Abstract

Soils are a finite resource that is under threat, mainly due to human pressure. Therefore, there is an urgent need to produce maps of soil properties, functions and behaviors that can support land management and various stakeholders’ decisions. Compaction is a major threat to soil functions, such as water infiltration and storage, and crops’ root growth. However, there is no general agreement on a universal and easy-to-implement indicator of soil susceptibility to compaction. The proposed indicators of soil compaction require numerous analytical determinations (mainly bulk density measurements) that are cost prohibitive to implement. In this study, we used data collected in numerous in situ topsoil observations during conventional soil survey and compared field observations to usual indicators of soil compactness. We unraveled the relationships between field estimates of soil compactness and measured soil properties. Most of the quantitative indicators proposed by the literature were rather consistent with the ordering of soil compactness classes observed in the field. The best relationship was obtained with an indicator using bulk density and clay (BDr2) to define three classes of rooting limitation. We distinguished six clusters of topsoil behaviors using hierarchical clustering. These clusters exhibited different soil behaviors to compaction that were related to soil properties, such as particle-size fractions, pH, CaCO3 and organic carbon content, cation exchange capacity, and some BDr2 threshold values. We demonstrate and discuss the usefulness of field observations to assess topsoil behavior to compaction. The main novelty of this study is the use of large numbers of qualitative field observations of soil profiles and clustering to identify contrasting behavior. To our knowledge, this approach has almost never been implemented. Overall, analysis of qualitative and quantitative information collected in numerous profiles offers a new way to discriminate some broad categories of soil behavior that could be used to support land management and stakeholders’ decisions.

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