Black spruce seedlings in a <i>KalmiaVaccinium</i> association: microsite manipulation to explore interactions in the field
Bibliographic record
Abstract
We established a field trial on an ericaceous-dominated clearcut in Quebec to determine the effect of Kalmia angustifolia L., Vaccinium angustifolium (Ait.), and V. myrtilloides (Michx.) on the growth and physiology of black spruce (Picea mariana (Mill.) BSP) seedlings and on soil characteristics over the first two growing seasons. Plots undergoing one of three treatments (shrub removal, humus removal, or undisturbed control) were planted with black spruce seedlings that were either unfertilized or spot fertilized at time of planting. In some of the undisturbed control plots, we also used 15NH415NO3 to compare uptake of broadcast N fertilizer by vegetation. The ericaceous shrubs had a significant negative impact on seedling growth. Growth reductions were not related to water stress, soil temperature, or soil moisture. Extractable NH4-N and P concentrations in mineral soil tended to decrease in the presence of ericaceous shrubs, but effects were not significant. Seedling foliar N concentration was also reduced in the presence of ericaceous shrubs. Of the total amount of 15N fertilizer found in vegetation, 64% was immobilized in Vaccinium spp., 31% in Kalmia, and 5% in black spruce, but spruce took up more 15N per unit of root biomass than the ericaceous shrubs. Kalmia had consistently higher predawn xylem water potentials than black spruce.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".