The activity characteristics of the village and its symbiotic relationship with the environment play an important role in the sustainable development of the surrounding environment. Miao villages have a long history. In the process of long-term interaction with the surrounding natural environment, Miao villages have formed a unique forest culture, which has an important impact on the distribution of the surrounding forests and plays a crucial role in local forest management. In this study, we took the Miao villages of China that are distributed in Qiandongnan Miao and Dong Autonomous Prefecture of China as an example and constructed a research framework to study the interaction between the natural environment and human activities around the Miao villages and its impact on forest change based on partial least squares structural equation modeling (PLS-SEM) and geographically weighted regression modeling (GWR) methods. The validity and reliability evaluations showed that the PLS-SEM model was reasonable. The results showed that the Miao villages were randomly distributed within 0–2 km and clustered in the 8–10 km buffer zone. The temporal variation of the forest landscape around the Miao villages was small, and the spatial heterogeneity was obvious. Within the 0~2 km buffer zone, the proportion of closed-canopy forest was the largest, and with the increase in the buffer zone radius, the proportion of closed-canopy forest gradually decreased, the open-canopy forest gradually grew, and the proportion of shrubbery and other forests showed an upward trend first and then a downward trend. Temporally, the four forest landscapes did not change much, with closed and open forests sliding, and shrubbery and other forests increasing. Regarding the drivers of forest structure change, topographic factors and landscape patterns had a positive effect on forest structure, while human activities had a negative effect. The influence of topography on human activities in the Miao villages weakened the direct positive effect of topography on forests and promoted the positive effect of the landscape pattern on forests. There were significant spatial differences in the GWR regression coefficients of the effects of different factors on forest structure in 2020, with a pivotal negative correlation between NDVI and night-time light data. In addition, the higher the elevation, the more unfavorable the distribution of open-canopy forests and the better the distribution of closed-canopy forests. The higher the slope, the higher the NDVI but the more unfavorable the distribution of closed-canopy forests. In general, the impacts of Miao villages on forest structure are highly complex and interactive, with both direct and indirect effects. Different factors interact to affect the structure of the forest. The study on the effect of Miao villages on forests is helpful for more targeted forest protection and the formulation of laws and regulations, so as to find a balance between human activities and forest management, in order to maintain the ecological balance of local areas. This study introduced the PLS-SEM model to investigate the impacts of Miao villages on forest structure, which effectively enhanced our understanding of the drivers and impacts of forest change and provides theoretical support and a basis for forest protection and management.
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