White-footed mouse (<i>Peromyscus leucopus</i>) response to restoration of grassland alvar
Bibliographic record
Abstract
Grassland alvar is a rare plant community that occurs throughout North America and northern Europe, and may require control of encroaching vegetation to be maintained or restored. We evaluated the hypothesis that restoration techniques used to restore the alvar ecosystem do not lead to declines in small mammal abundance. More specifically, we used a Before-After Control-Impact (BACI) design to compare how two methods of vegetation control, prescribed burns and mechanical removal, affected small mammal populations. The restoration was conducted beginning in 2019 on Pelee Island, Ontario, Canada. Live trapping of small mammals and associated vegetation sampling were conducted before and after on treatment and control locations. The only small mammal species to be caught during the study was the white-footed mouse ( Peromyscus leucopus (Rafinesque, 1818)), which had an observed decrease across all treatment sites and the control site. Generalized linear mixed effects models demonstrated that the main effects of treatment and year best explained mouse abundance at the site level. Interannual variability appeared to explain more variation in mouse abundance than treatment effects. Our study did not provide strong evidence that the vegetation control measures we employed might limit white-footed mouse abundance.
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 | 0.001 |
| 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".