Yu Chengqun
Chinese Academy of Sciences
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Publication
Featured researches published by Yu Chengqun.
Journal of resources and ecology | 2017
Fu Gang; Sun Wei; Li Shaowei; Zhang Jing; Yu Chengqun; Shen Zhenxi
Abstract: Accurate quantification of aboveground biomass of grasslands in alpine regions plays an important role in accurate quantification of global carbon cycling. The monthly normalized difference vegetation index (NDVI), enhanced vegetation index (EVI), mean air temperature (Ta), ≥5°C accumulated air temperature (AccT), total precipitation (TP), and the ratio of TP to AccT (TP/AccT) were used to model aboveground biomass (AGB) in grasslands on the Tibetan Plateau. Three stepwise multiple regression methods, including stepwise multiple regression of AGB with NDVI and EVI, stepwise multiple regression of AGB with Ta, AccT, TP and TP/AccT, and stepwise multiple regression of AGB with NDVI, EVI, Ta, AccT, TP and TP/AccT were compared. The mean absolute error (MAE) and root mean squared error (RMSE) values between estimated AGB by the NDVI and measured AGB were 31.05 g m-2 and 44.12 g m-2, and 95.43 g m-2 and 131.58 g m-2 in the meadow and steppe, respectively. The MAE and RMSE values between estimated AGB by the AccT and measured AGB were 33.61g m-2 and 48.04 g m-2 in the steppe, respectively. The MAE and RMSE values between estimated AGB by the vegetation index and climatic data and measured AGB were 28.09 g m-2 and 42.71 g m-2, and 35.86 g m-2 and 47.94 g m-2, in the meadow and steppe, respectively. The study finds that a combination of vegetation index and climatic data can improve the accuracy of estimates of AGB that are arrived at using the vegetation index or climatic data. The accuracy of estimates varied depending on the type of grassland.
Journal of resources and ecology | 2018
Shen Zhenxi; Sun Wei; Li Shaowei; Zhang Haorui; Fu Gang; Yu Chengqun; Zhang Guangyu
Abstract: Vapor pressure deficit (VPD) is an important parameter in modelling hydrologic cycles and vegetation productivity. Meteorological stations are scarce in remote areas, which often results in imprecise estimations of VPD on the Tibetan Plateau. Moderate Resolution Imaging Spectroradiometer (MODIS) provides evapotranspiration data, which may offer the possibility of scaling up VPD estimations on the Tibetan Plateau. However, no studies thus far have estimated VPD using MODIS evapotranspiration data on the Tibetan Plateau. Therefore, this study used MODIS potential evapotranspiration (PET) to estimate VPD in alpine meadows, alpine steppes, croplands, forests and shrublands for the year, spring, summer, autumn and winter in 2000–2012. A series of root-meansquared-error (RMSE) and mean-absolute-error (MAE) values were obtained for correlating measured VPD and estimated VPD using MODIS PET data for each listed time period and vegetation type: whole year (0.98–2.15 hPa and 0.68–1.44 hPa), spring (0.95–2.34 hPa and 0.72–1.54 hPa), summer (1.39–2.60 hPa and 0.89–1.96 hPa), autumn (0.78–1.93 hPa and 0.56–1.36 hPa), winter (0.48–1.40 hPa and 0.36–0.98 hPa), alpine steppes (0.48–1.39 hPa and 0.36–1.00 hPa), alpine meadows (0.58–1.39 hPa and 0.44–0.90 hPa), croplands (1.10–2.55 hPa and 0.82–1.74 hPa), shrublands (0.98–1.90 hPa and 0.78–1.37 hPa), and forests (1.40–2.60 hPa and 0.98–1.96 hPa), respectively. Therefore, MODIS PET may be used to estimate VPD, and better results may be obtained if future studies incorporate vegetation types and seasons when the VPD data are estimated using MODIS PET on the Tibetan Plateau.
Journal of resources and ecology | 2018
Tian Yuan; Yu Chengqun; Zha Xinjie; Wu Jianshuang; Gao Xing; Feng Chujian
Abstract: The North Tibet plateau is the world highest plateau with a unique alpine grassland and water environment. To obtain a better understanding of the correct supply of Molybdenum (Mo) to livestock in north Tibet, we investigated the content and geographical variation of Mo in different families of pasture plants (n=1017) and water (n=40), then discuss the Cuprum (Cu):Mo ratio in different plant families, and calculate the total Mo intake of the yak in north Tibet. The average Mo concentration in five families preferred for grazing are: Compositae (2.71 μg g-1), Leguminosae (2.70 μg g-1), Gramineae (2.48 μg g-1), Cyperaceae (1.63 μg g-1), and Rosaceae (1.51 μg g-1). There was a strong geographical variation in Mo concentration (p < 0.001). The mean value of Mo in north Tibet surface water from 15 sites is 0.89 μg L-1. The Mo ingestion by yak through these plants and water in north Tibet is about 9586 μg day-1 which means the toxicity of Mo does not exist in the average daily diet. However, the large geographical variation found may cause some toxicity of Mo in the average daily intake of north Tibet pasture plants in some areas. The Cu:Mo ratio of 2:60 is considered the limit for risk of Mo hyperactivity, while extremely high Cu:Mo ratios may lead to chronic copper poisoning. Our survey of plant samples found 43.29% below and 29.3% above the limiting Cu:Mo ratio of 60 indicating some risk to north Tibet livestock.
Journal of resources and ecology | 2017
Zhang Xianzhou; Wang Ling; He Yongtao; Du Mingyuan; Zhang Jing; Shi Peili; Yu Chengqun; Zhang Yangjian
Abstract: Elevation dependency amongst climate change signals has been found in major mountain ranges around the world, but the main factors causing this dependency have not been clarified. In this study, four different datasets of observation and reanalysis for China were used to examine the elevation dependency of climate change. A lack of consistency was found in dependency between warming magnitude and elevation across the Tibetan Plateau and China. However, a dependency of climate change on water vapor was detected whereby the temperature trend initially increased at low specific humidity, and then decreased as specific humidity increased. At ground level the maximum trend in temperature appeared in the specific humidity range 2.0–3.0 g kg-1. This suggests that water vapor is a mediator of climate change and may be responsible for elevation-dependent climate change.
资源与生态学报(英文版) | 2012
Wu Jianshuang; Zhang Xianzhou; Shen Zhenxi; Shi Peili; Yu Chengqun; Song Minghua; Li Xiaojia
资源科学 | 2017
高利伟; 徐增让; 成升魁; 许世卫; 张宪洲; 余成群; 孙维; 武俊喜; 曲云鹤; 马杰; Gao Liwei; Xu Zengrang; Cheng Shengkui; Xu Shiwei; Zhang Xianzhou; Yu Chengqun; Sun Wei; Wu Junxi; Qu Yunhe; Ma Jie
Archive | 2017
Yu Chengqun; Zhu Xinqiang; Sun Wei; Li Jinhua
Zhongguo Kexueyuan Yuankan | 2016
He Yongtao; Zhang Xianzhou; Yu Chengqun
Archive | 2016
Yu Chengqun; Li Shaowei; Sun Wei
Archive | 2016
Li Shaowei; Yu Chengqun; Sun Wei