased evolutionary patterns of the mechanisms driving sustainable development.
Mangroves are a vital component of coastal blue carbon ecosystems. The aboveground biomass (AGB) of mangroves must be accurately estimated for meeting carbon neutrality objectives. However, traditional field biomass measures face many constraints in estimating the AGB of mangroves because of the special ecological status of mangroves as nationally protected plants, challenging tidal environments, and high costs associated with field sampling. As such, the limited number of field-measurement sample plots available for mangrove AGB inversion imposes serious challenges, which we addressed by developing a novel semi-supervised coregression (COREG) approach. We developed and validated the semi-supervised COREG regression method based on Sentinel-2 optical, GEDI vegetation canopy height, and field survey data from 120 standard plots (10m×10m) established in Dongzhai Harbor Mangrove National Nature Reserve, Hainan, China. Firstly, in the study area the method evaluated six classical AGB regression models, from which the two base models—the random forest and XGBoost algorithms— with the highest accuracy were selected. Subsequently, collaborative feature importance assessment was used to select seven key feature variables (MTVI2, MSRren, NDVIre, CIre, MDI2, GEDI canopy height, TNDVI), and then dual-regressor collaborative training was applied. Then the method successfully expanded the original 96 training samples to 413 samples via incorporating 317 high-confidence pseudo-labeled samples from
Mangrove ecosystems deliver disproportionate ecological and socioeconomic benefits to coastal zones. However, assessments of the habitat suitability of mangroves seldom explicitly account for anthropogenic pressures. In this study, habitat suitability modeling was enhanced by integrating human disturbance indicators into the MaxEnt framework and introducing the Human-Integrated Mangrove Suitability Index (HMSI) as the probabilistic output of the model when anthropogenic variables are included. We applied this approach to two representative protected areas in Guangdong Province in China to evaluate whether incorporating human activity information improves the predictive performance of the model and its ecological interpretability. The areas studied were Gaoqiao (Zhanjiang) and Qi’ao Island (Zhuhai), which differ markedly in their human footprints. Twelve environmental predictors were compiled, covering the topography (elevation, slope, and distance to the coastline), oceanographic conditions (sea surface temperature (SST) and salinity), and anthropogenic pressures (population density, land-use type, and nighttime light intensity). MaxEnt models were trained using 75% of the occurrence records and tested on the remaining 25% and their robustness was assessed using the area under the receiver operating characteristic curve (AUC) and complemented using threshold-based true skill statistic (TSS). Experiments were performed to compare a natural factor-only configuration with an integrated configuration that yields HMSI values. The incorporation of anthropogenic predictors consistently improved the discriminative capability of the model: the AUC for Gaoqiao increased from 0.826 to 0.887 and that for Qi’ao Island from 0.875 to 0.918, and the TSS values increased in parallel, indicating enhanced sensitivity and specificity under realistic thresholding. The model outputs revealed contrasting controls across the study sites. The suitability of Gaoqiao was primarily driven by natural controls, with the slope, land use, and SST collectively explaining the majority of model gain and the response curves indicating peak suitability on gentle slopes (0.3°~5°) and near 27.5℃ SST. By contrast, the suitability of Qi’ao Island was dominated by anthropogenic pressure, with the population density, land use, and salinity exerting the strongest influence and the suitability elevated at lower population densities (approx. <650 people/km2) and intermediate salinity and temperature ranges (19.3‰ and 26℃, respectively). HMSI-based zoning identified substantially more high- and mid-suitability areas in Gaoqiao than on Qi’ao Island under the current land-use regimes. Methodologically, HMSI does not constitute an additional mathematical transformation but denotes the MaxEnt probability surface produced when anthropogenic predictors are included. This naming clarifies the interpretation and encourages the explicit consideration of human pressures in habitat assessments. This study further highlights data-scale limitations, potential sources of uncertainty from resampling coarse marine datasets and anthropogenic proxies, and the distinction between current-condition suitability and paleo- or pre-disturbance potential suitability. By coupling MaxEnt with representative human activity indicators, this strategy provides a practical and interpretable pathway to better inform the spatial prioritization of mangrove conservation and restoration in contemporary socio-environmental contexts. The HMSI approach offers managers a scalable tool to balance ecological suitability with anthropogenic constraints when planning interventions.
