Influence of wind on movement behaviour in Arctic grizzly bears
Bibliographic record
Abstract
Odours are emitted from organic matter and can contain important information about an animal’s surroundings, including the presence and location of other organisms. Wind acts as a conduit of olfactory information, affecting the spread and direction of odour dispersal across terrestrial landscapes. To increase the likelihood of detecting an odour molecule, individuals may exhibit anemotaxis – orientation bias to wind during movement – where the theoretical optimal olfactory search strategy is to move crosswind. We tested for biased movement relative to wind in Arctic grizzly bears ( Ursus arctos ) during the spring hypophagic period in the Mackenzie Delta, Northwest Territories, Canada using modelled winds and satellite-linked telemetry data (n = 12,430 locations) from 40 Arctic grizzly bears monitored between 2003 and 2010. Our results show that orientation relative to wind varied with movement rate, a proxy for active search effort. During steps where bears had high movement rates (> 90th percentile), bears predominantly oriented crosswind. We also found a positive relationship between movement rate and crosswind orientation: as bears moved faster, they increased their crosswind component of orientation. These results suggest an adaptive pattern of movement in response to wind, where bears oriented relative to the wind in a way that increased the likelihood of odour detection during active search. We suggest that future studies could include wind data in habitat selection and foraging models to examine its influence on habitat selection and use. • Arctic grizzly bears occupy a harsh environment, ranging widely to find resources. • The optimal anemotactic orientation during olfactory search is crosswind. • Search effort was positively associated with crosswind orientation. • Wind may be an important factor shaping movement decisions and habitat selection.
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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 | 0.000 | 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) | 0.000 | 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".