Taphonomic impact of vertebrate scavengers on degradation and dispersal of remains, southeastern British Columbia
Bibliographic record
Abstract
Vertebrate scavengers represent important taphonomic agents that can act on a body, particularly when in an outdoor environment. Understanding the effects of these agents will direct how and where to search for human remains and influence the likelihood of discovery in a particular region. The current study aimed to identify the taphonomic impact of scavenger guilds in the peri-urban and rural regions of southeastern British Columbia. Vertebrate scavenger activity on pig carcasses was recorded remotely using trail cameras and analyzed to determine temporal scavenging profiles. Both the peri-urban and rural environments produced comparable scavenger guilds, namely: turkey vultures, American crows/northern ravens (classified as "corvids"), American black bears, and coyotes. Although the two locations had different study lengths due to variable degrees of scavenging, for the period that was common to both locations (summer to early fall), the black bear was the most frequent scavenger followed by coyote. However, the dispersal of remains by the mammalian scavengers was distinctly different between sites. Only 12%-33% of skeletal elements were recovered at the rural sites compared to 80%-90% recovered at the peri-urban sites, even though the latter sites had a longer study timeframe. The extended timeframe of the peri-urban sites confirmed that certain scavengers (e.g., turkey vultures and black bears) are only seasonally active in this region. These findings demonstrate the variability of scavenger behavior and the need to assign caution and local ecological knowledge when predicting scavenger trends. Such taphonomic information is relevant for human remains searches in regions with comparable scavenger guilds.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".