1. Research Concerns
(1) Interfacial process of efficient water use in dryland agriculture and its regulatory mechanism. The team explains the water dynamics of soil-plant-atmosphere continuum (SPAC) in dryland, reveals the drought signal transduction mechanism and metabolic process of dryland crops, and clarifies the microbial action mechanism of carbon, nitrogen and water coupling process in dryland soils.
(2) Key technologies and equipment and regional development model of dryland agriculture. The team makes breakthroughs in methods of dryland sponge field construction, and developes key technologies and equipment for intelligent control of irrigation and fertilization; evaluates the water and carbon footprint and environmental effects of dryland farming techniques, optimizes the water-adaptive farming system, and integrates dryland water conservation techniques to form a green development model of dryland agriculture in harmony with resources and environment.
2. Chief Scientist
Prof. Gong Daozhi
Email: gongdaozhi@caas.cn
3. Representative Publications
1.Daozhi Gong, Xurong Mei, Weiping Hao, Hanbo Wang, and Kelly K. Caylor. "Comparison of multi-level water use efficiency between plastic film partially mulched and non-mulched croplands at eastern Loess Plateau of China" Agricultural Water Management 179, (2017): 215-226. doi: 10.1016/j.agwat.2016.06.006
2.Ximei Zhang, Eric R. Johnston, Albert Barberán, Yi Ren, Xiaotao Lü, and Xingguo Han. "Decreased plant productivity resulting from plant group removal experiment constrains soil microbial functional diversity" Global Change Biology 23(10), (2017): 4318-4332. doi: 10.1111/gcb.13783
3.Fengxue Gu, Yuandong Zhang, Mei Huang, Bo Tao, Zhengjia Liu, Man Hao, and Rui Guo. "Climate-driven uncertainties in modeling terrestrial ecosystem net primary productivity in China" Agricultural and Forest Meteorology 246, (2017): 123-132. doi: 10.1016/j.agrformet.2017.06.011
4.Zhang, X., Johnston, E. R., Li, L., Konstantinidis, K. T., & Han, X.. Experimental warming reveals positive feedbacks to climate change in the Eurasian Steppe. The ISME Journal, 11(4), (2017): 885–895. doi.org/10.1038/ismej.2016.180.
5.Feng, Yu; Hao, Weiping; Li, Haoru; Cui, Ningbo; Gong, Daozhi & Gao, Lili. "Machine learning models to quantify and map daily global solar radiation and photovoltaic power" Renewable and Sustainable Energy Reviews, 118(2), (2020): 109393..doi.org/10.1016/j.rser.2019.109393.
