Thirty-year effects of liming on soil and foliage chemistry and growth of northern hardwoods in Pennsylvania, USA
Bibliographic record
Abstract
The longevity of a single 22.4 Mg·ha−1 application of dolomitic limestone at four northern hardwood stands was evaluated over 30 years (1986–2016) to determine whether changes in soils, foliage, and tree growth were sustained on the unglaciated Allegheny Plateau in northern Pennsylvania, USA. In limed plots, soils, sampled to 45–55 cm depth, and sugar maple (Acer saccharum Marsh.) and black cherry (Prunus serotina Ehrh.) foliage had significantly (P ≤ 0.05) greater concentrations of calcium (Ca) and magnesium (Mg) through 2016 compared with samples from unlimed plots. Ca and Mg capitals (g·m−2) in the Oi through A horizons combined were greater on limed plots than unlimed plots, largely due to increases in the thickness and nutrient concentration in the A horizon. Over 30 years, sugar maple basal area increment (cm2·year−1 BAINC) was greater in limed plots (30.6 cm2·year−1 vs unlimed 13.3), American beech (Fagus grandifolia Ehrh.) BAINC was unaffected by lime application, and black cherry BAINC was reduced in limed plots compared with unlimed plots. The sustained effect of this one-time lime treatment shows the strong role of efficient nutrient cycling in forests and suggests that the benefits over a substantial portion of a stand rotation may increase the feasibility of operational liming.
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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".