Land use change (LUC) is a fundamental anthropogenic disturbance in the global carbon cycle. Here we present model developments in a global dynamic vegetation model ORCHIDEE-MICT for more realistic representation of LUC processes. First, we included gross land use change (primarily shifting cultivation) and forest wood harvest in addition to net land use change. Second, we included sub-grid even-aged land cohorts to represent secondary forests, and to keep track of the age of agricultural lands since LUC, which are associated with variable soil carbon stocks. Combination of these two features allows simulating shifting cultivation with a short rotation length involving mainly secondary forests instead of primary ones. This is in contrast with the traditional approach where a single patch is used for a given land cover type in a model grid cell and forests are thus close to primary ones. We have tested the model over Southern Africa for the period 1501–2005 forced by a historical land use change data set. Including gross land use change and wood harvest has increased LUC emissions in both simulations with (Sage) and without (Sageless) sub-grid secondary forests, but larger increase is found in Sageless (by a factor of 2) than Sage (by a factor of 1.5). Emissions from bi-directional land turnover alone are 35 % lower in Sage than Sageless, mainly because the secondary forests cleared for agricultural land have a lower aboveground biomass than primary ones. We argue that, without representing sub-grid land cohort demography, the additional emissions from land turnover/gross land use change are overestimated. In addition, our developments provide possibilities to account for continental or global forest demographic change resulting from past anthropogenic and natural disturbances.
Yue, C., Ciais, P., Luyssaert, S., Li, W., McGrath, M. J., Chang, J., & Peng, S. (2017). Representing anthropogenic gross land use change, wood harvest and forest age dynamics in a global vegetation model ORCHIDEE-MICT (r4259). Geoscientific Model Development Discussions, 1-38. https://doi.org/10.5194/gmd-2017-118