Canadian farm-level soil carbon change assessment by merging the greenhouse gas model Holos with the Introductory Carbon Balance Model (ICBM)

Citation

Kröbel, R., Bolinder, M.A., Janzen, H.H., Little, S.M., VandenBygaart, A.J., and Kätterer, T. (2016). "Canadian farm-level soil carbon change assessment by merging the greenhouse gas model Holos with the Introductory Carbon Balance Model (ICBM).", Agricultural Systems, 143, pp. 76-85. doi : 10.1016/j.agsy.2015.12.010

Abstract

© 2015 .The farm-level model Holos, developed to explore mitigation options for greenhouse gas emissions (GHG) from Canadian farming systems, includes soil carbon change as a prominent component. Soil carbon was assumed to be constant, except where there was recent change in land use or management (e.g., conventional vs. reduced vs. no tillage). The factors associated with the changes were derived using CENTURY model simulations. To make Holos more responsive to farm management (e.g., crop rotation and residue management) and inter-annual climate variation, it was decided to replace the carbon change factors with the Introductory Carbon Balance Model (ICBM), a simple two carbon pool model driven by inputs from above- and belowground crop residues and manure. We showcase how the model will simulate the impact of crop rotation management decisions on soil carbon change, focussing on the choice of crop and crop residue retention, but considering also tillage and fertilization management. We argue that simulating carbon change at each field involved in the rotation is advantageous because it allows to test the rotation resilience with respect to inter-annual climate variation as well as to validate the model outputs using measurements of scientific long-term field experiments. We propose to report the farm-level carbon change results ranging from annual to centennial time frames which would be in line with the reporting requirements in carbon credit programs, while giving the user the capability to project and test new crop rotation systems using long-term carbon change forecasts.