scholarly journals Linkage of N2O emissions to the abundance of soil ammonia oxidizers and denitrifiers in purple soil under long-term fertilization

2015 ◽  
Vol 61 (5) ◽  
pp. 799-807 ◽  
Author(s):  
Zhixin Dong ◽  
Bo Zhu ◽  
Keke Hua ◽  
Yan Jiang
2021 ◽  
Vol 166 ◽  
pp. 104062
Author(s):  
Rui Tao ◽  
Xiran Zhao ◽  
Xiaoliang Wu ◽  
Baowei Hu ◽  
Kollie B. Vanyanbah ◽  
...  

AMB Express ◽  
2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Songhe Chen ◽  
Rencai Gao ◽  
Xiaoling Xiang ◽  
Hongkun Yang ◽  
Hongliang Ma ◽  
...  

AbstractMicrobe-mediated ammonia oxidation is a key process in soil nitrogen cycle. However, the effect of maize straw mulching on the ammonia oxidizers in the alkaline purple soil remains largely unknown. A three-year positioning experiment was designed as follows: straw mulching measures as the main-plot treatment and three kinds of nitrogen application as the sub-plot treatment. We found the contents of soil organic carbon (SOC), total nitrogen (TN), available potassium (AK), available nitrogen (AN), available phosphorus (AP), and NH4+-N were increased after straw mulching and nitrogen application in alkaline purple soil, so did the amoA genes abundance of ammonia-oxidizing archaeal (AOA) and bacterial (AOB). Terminal restriction fragment length polymorphism (T-RFLP) analysis revealed that Thaumarchaeote (448-bp T-RF) was dominated the AOA communities, whereas Nitrosospira sp (111-bp T-RF) dominated the AOB communities. The community compositions of both AOA and AOB were altered by straw mulching and nitrogen application in alkaline purple soil, however, the AOB communities was more responsive than AOA communities to the straw mulching and nitrogen application. Further analysis indicated that SOC and AP were the main factors affecting the abundance and community compositions of AOA and AOB in alkaline purple soil. The present study reported that straw mulching and nitrogen strategies differently shape the soil ammonia oxidizers community structure and abundance, which should be considered when evaluating agricultural management strategies regarding their sustainability and soil quality.


2009 ◽  
Vol 167 (1-4) ◽  
pp. 545-558 ◽  
Author(s):  
Recep Kulcu ◽  
Kamil Ekinci ◽  
Fatih Evrendilek ◽  
Can Ertekin

Geoderma ◽  
2019 ◽  
Vol 338 ◽  
pp. 107-117 ◽  
Author(s):  
Pei-Pei Li ◽  
Yan-Lai Han ◽  
Ji-Zheng He ◽  
Shui-Qing Zhang ◽  
Li-Mei Zhang

Agronomy ◽  
2019 ◽  
Vol 10 (1) ◽  
pp. 50
Author(s):  
Ralf Liebermann ◽  
Lutz Breuer ◽  
Tobias Houska ◽  
David Kraus ◽  
Gerald Moser ◽  
...  

The rising atmospheric CO2 concentrations have effects on the worldwide ecosystems such as an increase in biomass production as well as changing soil processes and conditions. Since this affects the ecosystem’s net balance of greenhouse gas emissions, reliable projections about the CO2 impact are required. Deterministic models can capture the interrelated biological, hydrological, and biogeochemical processes under changing CO2 concentrations if long-term observations for model testing are provided. We used 13 years of data on above-ground biomass production, soil moisture, and emissions of CO2 and N2O from the Free Air Carbon dioxide Enrichment (FACE) grassland experiment in Giessen, Germany. Then, the LandscapeDNDC ecosystem model was calibrated with data measured under current CO2 concentrations and validated under elevated CO2. Depending on the hydrological conditions, different CO2 effects were observed and captured well for all ecosystem variables but N2O emissions. Confidence intervals of ensemble simulations covered up to 96% of measured biomass and CO2 emission values, while soil water content was well simulated in terms of annual cycle and location-specific CO2 effects. N2O emissions under elevated CO2 could not be reproduced, presumably due to a rarely considered mineralization process of organic nitrogen, which is not yet included in LandscapeDNDC.


2015 ◽  
Vol 84 ◽  
pp. 28-37 ◽  
Author(s):  
Xinli Wang ◽  
Cheng Han ◽  
Jinbo Zhang ◽  
Qianru Huang ◽  
Huan Deng ◽  
...  

2013 ◽  
Vol 143 ◽  
pp. 682-685 ◽  
Author(s):  
Sen Yang ◽  
Ming-Ming Gao ◽  
Shuang Liang ◽  
Shu-Guang Wang ◽  
Xin-Hua Wang
Keyword(s):  

2016 ◽  
Vol 93 ◽  
pp. 131-141 ◽  
Author(s):  
Peiyuan Cui ◽  
Fenliang Fan ◽  
Chang Yin ◽  
Alin Song ◽  
Pingrong Huang ◽  
...  

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