Cheng Yunxiang

Dr. Cheng Yunxiang

orcid

Research Focus & Metrics

Academic Career Length

12Years (2015-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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7 April 2017 in Frontiers in Microbiology
Verified
Journal Article
Open access
HUHuhe
Huhe
XCXianjiang Chen
Xianjiang Chen
Fujiang HouFujiang Hou
Fujiang Hou
YWYanpei Wu
Yanpei Wu
CYCheng Yunxiang
Cheng Yunxiang
The Loess Plateau of China is one of the most fragile ecosystems worldwide; thus, human production activities need to be conducted very cautiously. In this study, MiSeq high-throughput sequencing was applied to assess the relationship between bacterial and fungal community structures and changes in vegetation and soil physical and chemical properties induced by grazing, in four grasslands with different levels of grazing intensity (0, 2.67, 5.33, and 8.67 sheep/ha) in the semiarid region of the Loess Plateau. The relative abundances of the bacterial community in the grasslands with 2.67 and 5.33 sheep/ha were significantly higher than those in grasslands with 0 and 8.67 sheep/ha, and the fungal diversity was significantly lower for grasslands with 2.67 sheep/ha than for the other grasslands. Redundancy analysis showed that plant biomass, nitrate, and total nitrogen have significant effects on bacterial community structure, whereas nitrate and total nitrogen also significantly affect fungal community structure. Variation partitioning showed that soil and plant characteristics influence the bacterial and fungal community structures; these characteristics explained 51.9% and 52.9% of the variation, respectively. Thus, bacterial and fungal community structures are very sensitive to grazing activity and change to different extents with different grazing intensities. Based on our findings, a grazing intensity of about 2.67 sheep/ha is considered the most appropriate in semiarid grassland of the Loess Plateau.

24 July 2017 in Microbiologyopen
Verified
Journal Article
Open access
PDF file
HUHuhe
Huhe
CJChao Jiang
Chao Jiang
YWYanpei Wu
Yanpei Wu
CYCheng Yunxiang
Cheng Yunxiang
During composting, the composition of microbial communities is subject to constant change owing to interactions with fluctuating physicochemical parameters. This study explored the changes in bacterial and fungal communities during cattle farm waste composting and aimed to identify and prioritize the contributing physicochemical factors. Microbial community compositions were determined by high‐throughput sequencing. While the predominant phyla in the bacterial and fungal communities were largely consistent during the composting, differences in relative abundances were observed. Bacterial and fungal community diversity and relative abundance varied significantly, and inversely, over time. Relationships between physicochemical factors and microbial community compositions were evaluated by redundancy analysis. The variation in bacterial community composition was significantly related to water‐soluble organic carbon (WSOC), and pile temperature and moisture (p < .05), while the largest portions of variation in fungal community composition were explained by pile temperature, WSOC, and C/N (p < .05). These findings indicated that those parameters are the most likely ones to influence, or be influenced by the bacterial and fungal communities. Variation partitioning analyses indicated that WSOC and pile temperature had predominant effects on bacterial and fungal community composition, respectively. Our findings will be useful for improving the quality of cattle farm waste composts.

15 January 2019 in Sustainability
Verified
Journal Article
Open access
PDF file
QMQingqing Ma
Qingqing Ma
LCLinrong Chai
Linrong Chai
Fujiang HouFujiang Hou
Fujiang Hou
SCShenghua Chang
Shenghua Chang
MMMayushou yushou Ma
Mayushou yushou Ma
CYCheng Yunxiang
Cheng Yunxiang
Remote sensing data have been widely used in the study of large-scale vegetation activities, which have important significance in estimating grassland yields, determining grassland carrying capacity, and strengthening the scientific management of grasslands. Remote sensing data are also used for estimating grazing intensity. Unfortunately, the spatial distribution of grazing-induced degradation remains undocumented by field observation, and most previous studies on grazing intensity have been qualitative. In our study, we tried to quantify grazing intensity using remote sensing techniques. To achieve this goal, we conducted field experiments at Gansu Province, China, which included a meadow steppe and a semi-arid region. The correlation between a vegetation index and grazing intensity was simulated, and the results demonstrated that there was a significant negative correlation between NDVI and relative grazing intensity (p < 0.05). The relative grazing intensity increased with a decrease in NDVI, and when the relative grazing intensity reached a certain level, the response of NDVI to relative grazing intensity was no longer sensitive. This study shows that the NDVI model can illustrate the feasibility of using a vegetation index to monitor the grazing intensity of livestock in free-grazing mode. Notably, it is feasible to use the remote sensing vegetation index to obtain the thresholds of livestock grazing intensity.

23 February 2022 in Microbiology Spectrum
Verified
Journal Article
Open access
YYYalin Yin
Yalin Yin
YYYe Yuan
Ye Yuan
XZXiaowen Zhang
Xiaowen Zhang
HUHuhe
Huhe
CYCheng Yunxiang
Cheng Yunxiang
SBShinchilelt Borjigin
Shinchilelt Borjigin
Determining the response of soil fungi in sensitive ecosystems to external environmental disturbances is an important, yet little-known, topic in microbial ecology. In this study, we evaluated the impact of traditional fertilization management practices on the composition, co-occurrence pattern, and functional groups of fungal communities in loessial soil.

3 May 2016 in PLOS ONE
Verified
Journal Article
Open access
PDF file
HUHuhe
Huhe
SBShinchilelt Borjigin
Shinchilelt Borjigin
BUBuhebaoyin
Buhebaoyin
YWYanpei Wu
Yanpei Wu
MLMinquan Li
Minquan Li
CYCheng Yunxiang
Cheng Yunxiang
In Inner Mongolia, steppe grasslands face desertification or degradation because of human overuse and abandonment after inappropriate agricultural management. The soils in these abandoned croplands exist in heterogeneous environments characterized by widely fluctuating microbial growth. Quantitative polymerase chain reaction analysis of microbial genes encoding proteins involved in the nitrogen cycle was used to study Azotobacter species, nitrifiers, and denitrifiers in the soils from steppe grasslands and croplands abandoned for 2, 6, and 26 years. Except for nitrifying archaea and nitrous oxide-reducing bacteria, the relative genotypic abundance of microbial communities involved in nitrogen metabolism differed by approximately 2- to 10-fold between abandoned cropland and steppe grassland soils. Although nitrogen-cycle gene abundances varied with abandonment time, the abundance patterns of nitrogen-cycle genes separated distinctly into abandoned cropland versus light-grazing steppe grassland, despite the lack of any cultivation for over a quarter-century. Plant biomass and plant diversity exerted a significant effect on the abundance of microbial communities that mediate the nitrogen cycle (P < 0.002 and P < 0.03, respectively). The present study elucidates the ecology of bacteria that mediate the nitrogen cycle in recently abandoned croplands.

1 July 2015
Verified
Journal Article
Closed access
YZYan Zhanq
Yan Zhanq
XCXianjiang Chen
Xianjiang Chen
CYCheng Yunxiang
Cheng Yunxiang
SCShenghua Chang
Shenghua Chang
FHFujiang Hou
Fujiang Hou