Death and <i>Taxus</i>: the high cost of palatability for a declining evergreen shrub, <i>Taxus canadensis</i>
Bibliographic record
Abstract
Taxus canadensis Marsh., a shade-tolerant evergreen shrub, is in decline as a result of past anthropogenic disturbances and increased cervid browsing. To identify factors that may be influencing establishment for this species, we planted 1080 T. canadensis cuttings in a hemlock–hardwood forest in the spring of 2004. Cuttings were planted across a gradient of light environments, consisting of artificial canopy gaps (61–441 m2) and closed-canopy conditions, and half were protected with deer exclosures. Following four growing seasons, T. canadensis survival in exclosures was 92% compared with 75% in controls. A mixed-effects binary logistic regression analysis revealed that deer exclusion had the most influence on the probability of survival; all else being equal an individual was nearly seven times more likely to survive if planted inside an exclosure (P < 0.001). Increasing light intensity had a counterbalancing effect on growth and survival; light increased leader growth (P = 0.019) but reduced an individual’s probability of survival (P < 0.001), possibly owing to enhanced herbivory and elevated moisture stress. Consequently, enhancing resource availability and growth may not decrease the impact of biomass loss to herbivory. These results suggest that even with relatively low herbivore densities, exclosures are required for the recovery of highly palatable species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".