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RS/GISbased evaluation of forest ecosystem service value in Northeast China.

XIAO Xiao1,2, MU Zhi-lin3, ZHAO Xue-yan4, LI Jing-zhong2,5, XUE Bing1,2*#br#   

  1. (1Key Lab of Pollution Ecology and Environmental Engineering, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; 2 Key Lab for Environmental Computation and Sustainability of Liaoning Province, Shenyang 110016, China; 3Environment Protection and Resources Conservation Committee of the National People’s Congress, Beijing 100805, China; 4College of Geography and Environmental Sciences, Northwest Normal University, Lanzhou 730070, China; 5College of Urban Planning and Architecture, Xuchang University, Xuchang 461000, Henan, China).
  • Online:2017-11-10 Published:2017-11-10

Abstract: Forest ecosystem is a critical component of the terrestrial ecosystem, and its service value evaluation could offer a scientific basis for improving forestry sustainability as well as for policy making. This study applied the remote sensing interpretation data of the forest in Northeast China in 2015 to assess the ecosystem service value and figure out its spatial distribution pattern. The results showed that the ecosystem service value in Northeast China achieved 2.4066 trillion CNY, consisting of biodiversity protection (942.4 billion CNY), carbon fixation and oxygen releasing (784.2 billion CNY), water conservation (546.9 billion CNY), soil conservation (111.8 billion CNY), accumulation of nutrients (12.3 billion CNY), and purification of atmospheric environment (9.0 billion CNY). Spatially, the ecosystem service value showed an increasing trend from west to east, particularly between the eastern and western regions of Heilongjiang and Jilin provinces. The research results were of great significance to policymaking of forest resources management and establishing sustainable environmental accounting system in Northeast China.

Key words: wind-water erosion crisscross region, slope gradient, runoff yield, sediment yield., grain for green, utilization intensity of vegetation