The effects of UV-B, nitrogen fertilization, and springtime warming on sugar maple seedlings and the soil chemistry of two central Ontario forests
Bibliographic record
Abstract
The interactive effects of springtime warming, ambient UV-B, and nitrogen fertilization on the chemistry of sugar maple (Acer saccharum Marsh.) seedlings and soils from two contrasting sites were assessed. Open-top chambers increased average springtime air temperatures by approximately 1.5 °C, but their heating effect was diminished upon closure of the overstory canopy. Ambient levels of UV-B were reduced with Mylar D polyester film. Ammonium nitrate fertilizer was added in an amount equivalent to an additional 50 kg N·ha1. The soils of the Oliver forest were deep luvisols overlying a strongly calcareous till (average pH 6.0), while the naturally acidic soils of Haliburton were derived from the Precambrian Shield (average pH 4.7). Of the three main treatments used in this study, application of nitrogen fertilizer had the greatest impacts on foliar chemistry. At both sites, fertilizer application increased the acidity of the soils, while at Haliburton there were losses in total soil calcium. Haliburton maple seedlings had increased foliar concentrations of aluminum and manganese, decreased concentrations of calcium, and reduced calcium/manganese and magnesium/manganese nutrient ratios, after fertilizer was applied. Meanwhile, seedlings growing on the more alkaline soils of Oliver had increased foliar concentrations of magnesium following application of the nitrogen fertilizer. We suggest that these changes in the elemental chemistry of the soils and foliage brought on by continued nitrogen loading may predispose seedlings growing on naturally acidic soils, such as those of the Precambrian Shield, to further stress from additional abiotic and biotic stressors.
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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 | 0.000 | 0.000 |
| 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".