Risk avoidance during dispersal: Temporal and behavioral shifts in selection by non-resident eastern wolves (Canis c.f. lycaon)
Bibliographic record
Abstract
Dispersal is important for connectivity and persistence of small, disjunct wildlife populations. However, in human-altered landscapes dispersing animals are often more likely than residents to use anthropogenic features that increase mortality risk. As such, quantifying spatial and temporal responses of dispersing animals to anthropogenic features will improve our understanding of the potential for small, isolated populations to expand in human-altered landscapes. The distribution of eastern wolves ( Canis c.f. lycaon ; a threatened species in Canada) is limited to portions of eastern Canada within and adjacent to the population core in Algonquin Park. Recently, it was found that non-resident eastern wolves dispersing outside of Algonquin Park survive poorly, primarily due to high rates of human-caused mortality. We deployed Global Positioning System collars on 26 non-resident eastern wolves. We evaluated resource selection of dispersing individuals during different movement states to better understand their behavioral responses to anthropogenic landscape features during this critical, but risky period of their life history. Eastern wolves avoided areas with high building density during the day. However, during directed movements outside the winter period, eastern wolves selected areas closer to unpaved roads and areas with higher building densities at night. During winter, eastern wolves selected areas with high building densities at night while displaying tortuous movements. We demonstrate that harvested species may increase and relax avoidance of anthropogenic features at both daily and seasonal timescales. Failing to account for temporal and state-specific variation in resource selection patterns of dispersing animals may underestimate their ability to move through human-altered landscapes. • We quantified resource-selection of dispersing eastern wolves, a threatened species. • Wolves avoided anthropogenic features more strongly when humans are most active. • Risk avoidance by dispersing wolves varied relative to movement state and season. • Wolves selected anthropogenic features when travelling at night during non-winter. • Landscape connectivity studies should assess temporal variation in dispersal.
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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".