Mid‐day temperature variation influences seasonal habitat selection by moose
Bibliographic record
Abstract
ABSTRACT We tracked 122 female moose in northwestern Ontario, Canada, using global positioning system (GPS) radio‐collars between 1995 and 2001. We used step‐selection functions (SSF) to evaluate changes in moose habitat selection as a function of temperature across seasons (summer and winter), stand types, and stand heights. We obtained mean activity levels of moose within stand types and across seasons from motion sensors in the collars. Selection increased for aquatic stand types as a function of temperature across both summer and winter. Selection for stand height was also temperature‐dependent, with tall stands being most favored at warm temperatures and least favored at cold temperatures. Moose activity levels increased slightly at higher temperatures during the winter but were mostly constant, whereas summer activity declined significantly with increasing temperature. Seasonal activity levels were mostly constant within habitats, but activity was consistently higher in aquatic habitats compared to woody habitats, with the highest mean activity levels observed when moose were located in open water and marshes during the summer. Our findings corroborate the work of others that moose primarily select habitat based on documented foraging requirements, whereas they may alter mid‐day selection for specific stand types providing thermal cover under varied temperatures, indicating a behavioral response to thermoregulatory needs. Increased activity levels at low summer temperatures, and in habitats found to provide thermal cover, support the conclusion that moose may alter their activity to alleviate heat stress, and that temperature‐mediated changes in habitat selection may facilitate otherwise energetically costly behavior (e.g., movement). © 2015 The Wildlife Society.
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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 | 0.001 | 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".