globalchange  > 影响、适应和脆弱性
DOI: 10.1111/gcb.13830
Scopus记录号: 2-s2.0-85028655008
论文题名:
Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years
作者: Yao Y.; Wang X.; Li Y.; Wang T.; Shen M.; Du M.; He H.; Li Y.; Luo W.; Ma M.; Ma Y.; Tang Y.; Wang H.; Zhang X.; Zhang Y.; Zhao L.; Zhou G.; Piao S.
刊名: Global Change Biology
ISSN: 13541013
出版年: 2018
卷: 24, 期:1
起始页码: 184
结束页码: 196
语种: 英语
英文关键词: China ; climate change ; eddy covariance ; gross primary productivity ; interannual variability ; model tree ensemble
Scopus关键词: algorithm ; annual variation ; climate change ; climate variation ; ecosystem response ; eddy covariance ; primary production ; spatiotemporal analysis ; China
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° 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/year2 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. © 2017 John Wiley & Sons Ltd
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/110580
Appears in Collections:影响、适应和脆弱性
气候变化事实与影响

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作者单位: Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China; Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China; Center for Excellence in Tibetan Earth Science, Chinese Academy of Sciences, Beijing, China; Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, Tsukuba, Japan; Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China; Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China; State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, China; Cold and Arid Regions Remote Sensing Observation System Experiment Station, Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, Lanzhou, China; Key Laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, China; Key Laboratory of Adaptation and Evolution of Plateau Biota, Haibei Alpine Meadow Ecosystem Research Station, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining, China; State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China

Recommended Citation:
Yao Y.,Wang X.,Li Y.,et al. Spatiotemporal pattern of gross primary productivity and its covariation with climate in China over the last thirty years[J]. Global Change Biology,2018-01-01,24(1)
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