Search Results (10,652)

The contradiction between ecological environment protection and economic development in the Yangtze River Basin has become increasingly prominent in recent years, which seriously limits the sustainable development of the basin. Research on water environment changes of the main tributaries of the Yangtze River helps explore measures to improve the ecological environment of the Yangtze River Basin. In this study, based on the theory of behavioral science in modern management, water quality data in the field were collected, and the farmers’ garbage stacking behavior was also investigated in the water source area of the Dabie Mountains. The results showed that ammonia nitrogen (AN), chemical oxygen demand (COD), total organic carbon (TOC), and total dissolved solids (TDS) in the water bodies showed an overall negative correlation with the distance of water quality collection sites from the garbage stacking point. AN was the most important pollution element affecting the rural water quality in the water source area of the Dabie Mountains. The unsuitable garbage stacking locations and the farmers’ behavior of dumping garbage along the riverbanks were the important causes of water pollution. The garbage stacking locations were optimized and designed by using a GIS spatial analysis tool and a developed suitability evaluation model for the garbage stacking points. The optimized garbage stacking locations were more suitable for improving the local water environment, and their average suitability values increased to 2.01 times and 2.94 times that of the original stacking locations in Kanxiawan and Lengshuigou, respectively. This study can be used as a scientific and methodological reference for improving the rural water environment in the water source area of the Dabie Mountains and in other similar regions in the world. Full article

Food security is an important foundation of national security. Since China entered a new era in 2012, the supply of agricultural and animal husbandry products in Qinghai has continuously enhanced. However, the implementation of ecological policies such as Grain for Green and Grassland Ecological Compensation restricted the cultivation and grazing areas. At the same time, with the improvement in living standards and food consumption demand of local residents, the contradiction between human beings and land has become increasingly prominent. It is necessary to analyze the balance between food supply and demand to evaluate food security. This study used supply–demand analysis and spatial autocorrelation analysis based on county-level statistical data on production and consumption collected through random sampling surveys to reveal the characteristics of the production and consumption of the main food types in Qinghai during 2012–2022 as well as to analyze the food self-sufficiency changes and their spatial clustering features. The results showed that the regions with higher grain and meat production in Qinghai were concentrated in the northeast in the past decade, while the regions with higher consumption were mainly in the counties with larger populations. At the county level, grain could not achieve self-sufficiency, except in northeastern Qinghai; meat was self-sufficient in most counties. Through regional allocation, Qinghai had achieved grain and meat self-sufficiency at the provincial level. The self-sufficiency of grain and meat showed obvious clustering, with high-value clusters of grain self-sufficiency and low-value clusters of meat both distributed in the provincial capital and surrounding areas, which were related to the adjustment of urban residents’ dietary structure from staple foods to diversified foods. This study provides a scientific basis for decision makers when adjusting the agricultural and animal husbandry structure as well as the dietary structure of residents to ensure food security and the sustainable utilization of land resources. Full article

The humanities are often criticised for lacking a way through from the complexity they reveal to the challenges they might hope to address. In the face of the accelerating biodiversity crisis, we present two projects that aim to respond to the limitations and lack of interdisciplinary conversations in conservation and in humanities research. At field sites in Finnish Lapland and the French Pyrenees, we document how conservation humanities research can be used to develop a more pragmatic and integrated transdisciplinary approach to conservation in remote and fragile landscapes. Firstly, we show how sound and soundscapes are important subjects of study in both conservation biology and the humanities. We also highlight their importance to conservation planners and policy makers seeking to preserve biodiversity and landscape characteristics, as well as our social values thereof, which, together, are critical to their survival. Secondly, we demonstrate how integrated conservation humanities methods can lead to rich local-level insights on key conservation themes that can then be scaled via existing large-scale acoustic monitoring and spatial datasets to support decision making across much larger areas. Finally, we highlight how the participatory mapping approach at the core of our integrated methodology shows potential to generate change in the real world and meet the classic operationalisation challenge that academia faces. Full article

