Soil Ph Determines Microbial Network Complexity and the Relative Abundance of Keystone Taxa Across Wheat Fields of the North China Plain

2022 ◽  
Author(s):  
ying yang ◽  
Yu Shi ◽  
Jie Fang ◽  
Haiyan Chu ◽  
Jonathan M. Adams
Keyword(s):  
Soil Ph ◽  
Relative Abundance ◽  
North China Plain ◽  
North China ◽  
The North ◽  
Microbial Network ◽  
The North China Plain

scholarly journals Effects of Different Fertilizers on Rhizosphere Bacterial Communities of Winter Wheat in the North China Plain

Agronomy ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 93
Author(s):  
Rubiao Liang ◽  
Ruixing Hou ◽  
Jing Li ◽  
Yun Lyu ◽  
Sheng Hang ◽  
...  
Keyword(s):  
Winter Wheat ◽  
Relative Abundance ◽  
North China Plain ◽  
North China ◽  
Rhizosphere Soil ◽  
The North ◽  
The North China Plain ◽  
Bioorganic Fertilizer ◽  
Rhizosphere Bacterial Community ◽  
Copiotrophic Bacteria

The application of bioorganic fertilizer affects rhizosphere microbes and further improves soil fertility in farmlands. However, the effects of different fertilizers on rhizosphere bacterial community diversity and structure of winter wheat remains unclear. In this study, we explored the effects of different fertilization treatments (no fertilizer added, CK; nitrogen fertilizer, NF; bioorganic fertilizer, BOF) on the rhizosphere bacterial community of winter wheat in the North China Plain. Rhizosphere soil treated with BOF had a higher Shannon index than that of CK and NF. The relative abundance of the Proteobacteria treated with BOF was significantly higher than that of NF, while the Acidobacteria and Planctomycetes were significantly lower. The redundancy analysis (RDA) and Mantel test showed that soil bacterial communities were significantly correlated with pH, nitrate, available phosphorus (AP), and available potassium (AK). Our findings indicated that BOF increased bacterial diversity and the relative abundance of copiotrophic bacteria in rhizosphere soil, while NF reduced bacterial diversity and increased the relative abundance of oligotrophic bacteria. The increase in copiotrophic bacteria in the rhizosphere of winter wheat could indicate an increase in soil nutrient availability, which might have positive implications for soil fertility and crop production.

ROx Budgets and O3 Formation during Summertime at Xianghe Suburban Site in the North China Plain

2021 ◽  
Author(s):  
Min Xue ◽  
Jianzhong Ma ◽  
Guiqian Tang ◽  
Shengrui Tong ◽  
Bo Hu ◽  
...  
Keyword(s):  
North China Plain ◽  
North China ◽  
The North ◽  
The North China Plain ◽  
Suburban Site

scholarly journals Improving the Resolution and Accuracy of Groundwater Level Anomalies Using the Machine Learning-Based Fusion Model in the North China Plain

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 46
Author(s):  
Gangqiang Zhang ◽  
Wei Zheng ◽  
Wenjie Yin ◽  
Weiwei Lei
Keyword(s):  
Machine Learning ◽  
Data Fusion ◽  
Groundwater Level ◽  
North China Plain ◽  
North China ◽  
Gradient Boosting ◽  
Fusion Model ◽  
The North ◽  
The North China Plain ◽  
Prediction Module

The launch of GRACE satellites has provided a new avenue for studying the terrestrial water storage anomalies (TWSA) with unprecedented accuracy. However, the coarse spatial resolution greatly limits its application in hydrology researches on local scales. To overcome this limitation, this study develops a machine learning-based fusion model to obtain high-resolution (0.25°) groundwater level anomalies (GWLA) by integrating GRACE observations in the North China Plain. Specifically, the fusion model consists of three modules, namely the downscaling module, the data fusion module, and the prediction module, respectively. In terms of the downscaling module, the GRACE-Noah model outperforms traditional data-driven models (multiple linear regression and gradient boosting decision tree (GBDT)) with the correlation coefficient (CC) values from 0.24 to 0.78. With respect to the data fusion module, the groundwater level from 12 monitoring wells is incorporated with climate variables (precipitation, runoff, and evapotranspiration) using the GBDT algorithm, achieving satisfactory performance (mean values: CC: 0.97, RMSE: 1.10 m, and MAE: 0.87 m). By merging the downscaled TWSA and fused groundwater level based on the GBDT algorithm, the prediction module can predict the water level in specified pixels. The predicted groundwater level is validated against 6 in-situ groundwater level data sets in the study area. Compare to the downscaling module, there is a significant improvement in terms of CC metrics, on average, from 0.43 to 0.71. This study provides a feasible and accurate fusion model for downscaling GRACE observations and predicting groundwater level with improved accuracy.

scholarly journals The water-saving potential of using micro-sprinkling irrigation for winter wheat production on the North China Plain

2021 ◽  
Vol 20 (6) ◽  
pp. 1687-1700
Author(s):  
Li-chao ZHAI ◽  
Li-hua LÜ ◽  
Zhi-qiang DONG ◽  
Li-hua ZHANG ◽  
Jing-ting ZHANG ◽  
...  
Keyword(s):  
Winter Wheat ◽  
North China Plain ◽  
North China ◽  
Water Saving ◽  
Wheat Production ◽  
The North ◽  
The North China Plain

scholarly journals Corrigendum to “Folate content analysis of wheat cultivars developed in the North China Plain” [289 (2019) 377–383]

2021 ◽  
Vol 351 ◽  
pp. 129349
Author(s):  
Bisma Riaz ◽  
Qiuju Liang ◽  
Xing Wan ◽  
Ke Wang ◽  
Chunyi Zhang ◽  
...  
Keyword(s):  
Content Analysis ◽  
North China Plain ◽  
North China ◽  
Wheat Cultivars ◽  
The North ◽  
The North China Plain
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