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To achieve sustainable urban development, it is essential to gain insight into the spatial and temporal differentiation characteristics and the driving mechanisms of the urban thermal environment (UTE). As urbanization continues to accelerate, human activity and landscape configuration and composition interact to complicate the UTE. However, the differences in UTE-driven mechanisms at different stages of urbanization remain unclear. In this study, the UTE of Shenyang was measured quantitatively by using the land surface temperature (LST). The spatial and temporal differentiation characteristics were chronologically studied using the standard deviation ellipse (SDE) and hotspot analysis (Getis–Ord Gi*). Then, the relationship between human activities, landscape composition and landscape configuration and LST was explored in a hierarchical manner by applying the geographical detector. The results show that the UTE in Shenyang continues to deteriorate with rapid urbanization, with significant spatial and temporal differentiation characteristics. The class-level landscape configuration is more important than that at the landscape level when studying UTE-driven mechanisms. At the class level, the increased area and abundance of cropland can effectively reduce LST, while those of impervious surfaces can increase LST. At the landscape level, LST is mainly influenced by landscape composition and human activities. Due to rapid urbanization, the nonlinear relationship between most drivers and LST shifts to near-linear. In the later stage of urbanization, more attention needs to be paid to the effect of the interaction of drivers on LST. At the class level, the interaction between landscape configuration indices for impervious surfaces, cropland and water significantly influenced LST. At the landscape level, the interactions among the normalized difference building index (NDBI) and other selected factors are significant. The findings of this study can contribute to the development of urban planning strategies to optimize the UTE for different stages of urbanization.

Megaprojects need to be developed in a socially responsible manner as they may otherwise, like some mega water transfer (MWT) projects, cause ecological damage, environmental pollution, labor conflict, and other problems. Socially responsible collective action (SRCA) can be measured through intentions to take collective action (internal driving mechanisms) and behaviors to engage in collective action (external driving mechanisms). This research aims to develop and validate a network governance model to explore how SRCA, in the context of MWT projects, is enhanced. Data were collected from 365 respondents involved in MWT projects via an online survey. System dynamics (SD) was used to establish the system flow diagram model. Thereafter, Vensim PLE software was used to perform simulation and sensitivity analyses of the model. The results demonstrate that the network governance model explains how to enhance the SRCA of stakeholders in MWT projects. The main findings indicate that external driving mechanisms positively impact the SRCA during the entire project lifecycle, with values fluctuating around the initial level from the early to the mid-late stages, with small fluctuation. Internal driving mechanisms also positively impact SRCA, with values continuously increasing from the early to the mid-late stage.

Against the backdrop of rapid development in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA), the spatiotemporal evolution of Production-Living-Ecological Land (PLEL) in its peri-urban regions has emerged as a critical research focus for achieving regional coordinated development. This study employs Huiyang District as a representative case study area, utilizing multisource geospatial data and analytical methodologies including land use dynamic degree, land transfer matrix, binary logistic regression, and ROC analysis to systematically investigate PLEL’s spatiotemporal evolution patterns and underlying driving mechanisms from 2007 to 2023. The empirical results demonstrate that: (1) During the observation period, aggregate production and ecological land areas exhibited a declining trend, while living land manifested persistent expansion, reflecting accelerated urbanization process and intensified population concentration. Specifically, between 2007 and 2015, production and ecological land areas decreased significantly while living land expanded markedly, reflecting accelerated urbanization. From 2015 to 2023, the decline in production land substantially moderated, whereas ecological land diminution accelerated. Living land maintained a consistent expansion throughout both periods. (2) Spatial analysis revealed a stable concentric pattern emerged, characterized by living land at the urban core, encircled by production land, with ecological land occupying the peripheral zones. Notable land conversion dynamics were observed between ecological and production land, revealing the tension between conservation and development. Living land conversions to other categories remained negligible, with its expansion predominantly sourced from production land, suggesting urban expansion has largely occurred through agricultural land appropriation. (3) Driving factor analysis identified population size as the predominant influence. Following GBA development, the impact of population size on living land expansion intensified. Model validation through ROC curve analysis confirmed robust predictive performance. This research systematically elucidates PLEL’s spatiotemporal evolution patterns and driving mechanisms within a GBA peripheral urban unit, thereby contributing scientific insights for territorial spatial optimization in rapidly urbanizing regions.