Coastal areas with dense populations and concentrated urban development face ecological and environmental issues such as pollution from emerging contaminants, with a large number of land-based pollutants being transported to the ocean via the land–sea interaction zone. Pharmaceutical and personal care products (PPCPs), which are not easily degraded in groundwater, have bioaccumulative and chronic toxicity properties that pose a threat to the health of ecosystems in the land–sea interaction zone. Moreover, PPCPs in this zone may be transported to the ocean via submarine groundwater discharge and can thereby potentially harm coastal aquatic organisms and the marine environment. Therefore, given that the coastal zone is a key node for land–sea integration and a strategic location for the scientific coordination of development and protection, further attention to its pollution by PPCPs is urgently required. The purpose of this study was to explore the behavioral characteristics of PPCPs in groundwater bodies in the land–ocean interzone of South China. In total, 60 groundwater samples were collected from Tangjiawan Town in Zhuhai City in September 2021, October 2022, and March 2023, respectively. The samples and data were analyzed using experimental and mathematical statistical methods, respectively. The following results were found: 1) During the wet season (April–October), six types of PPCPs were detected in the study area: sulfamethoxazole, sulfamethazine, sulfadimidine, cimaterol, carbamazepine, and caffeine. During the dry season (November–March of the following year), five types of PPCPs were detected: sulfamethoxazole, sulfadimidine, carbamazepine, caffeine, and atrazine. The concentrations of sulfamethoxazole, sulfamethazine, carbamazepine, and caffeine exhibited significant seasonal variations (P < 0.05). The rainfall-facilitated leaching or dilution of PPCPs in groundwater was the main cause of the seasonal differences in PPCP mass concentration. 2) Caffeine was a potential PPCP pollutant that could be discharged into the sea. The spatial variation in caffeine showed a decreasing trend as it moved from upstream to downstream of the watershed, nearing the sea. The flux of caffeine from submarine groundwater discharge into the sea along the unit length of the Zhuhai coastline was estimated to be approximately 33.2 μg/d. 3) The quantification of tritium (3H) isotopes in the groundwater revealed that the values at most sampling points were below 2 TU, indicating that the age of the groundwater can reach approximately 30 years. This is due to the mixing effect of residual groundwater in the aquifer medium and precipitation recharge. Using 3H dating software, a preliminary analysis of the changes in carbamazepine and caffeine contents in the groundwater over the past three decades revealed that the concentration of carbamazepine exhibited a decreasing trend, whereas that of caffeine showed a fluctuating downward trend, which was significantly influenced by annual precipitation and generally followed the same variation trend as annual precipitation. The results of this study can help to inform strategies for the prevention and management of groundwater pollution in the South China land–ocean interzone and provide a theoretical basis for the protection and sustainable utilization of groundwater resources.
Carbonate dissolution, a key process in the global carbon cycle, sequesters large quantities of atmospheric CO2 and directly regulates inorganic carbon fluxes from terrestrial, river, and ocean ecosystems. Therefore, the accurate quantification of carbonate dissolution rates is essential for refining global carbon cycle models. Although carbonate dissolution rates and their influencing factors have been extensively studied in southwestern karst regions in China, such research in subtropical southern China remains limited, especially regarding the dissolution characteristics, environmental drivers, and dissolution mechanisms under different vegetation types and soil depths. This limits the accuracy of regional and global carbon sink assessments, as the unique environmental conditions in southern China may drive distinct carbonate dissolution dynamics compared with those in the southwestern parts of the country. To address this knowledge gap, we focused on key scientific questions regarding carbonate dissolution characteristics, environmental controlling factors, and dissolution mechanisms under different vegetation types and soil depths in the subtropical karst region of northern Guangdong. We used the dissolution tablet method, a reliable technique for simulating natural rock weathering, to measure the dissolution rates across four burial positions (30 cm above ground, 0 cm at the ground surface, 20 cm below ground, and 50 cm below ground) under two dominant vegetation cover types (evergreen broad-leaved forest and coniferous forest) in the Shimentai National Nature Reserve, a typical karst area in northern Guangdong. The following three critical results were found: (1) The vegetation type significantly affected the carbonate dissolution rate and carbon sink intensity. The average dissolution rate under the evergreen broad-leaved forest (204.4 ± 238.7 g·m-2·a-1) was approximately 7.5 times higher than that under the coniferous forest (27.5 ± 20.1 g·m-2·a-1). Correspondingly, the karst carbon sink intensity under the broad-leaved forest (54.6 ± 63.8 g C·m-2·a-1) was approximately 7.4 times greater than that under the coniferous forest (7.3 ± 5.4 g C·m-2·a-1). (2) The dissolution rate increased