A Markov Model Projection of Soil Organic Carbon Stores Following Land Use Changes

✍ Scribed by D.M. Howard; P.J.A. Howard; D.C. Howard

• Publisher: Elsevier Science
• Year: 1995
• Tongue: English
• Weight: 107 KB
• Volume: 45
• Category: Article
• ISSN: 0301-4797
• DOI: 10.1006/jema.1995.0076

✦ Synopsis

Soils are major sinks of carbon, and land use can affect the magnitudes of soil organic carbon stores and the net flux of carbon between the land and atmosphere. Hence, it is of some interest to have a method for examining the future consequences of changes in the patterns of land use for soil organic carbon stores, and to allow experiments to be carried out to assess the likely effects of various policy options. We illustrate the use of a Markov model to project future areas of land use from land cover transition matrices for England, Wales and Scotland, 1984-1990, and by the application of vectors of soil organic carbon stores for each land use types to the changes in areas to obtain projected changes in the soil carbon stores. In England and Wales, much depends on whether or not urban land is assumed to store soil carbon. For example, during 1984-1990, there was an overall decrease in potential organic carbon store in England and Wales of 32•64 MtC assuming that urban land stores no soil carbon, but that overall decrease is reduced by 73% if urban land is assumed to store 26•25×10 3 tC km -2 . For England and Wales, the limiting probabilities show 37•9% of the land as urban and 15•3% as arable. There would be a decrease in the overall potential soil carbon storage capacity of 610 MtC or 239 MtC, depending on whether or not urban land is assumed to store soil carbon. For Scotland, the limiting probabilities show 53•1% of the land as lowland heath and 16•9% as coniferous forest. There would be a decrease in the overall potential soil carbon storage capacity of 9414 MtC if urban land is assumed to store no carbon, and 9668 MtC if it is assumed to store carbon. By changing entries in the land cover transition matrices, the consequences of different policy options can be examined.