Dusky Grouse Population Ecology and Thermal Landscape Ecology in the Great Basin Ecosystem
Bibliographic record
Abstract
Dusky Grouse are a mountainous forest grouse found throughout the western, inland mountain ranges of the United States and Canada. While a few studies have looked at Dusky Grouse in the Rocky Mountain Ecosystem of their range, there have been no prior studies of the Dusky Grouse in the Great Basin Ecosystem aside from a brief survey by Zwickel and Bendell in 2004 in the Duck Creek Range of Nevada. With the available habitats differing in both species diversity and availability on the landscape between the two Ecosystems, I wanted to assess characteristics about the Dusky Grouse populations at the southwestern edge of their range in the Great Basin Ecosystem. Thus, I estimated the abundance of Dusky Grouse in the Schell Creek, Duck Creek, and Egan Ranges of White Pine County, Nevada, as well as created a monitoring protocol for continued monitoring of abundance in these areas. I estimated a density of 5 males/km2. I also assessed the seasonal habitat selection of Dusky Grouse in the White Pine County study areas during breeding, nesting, brooding, and over winter. Dusky Grouse used aspen, conifers, and mountain shrubland habitat types the most across the seasons. Finally, I determined the varying temperatures of the study area’s landscape during peak summer and identified possible thermal refuge, or areas that protect species from extreme heat, for an array of wildlife taxa on the landscape. Aspen and conifer stands offered the coolest thermal refuge during peak hours of the summer compared to mountain mahogany, pinyon-juniper, and mountain shrublands. This research is new for the Great Basin Ecosystem, as well as for Dusky Grouse literature as a whole.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".