Seasonal impact of scavenger guilds as taphonomic agents in central and northern Ontario, Canada
Bibliographic record
Abstract
The process of human decomposition is driven by biological decomposers, mainly bacteria, vertebrates, and invertebrate scavengers. When vertebrate scavengers have access to a body, they can considerably accelerate decomposition through consumption of soft tissue and dispersal of skeletal elements. Presently, there are limited data available on vertebrate scavenging activity in Canada, particularly in densely populated provinces such as Ontario. This study aimed to determine which vertebrate species belong to the scavenger guilds in central and northern Ontario, and the impact of season and habitat on these taphonomic agents. Seasonal trials were conducted in summer, fall, and spring of 2020/2021 with pig carcasses placed in open (grassland) and closed (forest) sites. Vertebrate scavenger activity was recorded continuously using cellular and non-cellular trail cameras. Photographs were analyzed to identify species, quantify feeding intensity, and document scavenging behavior. We identified four mammalian scavengers, namely coyote, red fox, fisher, and pine marten, and three avian scavengers, namely bald eagle, turkey vulture, and American crows/northern ravens (grouped as corvids) across the trials. Season impacted scavenger presence with feeding and loss of soft tissue occurring more quickly in the summer, followed by spring and fall. None of the scavengers demonstrated a clear preference for the open versus closed sites. Our findings have identified the most prevalent vertebrate scavengers in central and northern Ontario and their taphonomic impact on soft and hard tissues. It is important to consider these agents and their ability to degrade and disperse remains during the search and recovery of human remains.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 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".