Forests are fundamental to maintaining ecological security and achieving regional sustainable development in China. Forest land change can result in many ecological problems including soil erosion, water shortages dro...Forests are fundamental to maintaining ecological security and achieving regional sustainable development in China. Forest land change can result in many ecological problems including soil erosion, water shortages drought and biodiversity loss. Based on landscape ecology and logistic regression we explored the spatiotemporal patterns and factors affecting forest land changes from 1985 to 2000 in the Beijing-Tianjin-Hebei Region of China. The results show decreased local fragmentation of woodland landscapes and that the shapes of forest patches have become more regular. For forest land cover change, soil organic matter content, slope type I （〈5°）, distance to the nearest village and per capita GDP were the most important independent variables from 1985 to 2000. This study indicates that spatial heterogeneity can affect the predictability of logistic regression models for forest land change.展开更多
基金National Natural Science Foundation of China(41361111)the Natural Science Foundation of Jiangxi Province(20143ACB21023)+2 种基金the Fok Ying Tung Foundation(141084)the Technology Foundation of Jiangxi,Education Department of China(KJLD14033)the Key project of Social Science Foundation of Jiangxi Province(15ZQZD10)
文摘Forests are fundamental to maintaining ecological security and achieving regional sustainable development in China. Forest land change can result in many ecological problems including soil erosion, water shortages drought and biodiversity loss. Based on landscape ecology and logistic regression we explored the spatiotemporal patterns and factors affecting forest land changes from 1985 to 2000 in the Beijing-Tianjin-Hebei Region of China. The results show decreased local fragmentation of woodland landscapes and that the shapes of forest patches have become more regular. For forest land cover change, soil organic matter content, slope type I （〈5°）, distance to the nearest village and per capita GDP were the most important independent variables from 1985 to 2000. This study indicates that spatial heterogeneity can affect the predictability of logistic regression models for forest land change.
