The divergent advancements of sap phenology in maple under warming conditions can shorten the sugar season
Bibliographic record
Abstract
Climate change raises concerns for the maple syrup industry, mainly regarding the expected changes in the timings of the sugar season and the resulting uncertainty of sap yield. This study investigates the temporal relationships between the environmental factors and sap phenology (i.e., timings of the onset and ending of sap season) in sugar maple ( Acer saccharum Marsh.) during 2018-2022 at the northern limit of the species in Quebec, Canada, and predicts the impact of warming under greenhouse gas emission scenarios (RCP 2.6, 4.5, and 8.5). March and April temperatures are correlated to the onset and ending of sap exudation, occurring on average on DOY (day of the year) 86 and 133, respectively. Sap exudation corresponds with the start of snowmelt and the consequent increase in soil water content. Complete snowmelt and the increase in soil temperature coincide with the ending of sap exudation. Our partial least squares regressions estimate an advancement of up to 20 days for the start and 26 days for the end of sap production by 2100 at RCP 8.5. The predictions suggest a divergent advancement of the onset and ending of sap production under warming, resulting in a shorter duration of the sugar season. The earlier sap season represents an important challenge for producers, who will need to adjust their activities in the sugarbushes to match the warmer conditions predicted for late winter and early spring. Any delay in tapping will increase the risk of substantial losses in production, especially in the context of a shorter sap season.
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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".