Abstract

Soil bulk density (BD), degree of compactness (DC), maximum bulk density (MBD), and critical water content (CWC) at which MBD is reached are commonly used to characterize soil compaction, and can be predicted from soil texture and organic matter content, omitting other components such as sand sub-classes and soil cementing agents and potential biases such as data redundancy and sub-compositional incoherence. Compositional data analysis is needed to account for interactions among soil components and to avoid biases. The aim of this study was to relate soil compaction indexes to the basic components of coarse-textured soils using unbiased numerical techniques. Soil samples collected in horizons A and B at 49 sites in Quebec, Canada, were analyzed for gravimetric water content, BD, particle-size distribution, MBD, CWC, organic C, total N, Si, Fe, Al, Mn, Mg and Ca. DC was calculated as the ratio of BD to MBD. The 14 physical-chemical soil properties were expressed as isometric log-ratios balances. We conducted principal component analysis to identify the components most correlated with compaction indexes. We used regression analysis to predict MBD and CWC, and used linear mixed-effects models to predict BD and DC. The regression models accounted for up to 83% of total variation in MBD and CWC, and the linear mixed-effects models explained 58–64% of total variation in BD and DC. BD and DC were found to decrease with clay content, and increase with larger proportion of coarser particles. Organic matter content tended to reduce BD and DC, and showed little effects on MBD. Increasing evenness of sand fractions resulted in a higher MBD value. Relationships between CWC and soil texture, and between CWC and organic C were not significant. Mineral cementing agents were the major contributors to soil compaction indexes. Si, Al, Fe and Ca oxides increased BD, DC and CWC, but reduced MBD. The sensitivity of coarse-textured soils to compaction could be predicted to support decisions on soil resilience after ripping and on the need to implement corrective chemical, biological and physical methods such as soil amendments, structure-building crops or textural mixtures to rebalance soil compositions.

Highlights

  • Soil quality is defined by the chemical, physical and biological attributes of the top 15 cm (Doran and Parkin, 1996; Boiteau et al, 2014) down to rooting depth (Spoor et al, 2003)

  • The first four principal components (PCs) explained 71.3% of the total variation in the variables included in principal component analysis (PCA) (Table 1)

  • For maximum bulk density (MBD), an intrinsic soil property reflecting the maximum effect of machines on the degradation of soil physical quality

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Summary

Introduction

Soil quality is defined by the chemical, physical and biological attributes of the top 15 cm (Doran and Parkin, 1996; Boiteau et al, 2014) down to rooting depth (Spoor et al, 2003). Crop yields may drop by average rates ranging from 15% in maize across soil textural groups (Duiker and Curran, 2004; Wolkowski and Lowery, 2008) to 34% in potato grown in coarse-textured soils (Stalham et al, 2005; Wolkowski and Lowery, 2008). Potato and maize crops grown sequentially in coarse-textured soils may suffer considerably from soil compaction. Compacted layers within 50 cm of the soil surface limit rooting depth (Grossman and Carlisle, 1969). Rootability is hampered where soil resistance exceeds 1 MPa for potato and 2–3 MPa for most other crops (Håkansson and Lipiec, 2000; Stalham et al, 2005)

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