Intrapopulation variation in habitat use of an alpine ungulate: mountain goats in Kitasoo Xai'xais Territory
Bibliographic record
Abstract
Intraspecific variation in space use among wildlife arises from different selective pressures facing individuals within populations. Such variation is important for wildlife management, especially when differences occur among reproductive individuals, juveniles, or other demographically significant groups. Age- and sex-specific segregation is common among ungulates, including mountain goats ( Oreamnos americanus (Blainville, 1816)). We hypothesized that mountain goats with and without kids would exhibit different space use in a peripheral population inhabiting Kitasoo Xai'xais First Nation Territory on the coast of British Columbia, Canada. Using aerial survey data from August 2019 and 2020, we fit multi-state occupancy models to estimate mountain goat habitat use in relation to landscape features. We predicted that groups with kids would preferentially use more rugged areas with ample escape terrain, while groups without kids (including solitary males and non-reproductive individuals) would use areas with greater forage availability. We found that the probability of mountain goat occurrence increased with elevation ( p < 0.001), while the probability of detecting kids, conditional on presence, increased with terrain ruggedness ( p < 0.001). These results suggest that pooling observations across group types may obscure important habitat use patterns and caution is warranted when delineating habitat or managing activities such as hunting or aerial tourism.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".