Abstract

China has experienced an extensive forest transition. However, the biophysical conditions and socio-economic effects in different regions are quite different in such a large country. Few studies on the forest transition of China have focused on how forest transitions occur and what process of forest transition in quality experience at the regional level. This study conducts a regional analysis on forest transition in Inner Mongolia from the dual perspectives of forest quantity and quality using data from 1980 to 2018. Radial Basis Function Neural Network (RBFNN) modeling combining the sensitivity analysis method is used to comprehensively analyze potential socio-economic factors that may drive the forest transition observed in Inner Mongolia. The results show that the changing trend of the forest area in Inner Mongolia shaped a “N" curve, while the standing forest stock showed a general slow-growing trend. It is important to note that Inner Mongolia achieved a complete forest transition around 1993. The forest transition witnessed in Inner Mongolia mainly followed two pathways: the “economic development pathway” and the “national forest policy pathway.” The results suggest that the forest area in Inner Mongolia is changing into an “N" shaped curve with the number of live standing trees in the forests generally growing slowly. The results further suggest that, rather than only analyzing the spatial expansion of forest area, ecological construction is also an important determinant of future forest quality.

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