Effects of conservation policy on China's forest recovery

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March 18, 2016 - Author: <vina@msu.edu>, William J. McConnell, <hbyang@rcees.ac.cn>, Zhenci Xu, <liuji@msu.edu>

Journal or Book Title: Science Advances

Keywords: China, forests, remote sensing, NFCP, climate change

Volume/Issue: 2 e1500965

Year Published: 2016

Forest loss is one of the most pervasive land surface transformations on Earth, with drastic effects on global climate, ecosystems, and human well-being. As part of biodiversity conservation and climate change mitigation efforts, many countries, including China, have been implementing large-scale policies to conserve and restore forests. However, little is known about the effectiveness of these policies, and information on China’s forest dynamics at the national level has mainly relied on official statistics. In response to international calls for improved reliability and transparency of information on biodiversity conservation and climate change mitigation efforts, it is crucial to independently verify government statistics. Furthermore, if forest recovery is verified, it is essential to assess the degree to which this recovery is attributable to policy, within the context of other relevant factors. We assess the dynamics of forest cover in China between 2000 and 2010 and evaluate the effectiveness of one of the largest forest conservation programs in the world—the Natural Forest Conservation Program (NFCP). Results indicate that forest cover has significantly increased in around 1.6% of China’s territory and that the areas exhibiting forest gain experienced a combined increase in net primary productivity (ca. 0.9 Tg of carbon). Among the variables evaluated at county level, the NFCP exhibited a significantly positive relation with forest gain, whereas reduction in rural labor showed a negative relationship with both forest loss and gain. Findings such as these have global implications for forest conservation and climate change mitigation efforts.

DOI: 10.1126/sciadv.1500965

Type of Publication: Journal Article

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