Increasing nitrogen availability and soil temperature: effects on xylem phenology and anatomy of mature black spruce<sup>1</sup>This article is one of a selection of papers from the 7th International Conference on Disturbance Dynamics in Boreal Forests.
Bibliographic record
Abstract
Since plant growth in the boreal forest is often considered to be limited by low temperatures and low N availability and these variables are projected to increase due to climate warming and increased anthropogenic activities, it is important to understand whether and to what extent these disturbances may affect the growth of boreal trees. In this study, the hypotheses that wood phenology and anatomy were affected by increased soil temperatures and N depositions have been tested in two mature black spruce ( Picea mariana (Mill.) BSP) stands at different altitudes in Quebec, Canada. For 3 years, soil temperature was increased by 4 °C during the first part of the growing season and precipitations containing three times the current N concentration were added in the field by frequent canopy applications. Soil warming resulted in earlier onsets of xylogenesis and interacted with N addition producing longer durations of xylogenesis for the treated trees. The effect of warming was especially marked in the phenology of roots, while wood production, in terms of number of tracheids, was not affected by the treatment. Xylem anatomy and soil and needle chemistry showed no effect of the treatments, except for an increase of cell wall thickness in earlywood of treated trees. This short-term experiment with black spruce suggested that previous fertilization studies that used large and unrealistic rates of N addition may have overestimated the impact of N depositions on boreal forest productivity.
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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 | 0.000 | 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".