IGSNRR OpenIR  > 历年回溯文献
Detection and attribution of vegetation greening trend in China over the last 30 years
Piao S. L.; Yin, G. D.; Tan, J. G.; Cheng, L.; Huang, M. T.; Li, Y.; Liu, R. G.; Mao, J. F.; Myneni, R. B.; Peng, S. S.; Poulter, B.; Shi, X. Y.; Xiao, Z. Q.; Zeng, N.; Zeng, Z. Z.; Wang, Y. P.
Source PublicationGlobal Change Biology
2015
Volume21
Issue4
Pages1601-1609
KeywordAfforestation Attribution China Co2 Fertilization Effect Detection Greening Trend Nitrogen Deposition Leaf-area Index Terrestrial Carbon-cycle Net Primary Production Climate-change Nitrogen Deposition Plant Geography Forest Temperature Co2 Ecosystems
AbstractThe 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 (LAI(GS)) estimated by satellite datasets (average trend of 0.0070yr(-1), ranging from 0.0035yr(-1) to 0.0127yr(-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 LAI(GS) 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 LAI(GS) (P<0.05), and marginally significantly (P=0.07) correlated with the residual of LAI(GS) 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.
Indexed BySCI
Language英语
ISSN1354-1013
DOI10.1111/gcb.12795
Citation statistics
Cited Times:107[WOS]   [WOS Record]     [Related Records in WOS]
Document TypeSCI/SSCI论文
Identifierhttp://ir.igsnrr.ac.cn/handle/311030/38801
Collection历年回溯文献
Recommended Citation
GB/T 7714
Piao S. L.,Yin, G. D.,Tan, J. G.,et al. Detection and attribution of vegetation greening trend in China over the last 30 years. 2015.
Files in This Item: Download All
File Name/Size DocType Version Access License
Piao-2015-Detection (617KB) 开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Piao S. L.]'s Articles
[Yin, G. D.]'s Articles
[Tan, J. G.]'s Articles
Baidu academic
Similar articles in Baidu academic
[Piao S. L.]'s Articles
[Yin, G. D.]'s Articles
[Tan, J. G.]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Piao S. L.]'s Articles
[Yin, G. D.]'s Articles
[Tan, J. G.]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Piao-2015-Detection and attrib.pdf
Format: Adobe PDF
This file does not support browsing at this time
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.