Planting stock type and seasonality of simulated browsing affect regeneration establishment of<i>Quercus rubra</i>
Bibliographic record
Abstract
Animal herbivory is a major limiting factor to successful oak (Quercus spp.) regeneration. Although bare-root seedlings are the most commonly used nursery stock type for oak plantings in the eastern United States, container seedlings may better resist planting stress and help enable seedlings to overcome browsing pressure. Four stock types (1 + 0 bare-root seedlings and seedlings in 164, 336, and 520 mL containers) of northern red oak (Quercus rubra L.) were planted on two reforestation sites in Indiana, USA, which were fenced to exclude white-tailed deer (Odocoileus virginianus Zimmerman). Seedlings were then subjected to three simulated browsing treatments (control unclipped, dormant clipped, and summer clipped). Container seedlings exhibited higher relative growth rates on both sites; for example, at one site, control seedlings in 336 mL containers had relative height growth of 558% compared with 79% for bare-root control seedlings. On both sites, summer-browsed seedlings of all stock types had negligible height growth, and summer browsing reduced survival at one site by 23% for all stock types compared with control seedlings. Browsing of seedlings during the dormant period did not affect growth for any stock type. Container seedlings may help facilitate rapid establishment of planted oak seedlings, but browse protection is necessary to ensure oak regeneration success in areas of large populations of deer.
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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) | 0.001 | 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".