Recommendation: To flow or to grow? Impacts of tapping on sugar maple — R0/PR4
Bibliographic record
Abstract
Maple sugaring is a rapidly growing industry in North America. Maples are tapped annually, thus undergoing repeated wounding and resource reduction for sap water collection. We aim to understand the effects of tapping and sap exudation on annual radial wood growth and xylem traits in sugar maple (Acer saccharum Marsh.), utilizing eight mature trees monitored during 2018-2021 in Simoncouche, Canada. Compared to the first year of tapping, trees exhibited a 49.7% drop in tree-ring width. Vessel density, potential hydraulic conductivity and hydraulic vessel diameter decreased, but not lumen area. We showed evidence of a trade-off among sap extraction, resource depletion and reduced tree growth. The repeated reduction of resources through tapping can have a detrimental effect on tree growth, even if the effect on the hydraulic function remains marginal. These insights underscore the need for sustainable tapping practices that consider the long-term health and productivity of sugar maple trees.
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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 | 0.002 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.487 | 0.330 |
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".