Influence of heterospecifics on mesocarnivore behaviour at shared scavenging opportunities in the Canadian Rocky Mountains
Bibliographic record
Abstract
In seasonal environments, the ability of mustelid species to acquire carrion-a dietary resource heavily depended upon-is driven by a collection local habitat characteristics and competition dynamics. In resource-scarce winter, sympatric mesocarnivores must balance energetic rewards of carrion with avoiding antagonistic interactions with conspecifics. We examined scavenging interactions among three mustelid species in the northern Canadian Rocky Mountains. Camera traps (n = 59) were baited with carrion during winter between 2006 to 2008. Spatial and temporal dimensions of scavenger behaviour (i.e., carcass use) were evaluated using a multi-model approach, which enabled us to recognize potentially adaptive behavioural mechanisms for mitigating competition at carcass sites. Best performing models indicated that carrion site use is governed by a combination of competition threats and environmental factors. A decrease in scavenging with increasing snow depth was observed across all species. Mustelids adopted a host of adaptive behavioural strategies to access shared scavenging opportunities. We found evidence that wolverine (Gulo gulo) and American marten (Martes americana) segregate in space but temporally tracked one another. Short-tailed weasel (Mustela erminea) scavenging decreased with greater site use by marten. Carcass availability across a spatially complex environment, as well as spatial-temporal avoidance strategies, can facilitate carrion resource partitioning.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".