Eleven-year response of foliar chemistry to chronic nitrogen and sulfur additions at the Bear Brook Watershed in Maine
Bibliographic record
Abstract
The foliar chemistry of sugar maple (Acer saccharum Marsh.), American beech (Fagus grandifolia Ehrh.), and red spruce (Picea rubens Sarg.) was studied from 1993 to 2003 at the Bear Brook Watershed in Maine (BBWM). The BBWM is a paired-watershed forest ecosystem study, with one watershed treated bimonthly since 1989 with ammonium sulfate ((NH4)2SO4) at a rate of 25.2 kg N·ha1·year1. Foliar N concentrations were higher in all tree species within the treated watershed compared with trees within the reference watershed. Foliar Ca and Mg concentrations were lower in American beech and red spruce within the treated watershed. There were no significant differences in foliar K concentrations between watersheds. Foliar P and Mn concentration differences between watersheds were inconsistent among years. Differences in foliar N concentrations between watersheds declined over time in sugar maple but not in red spruce or American beech. Differences in foliar Ca and Mg concentrations between the treated and reference watersheds increased over time for American beech and red spruce, primarily because of a consistent decline in concentrations of these nutrients in trees within the treated watershed. No temporal trends in foliar Ca and Mg concentration differences between watersheds were observed for sugar maple.
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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 | 0.001 | 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".