Timely and accurate agricultural drought monitoring and drought-driven mechanism analysis in karst basins in the context of global warming are highly important for drought disaster monitoring and sustainable ecological development in a basin. In this study, based on MODIS data, meteorological and topographic data and land use data from 2001 to 2020, we used the Sen slope, the Mann–Kendall test and a geographic detector to explore the driving mechanisms of agricultural drought caused by climate change and human activities in the karst basin of southern China from 2001 to 2020. The results showed that (1) the spatial distribution of the TVDI in the karst basin in southern China has obvious regional characteristics, showing a decreasing trend from west to east. (2) According to the interannual trend of drought, the degree of drought in the South China karst basin exhibited a weakening trend over the last 20 years, with the most severe drought occurring in 2003. Regarding the seasonal change in the TVDI, drought in spring, summer and autumn exhibited a decreasing trend, while that in winter exhibited an increasing trend, and the drought intensity decreased in the following order: spring (0.58) > autumn (0.53) > summer (0.5) > winter (0.48). (3) Single-factor detection the results showed that rainfall, temperature and elevation were the main factors driving aridification in the study area; multifactor coupling (mean) drove drought in descending order: rainfall (q = 0.424) > temperature (q = 0.340) > elevation (q = 0.219) > land use (q = 0.188) > population density (q = 0.061) > slope (q = 0.057). Therefore, revealing the mechanism of agricultural drought in karst basins through the study of this paper has important theoretical significance and provides technical guidance for drought relief in karst areas.

The coastal zone, as a typical land-sea interaction area, has experienced significant changes in habitat quality under the dual influence of climate change and human activities. Identifying the land-sea differences in the mechanisms influencing habitat quality in the coastal zone is essential for the development of targeted ecological protection strategies. Based on the integrated habitat quality assessment results for the Jiangsu coastal zone from 2010 to 2020, kernel density curves and Optimal Parameter Geographic Detector (OPGD) were employed to investigate the land-sea differences in the composition, spatiotemporal variations, and driving mechanisms of habitat quality. The results indicate that, in terms of composition, low-quality habitats are mainly distributed on land, while areas with medium to high habitat quality are concentrated in the sea; in terms of spatiotemporal changes, from 2010 to 2020, habitat quality degradation in the Jiangsu coastal zone is primarily manifested as the expansion of low-quality terrestrial habitats into natural areas, as well as the transition of high-quality marine habitats into suboptimal habitats; in terms of driving mechanisms, changes in terrestrial habitat quality are primarily driven by human activities, whereas marine changes are mainly influenced by natural factors such as topography and hydrodynamics, with indirect disturbances from human activities observed in specific years. These findings provide a scientific basis for the targeted formulation of coastal zone ecological protection policies.

HighlightsIn-depth overview of the classification of one-dimensional (1D) micro/nanomotors and strategies for fabricating them are reviewed.Driving mechanisms and progress of 1D micro/nanomotors for applications are summarized.Challenges and future prospects of 1D micro/nanomotors are discussed.Due to their tiny size, autonomous motion and functionalize modifications, micro/nanomotors have shown great potential for environmental remediation, biomedicine and micro/nano-engineering. One-dimensional (1D) micro/nanomotors combine the characteristics of anisotropy and large aspect ratio of 1D materials with the advantages of functionalization and autonomous motion of micro/nanomotors for revolutionary applications. In this review, we discuss current research progress on 1D micro/nanomotors, including the fabrication methods, driving mechanisms, and recent advances in environmental remediation and biomedical applications, as well as discuss current challenges and possible solutions. With continuous attention and innovation, the advancement of 1D micro/nanomotors will pave the way for the continued development of the micro/nanomotor field.

