Abstract

Abstract Soil maps provide essential information for forest management, and a recent transformation of the map making process through digital soil mapping (DSM) is providing much improved soil information compared to what was available through traditional mapping methods. The improvements include higher resolution soil data for greater mapping extents, and incorporating a wide range of environmental factors to predict soil classes and attributes, along with a better understanding of mapping uncertainties. In this chapter, we provide a brief introduction to the concepts and methods underlying the digital soil map, outline the current state of DSM as it relates to forestry and global change, and provide some examples of how DSM can be applied to evaluate soil changes in response to multiple stressors. Throughout the chapter, we highlight the immense potential of DSM, but also describe some of the challenges that need to be overcome to truly realize this potential. Those challenges include finding ways to provide additional field data to train models and validate results, developing a group of highly skilled people with combined abilities in computational science and pedology, as well as the ongoing need to encourage communication between the DSM community, land managers and decision makers whose work we believe can benefit from the new information provided by DSM.

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