Modelling soil carbon in agricultural systems: A way to widen the experimental space

Abstract

Mechanistic and explanatory simulation models provide robust and objective methods to extrapolate likely responses of crops and soils to climate change over different landscapes and time periods. Central to such simulation models are the supply of mineralised nutrients, in particular nitrogen, to crops through linked crop and nutrient sub-models that is achieved through modelling soil carbon dynamics. Attention to soil processes is therefore an essential part of building robust and sustainable production systems and understanding the potential impacts of climate change. To the farmer, focus must be on the productive capacity of the land and its rejuvenation to sustain production. In the broader context of reducing atmospheric CO2 concentration through soil C sequestration, understanding soil processes and the immediate environment likewise require attention to productivity issues. This is because without maintaining productivity a better understanding of soil organic carbon (SOC) processes is unlikely to lead to increased SOC sequestration in Australia's farming land. Some gaps in knowledge of how to manage SOC are being addressed in a national research effort, including the scant measured data against which models can be tested. Nevertheless, continuing to apply models to push the boundaries well beyond what can be achieved in practice widens the experimental space, allowing new ideas to be tested where physical experiments are not possible. This raises optimism that new ways may be discovered to explain change in SOC and increase SOC where it is possible in a beneficial way.