Tree seedling growth and mortality responses to manipulations of calcium and aluminum in a northern hardwood forest
Bibliographic record
Abstract
To assess potential forest compositional responses to exchangeable soil calcium (Caexch) and aluminum (Alexch), we characterized light-dependent growth and mortality of tree seedlings under amendments of CaCl2 and AlCl3 at Hubbard Brook Experimental Forest (HBEF), New Hampshire, U.S.A. Seedlings of Acer saccharum Marsh., Fagus grandifolia Ehrh., Betula alleghaniensis Britton, Abies balsamea (L.) Mill., and Picea rubens Sarg. were transplanted into field plots, which were randomly assigned to control, CaCl2, or AlCl3 treatments and stratified across <1 to 35% full sun. Acer saccharum and P. rubens exhibited significantly higher mortality in Al-amended than Ca-amended or control plots. Acer saccharum showed significant increases in relative diameter growth in Ca-amended plots versus controls; all other species showed nonsignificantly higher relative diameter growth under Ca amendments. We incorporated significant seedling responses into a model of forest dynamics (SORTIE) to assess potential changes in species composition under Alexch increases and Caexch losses. SORTIE predicts that further increases in Alexch would have negligible effects on canopy composition within 200 years but that the estimated Caexch depleted from HBEF between 1968 and 1995 and its influence on seedling dynamics could lead to substantial decreases in A. saccharum canopy dominance within a single forest generation (<125 years).
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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) | 0.000 | 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".