East Dongting Lake is an important habitat for migratory birds. Accurately counting the number of migratory birds is crucial to assessing the health of the wetland ecological environment. Traditional manual observation and low-precision methods make it difficult to meet this demand. To this end, this paper proposes a weighted feature fusion network based on multi-level supervision (MS-WFFNet) to count migratory birds. MS-WFFNet consists of three parts: an EEMA-VGG16 sub-network, a multi-source feature aggregation (MSFA) module, and a density map regression (DMR) module. Among them, the EEMA-VGG16 sub-network cross-injects enhanced efficient multi-scale attention (EEMA) into the truncated VGG16 structure. It uses multi-head attention to nonlinearly learn the relative importance of different positions in the same direction. With only a few parameters added, EEMA effectively suppresses the noise interference caused by a cluttered background. The MSFA module integrates a weighted mechanism to fully preserve low-level detail information and high-level semantic information. It achieves this by aggregating multi-source features and enhancing the expression of key features. The DMR module applies density map regression to the output of each path in the MSFA module. It ensures local consistency and spatial correlation among multiple regression results by using distributed supervision. In addition, this paper presents the migratory bird counting dataset DTH, collected using local monitoring equipment in East Dongting Lake. It is combined with other object counting datasets for extensive experiments, showcasing the proposed method’s excellent performance and generalization capability. Full article

Team dynamics significantly influence the outcomes of modern football matches. This study employs an information-theoretical approach, specifically causal emergence, combined with graph theory to explore how team-level dynamics arise from complex interactions among players, utilizing tracking data from 34 J-League matches. We focused on how collective behaviors arise from the interdependence of individual actions, examining team coordination and dynamics through player positions and movements to identify emergent properties. Specifically, we selected relative distance to the field’s center, center of mass (CoM) and clustering coefficients based on velocity similarity and inverse distance as macroscopic features to capture the key aspects of team structure, coordination, and spatial relationships. Relative distance and CoM represent the collective positioning of the team, while clustering coefficients provide insights into localized cooperation and movement similarity among the players. The results indicate that average causal emergence with relative distance and CoM as a macroscopic feature across entire games shows a strong correlation with differences in ball possession rate between home and away teams. In contrast, clustering coefficients based on inverse distance and velocity similarity showed moderate to weak correlations with ball possession rate, indicating that these metrics may capture localized interactions that are less directly tied to team-level emergent behavior compared to CoM. Additionally, relative distance and CoM as macroscopic features yield higher causal emergence in attacking phases than in defending phases before shooting, suggesting that the collective positioning of players may play a more significant role in facilitating successful attacks than in defensive stability. This study offers a novel perspective on team coordination in football, suggesting that effective team coordination may be characterized by emergent patterns arising from collective positioning. These findings have practical implications for understanding coordinated team behaviors and inform coaching and performance analysis focused on enhancing team dynamics. Full article

Mesoscale convective systems (MCSs) are major contributors to extreme precipitation in urban agglomerations, exhibiting complex characteristics influenced by large-scale climate variability and local urban processes. This study utilizes a high-resolution MCS database spanning from 2001 to 2020 to investigate the spatiotemporal variations of MCSs in the Yangtze River Delta (YRD) urban agglomeration and assess their response to urbanization. Our analysis reveals significant spatial and temporal differences in MCS activities during the warm season (April to September), including initiation, movement, and lifespan, with notable trends observed over the study period. MCSs are found to contribute substantially to hourly extreme precipitation, accounting for approximately 60%, which exceeds their contribution to total precipitation. Furthermore, the role of MCSs in extreme precipitation has also increased, driven by the intensification of MCS-induced extreme rainfall. Additionally, MCS characteristics exhibit significant regional differences. Urban areas experience more pronounced changes in MCS activity and precipitation compared to the surrounding rural regions. Specifically, urbanization contributes approximately 16% to MCS-related precipitation and 19% to MCS initiation, highlighting its substantial role in enhancing these processes. Moreover, mountainous areas and water bodies surrounding cities show stronger trends in certain MCS characteristics than urban and rural plains. This may be attributed to climatological conditions that favor MCS activity in these regions, as well as the complex interactions between urbanization, topography, and land–sea contrasts. These complicated dynamics warrant further investigation to better understand their implications. Full article

