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Detection and attribution of vegetation greening trend in China over the last 30 years

Piao, Shilong, Yin, Guodong, Tan, Jianguang, Cheng, Lei, Huang, Mengtian, Li, Yue, Liu, Ronggao, Mao, Jiafu, Myneni, Ranga B., Peng, Shushi, Poulter, Ben, Shi, Xiaoying, Xiao, Zhiqiang, Zeng, Ning, Zeng, ZhenZhong, Wang, Yingping
Global change biology 2015 v.21 no.4 pp. 1601-1609
afforestation, climate change, data collection, ecosystem management, ecosystems, forests, growing season, leaf area index, models, nitrogen, plateaus, China
The reliable detection and attribution of changes in vegetation growth is a prerequisite for the development of strategies for the sustainable management of ecosystems. This is an extraordinary challenge. To our knowledge, this study is the first to comprehensively detect and attribute a greening trend in China over the last three decades. We use three different satellite‐derived Leaf Area Index (LAI) datasets for detection as well as five different process‐based ecosystem models for attribution. Rising atmospheric CO₂concentration and nitrogen deposition are identified as the most likely causes of the greening trend in China, explaining 85% and 41% of the average growing‐season LAI trend (LAIGS) estimated by satellite datasets (average trend of 0.0070 yr⁻¹, ranging from 0.0035 yr⁻¹to 0.0127 yr⁻¹), respectively. The contribution of nitrogen deposition is more clearly seen in southern China than in the north of the country. Models disagree about the contribution of climate change alone to the trend in LAIGSat the country scale (one model shows a significant increasing trend, whereas two others show significant decreasing trends). However, the models generally agree on the negative impacts of climate change in north China and Inner Mongolia and the positive impact in the Qinghai–Xizang plateau. Provincial forest area change tends to be significantly correlated with the trend of LAIGS(P < 0.05), and marginally significantly (P = 0.07) correlated with the residual of LAIGStrend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO₂concentration and nitrogen deposition, across different provinces. This result highlights the important role of China's afforestation program in explaining the spatial patterns of trend in vegetation growth.