Influence of forest structure on the abundance of snowshoe hares in western Wyoming
Bibliographic record
Abstract
Abstract Snowshoe hares ( Lepus americanus ) are a primary prey species for Canada lynx ( Lynx canadensis ) in western North America. Lynx management plans require knowledge of potential prey distribution and abundance in the western United States. Whether even‐aged regenerating forests or multi‐storied forests contain more snowshoe hares is currently unknown. During 2006–2008, we estimated snowshoe hare density in 3 classes of 30–70‐year‐old lodgepole pine ( Pinus contorta ) and 4 classes of late seral multi‐storied forest with a spruce ( Picea engelmannii )‐fir ( Abies lasiocarpa ) component in the Bridger‐Teton National Forest, Wyoming. We recorded physiographic variables and forest structure characteristics to understand how these factors influence abundance of snowshoe hares. In many instances, snowshoe hares were more abundant in late seral multi‐storied forests than regenerating even‐aged forests. Forest attributes predicting hare abundance were often more prevalent in multi‐storied forests. Late seral multi‐storied forests with a spruce–fir component and dense horizontal cover, as well as 30–70‐year‐old lodgepole pine with high stem density, were disproportionately influential in explaining snowshoe hare densities in western Wyoming. In order to promote improved habitat conditions for snowshoe hares in this region, management agencies should consider shifting their focus towards maintaining, enhancing, and promoting multi‐storied forests with dense horizontal cover, as well as developing 30–70‐year‐old lodgepole pine stands with high stem density that structurally mimic multi‐storied forests. © 2012 The Wildlife Society.
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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 | 0.001 | 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".