Assessing the relative contributions transmission line rights-of-way have on habitat utilization by moose case study : Riding Mountain National Park
Bibliographic record
Abstract
Moose (Alces alces andersoni) are one of many game animals managed for sustainable subsistence, sport hunting, and for non-consumptive users in Manitoba. Managing this species is essential if we are to ensure healthy populations for present and future generations. An important component of moose management is understanding how resource development affects moose-habitat relationships. Modifications to the landscape through resource development (ie. timber harvesting), often promote the growth of young vegetation that is favorable to moose. Growth of young vegetation can also be enhanced through the maintenance of an established transmission line right-of-way (ROW). However, few studies have examined the habitat relationship that exists between moose and transmission line rights-of-way. The focus of this study was to give insight into the relative habitat contributions these areas may provide for moose. Set in Riding Mountain National Park, this study examined habitat use by moose along a transmission line ROW using methods that included a browse study, pellet group counts, track counts and aerial survey data. The results indicated that moose used ROWs for foraging, traveling to new food patches and for bedding. Beaked hazelnut in ROW areas experienced more intensive use by moose throughout the winter period when compared to adjacent forests. Bedding and pellet group occurrence were greater within the aspen ROW when compared to the adjacent forest. No differences were found in bedding or pellet group occurrence between the mixed-wood ROW and adjacent forest.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".