Spatiotemporal variation in the distribution of potential predators of a resource pulse: Black bears and caribou calves in Newfoundland
Bibliographic record
Abstract
ABSTRACT Understanding spatiotemporal variability in prey accessibility is important for disentangling predator‐prey interactions and is relevant to management interventions to reduce predation. Recently, caribou (Rangifer tarandus) in Newfoundland declined by 66%, with calf predation by black bears (Ursus americanus) implicated as a major proximate mechanism of the decline. Most predation occurs when calves are aggregated on calving grounds. We used telemetry data from 271 caribou and 45 black bears in 2 caribou herd ranges to examine spatial variability in calf accessibility, identify the distribution of potentially predatory bears, and assess the aggregative response of bears to the calf resource. We predicted whether a bear was a visitor to a calving ground during the calving season (a potentially predatory bear) based upon its sex, the herd range it occupied, its distance to the calving grounds, and the season. The distribution of potentially predatory bears and their degree of segregation from non‐predatory bears varied seasonally. The probability of a bear visiting the calving grounds during calving decreased with increasing distance from the calving grounds, and was greater for males than for females in all seasons at distances beyond 2.4 km from the calving grounds. Residency time of bears increased in the calving grounds of 1 herd during calving, suggesting an aggregative response to neonates in that area. For both herds, the estimated distribution of potentially predatory bears was much larger than the calving grounds, illustrating that the relevant scale of predator‐prey interactions may extend far beyond the area where lethal encounters occur. Our work highlights the value of examining spatiotemporal dynamics of predator movements prior to implementing ecosystem manipulations designed to reduce predation and provides a modeling framework that can be used to guide management interventions in systems with aggregated prey. © 2015 The Wildlife Society.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".