Literature DB >> 25369401

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

Shilong Piao1, Guodong Yin, Jianguang Tan, Lei Cheng, Mengtian Huang, Yue Li, Ronggao Liu, Jiafu Mao, Ranga B Myneni, Shushi Peng, Ben Poulter, Xiaoying Shi, Zhiqiang Xiao, Ning Zeng, ZhenZhong Zeng, Yingping Wang.   

Abstract

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 CO2 concentration 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(-1) to 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 LAIGS at 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 LAIGS trend, calculated as the trend observed by satellite minus that estimated by models through considering the effects of climate change, rising CO2 concentration 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.
© 2014 John Wiley & Sons Ltd.

Entities:  

Keywords:  CO2 fertilization effect; China; afforestation; attribution; detection; greening trend; nitrogen deposition

Mesh:

Substances:

Year:  2015        PMID: 25369401     DOI: 10.1111/gcb.12795

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


  24 in total

1.  Analyzing nonlinear variations in terrestrial vegetation in China during 1982-2012.

Authors:  Yanxu Liu; Xianfeng Liu; Yi'na Hu; Shuangshuang Li; Jian Peng; Yanglin Wang
Journal:  Environ Monit Assess       Date:  2015-10-30       Impact factor: 2.513

2.  Nonlinear variations of forest leaf area index over China during 1982-2010 based on EEMD method.

Authors:  Yunhe Yin; Danyang Ma; Shaohong Wu; Erfu Dai; Zaichun Zhu; Ranga B Myneni
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6.  MODIS Based Estimation of Forest Aboveground Biomass in China.

Authors:  Guodong Yin; Yuan Zhang; Yan Sun; Tao Wang; Zhenzhong Zeng; Shilong Piao
Journal:  PLoS One       Date:  2015-06-26       Impact factor: 3.240

7.  Climatic change controls productivity variation in global grasslands.

Authors:  Qingzhu Gao; Wenquan Zhu; Mark W Schwartz; Hasbagan Ganjurjav; Yunfan Wan; Xiaobo Qin; Xin Ma; Matthew A Williamson; Yue Li
Journal:  Sci Rep       Date:  2016-05-31       Impact factor: 4.379

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Authors:  Songlin Shi; Zongshan Li; Hao Wang; Georg von Arx; Yihe Lü; Xing Wu; Xiaochun Wang; Guohua Liu; Bojie Fu
Journal:  Sci Rep       Date:  2016-06-21       Impact factor: 4.379

9.  Inconsistent estimates of forest cover change in China between 2000 and 2013 from multiple datasets: differences in parameters, spatial resolution, and definitions.

Authors:  Yan Li; Damien Sulla-Menashe; Safa Motesharrei; Xiao-Peng Song; Eugenia Kalnay; Qing Ying; Shuangcheng Li; Zongwen Ma
Journal:  Sci Rep       Date:  2017-08-18       Impact factor: 4.379

10.  A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

Authors:  Zhiyong Liu; Chao Li; Ping Zhou; Xiuzhi Chen
Journal:  Sci Rep       Date:  2016-10-07       Impact factor: 4.379

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