Wednesday, November 7, 2007
293-10

Dynamics of Crop Residue Composition-Decomposition: Temporal Modeling of Multivariate Carbon Sources and Processes.

Abdullah Jaradat1, Jane Johnson2, Sharon Weyers2, and Nancy Barbour2. (1) USDA-Agricultural Research Service, 803 Iowa Ave., Morris, MN 56267, (2) USDA-ARS, USDA-ARS, 803 Iowa Ave, Morris, MN 56267

We examined multivariate relationships in structural carbohydrates plus lignin (STC) and non-structural (NSC) carbohydrates and their impact on C:N ratio and the dynamics of active (ka) and passive (kp) residue decomposition of alfalfa, corn, soybean, cuphea and switchgrass as candidates in diverse crop rotations. Differences in residue composition indicate different patterns of investment, inconsistencies in the relationships between STCs and NSCs in stems, roots and leaves, and differences in construction cost (g glucose per g of dry matter) among crops and among organs within crops. Differences among crops accounted for large variances in acid insoluble lignin, hemicellulose and starch; differences among organs accounted for large variances in cellulose and hemicellulose; whereas differences among organs within crops accounted for significant variances in all STCs and NSCs. Variation in N, but not in C or N+C, content explained the greatest variance (R**2>73 for crops, and >62 for organs) in C:N ratios. Strong canonical relationships were found between both STCs and NSCs and each of ka (r=0.95; p<0.001) and kp (r=0.84; p<0.001) estimates during a 500-day decomposition period. C:N ratio was a major determinant of ka but not kp, with r-values decreasing with time from -0.95 to -0.60 (p<0.001) for ka and from -0.08 (p=0.24) to -0.38 (p<0.05) for kp. Differences among crops explained 32-64 and 5-33% of variation in ka and kp, respectively; whereas the respective values for differences among organs within crops were 5-23 and 20-41%. Sensitivity analyses and validation variances predicted the time-dependent contribution of each STC and NSC biochemical to residue decomposition as quantified by the dynamics of ka and kp values. Practical implications for crop sequencing in diverse crop rotations will be presented.