Urbanization and industrialization have driven rapid socio-economic development, leading to a significant population shift from rural areas to cities. This demographic transition has resulted in substantial changes in rural settlements, presenting considerable challenges for rural revitalization. Given the spatial differentiation, it is crucial to analyze the spatiotemporal evolution patterns and driving mechanisms of rural settlements under various development scenarios and at multiple scales within a county. Such analysis is essential for rational planning and sustainable development. This study analyzes the spatial and temporal evolution patterns and driving mechanisms of rural settlements in Xunwu County, Jiangxi Province, China, using land use dynamics, hot and cold spot analysis, and center of gravity migration models. The Multiscale Geographically Weighted Regression Model (MGWR) is employed to explore their transformation driving mechanisms. The results show that during 2010–2020 in the study area, the total change rate of rural settlements was 39.82%, with a dynamic degree of 2.87%. The average centroid of the settlements is located in Wenfeng Township, gradually migrating southeastward by 3.7 km. Cold spots are shrinking northward, while hotspots are gathering in Chengjiang Town. Socio-economic conditions dominate the evolution of rural clusters in this region, showing obvious spatial heterogeneity. This is followed by locational conditions that are weakening in influence, while the impact of natural geographical conditions exists in the northeast region. The research findings offer a scientifically rigorous and well-founded analysis of the evolution and driving mechanisms of rural settlements. This analysis provides a solid theoretical basis for policy planning in urban-rural integrated development and supports the sustainable growth of rural communities.

The synergies and trade-offs between ecosystem services (ESs) and their driving mechanisms are hot topics in ecology and geography research. In recent years, the Han River Basin (HRB) has been continuously impacted by high-intensity urban sprawl and the Middle Route of the South-to-North Water Diversion Project, which have posed severe threats to the ecology and regional stability along the route. It is thus critical to study the ES synergies/trade-offs and their driving mechanisms. Based on the InVEST model and the value coefficient method, four vital types of ESs in the HRB, i.e., carbon sequestration (CS), food supply (FS), net primary productivity (NPP), and water yield (WY), were evaluated at town, county, and sub-watershed scales. Then, the Pearson correlation analysis was adopted to quantify the interrelationship among different ESs. Finally, the ordinary least squares (OLS) and geographical detector model (GDM) were applied to reveal the driving mechanisms of the ES synergies/trade-offs. The results showed that (1) apart from NPP, which increased at a rate of 7.54 gC·m −2 ·a −1 during 2000–2018, the other three types of ESs in the HRB deteriorated, with WY almost halving. (2) While CS, FS, and WY tended to exhibit high synergistic relationships, NPP showed mostly trade-off relationships, and the evaluation scale did not affect those main relationships. (3) Precipitation is the strongest driving force for the ES synergies/trade-offs in the HRB, and natural factors are generally more influential than socioeconomic factors on the ES synergies/trade-offs. This study warns of the deteriorating ecological condition of the HRB and provides empirical evidence for the synergistic enhancement of regional ESs and the optimization of ecological management policies.

Ecosystem service value (ESV) constitutes the ecological value foundation for enhancing tourism economic resilience (TER), serving as the central catalytic mechanism that drives the synergistic evolution of system disturbance resistance, recovery efficiency, and transformative adaptability. This study conducts a comprehensive evaluation of the interrelation between ESV and TER while exploring the key influencing factors to optimize human-environment interactions within the tourism system. The Coupling Coordination Degree (CCD) model is utilized to examine the association between ESs and TER across China. Additionally, spatial evolution patterns and key driving factors are explored using Exploratory Spatial Data Analysis (ESDA) and Geographically Weighted Regression (GWR). The key findings are as follows: (1) ESV displayed an inverted “N” trend, declining from southeast to northwest. (2) The spatial distribution of TER showed a persistent pattern of “high in the south, low in the north,” indicating a sustained stage of coordination. (3) The CCD of TER revealed positive spatial clustering, characterized by a distinct “two poles” pattern. (4) Economic and tourism-related factors were the dominant forces enhancing the CCD of TER, while social factors imposed constraints. These insights can support regional tourism economic planning and ecosystem management strategies.

Nowadays, the development or improvement of soft actuation mechanisms is a crucial topic for the achievement of dexterous manipulation using. Then, a primary target of research is the design of actuation and driving devices. Consequently, in this paper, we introduce a soft driving epicyclical mechanism that mimics human muscle behavior and fulfills motion requirements to achieve grasping gestures using a robotic finger. The prototype is experimentally assessed, and results show that our approach has enough performance for the implementation in grasping tasks. Furthermore, we introduce the basis for a new soft epicyclical mechanism merger with shape memory alloys to allow active stiffness control of the mechanism.