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DIVISION S-7—FOREST & RANGE SOILS

Predicting Soil Properties from Organic Matter Content following Mechanical Site Preparation of Forest Soils

Ministère des Ressources Naturelles, de la Faune et des Parcs, Forêt Québec, Direction de la Recherche Forestière, 2700, rue Einstein, Sainte-Foy, QC, Canada G1P 3W8

^* Corresponding author (marcel.prevost{at}mrnfp.gouv.qc.ca).

The difficulties of sampling forest soils and their high spatial variability make estimation of soil physical properties following forest operations laborious. To develop prediction tools, soils were sampled from two sites located in the boreal forest of northern Québec, Canada. Soil organic matter (OM) content was found to be closely related to bulk density (D_b) and porosity after clearcutting and mechanical site preparation (MSP) on these sites. Reasonably good estimates of D_b, with an average error of 18 to 20%, can be made from the easily measurable OM concentration and the logarithmic relationships (R² = 0.731 and 0.847, respectively for the Alma and Chibougamau sites) developed in this study. The organic density approach, recently developed for forest soils in New England, was found to be less precise (R² = 0.637) than the logarithmic relationships following soil disturbance. For the two sandy till soils in northern Québec, the equation based on this concept best fit the data with a pure OM bulk density (D_bo) of 0.159 Mg m^–3 and a pure mineral matter bulk density (D_bm) of 1.561 Mg m^–3. The equations presented in this study also explain between 60 and 70% of the variation in porosity and C/N ratio from OM concentration, with prediction errors of 13 and 24%, respectively. In spite of soil surface disturbance associated with MSP, the easily measurable OM concentration can be used to predict D_b, porosity, and C/N ratio.

Abbreviations: D_b, bulk density • D_bo, pure organic matter bulk density • D_bm, pure mineral matter bulk density • EU, experimental unit • MBIA, mean bias • MSP, mechanical site preparation • OM, organic matter • RMSEP, Root mean square error of prediction

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