Estimating a region's soil organic carbon baseline: The undervalued role of land-management

In light of recent concern over the extent of global warming and the role of soil carbon as a potential store of atmospheric carbon, there is increasing pressure and demand for regions to estimate their current soil organic carbon (SOC) stocks with the greatest possible accuracy. This study began by approaching the task in a similar way to previous studies where attempts at calculating SOC baselines at global, national or regional scale have used mean values for soil orders and multiplied these values by the mapped areas of the soils they represent. It also followed other methods that have approached the task from a land-cover point of view, making estimates using only land-use, or soil order/land-use combinations and others that have included variables such as altitude, climate and soil texture. The research assessed forms of stratification which could improve these baseline estimates by determining the major controls on SOC concentrations (%SOC) at the National Trust Wallington estate in Northumberland, NE England (area = 55 km2) where an extensive soil sampling campaign was used to test what level of accuracy could be achieved in modelling the %SOC values on the Estate using a range of existing national and local data. Mapped %SOC values were compared to the values predicted from The National Soils Resources Institute (NSRI) representative soil profile data for major soil group, soil series and land-use corrected soil series values, as well as land-use/major soil group combinations from the Countryside Survey database.The results of this study show that:
• When only soil series or land-use was used as a predictor only 48% and 44% of the variation in the dataset was explained.
• When soil series/land-use combinations were used explanatory power increased to 57%.
• Both altitude and soil pH proved to be significant controls on %SOC and including these variables gave an improvement to 59%.A further improvement from 59% to 66% in the ability to predict %SOC levels at point locations when farm tenancy was included suggests that differences in land-management practices between farm tenancies could be responsible for more of the variation in %SOC than either soil series or land-use.