Quantifying Soil Carbon Sequestration: Textural Effects
Demonstrate that we can accurately quantify changes in soil C content by estimating soil C changes through the use of simulation models.
IPNI-2001-CAN-SK30
10 Apr 2001
Methodology
- We will conduct a spatial analysis of soil C and soil texture in three continuously cropped rotations [i.e., Continuous wheat (Cont W) receiving N+P fertilizer, Cont W receiving only P fertilizer, and Wheat-Lentil receiving N+P fertilizer (W-Lent (N+P)]. The rotations chosen (3 of 10 rotations comprising the experiment) appear to differ in texture and in the degree of uniformity of texture based on hypotheses drawn from long-term soil organic C trends. We will sample all 3 replicates of each treatment. Therefore there are 12 plots to be sampled [3 for Cont W (N+P), 3 for Cont W (+P), and 6 for W-Lent (N+P)]. Each plot is 10.5 m x 30 m.
Within each plot, 12 sampling points, with fixed measurements from the plot centre line (Fig. 2), will be established. Two cores (5 cm diameter cores) will be taken at each sampling point using a hydraulic coring machine mounted on a truck. The cores will be received in specially designed aluminum sleeves with sealed end caps, and the sleeves temporarily stored in a constant temperature cold room at 4C until further processing.
Each core will be carefully removed from the sleeve using a mechanical extractor device, and the undisturbed cores accurately and consistently segmented into the 0 - 7.5 and 7.5 - 15 cm depths. Subsamples will be taken for moisture determination, bulk density, and soil texture using the pipette method. The remaining soil will be sieved through a 2 mm mesh to separate all visible plant material (e.g., leaves, stems, crowns, and roots) and air dried. The plant materials collected will be dried, weighed placed in plastic bags, and stored. Sub-samples of air-dried, sieved soil will be submitted to the SPARC Analytical Chemistry Laboratory for determination of organic C and total N. All remaining soil samples will be archived.
All data will be analyzed using ANOVA for a stratified sampling design to determine spatial dependency
of soil attributes, and by correlation to determine the degree of association of organic C and particle size distribution (texture).
The relationships identified will be incorporated into a revised version of the CENTURY model, and other models (e.g., EPIC, Farming Systems Model) for predicting long- and short-term changes in soil carbon levels.