Extensive daily movement rates measured in territorial arctic foxes
Bibliographic record
Abstract
An animal's movement rate is a central metric of movement ecology as it correlates with its energy acquisition and expenditure. Obtaining accurate estimates of movement rate is challenging, especially in small highly mobile species where GPS battery size limits fix frequency, and geolocation technology limits positions' precision. In this study, we used high GPS fix frequencies to evaluate movement rates in eight territorial arctic foxes on Bylot Island (Nunavut, Canada) in July-August 2018. We also assessed the effects of fix interval and location error on estimated movement rates. We obtained 96 fox-days of data with a fix interval of 4 min and 12 fox-days with an interval of 30 s. We subsampled the latter dataset to simulate six longer fix intervals ranging from 1 to 60 min and estimated daily distances traveled by adding linear distances between successive locations. When estimated with a fix interval of 4 min, daily distances traveled by arctic foxes averaged 51.9 ± 11.7 km and reached 76.5 km. GPS location error averaged 11 m. Daily distances estimated at fix intervals longer than 4 min were greatly underestimated as fix intervals increased, because of linear estimation of tortuous movements. Conversely, daily distances estimated at fix intervals as small as 30 s were likely overestimated due to location error. To our knowledge, no other territorial terrestrial carnivore was shown to routinely travel daily distances as large as those observed here for arctic foxes. Our results generate new hypotheses and research directions regarding the foraging ecology of highly mobile predators. Furthermore, our empirical assessment of the effects of fix interval and location error on estimated movement rates can guide the design and interpretation of future studies on the movement ecology of small opportunistic foragers.
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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".