Studies on rural transformation in the context of urbanization have always analyzed it from a single linear perspective, either top-down or bottom-up. This leads to simplistic generalizations of rural transformation models and the standardization of policy implementation. Based on the TPSN analytical framework, this study adds the temporality dimension to form a more comprehensive TPSNT framework. This paper explores the complex construction of rural space in rural transformation from the five dimensions of “territory, place, scale, network and temporality“ and takes the urban village, Hongren, in Kunming City, China, as a case study to analyze the specific transformation process of a village. The research revealed the following: First, in the face of land loss caused by government land acquisition, traditional rural autonomous organizations that have been hidden under the modern governance system have been revived under the influence of traditional elites and completed bottom-up territorialization by using some “maneuver spaces “to form a spatial base for negotiation with the government. Second, the cohesion of traditional rural autonomous organizations has increased during this process, and with the help of mobile capital such as media and personal connections, they have developed social networks that transcend the spatial boundaries of villages. Third, these newly constructed social networks are used to carry out various political strategies at various scales and finally negotiated with the government to rewrite the planning plan so that the village can continue to develop and integrate into the city. Finally, the analysis of the temporal dimensions of Hongren village revealed that even within the same village, changes in the other four dimensions develop dynamically, and rural transformation is an ongoing process. Therefore, when the government deals with rural issues in the process of urbanization, it should avoid a one-size-fits-all approach. Unified policy implementation standards will have an irreversible negative impact on rural autonomous organizations.

As global sustainability debates increasingly stress the coupling of social power and ecosystem performance, this study examines the Honghe Hani Rice Terraces as a long-term hydrosocial system. Drawing on historical political ecology, we develop a topographic impact model that links terrain-driven water flows with governance nodes and village institutions across successive regimes—native chieftaincy, people’s communes, and the household responsibility system. Using archival sources, gazetteers, policy documents, and secondary literature, we trace how rules of water allocation, lineage- and village-level cooperation, and ritual/managerial authorities jointly stabilized the terraces’ irrigation network and landscape productivity. While recent restoration policies have improved certain biophysical indicators, the fragmentation of social organizations and uneven access to water and land have heightened vulnerability and management costs in some locales. Our analysis identifies strong institutional continuity in coordination logics encoded in the irrigation infrastructure and terrain, which underpins the terraces’ long-run functioning despite regime shifts. We argue that sustainable governance should avoid a simplistic return to tradition; instead, it should rebuild local subjectivity and institutional resilience, revitalize collaborative mechanisms, clarify multi-level rights and responsibilities, and align contemporary incentives with historically proven coordination rules. Embedding historical experience within modern policy design can better sustain this world-heritage cultural landscape as a coupled human–water system.

1. With accelerating development and openness in China’s border regions, cross-border mobility among local residents has become an everyday reality. This trend has stimulated economic exchange and ...

Wildlife trafficking poses substantial risks to biodiversity, ecosystem stability, and public health. Using panel data for 31 Chinese provinces, this study applies global spatial diagnostics, the spatial gravity model, and a two‐way fixed‐effects spatial Durbin model (SDM) to investigate the spatial distribution and socioeconomic drivers of wildlife smuggling. Global Moran’s I confirms significant positive spatial autocorrelation, while the gravity analysis reveals clear spatial disparities: High‐incidence clusters are concentrated in coastal and southern border provinces integrated into international trade and logistics networks, whereas inland and northwestern regions exhibit relatively low levels. Regression results indicate that wildlife smuggling is positively associated with regional GDP, while it is negatively associated with government intervention. Protected‐area coverage exhibits a positive association with smuggling before 2019 but turns negative and statistically insignificant after 2019, suggesting a possible shift in enforcement and monitoring dynamics during the postpandemic period, social consumption, digital infrastructure, and terrain ruggedness exert negative effects; industrial structure shows a marginally positive impact. Moreover, spillover estimates reveal that government intervention, industrial structure, and protected‐area coverage in neighboring provinces generate significant positive displacement effects, suggesting that conservation expansion or stricter enforcement in one province may shift smuggling activities to surrounding regions. By contrast, spillovers from digital infrastructure and social consumption are negative but statistically insignificant. Heterogeneity results show that the influence of socioeconomic and institutional factors on wildlife smuggling varies significantly before and after the COVID‐19 pandemic, with notable shifts in smuggling patterns and enforcement effectiveness in the post‐2019 period. These findings highlight the importance of cross‐regional coordination, digital governance tools, green industrial transformation, and international cooperation to effectively curb wildlife trafficking and strengthen biodiversity protection.