Influence of stand and landscape features on snowshoe hare abundance in fragmented forests
Bibliographic record
Abstract
Habitat fragmentation often separates and reduces populations of vertebrates, but the relative effects of habitat attributes within remnant patches versus the matrix surrounding the patches are less clear. For snowshoe hares (Lepus americanus) lower densities and disrupted cycles in their southern range have been ascribed to habitat fragmentation, although relevant scales of landscape influence remain unknown. In a fragmented forest in north-central Washington we counted fecal pellets of snowshoe hares to examine the extent to which relative snowshoe hare densities within stands of suitable habitat changed with the composition of surrounding habitats. Pellet densities were associated primarily with density of large shrubs and saplings and medium trees within a stand. Pellet densities also were correlated positively with the amount of moist forest (dominated by Engelmann spruce [Picea engelmannii] and subalpine fir [Abies lasiocarpa]) and correlated negatively with the amount of open-structured habitat within 300 m of the stand perimeter. These results suggest that forest managers will have positive impacts on hare densities by managing both focal stands and the surrounding stands for the higher densities of large shrubs and saplings and medium trees that hares select.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".