Soil drainage and vegetation control of nitrogen transformation in forest soils, southern Quebec.
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".