See more from this Session: Symposium--Mineral-Organic Interactions Across Time and Space: I & II
Monday, October 17, 2011: 10:00 AM
Henry Gonzalez Convention Center, Room 212B, Concourse Level
The soil mineral matrix, determined in large part by the type of parent material the soil is formed from, plays a key role in determining both the size and mean residence time of soil organic C stocks. However, variation in the mechanisms of soil organic C stabilization as a function of parent material remains poorly understood. We sampled a lithosequence of four parent materials (rhyolite, granite, basalt, and dolostone) under Pinus ponderosa to examine variation in soil organic matter composition (SOM), distribution, and mean residence time as a function of soil mineral assemblage. Three soil profiles were examined on each parent material. SOM was analyzed by a combination of density separation (into Free/Light, Occluded/Light, and Heavy/Mineral fractions), elemental analysis, 14C abundance, 13C NMR, and pyrolysis GC/MS. Quantitative and qualitative XRD were used to examine the mineral assemblages of the soils. Soil microbial communities from each of the soils were also compared on the basis of respiration rate, biomass abundance, and bacterial community composition (measured by TRFLP). Results indicated significant differences in SOM abundance, composition, and distribution among soils of differing mineral assemblage. Variation in microbial parameters was well correlated with variation in soil physiochemical characteristics including soil pH, metal-humus complex abundance, and Al3+ concentration. Specifically, the data suggest a gradient in the dominant SOM stabilization mechanism among sites, with chemical recalcitrance and metal– humus complexation the dominant control in the acidic rhyolite and granite soils, and mineral adsorption the dominant factor in the basic limestone and basalt soils. With further investigation, such knowledge of the influence of the soil mineral matrix on SOM dynamics may be useful in informing and improving parameters used in regional/ecosystem-scale C cycle models.