The purpose of this paper is to introduce the perspective of the “socio-spatial” relationship, to construct a theoretical analysis framework for the reconstruction of rural cultural space, and to explore effective strategies for the reconstruction of cultural space in the context of rural revitalization. Taking Zhuma Town as a case study, this study applies qualitative research methods, combining inductive synthesis, interpretive analysis, and literature review to analyze in depth the phenomenon of the revival of its camellia culture and the reconstruction of cultural space. It is found that the transformation of vernacular culture is the fundamental motive for the reconstruction of rural cultural space, which is embodied in Zhuma Town, as the camellia culture has gone through different stages of development, which promotes the transformation of cultural space from traditional to modern, and from single-function to composite function. On this basis, the design strategies of “landscape inheritance and functional regeneration”, “connotation remodeling and cultural value-added”, and “role transformation and coordination and cooperation” are proposed. The research results provide theoretical references and practical guidance for the reconstruction of contemporary rural cultural space, help promote the construction of high-quality rural habitat, enrich the knowledge system of rural cultural space research in interdisciplinary background, and are of great significance in awakening the cultural self-consciousness of the vernacular society and promoting the reconstruction of rural cultural values. Full article

Forests, with their ecosystem services capabilities, play a critical role in absorbing carbon dioxide from the atmosphere, positioning forest carbon sinks as important components of China’s strategy to achieve carbon neutrality. However, due to the spatial correlation inherent in forest carbon sink dynamics, the development of these sinks cannot be fully segmented by region. Due to the interconnected nature of forest ecosystems, carbon sink growth exhibits regional interactions rather than isolated developments, necessitating a transregional perspective to comprehensively understand carbon sinks in China. This study derives a spatial effect model to analyze carbon sink growth and assess the transregional spillover effects of forest carbon sink growth. The analysis is based on panel data from 26 provinces in China from 2003 to 2021. The results show that the forest carbon sink growth in one province is often influenced by the neighboring regions, highlighting significant transregional spillover effects. Policies, e.g., Carbon Emission Trading (CET), and forest management practices like tending were found to positively influence the local forest carbon sink growth and generate substantial positive spillover effects in the neighboring provinces. Our results indicate that the total effect of the implementation of the CET policy leads to a 3% increase in carbon sink growth across the 26 provinces in China over the study period from spatial DID estimation. In contrast, urbanization and the increasing value-added services associated with economic growth negatively impact forest carbon sink growth both locally and in neighboring regions. These findings underscore the necessity of a coordinated national strategy to enhance forest carbon sinks, integrating both direct and indirect regional effects. Aligning economic development with carbon sink goals will enable China to effectively balance environmental and economic priorities. Policy recommendations are provided to improve CET mechanisms and foster regional collaboration for sustainable forest management. Full article

The European rabbit (Oryctolagus cuniculus) presents a significant conservation and management challenge in Greece. While it has been listed in national biodiversity assessments, its population dynamics on the island of Lemnos demonstrate the characteristics of a highly adaptable and rapidly expanding species, exerting substantial ecological and economic impacts. Addressing this issue requires a spatially explicit understanding of its distribution patterns and habitat preferences, particularly given its extensive population growth over the past three decades. To this end, we conducted 40 field surveys across the island, documenting 1534 presence records of the species. We applied Kernel Density Estimation, Getis-Ord Gi *, and Anselin Local Moran’s I to identify the spatial distribution patterns and significant hotspots. A spatial lag model was used to quantify hotspot intensity and clustering dynamics, while abiotic, biotic, and anthropogenic factors were analyzed to assess habitat associations. Our results revealed that rabbit hotspots are predominantly concentrated in fertile lowland agroecosystems, with nearly 60% of high-density areas overlapping conservation zones. Soil and field conditions, grazing-supporting landscapes, and arable and subsidized agricultural areas emerged as significant predictors of O. cuniculus presence. The observed spatial dependencies indicated that while hotspot intensities and clustering dynamics are influenced by the conditions in neighboring areas, habitat characteristics remain fundamental in shaping their distribution, highlighting the broader landscape-scale spatial patterns affecting rabbit populations. These findings underscore the necessity of adopting spatially informed management strategies that mitigate agricultural impacts while accounting for interconnected spatial dynamics, providing a foundation for informed decision-making to manage rabbit populations while balancing conservation and agricultural priorities. Full article

Despite the huge progress achieved in the optimization of perovskite solar cell (PSC) performance, stability remains a limiting factor for technological commercialization. Here, a study on the photovoltaic, structural and morphological stability of semi-transparent formamidinium lead bromide-based PSCs is presented. This work focuses on the positive role of 2D nanoscale layer passivation, induced by perovskite surface treatment with a mixture of iso-Pentylammonium chloride (ISO) and neo-Pentylammonium chloride (NEO). In situ X-ray diffraction (XRD) is applied in combination with atomic force microscopy (AFM), and the results are correlated to the devices’ photovoltaic performances. The superior power conversion efficiency and overall stability of the ISO-NEO system is evidenced, as compared to the un-passivated device, under illumination in air. Furthermore, the role of the ISO-NEO treatments in increasing the morpho-structural stability is clarified as follows: a bulk effect resulting in a protective role against the loss in crystallinity of the perovskite 3D phase (observed only for the un-passivated device) and an interface effect, being the observed 2D phase crystallinity loss spatially localized at the interface with the 3D phase where a higher concentration of defects is expected. Importantly, the complete stability of the device is achieved with the passivated ISO-NEO-encapsulated device, allowing us to exclude the intrinsic degradation effects. Full article

