The Conservation Value of Hedgerows for Small Mammals in Prince Edward Island, Canada
Bibliographic record
Abstract
The aim of this study was to investigate the use of hedgerows by small mammals in four agricultural landscapes in Prince Edward Island, Canada. The Island has one of the highest percentages of land (about 48%) devoted to crop production and pasture in all of Canada. Therefore, identifying the landscape elements that can mitigate the effects of habitat fragmentation resulting from agricultural practices is essential to preserve the biodiversity of Prince Edward Island. We quantified species richness, abundance and diversity of small mammals in 13 hedgerows and 13 attached forest patches. Although all the species detected in forest patches were also found in hedgerows, significant differences in species diversity and abundance suggest that not all species benefit equally from hedgerows. The abundance of small mammals other than the eastern chipmunk (Tamias striatus) increased in hedgerows longer than about 225–250 m, but was independent of hedgerow's length in hedgerows smaller than 225–250 m. Predators (Mustela erminea) were captured in hedgerows, but not in forest patches. Relationships between small mammal variables and hedgerow features (microhabitat, macrohabitat and landscape) suggested that most small mammal species would benefit from hedgerows having high shrub diversity, ground cover with vines and leaf litter, and few non-vegetated gaps. Removal of hedgerows, especially large ones, may affect long-term survival of some small mammal species inhabiting agricultural landscapes of Prince Edward Island.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".