We investigated the influence of soil drainage class and tree species on nitrogen (N) mineralization and nitrification rates in two forest catenas in southern Quebec. Monthly net N mineralization and nitrification rates were determined along transects running from well-drained to poorly drained soils for 2 years through in situ incubation of homogenized soils. Potential N transformation rates in soils under American beech, sugar maple, and eastern hemlock trees were determined through incubation of homogenized soils in the laboratory under two different moisture regimes (50 and 100% water by volume) mimicking well-drained and poorly drained soil conditions in the two watersheds. Field-based N mineralization rates averaged 38 ± 6 mg m−2 d−1 in well-drained soils, while those in the poorly drained soils averaged 17 ± 5 mg N m−2 d−1. Similarly, net nitrification rates in well-drained soils (18 ± 4 mg N m−2 d−1) were 3 times greater than those in poorly drained soils (6 ± 3 mg N m−2 d−1). Laboratory-based potential N mineralization rates in soils ranked sugar maple > American beech > eastern hemlock under both well-drained (incubated at 50% water by volume) and poorly drained soil conditions (incubated at 100% water by volume). Potential nitrification rates ranked sugar maple > American beech > eastern hemlock under well-drained soil conditions, while under poorly drained conditions, American beech > sugar maple ≥ eastern hemlock. Nitrification enzyme activity determined through a soil slurry method correlated significantly with field-based nitrification rates. Differences in soil volumetric water contents, leaf litter N input, and soil C:N ratios, as surrogates of soil drainage and floristic heterogeneity, respectively, correlated significantly with field-based N mineralization and nitrification rates. Field-based N mineralization and nitrification rates were higher in summer than in early spring and autumn. Soil drainage class and tree species exert marked controls over N transformation rates in forested landscapes and need to be incorporated when characterizing and/or modeling internal N cycling at watershed scales.
