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Soils and climate change: potential impacts on carbon stocks and greenhouse gas emissions, and future research for Australian agriculture

Baldock, J. A., Wheeler, I., McKenzie, N., McBrateny, A.
Crop & pasture science 2012 v.63 no.3 pp. 269-283
adaptation, agricultural management, agricultural research, atmosphere, carbon, carbon dioxide, carbon sinks, climate, climate change, greenhouse gas emissions, greenhouse gases, issues and policy, methane, models, nitrogen, nitrous oxide, risk reduction, soil air, soil types, soil water content, Australia
Organic carbon and nitrogen found in soils are subject to a range of biological processes capable of generating or consuming greenhouse gases (CO2, N2O and CH4). In response to the strong impact that agricultural management can have on the amount of organic carbon and nitrogen stored in soil and their rates of biological cycling, soils have the potential to reduce or enhance concentrations of greenhouse gases in the atmosphere. Concern also exists over the potential positive feedback that a changing climate may have on rates of greenhouse gas emission from soil. Climate projections for most of the agricultural regions of Australia suggest a warmer and drier future with greater extremes relative to current climate. Since emissions of greenhouse gases from soil derive from biological processes that are sensitive to soil temperature and water content, climate change may impact significantly on future emissions. In this paper, the potential effects of climate change and options for adaptation and mitigations will be considered, followed by an assessment of future research requirements. The paper concludes by suggesting that the diversity of climate, soil types, and agricultural practices in place across Australia will make it difficult to define generic scenarios for greenhouse gas emissions. Development of a robust modelling capability will be required to construct regional and national emission assessments and to define the potential outcomes of on-farm management decisions and policy decisions. This model development will require comprehensive field datasets to calibrate the models and validate model outputs. Additionally, improved spatial layers of model input variables collected on a regular basis will be required to optimise accounting at regional to national scales.