The dynamics of Land Use/Land Cover changes are crucial to environmental sustainability, socio-economic development, and spatial planning. These changes stem from complex interactions between human activities, natural processes, and policies. In recent decades, LULC transformations have been linked to global challenges such as biodiversity loss, climate change, and resource degradation. Key drivers include urban sprawl, agricultural expansion and abandonment, and deforestation, emphasizing the need for effective frameworks to monitor and assess their impacts. This study investigates Land Use/Land Cover (LULC) changes in Tuscany (Italy) over the period from 2007 to 2019. To achieve this, statistical analyses were conducted to quantify variations in LULC across different classes and administrative territories represented by provincial local authorities. Specifically, data spanning five temporal intervals (2007, 2010, 2013, 2016, and 2019) enabled a comprehensive comparative analysis of spatial persistence in LULC patterns. Changes were assessed using a statistical approach based on Odds Ratios (OR). Additionally, Generalized Linear Models (GLMs) at the provincial level were employed to facilitate one-to-many provincial comparisons and to evaluate the statistical significance of observed LULC changes. The analysis revealed that certain classes exhibit a greater susceptibility to changes compared to others. Specifically, the classes categorized under ’Artificial Surfaces’ (LC_100) were, on average, 6.7 times more likely to undergo changes than those classified as ’Agricultural Areas’ (LC_200) and 11 times more likely than those under ’Forest and Semi-natural Areas’ (LC_300). Over time, the areas classified as artificial territories have exhibited a progressively decreasing probability of change. Notably, during the first update period (2007–2010), these areas were 3.5 times more susceptible to change compared to the most recent update period (2016–2019). An additional significant finding emerged from the statistical comparison of LULC changes across administrative regions governed by different authorities (Provinces). These findings underscore the potential of using administrative indicators and morphological parameters to analyze LULC change trends. The proposed approach provides a robust framework for interpreting territorial resilience and informing spatial planning strategies effectively. Full article

Residential segregation, which has been centered on race and ethnicity, has recently expanded to include income and social class as social inequality has increased. In particular, South Korea is one of the countries where social inequality is increasing as a result of economic growth. Existing studies have considered a relationship between redevelopment and residential segregation with respect to income, but there is a lack of factual evidence incorporating analysis in terms of spatial units. We analyzed patterns of low-income residential segregation (LiRS) in South Korea from the macro and micro perspectives to determine the net effect of redevelopment on this phenomenon. By classifying recipients of the National Basic Livelihood Security System (NBLSS) as low-income people, we measured LiRS using the dissimilarity index, the isolation index, the location quotient, and local Moran’s I (LISA) in seven metropolitan cities in South Korea between 2011 and 2020. We explored the net effect of redevelopment on LiRS using propensity score matching (PSM), and we estimated that redevelopment would reduce LiRS by 0.0289. The findings reveal that low-income residential segregation declined from 2011 to 2020. PSM analysis indicates that redevelopment mitigates LiRS. This study provides insights into the need to consult with those responsible for low-income housing policies to ensure the positive impact of redevelopment on LiRS. Full article

