气候变化领域集成服务门户(CCPortal): Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years

CCPortal

DOI	10.1111/gcb.13830
	Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years
	Yao, Yitong; Wang, Xuhui; Li, Yue; Wang, Tao; Shen, Miaogen; Du, Mingyuan; He, Honglin; Li, Yingnian; Luo, Weijun; Ma, Mingguo; Ma, Yaoming; Tang, Yanhong; Wang, Huimin; Zhang, Xianzhou; Zhang, Yiping; Zhao, Liang; Zhou, Guangsheng; Piao, Shilong
发表日期	2018
ISSN	1354-1013
EISSN	1365-2486
卷号	24 期号:1
英文摘要	The uncertainties of China's gross primary productivity (GPP) estimates by global data-oriented products and ecosystem models justify a development of high-resolution data-oriented GPP dataset over China. We applied a machine learning algorithm developing a new GPP dataset for China with 0.1 degrees spatial resolution and monthly temporal frequency based on eddy flux measurements from 40 sites in China and surrounding countries, most of which have not been explored in previous global GPP datasets. According to our estimates, mean annual GPP over China is 6.62 +/- 0.23 PgC/year during 1982-2015 with a clear gradient from southeast to northwest. The trend of GPP estimated by this study (0.020 +/- 0.002 PgC/year(2) from 1982 to 2015) is almost two times of that estimated by the previous global dataset. The GPP increment is widely spread with 60% area showing significant increasing trend (p <.05), except for Inner Mongolia. Most ecosystem models overestimated the GPP magnitudes but underestimated the temporal trend of GPP. The monsoon affected eastern China, in particular the area surrounding Qinling Mountain, seems having larger contribution to interannual variability (IAV) of China's GPP than the semiarid northwestern China and Tibetan Plateau. At country scale, temperature is the dominant climatic driver for IAV of GPP. The area where IAV of GPP dominated by temperature is about 42%, while precipitation and solar radiation dominate 31% and 27% respectively over semiarid area and cold-wet area. Such spatial pattern was generally consistent with global GPP dataset, except over the Tibetan Plateau and northeastern forests, but not captured by most ecosystem models, highlighting future research needs to improve the modeling of ecosystem response to climate variations.
关键词	China climate change eddy covariance gross primary productivity interannual variability model tree ensemble
学科领域	Biodiversity & Conservation; Environmental Sciences & Ecology
语种	英语
WOS研究方向	Biodiversity Conservation ; Ecology ; Environmental Sciences
来源期刊	GLOBAL CHANGE BIOLOGY
来源机构	中国科学院西北生态环境资源研究院
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/111974
作者单位	Peking Univ, Coll Urban & Environm Sci, Sinofrench Inst Earth Syst Sci, Beijing, Peoples R China
推荐引用方式 GB/T 7714	Yao, Yitong,Wang, Xuhui,Li, Yue,et al. Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years[J]. 中国科学院西北生态环境资源研究院,2018,24(1).
APA	Yao, Yitong.,Wang, Xuhui.,Li, Yue.,Wang, Tao.,Shen, Miaogen.,...&Piao, Shilong.(2018).Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years.GLOBAL CHANGE BIOLOGY,24(1).
MLA	Yao, Yitong,et al."Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years".GLOBAL CHANGE BIOLOGY 24.1(2018).