Seed production of sugar maple and American beech in northern hardwood forests, New Hampshire, USA
Bibliographic record
Abstract
Mast seeding is the synchronous production of large seed crops in plant populations and for many tree species is known to be determined by the interaction between weather cues and internal plant resources. We use a 24-year record of seedfall for sugar maple (Acer saccharum Marsh.) and American beech (Fagus grandifolia Ehrh.) across a northern hardwood forest landscape to quantify their masting patterns and explore the relationship between mast years, resources, and weather cues, particularly the difference between summer temperatures in the two years prior to the seedfall year (ΔT). We found clear evidence of masting in these species, and mast years were often coincident in the two species; masting was best predicted by ΔT or ΔT plus previous-year seedfall. We saw no evidence for correspondence of masting in these trees to precipitation cues. A soil calcium addition modified elevation effects on seed production. Clarification of the controls on mast seeding for these important tree species will aid in predicting such resources as mast for wildlife and maple sugar production in northern hardwood forests.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".