The “Village Merger and Resettlement” policy, as an adjustment of rural living arrangements and spatial organization, addresses the rural population outflow against the backdrop of global urbanization and industrialization. It has profound impacts on agricultural resource allocation, technological innovation, and carbon emissions, playing a significant role in achieving green and low-carbon development alongside high-quality agricultural advancement. This paper conducts an empirical analysis based on panel data from 30 provincial regions in China from 2001 to 2022 (excluding Tibet, Hong Kong, Macau, and Taiwan) to examine the impact of the “Village Merger and Resettlement” policy on agricultural carbon emissions. It explores the mediating effects of agricultural informatization and the integration of agricultural industries and analyzes the moderating roles of government environmental regulations and public environmental participation. The findings indicate that the “Village Merger and Resettlement” policy significantly suppresses agricultural carbon emissions, with the effects being more pronounced in major grain-producing areas, regions with flat terrain, convenient transportation, and higher levels of technology and labor, as well as on the east side of the Hu Huanyong Line, where the degree of agricultural industrial restructuring is lower and government policy enforcement is stronger. The mediation analysis reveals that the processes of agricultural informatization and industry integration both play positive transmission roles in the policy’s impact on reducing agricultural carbon emissions. The moderation analysis shows that compulsory government environmental regulations have a negative moderating effect on the policy’s carbon emission suppression, while public environmental participation has a positive moderating effect. Therefore, in implementing the “Village Merger and Resettlement” policy, it is necessary to tailor strategies to local conditions, make full use of agricultural informatization resources, reasonably plan the integration of agricultural industries, and accurately grasp the roles of environmental regulations to promote the positive effects on green, low-carbon, and high-quality agricultural development. Full article

The accurate and efficient detection of steel surface defects remains challenging due to complex backgrounds, diverse defect types, and varying defect scales. The existing CNN-based methods often struggle with capturing long-range dependencies and handling complex background noise, resulting in suboptimal performance. Meanwhile, although Transformer-based approaches are effective in modeling global context, they typically require large-scale datasets and are computationally expensive, limiting their practicality for industrial applications. To address these challenges, we introduce a novel attention-based salient object detector, called the ASOD, to enhance the effectiveness of detectors for strip steel surface defects. In particular, we first design a novel channel-attention-based block including global max/average pooling to focus on the relevant channel-wise features while suppressing irrelevant channel responses, where maximizing pooling extracts the main features of local regions, while removing irrelevant features and average pooling obtain the overall features while removing local details. Then, a new block based on spatial attention is designed to emphasize the area with strip steel surface defects while suppressing irrelevant background areas. In addition, a new cross-spatial-attention-based block is designed to fuse the feature maps with multiple scales filtered through the proposed channel and spatial attention to produce features with better semantic and spatial information such that the detector adapts to strip steel defects of multiple sizes. The experiments show that the ASOD achieves superior performance across multiple evaluation metrics, with a weighted F-measure of 0.9559, an structure measure of 0.9230, a Pratt’s figure of meri of 0.0113, and an mean absolute error of 0.0144. In addition, the ASOD demonstrates strong robustness to noise interference, maintaining consistently high performance even with 10–20% dataset noise, which confirms its stability and reliability. Full article

Coastal erosion is a critical environmental challenge in the Upper Gulf of Thailand, driven by both natural processes and human activities. This study analyzes 35 years (1988–2023) of shoreline changes using geoinformatics, machine learning algorithms (Random Forest, Support Vector Machine, Maximum Likelihood, Minimum Distance), and the Digital Shoreline Analysis System (DSAS). The results show that the Random Forest algorithm, utilizing spectral bands and indices (NDVI, NDWI, MNDWI, SAVI), achieved the highest classification accuracy (98.17%) and a Kappa coefficient of 0.9432, enabling reliable delineation of land and water boundaries. The extracted annual shorelines were validated with high accuracy, yielding RMSE values of 13.59 m (2018) and 8.90 m (2023). The DSAS analysis identified significant spatial and temporal variations in shoreline erosion and accretion. Between 1988 and 2006, the most intense erosion occurred in regions 4 and 5, influenced by sea-level rise, strong monsoonal currents, and human activities. However, from 2006 to 2018, erosion rates declined significantly, attributed to coastal protection structures and mangrove restoration. The period 2018–2023 exhibited a combination of erosion and accretion, reflecting dynamic sediment transport processes and the impact of coastal management measures. Over time, erosion rates declined due to the implementation of protective structures (e.g., bamboo fences, rock revetments) and the natural expansion of mangrove forests. However, localized erosion remains persistent in low-lying, vulnerable areas, exacerbated by tidal forces, rising sea levels, and seasonal monsoons. Anthropogenic activities, including urban development, mangrove deforestation, and aquaculture expansion, continue to destabilize shorelines. The findings underscore the importance of sustainable coastal management strategies, such as mangrove restoration, soft engineering coastal protection, and integrated land-use planning. This study demonstrates the effectiveness of combining machine learning and geoinformatics for shoreline monitoring and provides valuable insights for coastal erosion mitigation and enhancing coastal resilience in the Upper Gulf of Thailand. Full article