Mechanisms influencing thermal refuges and territory occupancy by collared pikas during summer and winter
Bibliographic record
Abstract
Collared pikas (<i>Ochotona collaris</i>) are cold adapted alpine lagomorphs of western Canada and Alaska, USA, that are vulnerable to direct and indirect effects of climate change. However, how and to what extent such changes influence persistence for this species is not well understood, particularly at fine spatial scales. Our goal was to evaluate how microclimate and microhabitat characteristics influence occupancy of collared pikas. We quantified thermal conditions during both summer and winter to test hypotheses about potential drivers of pika persistence. We recorded den occupancy and territory characteristics, including in situ measurements of den microclimate, across three study areas with contrasting climate gradients in southcentral and interior Alaska during 2017–2022. We examined changes in pika den occurrence by estimating annual colonization and extinction rates with a Bayesian dynamic occurrence model with forage availability, rock size, and multiple den temperature metrics as the explanatory variables. Our top model indicated that daily maximum temperature during both summer and winter best predicted den persistence and larger rocks had a moderating effect on warm summer den temperatures. This information helps to advance understanding about the mechanistic links between climate and population persistence for small mammal species under a rapidly changing arctic climate.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.008 | 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".