significantly with increasing soil depth. The rate at 50 cm below ground (282.4 ± 313.2g·m-2·a-1) was 5 times higher than that at the ground surface (57.5 ± 57.5 g·m-2·a-1) and 2.4 times higher than that at 20 cm below ground (119.5 ± 102.9 g·m-2·a-1), highlighting deep soil as being a hot spot for karst carbon sequestration in southern China. (3) The soil temperature was the core environmental factor regulating the dissolution rate at the small watershed scale, showing a significant negative correlation with this parameter (p < 0.01). The soil temperature decreased with increasing soil depth, and this cooler microenvironment promoted carbonate dissolution, indicating that warming may inhibit rock weathering in the subtropical context of southern China, a pattern distinct from that of temperate regions. This study provides critical in situ data on the carbonate dissolution rate and karst carbon sink intensity in the subtropical karst region of southern China, addressing the information gap in this understudied area. By identifying vegetation type and soil temperature as the key controlling factors and elucidating the mechanism of depth-dependent carbonate dissolution, our findings contribute to the development of region-specific carbonate weathering models for subtropical karst systems. This study also supports more accurate regional carbon sink assessments and provides science-based strategies for enhancing natural carbon sequestration in karst ecosystems of southern China.
Coral reefs, which are among the oldest and most biodiverse ocean ecosystems, play irreplaceable roles in sustaining global fishery resources and protecting coastal areas and biological habitats. However, with climate change and human activities threatening their survival, replacing traditional rigid coastal protection structures with ecofriendly alternatives is of urgent importance. In this study, we focused on the actual uneven topographies of coral reefs, which can more accurately simulate the impact of complex seabed morphologies on wave propagation than traditional simplified topographies can. Through physical modeling experiments, the hydrodynamic effects of a new porous column-type breakwater on regular wave propagation were explored. Currently, research on the influence of such structures (particularly new porous and permeable structures) on the wave propagation characteristics in complex uneven topographies is insufficient and requires further supplementation. The experiments were performed in a wave tank of 45 m length, 0.8 m width, and 1.0 m height, following a Froude similarity scale of 1:40. The breakwater was made up of 3D-printed cylindrical units, with adjustable wall perforation rates (n = 0 to 0.4), lateral spacing (D = 0.25 to 1.0 times d1), and positioning along the reef flat (l = 0 to 0.75 times the Lp). The testing parameters were the incident wave height (H = 0.04 to 0.1 m), reef flat water depth (hr = 0 to 0.075 m), and wave period (T = 1.0 to 1.75 s). Eighteen wave height gauges were used to record free-surface elevations, and the data on skewness, asymmetry, spectral energy, average wave height, and average water depth characteristics were analyzed. The following results were found: (1) According to the observed spatial variation in wave spectral energy along the reef, the wave energy was mainly concentrated at the primary frequency (f = 0.667 Hz) before reaching the reef, with second harmonic energy being slightly present. As waves propagated from the open sea toward the shore and reached the reef, they underwent shallow water transformation, nonlinear enhancement, and increased high-order harmonic energy. After the waves broke, the wave energy decayed rapidly, and the energy near the primary frequency continually decreased owing to wave-breaking losses. Compared with that in the no-breakwater scenario, the wave energy near the primary frequency in the nearshore region with the column-type breakwater was significantly decreased. (2) At the end of the reef flat, the average wave height in the scenario with the breakwater was slightly larger than that without the structures when the incident wave height was small. However, when the incident wave height was large, the average wave height was smaller with the breakwater present. In the no-breakwater scenario, the average water level on the reef flat was higher than that with the breakwater present. (3) When the reef flat depth was small, the presence of the breakwater had little effect on the average wave height. However, when the reef flat depth was 0.075 m, the average wave height fluctuated noticeably on the reef flat. At the end of the reef flat, the average wave height with the breakwater present was smaller than that without it for the same reef flat depth. At measurement point G18, the average water level without the breakwater was greater than that with the structures present, and the differences between the two at the reef flat end gradually decreased with increasing reef flat depth. (4) Compared with the other wave parameters, the wave period had a less regular impact on the average wave height and water level. On the reef flat, the average water level was generally lower for shorter periods than for longer periods, and the average wave height and water level fluctuations with the breakwater were more concentrated. (5) The different arrangement methods and wall perforation rates significantly affected the hydrodynamic characteristics along the reef flat, whereas the wall perforation rate had a limited impact on overall wave energy transmission.
