Habitat-based adaptive management at Mount Haggin Wildlife Management Area
Bibliographic record
Abstract
The 22,743-hectare Mount Haggin Wildlife Management Area was purchased in 1976, in part for moose (Alces alces) winter range. Observed moose populations climbed from a low of 7 in 1976 to a high of 56 in 2000. A 4-step management program was initiated in 2000 consisting of definition of management objective, monitoring to determien if the objective was attained, developing a management strategy, and implementing the strategy. The management objective for browse was defined to be: browsing will not prevent young plants from attaining their potential stature, their growth being primarily limited by local environmental conditions. A survey of Geyer willow (Salix geyeriana) in critical moose habitat indicated that browse plants were 100% intensely browsed, suggesting that browsing could prevent willow height growth. Beginning in 2000, willow trend was monitored annually at 4 sites using an index based on the height of the tallest live stem and the height of the tallest, dead intensely browsed stem (LD Index). Low LD Index values indicated that browsing did prevent height growth. In 2000 moose harvest quotas were increased by 40%; in 2002 harvest quotas were increased an additional 7%. From 2000 to 2002, willow growth increased at all 4 locations. From 2002 to 2004, growth indicators changed relatively little at Sullivan Creek, Deep Creek, and French Creek; at these sites willow condition in 2004 had improved compared to willow condition in 2000. From 2002 to 2004, growth indicators declined markedly at American Creek; in 2004, growth indicators at American Creek were lower compared to measurements made in 2000. The improvement of willow condition at 3 sites was likely due to a combination of reduced moose numbers (due to an increase in harvest) and increased dispersal (due to low snow cover conditions). Over the study period, the sporting public complained of reduced moose sightability; harvest quotas were lowered substantially in 2003.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.024 | 0.003 |
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".