64-3 Reporting Reliable Soil C Stocks From the Field to the Region.

See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Symposium--Partnering Soil Science and Statistics, Ways to Avoid Statistical Malpractice In Soil Research: I
Monday, October 17, 2011: 2:00 PM
Henry Gonzalez Convention Center, Room 209
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Bas van Wesemael, Esther Goidts and Antoine Stevens, Earth and Life Institute, Universite catholique de Louvain, Louvain-la-Neuve, Belgium
Uncertainties in soil organic carbon (SOC) stock assessments are rarely quantified even though they are critical in determining the significance of the results. Previous studies on this topic generally focused on a single variable involved in the SOC stock calculation (SOC concentration, sampling depth, bulk density and rock fragment content) or on a single scale, rather than using an integrated approach (i.e. taking into account interactions between variables). Different sources of uncertainty in SOC stock prevail when the assessment unit increases from the individual field to a homogeneous agricultural zone and finally a region.  A case study in southern Belgium shows that the coefficient of variation of the SOC stock increases across scales (from 5 to 35%), and is higher for grassland than for cropland. The variability of SOC concentration (due to errors in the laboratory and to the high SOC spatial variability) and of the rock fragment content predominate the uncertainties in SOC stock. Proximal sensing techniques are being developed to map the SOC content, bulk density and stone content at high resolution for a field. Such techniques will provide SOC stock estimates with narrow confidence limits instead of traditional sampling and analysis that are not cost-efficient for individual fields. At the regional scale, SOC stock monitoring of agricultural soils in southern Belgium allows the detection of an average SOC stock change of 20% within 11 years if very high rates of SOC stock changes occur (1 t C/ha/y).
See more from this Division: ASA Section: Biometry and Statistical Computing
See more from this Session: Symposium--Partnering Soil Science and Statistics, Ways to Avoid Statistical Malpractice In Soil Research: I