Constructing ecological networks is an effective means to ensure regional ecological security and enhance human ecological well-being. Guizhou is a karst mountainous tourism province in China, and one of the most severely affected regions by geological disasters. Therefore, establishing ecological networks to integrate the scattered ecological resources and spaces in the region and promoting regional ecological construction and industrial development is urgently required. In this study, Guanling County, Guizhou Province, was the research area, and the needs of human beings for ecological well-being were fully considered. Morphological spatial pattern analysis (MSPA) and landscape connectivity were used to identify and select core patches with high connectivity as ecological source areas. Ecological corridors and nodes were simulated using the circuit theory to construct an ecological network. Additionally, differentiated restoration strategies were proposed by integrating the lithology and distribution characteristics of geological disasters with the aim of maintaining ecological security in karst areas prone to geological disasters. The results show that: (1) Guanling County contains 28 ecological source areas (587.58 km2) that serve as key zones for supplying ecological resources and ecosystem services. These areas are discretely distributed, with dense geological hazard points surrounding the source areas, primarily located in contiguous forest regions in the eastern and western parts of the study area, where rocky desertification is low and provides favorable habitats for species. (2) Sixty ecological corridors (102.14 km) were identified in Guanling County, including 12 key (11.89 km), 27 important (57.11 km), and 21 general corridors (33.14 km). These corridors connect all ecological source areas, promote species dispersal, and maintain the overall connectivity of the ecosystems. Notably, the corridors in the northern and southeastern parts of the study area are surrounded by dense distributions of geological disaster points, such as landslides and debris flows, which severely affect the connectivity of the ecological corridors. (3) Thirty-six ecological pinch points and 38 ecological barrier points were crucial for maintaining regional ecological flow. Their discrete and partially overlapping distributions suggest significant interference from human activity in these areas. Prioritizing protection and restoration can help enhance ecosystem connectivity. Furthermore, 22 ecological breakpoints were identified, where intersecting road networks disrupted corridor connectivity, exacerbated landscape fragmentation, and posed serious threats to biological migration. Based on these findings, this study proposes a spatial optimization framework for the "three zones, two belts, and one system." The "three zones" are the rocky desertification restoration zone in the west, the ecological coordination zone in the center, and the agricultural enhancement zone in the east. The "two belts" are the Beipan River and Dabang River, which constitute the ecological barriers in Guanling County. The "one system" refers to the ecological connectivity system protection framework. After considering the prominent ecological issues in Guanling County and integrating the distribution characteristics of lithological and geological hazards, this study proposes spatially optimized layouts and targeted restoration strategies for different zones. These efforts aim to protect biodiversity, maintain ecosystem functions, and effectively regulate regional ecological security, ultimately achieving holistic ecosystem protection and sustainable development. This study provides a practical framework for future ecological network construction and restoration planning in karst regions.
The Pearl River Delta (PRD) was constructed as China’s first "National Forest City Cluster" in 2020. While ecological restoration projects have significantly increased vegetation coverage, a critical question remains: has the increase in "green quantity" (Leaf Area Index, LAI) effectively translated into "carbon quality" (Gross Primary Productivity, GPP)? Existing studies have often focused on pixel-scale vertical processes, neglecting horizontal ecological flows within the landscape. This study introduced an Ecological Spatial Network (ESN) perspective to construct an analytical framework for carbon sequestration in urban ecosystems. The primary objective was to evaluate the spatiotemporal evolution of the degree of coupling between GPP and LAI from 2015 to 2020 and to quantify how network topological characteristics drive these functional changes, specifically differentiating between Ecological Construction Sources (artificial/restored areas) and Natural Development Sources (remnant natural patches). This study utilized multi-source data, including MODIS GPP, high-quality reprocessed LAI (HiQ-LAI), and meteorological data. First, Morphological Spatial Pattern Analysis (MSPA) and Minimum Cumulative Resistance (MCR) models were employed to identify ecological sources and extract corridors, constructing ESNs for 2015 and 2020. Complex network theory was applied to calculate topological indices (e.g., Betweenness Centrality, Modularity). Second, the degree of coupling between GPP and LAI was quantified using linear regression. Finally, a Random Forest (RF) algorithm combined with the SHapley Additive exPlanations (SHAP) model was used to quantitatively attribute the variations in GPP-LAI coupling to network topology and environmental factors. The