Reduction in local white-tailed deer abundance allows the positive response of northern white cedar regeneration to gap dynamics
Bibliographic record
Abstract
Gap dynamics play a crucial role in forest regeneration by creating favourable regeneration and survival niches for some plant species. Nonetheless, potentially overriding factors, such as ungulate browsing, could limit or eliminate this gap dynamic-related regeneration. The deleterious effects of browsing may be exacerbated for slow-growing species such as northern white cedar ( Thuja occidentalis L.), a tree highly selected by white-tailed deer ( Odocoileus virginianus Zimmerman). We therefore aimed to understand how deer browsing and gap dynamics interact to affect cedar regeneration and hypothesized that cedar regeneration benefits from natural gaps but that deer browsing could override this effect. We inventoried natural canopy gaps along a spatiotemporal gradient of deer habitat use. We evaluated cedar regeneration abundance, tree height, and various gap, stand, and competition metrics. We found that deer browsing pressure greatly limited cedar regeneration; however, when deer populations decreased, cedar regeneration abundance increased within a decade, even after prolonged browsing pressure, and increased further over time. Our study illustrates that cedar regeneration can be favoured by gap creation and deer population control.
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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".