Estimation of plant litter pools and decomposition-related parameters in a mechanistic model

• DOI: 10.1007/s11104-010-0404-4
• Publication Date: 2010-05-11T16:40:39Z
• Authors: Signe Kynding Borgen; Lars Molstad; Sander Bruun; Tor Arvid Breland; Lars Reier Bakken; Marina Azzaroli B...
• Keywords: 0401 agriculture, forestry, and fisheries; 04 agricultural and veterinary sciences

Modeling the C and N dynamics during decomposition of plant residues depends on robust estimation of the litter pool partitioning (LPP) of residues, i.e. the fraction of their C and N allocated to rapidly and slowly decomposing pools. We searched for ways to estimate LPP by analyzing data on C and N mineralization during decomposition of 60 widely different plant residues, using a simple model with two litter pools and one microbial pool. LPP and relevant global parameters were estimated by model optimization (Levenberg-Marquardt-least-squares algorithm) in one operation. These kinetically-defined LPP values were used in regression analyses against data from stepwise chemical digestion (SCD) and near-infrared reflectance (NIR) analysis of the plant residues. LPP predicted by these regression models resulted in better performance than LPP from measured neutral-detergent-soluble (NDS) C and N when validated on independent data (n = 15 plant residues). The results demonstrated the potential improvement by simultaneous estimation of residue specific LPP and global parameters, and that kinetically-defined LPP can be equally well predicted by NIR as by total N and NDS-C. Model failure for a minority of the plant-residues could partly be removed by altering the microbial C/N ratio (global optimum 7.1) within the range 5–15, possibly reflecting a variable dominance of bacteria or fungi.