The influence of non-nitrogenous nutrient additions on growth and physiology of sugar maple and composition of understory vegetation in northern hardwoods of central Ontario
Bibliographic record
Abstract
While it is widely assumed that most temperate forests are nitrogen limited, many stands located in areas affected by high N deposition exhibit signs of nitrogen excess. Symptoms include an increase in nitrate concentration and a decrease in the C:N ratio of both soil and foliage; thus affected ecosystems are expected to experience a significant reduction in their natural nitrogen limitation. This process is likely accompanied by changes in availability of phosphorus and basic cations. This work demonstrates that N-induced deficiency of P, K, Ca and Mg is evident in sugar maple dominated northern hardwoods of central Ontario. Research presented here also examines several interrelated aspects of forest responses to additions of non-N mineral nutrients, including their effects on forest floor and mineral soil, diameter increment of trees, canopy physiology and morphology, and diversity of understory vegetation. This thesis demonstrates that the addition of truly growth-limiting nutrients does increase tree growth even among slow-growing, tolerant species such as sugar maple. Furthermore, growth increase is evident among mature and young trees within a relatively short time if monitoring of tree canopy response is included in research. This work also shows that while liming and non-N nutrient additions help alleviate many negative effects of nitrate pollution, they also escalate the process of forest eutrophication, which influences diversity of understory vegetation.
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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 | 0.000 | 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".