Automated sensor-based quantification of soil water retention and microbial respiration across drying conditions
Automated sensor-based quantification of soil water retention and microbial respiration across drying conditions
复制标题
基于传感器的自动化量化干燥条件下的土壤保水性和微生物呼吸
DOI:
10.1016/j.soilbio.2023.108987
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发表时间:
2023
影响因子:
9.7
通讯作者:
Guillard, Karl
中科院分区:
文献类型:
--
作者:
Gan, Huijie;Roper, Wayne R.;Groffman, Peter M.;Morris, Thomas F.;Guillard, Karl
Understanding soil responses to climate-induced precipitation variability is important for improving global carbon models and the development of climate-resilient agriculture. However, our knowledge remains limited regarding factors that influence soil water dynamics and microbial respiration across drying conditions, partially hindered by the lack of easily accessible methodologies. We developed a low-cost, automated, and integrated system to simultaneously quantify microbial respiration and soil water retention in response to drought conditions. This system integrates a CO2sensor and a digital scale, enabling continuous measurement of CO2concentration and soil water loss by evaporation when soils are incubated with desiccants inside air-tight chambers. Here we show that the sensor platform provides accurate and repeatable CO2measurements when compared to a spectroscopy gas analyzer and the alkali trap method. Using the sensor platform, we further demonstrated that averaged microbial respiration of rewetted soil over 4-day incubation declined as management intensity increased following the order of Till ≤ NoTill ≤ Till_fallow ≤ NoTill_fallow = Hay field < Forest. These soils were air-dried for two years before use in incubation experiments, and microbial respiration upon rewetting showed a unimodal response, which rapidly increased and peaked within 12 h except for in forest soils that exhibited a delayed response with respiration peaking at 30 h. Under drying conditions, rewetted soil from the Hay field showed lower water loss than other soils. Volumetric water content at the end of the drying period increased in the order of Till ≤ NoTill < Till_fallow ≤ NoTill_fallow = Hay field < Forest. We posit that this sensor platform provides a powerful tool for functional soil health assessments and fundamental understanding of soil water dynamics and microbial activities in responses to climate-induced water stress.
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影响因子:
6.4
作者:
A. Peters;S. Iden;W. Durner
通讯作者:
A. Peters;S. Iden;W. Durner
DOI:
--
发表时间:
2015
期刊:
影响因子:
--
作者:
B. Murphy
通讯作者:
B. Murphy
DOI:
--
发表时间:
2014
期刊:
影响因子:
--
作者:
Nan Ding;Yuehui Chen;Can Huan Li;Jiangni Lei;Jin He Qian;Bo Yang
通讯作者:
Bo Yang
影响因子:
--
作者:
Han J;Zhou Z
通讯作者:
Zhou Z
影响因子:
4.6
作者:
M. Wander;L. Cihacek;M. Coyne;R. Drijber;J. Grossman;J. Gutknecht;W. Horwath;S. Jagadamma;D. Olk;M. Ruark;S. Snapp;L. Tiemann;R. Weil;R. Turco
通讯作者:
R. Turco