findings reveal significant spatiotemporal heterogeneity: (1) Network Optimization: The PRD forest city construction significantly optimized the network structure. From 2015 to 2020, the number of nodes and corridors increased by more than 20%, and the average path length decreased by 18.6%. This indicates that the new small-scale patches acted as "stepping stones," enhancing the overall physical connectivity of the landscape. (2) Decoupling Phenomenon: Although regional LAI and GPP showed an overall increasing trend, a "quantity-quality decoupling" phenomenon was observed, particularly in ecological barrier and buffer zones. In these areas, rapid LAI growth did not synchronously enhance the GPP. (3) Source Heterogeneity: There is a distinct divergence between the source types. Ecological Construction Sources effectively improved GPP in low-vegetation areas but exhibited diminishing returns and stronger decoupling in high-greenness areas owing to immature community structures. In contrast, Natural Development Sources demonstrated a higher carbon sink potential and stability in the high-greenness zones. (4) Driving mechanisms:–The RFA-SHAP analysis identified distinct drivers for different sources. For Ecological Construction Sources, the degree of coupling is primarily constrained by precipitation (environmental stress) and network modularity (spatial isolation), characterizing a "physiologically limited" model. Conversely, Natural Development Sources are driven by GPP base levels and Closeness Centrality, characterizing a "topologically enhanced" model where central network positions facilitate stability and resource flow. This study confirms that simply increasing green quantity is insufficient for maximizing carbon sequestration in urban agglomerations. The effectiveness of carbon fixation is regulated nonlinearly by the topological structure of the ecological network. The study provides theoretical support for a differentiated optimization strategy: future ecological planning should prioritize reducing the modularity (fragmentation) of artificial construction sources by adding connecting corridors to break "ecological islands," while strictly protecting the central hub status of natural sources to maintain their functional stability. This network-based approach offers a precise scientific basis for transitioning urban ecological restoration from "increment-oriented" to "quality-oriented" management.
As the spatial mnemonics of human civilization, place names transcend their basic function as geographical identifiers to embody historical narratives, cultural genes, and societal values. Within the contemporary context of globalization and urbanization, place names participate dynamically in socio-spatial construction, reflecting power dynamics and shaping the formation of identity. Since the 1980s, the emergence of critical toponymy influenced by neo-Marxist geography has challenged the traditional perception of place names as neutral signifiers, reconceptualizing them as spatial representations of power struggles. Despite the long tradition of toponymic study in China, modern critical inquiry gained momentum only in the early 21st century, primarily in response to urban toponymic chaos. However, this development is embedded in China’s unique institutional and cultural contexts, navigating between market-driven cultural development and state-led principles of historical preservation. In this study, the author systematically compared the research trajectories of Sino-Western critical toponymy and analyzed their divergent theoretical frameworks, research priorities, and practical pathways rooted in distinct historical experiences and sociocultural backgrounds. With its origins in post-colonial and liberal urban contexts, Western critical toponymy has evolved from a macro-level political critique to incorporating cultural memory and spatial justice, focusing on deconstructing power and amplifying marginalized voices. By contrast, Chinese scholarship has progressed from initial institutional reflection toward analyzing power–culture relationships and, more recently, to addressing cultural heritage preservation and cross-cultural dialogue, demonstrating a problem-solving orientation aimed at balancing development with tradition under state guidance. Building on this comparative analysis, a systematic and prospective localized research framework for China was constructed in this study. This framework integrates the spatial critique of neo-Marxist geography with traditional Chinese toponymic ethics, focusing on four core practical contradictions inherent to Chinese toponymic governance: development versus preservation, market forces versus cultural integrity, diversity versus standardization, and digital technology versus traditional continuity. It proposes methodological innovation through interdisciplinary approaches and context-adapted technologies and advocates for a practical governance model characterized by multi-stakeholder collaboration and digital empowerment. The primary contribution of this study lies in its systematic delineation of Sino-Western differences, moving beyond isolated theoretical discussions. The proposed framework not only facilitates theoretical innovation and practical application within China but also challenges Western theoretical hegemony by offering a non-Western perspective. It provides valuable insights for other developing countries seeking compatible paths for cultural continuity and modernization, thereby enriching the global discourse on critical toponymy.
