Unraveling water pathways and sources in leafless maples during early spring sap ascent
Bibliographic record
Abstract
Summary Maple trees repair cold‐induced embolism by generating positive stem pressure during their leafless state, altering sap transport in ways that remain poorly understood. This xylem pressure also drives sap exudation, enabling maple sap harvest for syrup production. This study investigates water source dynamics in leafless maples in early spring and its impact on sap yields. We used heavy water (D 2 O) as a tracer, injected into the soil for root uptake or directly into the stem at various heights of 55 tapped maple trees. Sap isotopic composition was monitored over time and analyzed in relation to weather, sap volume, and sugar content. Our findings show that maple trees absorb soil water gradually in early spring, even when leafless and still under snow cover, with limited sap transport and significant water mixing within the stem. Root‐derived water first appeared around the sixth freeze–thaw event, marking a key rehydration phase coinciding with peak sap yields. Optimal daily maple sap yields also depended on cold nights to enhance sugar concentration, followed by extended thaws at moderate temperatures (3–5°C) to increase sap volume. These results highlight the combined influence of xylem physiology and weather conditions on spring stem rehydration and maple sap yields.
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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".