Data from: Vertebrate scavenging dynamics differ between carnivore and herbivore carcasses in the northern boreal forest
Bibliographic record
Abstract
Vertebrate scavenging can impact food web dynamics, but our understanding of this process stems predominantly from monitoring herbivore carrion and extrapolating results across carcass types. Recent evidence suggests carnivores may avoid intraguild scavenging to reduce parasite transmission. If this behavior is widespread across diverse ecosystems, estimation of nutrient cycling and community scavenging rates are likely biased to a currently unknown degree. We examined whether the time to initiate scavenging, carcass persistence, or the richness of species scavenging in the boreal forest of Yukon, Canada, differed between carnivore and herbivore carcasses. Vertebrates took longer to initiate scavenging on carnivore carcasses (3.2 days) relative to herbivore carcasses (1.1 days), and carnivore carcasses persisted on the landscape for over a month longer (48.4 days and 5.5 days, respectively). The longer persistence times were due to the reduction in scavenging by carnivores such as Canada lynx (Lynx canadensis). Decreased scavenging was caused by changes in the propensity to consume carnivore carrion, as the number of species detecting a carcass within the first week did not differ between carnivore and herbivore carcasses. These results have ramifications for our understanding of nutrient cycling and food web dynamics in the boreal forest, and provide further support that carcass type should be included in future studies.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 0.017 |
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".