Influence of No-Tillage on Soil CO2 Emissions Affected by Monitoring Hours in Maize in the North China Plain

被引:0
|
作者
Du, Kun [1 ]
Li, Fadong [2 ]
Leng, Peifang [2 ]
Zhang, Qiuying [3 ]
机构
[1] Linyi Univ, Coll Resources & Environm, Shandong Prov Key Lab Water & Soil Conservat & Env, Linyi 276000, Peoples R China
[2] Chinese Acad Sci, Shandong Yucheng Agroecosystem Natl Observat & Res, Yucheng Comprehens Expt Stn, IGSNRR, Beijing 100101, Peoples R China
[3] Chinese Res Inst Environm Sci, Beijing 100101, Peoples R China
来源
AGRONOMY-BASEL | 2025年 / 15卷 / 01期
基金
中国国家自然科学基金;
关键词
no-tillage; soil CO2 emissions; monitoring hours; maize; NITROGEN-FERTILIZATION; CARBON-DIOXIDE; RESPIRATION; TEMPERATURE; IRRIGATION; BALANCE; FIELD; FLUX;
D O I
10.3390/agronomy15010136
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
There is still controversy over the influence of no-tillage (NT) on CO2 emissions in farmland soil. Few studies focus on the impact of monitoring hours on the response of soil CO2 emissions to NT. Therefore, an in situ experiment was conducted in maize cropland in the Shandong Yucheng Agro-ecosystem National Observation and Research Station in the North China Plain. The soil CO2 emissions, soil water content (SWC), and soil temperature (ST) were automatically monitored using the morning sampling (MonS) and continuous sampling (multi-hour sampling in one day, DayS) methods during the whole maize growth stages. The results showed that the MonS method decreased the sum of soil CO2 emissions by 146.39 g CO2 m(-2) in the wet year 2018 and increased that by 93.69 g CO2 m(-2) in the dry year 2019 when compared to the DayS method. The influence intensity of NT on soil CO2 effluxes was decreased with the MonS method. In contrast, the MonS method had no significant effect on the differences in SWC between NT and conventional tillage. However, the MonS method increased the variance in ST between NT and conventional tillage by 0.45 degrees C, which was higher than that with the DayS method (0.20 degrees C) across years. Compared to the DayS method, the MonS method increased the regression coefficient of soil CO2 emissions with SWC but decreased that with ST. This study is beneficial for reducing the artificial impact of monitoring hours on the data accuracy of soil CO2 effluxes and deepening the understanding of the influence of NT on soil CO2 emissions.
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页数:10
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