Novel methods for spatial prediction of soil functions within landscapes (SP0531)

Abstract

Previous studies showed that soil patterns could be predicted in agriculturally managed landscapes by modelling and extrapolating from extensive existing but related integrated datasets. Based on these results we proposed to develop and apply predictive models of the relationships between environmental data and known soil patterns to predict capacity for key soil functions within diverse landscapes for which there is little detailed underpinning soil information available. Objectives were: To develop a high-level framework in which the non-specialist user-community could explore questions. To generate digital soil maps for three selected catchments at a target resolution of 1:50000 to provide the base information for soil function prediction. To use a modelling approach to predict the performance of key soil functions in catchments undergoing change but where only sparse or low resolution soil survey data are available. To use a modelling approach to assess the impact of different management scenarios and/or environmental conditions on the delivery of multiple soil functions within a catchment. To create a detailed outline of the requirements for ground-truthing to test the predicted model outputs at a catchment scale. To contribute to the development of a high-level framework for decision makers