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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.

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.

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.

Understanding ecosystem carbon sequestration change and its environmental drivers is fundamental for revealing regional carbon sink patterns and ecosystem response processes, yet differences in carbon sequestration dynamics between ethnic autonomous and non-autonomous areas in western China remain insufficiently explored. Here, these two regional types were regarded as socio-ecological units with distinct environmental backgrounds, ecosystem compositions, land-use structures, and governance contexts. Using total carbon sink (TCS), net primary productivity (NPP), and multi-source data from 2001 to 2025, we combined trend analysis, ridge regression, and interpretable machine learning to investigate differences in carbon sequestration change, climate sensitivity, and driving mechanisms between the two regional types. The results showed that ecosystem carbon sequestration in western China increased significantly during 2001–2025, with TCS rising from 1.40 to 1.60 PgC·yr -1 and NPP increasing from 440 to 500 gC·m -2 ·yr -1 . Ethnic autonomous areas constituted the dominant component of the regional carbon sink, with TCS increasing from 1.14 to 1.27 PgC·yr -1 and NPP increasing from 420 to 480 gC·m -2 ·yr -1 , contributing 78.55% of the total NPP and 106.29% to interannual variability. In contrast, non-autonomous areas had lower total carbon sink values but higher mean NPP and steeper growth rates, with TCS increasing from 0.25 to 0.33 PgC·yr -1 and NPP increasing from 550 to 650 gC·m -2 ·yr -1 . NPP in ethnic autonomous areas was more sensitive to precipitation and soil moisture, indicating stronger water limitation, whereas non-autonomous areas showed a more pronounced increase in temperature sensitivity and greater weakening in sensitivity to VPD and radiation. Analysis of driving mechanisms further revealed a climate-dominated pattern in ethnic autonomous areas and a more pronounced pattern of joint soil–climate control in non-autonomous areas. These differences reflect combined effects of administrative characteristics, environmental gradients, ecosystem composition, and land-use intensity, rather than administrative status alone.

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.

The urban agglomeration represents the predominant form of new urbanisation, yet the evolution of its internal spatial structure exhibits pronounced spatial and temporal heterogeneity. This study concentrates on the Bohai Rim urban agglomeration, one of three major urban agglomerations in China, which has received comparatively limited research attention but has also undergone substantial urbanisation. Therefore, we reassessed and explored the spatial-temporal evolution of the spatial structure of urban expansion using Exploratory Spatiotemporal Data Analysis (ESTDA), and summarized the driving mechanisms using Geographically and Temporally Weighted Regression (GTWR). Our study found that the urban land expansion intensity of Bohai Rim urban agglomeration presented the differences between megacities and large cities, coastal and inland cities and the regional disparities exhibited a gradual narrowing and balancing over time and space, with the high-expansion intensity zones undergoing alternation. The dynamics of the local spatial structure performed a clear positive correlation with the development level and a negative correlation with the exploitation time. The urban expansion intensity was influenced by various factors, including population, economic and other variables. Over time, the main drivers shifted from emphasis on economic quantity to quality, and from financial support to government policy. The objective of this study is to substantiate the impact of socio-economic factors on the spatio-temporal heterogeneity of urban expansion and to propose strategies for alleviating urban land pressure in the Bay Area urban agglomerations. This study enriches the research on the urban expansion mechanisms of different types of urban agglomerations and enhances a comprehensive understanding of the spatiotemporal heterogeneity of urban expansion within it. The findings can provide valuable theoretical support for urban planners in future urban development and construction and can also serve as exemplars for urbanisation in other urban agglomerations.

Rocky desertification is a key element affecting regional ecological quality. Rocky desertification in Southwest China directly affects the ecological security of the Yangtze River and Pearl River basins and also restricts regional economic and social development. In order to clarify the evolution laws and key influencing factors of ecological quality in Yunnan karst rocky desertification areas, a quantitative analysis based on the remote sensing-based ecological index (RSEI) model was conducted to explore the overall evolution characteristics and change laws of ecological quality in Yunnan karst rocky desertification areas in the past 30 years. The correlation between RSEI, rock outcrop rate (Fr), and driving factors was determined by redundancy analysis. The results showed the following: (1) RSEI in Yunnan karst rocky desertification areas generally showed a decreasing trend, with a fluctuation in the mid-term, followed by a tendency to recover. It fell into three stages: decline, trough, and recovery, with fitting coefficients of −0.121, −0.057, and 0.157, respectively. In contrast, Fr showed an opposite tendency, illustrating the inverse relationship between RSEI and Fr, and the rate of sequential succession was much faster than that of the reverse succession under human measures of intervention. (2) The mean value of RSEI of Yunnan karst rocky desertification areas was generally lower than that of the total Yunnan Province land areas and Yunnan non-karst rocky desertification areas, but the mean value of Fr was generally more than that of both the above-mentioned areas. In addition, the RSEI and Fr of Yunnan karst rocky desertification areas both showed lower stability values than those of both the above-mentioned areas. This generally suggested a low ecological quality and a high degree of desertification under a low stability in Yunnan karst rocky desertification areas. (3) The correlation of RSEI and Fr with driving factors followed the order of topographic factors, soil factors > water factors > anthropogenic factors. Anthropogenic factors were the driving force changing the state of rocky desertification, geological factors such as topography and soil to a larger extent determined the original macroscopic ecological relationship of rocky desertification, and water factors lay between the above two. The findings of this research will provide theoretical support and a basis for the improvement of ecological quality and comprehensive control of karst rocky desertification in Yunnan Province.