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United States Department of Agriculture

Agricultural Research Service

Title: Temporal Variability of Soil C02 Flux: Effect of Sampling Frequency on Cumulative Carbon Loss Estimation

Authors
item Parkin, Timothy
item Kaspar, Thomas

Submitted to: Soil Science Society of America Journal
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: November 23, 2003
Publication Date: July 1, 2004
Citation: Parkin, T.B., Kaspar, T.C. 2004. Temporal variability of soil C02 flux: effect of sampling frequency on cumulative carbon loss estimation. Soil Science Society of America Journal. 68(4):1234-1241.

Interpretive Summary: Carbon dioxide, a known greenhouse gas, is increasing in the atmosphere and is contributing to global climate change. Removing carbon dioxide from the atmosphere by plant photosynthesis and storing this fixed or organic carbon in the soil may be a strategy for decreasing potential global warming. However, once plant carbon is returned to the soil, it is acted on by soil microorganisms which convert this fixed carbon back into carbon dioxide. Thus, it is important to understand the factors contributing to organic carbon decomposition in soil and subsequent carbon dioxide release. Measuring the amount of carbon dioxide released by soil is problematic because the microbial activity varies through time. What is currently not known is how often measurements of carbon dioxide release must be made in order to accurately estimate the total amount of carbon dioxide released over an annual time period. This study investigates how frequently carbon dioxide release measurements must be made in order to accurately estimate total carbon dioxide production by the soil. We found that measurements must be made at least once every 4 days (approximately 2 times per week) in order to get an accurate estimate of carbon dioxide release. However, microbial activity in soil is influenced by temperature and rainfall, thus, we also determined that best measures of carbon dioxide release are obtained if measurements are made at the times of day when the outside temperature corresponds with the average daily temperature, and at 1 and 3 days following rainfall events. This information should aid scientists in making better measurements of carbon dioxide release from soil and in developing mathematical models to predict how temperature and rainfall influence soil carbon loss.

Technical Abstract: It is well known that soil C02 flux can exhibit pronounced day-to-day variations, however, measurements of soil C02 flux with soil chambers are typically only done at discrete points in time. This study was done to evaluate the impact of sampling frequency on the precision of cumulative C02 flux estimates calculated from field measurements. Automated chambers were deployed at two locations in a no-till corn/soybean field. The chambers were used to measure soil C02 fluxes every hour from March 4, 2000, through June 6, 2000. Sampling frequency effects on cumulative C02-C flux estimation were assessed using a jackknife technique whereby the populations of measured hourly fluxes were numerically sampled at regular time intervals ranging from 1 d to 20 d, and the resulting sets of jackknife fluxes were used to calculate estimates of cumulative C02-C flux. We observed that as the sampling interval increased from 1 d to 12 d, the variance associated with cumulative flux estimates increased. However, at sampling intervals of 12 to 20 d variance was relatively constant. At relatively frequenct sampling intensities (i.e. once every 3 d), estimates of cumulative C loss are within +- 20% of the expected value at both sites. As the time interval between sampling increases, the potential deviation in estimated cumulative C02 flux increases, such that sampling once every 20 d yielded potential estimates within +60% and -40% of the actual cumulative C02 flux. A stratified sampling scheme around rainfall events was also evaluated and was found to provide more precise estimates at lower sampling intensities. These results should aid investigators in designing sampling schemes to minimize temporal variability.

Last Modified: 8/30/2014
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