Spatial evaluation and trade-off analysis of soil functions through Bayesian networks

摘要

There is increasing recognition that soils fulfil many functions for society. Each soil can deliver a range of functions, but some soils are more effective at some functions than others due to their intrinsic properties. In this study we mapped four different soil functions on agricultural lands across the European Union. For each soil function, indicators were developed to evaluate their performance. To calculate the indicators and assess the interdependencies between the soil functions, data from continental long-term simulation with the DayCent model were used to build crop-specific Bayesian networks. These Bayesian Networks were then used to calculate the soil functions' performance and trade-offs between the soil functions under current conditions. For each soil function the maximum potential was estimated across the European Union and changes in trade-offs were assessed. By deriving current and potential soil function delivery from Bayesian networks a better understanding is gained of how different soil functions and their interdependencies can differ depending on soil, climate and management. Highlights