A comparison of the effects of different shelterwood harvest methods on the survival and growth of acorn-origin oak seedlings
Bibliographic record
Abstract
Timely development of newly germinated oak (Quercus spp.) seedlings into competitive-sized regeneration is an essential part of the oak regeneration process. The amount of sunlight reaching the forest floor partly governs this development, and foresters often use the shelterwood system to expose oak seedlings to varying degrees of insolation. To further understand the seedling development–sunlight–shelterwood relationships, I conducted a multiyear study at five locations in Pennsylvania. Each location had four stands either uncut or recently treated with one of three shelterwood harvest methods (preparatory cut, first removal cut, or final removal cut) resulting in four different levels of sunlight reaching the forest floor. In each stand, four 32 m2 plots were prepared, and each was planted with 400 acorns of black (Quercus velutina Lam.), chestnut (Quercus montana Willd.), northern red (Quercus rubra L.), or white oak (Quercus alba L.) and protected from wildlife. Germination success was universally high and for the next 8 years, I monitored seedling survival and measured seedling growth. The final and first removal cut treatments had higher seedling survival than the preparatory cut and uncut treatments. Oak seedling growth was positively related to sunlight availability; seedlings in the final removal cut grew the most, followed in descending order by those in the first removal cut, preparatory cut, and uncut treatments. These findings provide insight into the subtleties of regenerating oak forests with the shelterwood system.
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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 | 0.000 | 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".