A comparison of soil fertility and leaf nutrient status of sugar maples (<i>Acer saccharum</i>) in relation to microrelief in two maple forests in Québec
Bibliographic record
Abstract
This study was conducted to provide a better understanding of the relationship between foliar nutrient status, maple dieback and soil quality. Fieldwork was conducted in four maple stands, two of which were located in the Appalachians at Tingwick and two in the Laurentians at Duchesnay. All stands were characterised by a mound and depression microrelief. In one of the Tingwick maple stands (T1) the predominant soil type was found on mounds, and was well to moderately well-drained (Leeds and Woodbridge series). At the other site (T2), the predominant soil type was in depressions, and imperfectly to poorly drained (Sainte-Marie and Brompton series). At the first Duchesnay site (D1) the predominant soil type was found on mounds and was well to rapidly drained (Ste Agathe series). At the second Duchesnay site (D2), the predominant soil type was also found on mounds, but was well to moderately well-drained (Sergent series). On all sites, the soils were acidic and nutrient poor. The lowest pH values and nutrient concentrations (in the H-Ah horizons) were found in maple stands with well-drained soils (T1 and D1) (P < 0.05). On these sites, maple dieback was less than 10%. It was on the poorly to imperfectly drained soils at Tingwick (T2), as well as on the moderately drained soils at Duchesnay (D2), that we observed the lowest biological activity. Although these soils were the most nutrient rich, we observed foliar nutrient deficiencies, and maple dieback in excess of 25%. Our results suggest that maple dieback is the result of a poor physiological adaptation of sugar maple to poor drainage conditions in the areas studied. Key Words: Dieback, Acer saccharum, forest soils, biological activity index
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".