Seasonal nutrient transfers by foliar resorption, leaching, and litter fall in a northern hardwood forest at Lake Clair Watershed, Quebec, Canada
Bibliographic record
Abstract
A descriptive temporal model was used to evaluate the flow of macronutrients (N, P, K, Ca, and Mg) between the forest canopy and incident precipitation for the Lake Clair Watershed (LCW) located in the northern hardwood forest region of Quebec, Canada. The model also quantified the resorption mechanism. Wet precipitation, throughfall, foliage, and litter fall data for 1997 were used to quantify the following: (1) dry deposition intercepted by forest cover (0.38, 0.07, 0.07, and 0.03 kg·ha 1 for Ca, K, Mg, and P, respectively); (2) leaching from foliage (1.81, 6.46, 0.48, and 0.13 kg·ha 1 for Ca, K, Mg, and P, respectively); and (3) foliar resorption (N = 65%, P = 65%, K = 42%, Mg = 30%, and Ca = 10%). Foliar N, P, and K pools increased after bud break and remained constant until mid-September when they decreased rapidly. The foliar Ca pool increased until leaf fall, while the foliar Mg pool reached a maximum in early July and decreased slowly until leaf senescence. Phosphorus, K, Ca, and Mg were leached from the canopy whereas N from wet precipitation was retained by the canopy. The relatively high Mg and Ca resorption rates are consistent with the low soil Ca and Mg availability reported at the LCW. Consideration of leaching and dry deposition, as well as the temporal dimension, demonstrated the importance of each of these parameters for increasing the accuracy of the foliar nutrient resorption estimates.
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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 | 0.001 | 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 | 0.001 |
| 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".