Drought and simulated deer herbivory reduce growth in Atlantic white cedar seedlings
Bibliographic record
Abstract
White-tailed deer are overabundant in much of eastern North America and may be suppressing regeneration in some tree species. Herbivory initially reduces plant biomass, but it has the potential to stimulate compensatory growth. However, stressful environmental conditions may reduce recovery from herbivory. Seedlings of Atlantic white cedar, Chamaecyparis thyoides (L.) Britton, Sterns & Poggenb., are frequently browsed by white-tailed deer and also experience both flooded and dry soils in natural habitats. We conducted a growth chamber experiment to test for a potential interaction between simulated deer browsing and water availability treatments on seedling height, stem diameter, and above- and belowground biomass. Of the 180 study plants, half were subjected to an initial clipping treatment, and all plants were then exposed to high, intermediate, or low water availability for 90 days. We found that, over the short term, seedlings in favorable growing conditions could not compensate for lost biomass after simulated browsing. Drought reduced shoot biomass, and flooded soils reduced root but not shoot growth. Water stress and herbivory did not interact to reduce growth more than the effect of each treatment separately. In general, the effect of water stress on plant size was greater than the effect of simulated herbivory.
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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 | 0.001 |
| 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".