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ARS Home » Midwest Area » St. Paul, Minnesota » Soil and Water Management Research » Research » Publications at this Location » Publication #174032
Title: CORN ROOT INFLUENCE ON AUTOMATED MEASUREMENT OF CARBON DIOXIDE CONCENTRATIONS

Author
item CHEN, DONG - UNIV OF MINNESOTA
item MOLINA, JEAN ALEX - UNIV OF MINNESOTA
item Clapp, Charles
item Venterea, Rodney - Rod
item PALAZZO, ANTONIO - USACOE

Submitted to: Soil Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 5/17/2005
Publication Date: 10/1/2005
Citation: Chen, D., Molina, J.E., Clapp, C.E., Venterea, R.T., Palazzo, A.J. 2005. Corn root influence on automated measurement of carbon dioxide concentrations. Soil Science. 170:779-787.

Interpretive Summary: Soil respiration is a significant component of global carbon balance. It is recognized that CO2 production by microbial respiration in soil is a more desirable indicator of soil respiration than the CO2 flux at the soil-air interface. The objective of this paper was to design an automated measurement system to monitor CO2 concentration in soil and to use the data to compute CO2 production. The system was designed to require low maintenance with high temporal resolution of soil CO2 concentrations. Computed CO2 production was highest in the top soil layer. A peak of soil CO2 concentration occurred after each of the major rain events. The amplitude of the peaks decreased with depth. Differences between the CO2 concentration in the root and root-excluded soils were small between rainfalls, but large after rain events. Data from this experiment, combined with model verification will provide management suggestions that can increase biological carbon sequestration with minimal air and water nitrogen pollution.

Technical Abstract: Carbon dioxide (CO2) production is a more desirable indicator of soil carbon (C) dynamics than CO2 flux at the soil-air interface, which is significantly influenced by the gas-transport condition of the soil. Production of CO2 can be computed from CO2 concentrations if high-temporal measurements are made. Our objective was to design an automated CO2 measurement system that requires low maintenance with high-temporal resolution of CO2 concentration in the soil. The CO2 sensors were located at different soil depths from 10 to 60 cm, with and without roots, to measure the effect of corn (Zea mays, L.) root activities on CO2 concentrations and C dynamics. Computed CO2 production was highest in the soils above 20 cm. A peak of soil CO2 concentration occurred after each of the major rain events. The amplitude of the peaks decreased with depth. Differences between the CO2 concentrations in the root and root-excluded soils were small between rainfall events and large at and after rain. Soil CO2 concentration showed diurnal variations at the 10-, 20-, and 40-cm depths, whereas it was hardly detectable at the 60-cm depth. A direct comparison indicates that soil CO2 measured with the automated measurement system represents CO2 of soil surrounding the sensor.