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5 results on '"Ya‐Kun Tang"'

1. Spatiotemporal Pattern of Ecosystem Respiration in China Estimated by Integration of Machine Learning With Ecological Understanding

Author

Lang Han, Gui‐Rui Yu, Zhi Chen, Xian‐Jin Zhu, Wei‐Kang Zhang, Tie‐Jun Wang, Li Xu, Shi‐Ping Chen, Shao‐Min Liu, Hui‐Min Wang, Jun‐Hua Yan, Jun‐Lei Tan, Fa‐Wei Zhang, Feng‐Hua Zhao, Ying‐Nian Li, Yi‐Ping Zhang, Li‐Qing Sha, Qing‐Hai Song, Pei‐Li Shi, Jiao‐Jun Zhu, Jia‐Bing Wu, Zhong‐Hui Zhao, Yan‐Bin Hao, Xi‐Bin Ji, Liang Zhao, Yu‐Cui Zhang, Shi‐Cheng Jiang, Feng‐Xue Gu, Zhi‐Xiang Wu, Yang‐Jian Zhang, Li Zhou, Ya‐Kun Tang, Bing‐Rui Jia, Gang Dong, Yan‐Hong Gao, Zheng‐De Jiang, Dan Sun, Jian‐Lin Wang, Qi‐Hua He, Xin‐Hu Li, Fei Wang, Wen‐Xue Wei, Zheng‐Miao Deng, Xiang‐Xiang Hao, Xiao‐Li Liu, Xi‐Feng Zhang, Xing‐Guo Mo, Yong‐Tao He, Xin‐Wei Liu, Hu Du, and Zhi‐Lin Zhu

Subjects
Atmospheric Science, Global and Planetary Change, Environmental Chemistry, General Environmental Science
Published
2022

2. Mapping Chinese annual gross primary productivity with eddy covariance measurements and machine learning

Author

Xian-Jin Zhu, Gui-Rui Yu, Zhi Chen, Wei-Kang Zhang, Lang Han, Qiu-Feng Wang, Shi-Ping Chen, Shao-Min Liu, Hui-Min Wang, Jun-Hua Yan, Jun-Lei Tan, Fa-Wei Zhang, Feng-Hua Zhao, Ying-Nian Li, Yi-Ping Zhang, Pei-Li Shi, Jiao-Jun Zhu, Jia-Bing Wu, Zhong-Hui Zhao, Yan-Bin Hao, Li-Qing Sha, Yu-Cui Zhang, Shi-Cheng Jiang, Feng-Xue Gu, Zhi-Xiang Wu, Yang-Jian Zhang, Li Zhou, Ya-Kun Tang, Bing-Rui Jia, Yu-Qiang Li, Qing-Hai Song, Gang Dong, Yan-Hong Gao, Zheng-De Jiang, Dan Sun, Jian-Lin Wang, Qi-Hua He, Xin-Hu Li, Fei Wang, Wen-Xue Wei, Zheng-Miao Deng, Xiang-Xiang Hao, Yan Li, Xiao-Li Liu, Xi-Feng Zhang, and Zhi-Lin Zhu

Subjects
Machine Learning, Carbon Sequestration, Soil, Environmental Engineering, Climate Change, Environmental Chemistry, Carbon Dioxide, Pollution, Waste Management and Disposal, Ecosystem, Carbon
Abstract

Annual gross primary productivity (AGPP) is the basis for grain production and terrestrial carbon sequestration. Mapping regional AGPP from site measurements provides methodological support for analysing AGPP spatiotemporal variations thereby ensures regional food security and mitigates climate change. Based on 641 site-year eddy covariance measuring AGPP from China, we built an AGPP mapping scheme based on its formation and selected the optimal mapping way, which was conducted through analysing the predicting performances of divergent mapping tools, variable combinations, and mapping approaches in predicting observed AGPP variations. The reasonability of the selected optimal scheme was confirmed by assessing the consistency between its generating AGPP and previous products in spatiotemporal variations and total amount. Random forest regression tree explained 85 % of observed AGPP variations, outperforming other machine learning algorithms and classical statistical methods. Variable combinations containing climate, soil, and biological factors showed superior performance to other variable combinations. Mapping AGPP through predicting AGPP per leaf area (PAGPP) explained 86 % of AGPP variations, which was superior to other approaches. The optimal scheme was thus using a random forest regression tree, combining climate, soil, and biological variables, and predicting PAGPP. The optimal scheme generating AGPP of Chinese terrestrial ecosystems decreased from southeast to northwest, which was highly consistent with previous products. The interannual trend and interannual variation of our generating AGPP showed a decreasing trend from east to west and from southeast to northwest, respectively, which was consistent with data-oriented products. The mean total amount of generated AGPP was 7.03 ± 0.45 PgC yr

Published
2022

4. [Sap flux density in response to rainfall pulses for Pinus tabuliformis and Hippophae rhamnoides from mixed plantation in hilly Loess Plateau]

Author

Sen Bao, Lu, Yun Ming, Chen, Ya Kun, Tang, Xu, Wu, and Jie, Wen

Subjects
China, Soil, Rain, Hippophae, Water, Pinus, Trees
Abstract

Thermal dissipation probe (TDP) was used to continuously measure the sap flux density (F以黄土丘陵区油松-沙棘混交林为研究对象,运用热扩散式探针(TDP)于2015年6—10月对油松和沙棘的树干液流密度(F

Published
2018

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