Controlling Kalmia and reestablishing conifer dominance enhances soil fertility indicators in central Newfoundland, Canada
Bibliographic record
Abstract
Growth rates of young conifers can be poor on disturbed sites dominated by Kalmia angustifolia L. Hence, a conifer revegetation trial was established on a Kalmia -dominated site to evaluate the effects of various silvicultural options and planted species on selected soil organic layer characteristics. Larix laricina (Du Roi) K. Koch, Pinus banksiana Lamb., and Picea mariana (Mill.) BSP seedlings were planted in plots with or without Kalmia control with herbicides. The effect of fertilizer amendment was also assessed. Seventeen years postplanting, organic layer fertility indicators suggest that soil fertility improved after Kalmia control and conifer reestablishment, especially if nitrogen (N) – phosphorus – potassium fertilizer was also applied. When Kalmia was controlled, aerobically mineralizable N and exchangeable sodium concentrations were increased; fertilizer addition to herbicided plots also increased exchangeable potassium and calcium concentrations, and cation exchange capacity compared with untreated control plots. Conifer height, diameter, and canopy closure were Larix > Pinus > Picea. Kalmia cover in control plots was 87%; Kalmia reinvasion in herbicided plots achieved 40%–43% cover but did not differ among the conifer species. Principal component analysis indicated that aerobically mineralizable N and total N were positively correlated with canopy closure. Our results suggest that increases in organic-layer fertility were related to increased conifer size resulting from Kalmia control.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".