Understanding the diet of an unmanaged population of coyotes (<i>Canis latrans</i>) in southern Texas
Bibliographic record
Abstract
Coyotes ( Canis latrans Say, 1823) have great dietary plasticity, which can variably impact population dynamics and food availability of other wildlife. Understanding coyote diet in a system with a lack of human intervention can provide insight into their natural ecological role, a perspective muddled in the context of extrinsic influences . Our study evaluated the diet of a coyote population in southern Texas where no native wildlife is managed by harvesting, trapping, or supplemental feeding, and compared our results with previous studies. We collected coyote scat from transects on the roads of the East Foundation's San Antonio Viejo Ranch every month of 2022. From morphological analysis of fecal remains, we identified 23 unique species with white-tailed deer ( Odocoileus virginianus (Zimmermann, 1780)) and invasive wild pig ( Sus scrofa Linnaeus, 1758) being the most common prey items over the year, detected 38.4% and 14.4% among all prey items, respectively. The distinctly high proportion of ungulates consumed as opposed to small mammals is possibly due to high ungulate prey density as well as intraspecific niche differentiation by the unmanaged coyote population, where older, more experienced coyotes select for large mammals and younger coyotes select for small mammals. Future research exploring anthropogenic effects on predator and prey population demographics as well as predator behavior could provide more insight into how human presence may alter predator diet.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".