Chronic deer browsing leads to biotic homogenization of minerotrophic peatlands
Bibliographic record
Abstract
Peatlands could become important foraging habitats, and their plant communities threatened, in areas with an overabundance of large herbivores. Peatland response to herbivore exclusion may vary widely according to abiotic conditions and associated species because of a strong minerotrophic gradient. We assessed the impact of white-tailed deer (Odocoileus virginianus Zimm.) on peatland vegetation using an exclosure experiment. A total of 53 pairs of exclosures and unprotected plots were set up in bogs (13 pairs), sedge fens (20), shrub fens (7), and laggs (13), and surveyed prior to exclosure construction as well as three, five, and eight years after. Vascular plant composition of exclosures diverged from that of unprotected plots through time only in shrub fens and laggs. Bryophytes remained constant in all habitats. On average, shrub cover was 30% higher in exclosures in all habitats after five years, whereas herb cover increased only in laggs, by 43%, after eight years. Reclassification of sites by pH showed deer exclusion promoted alpha diversity in low- and high-moderate rich fens (pH 5.3–6.8) and beta diversity in the latter as well as in rich fens (pH 6.3–7.5). Overall, our results suggest that conservation efforts in areas with overabundant large herbivores should target richer peatland habitats since they showed a higher resilience and fostered alpha and beta diversity.
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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".