Tracking Cats: Problems with Placing Feline Carnivores on δ18O, δD Isoscapes
Bibliographic record
Abstract
BACKGROUND: Several felids are endangered and threatened by the illegal wildlife trade. Establishing geographic origin of tissues of endangered species is thus crucial for wildlife crime investigations and effective conservation strategies. As shown in other species, stable isotope analysis of hydrogen and oxygen in hair (δD(h), δ(18)O(h)) can be used as a tool for provenance determination. However, reliably predicting the spatial distribution of δD(h) and δ(18)O(h) requires confirmation from animal tissues of known origin and a detailed understanding of the isotopic routing of dietary nutrients into felid hair. METHODOLOGY/FINDINGS: We used coupled δD(h) and δ(18)O(h) measurements from the North American bobcat (Lynx rufus) and puma (Puma concolor) with precipitation-based assignment isoscapes to test the feasibility of isotopic geo-location of felidae. Hairs of felid and rabbit museum specimens from 75 sites across the United States and Canada were analyzed. Bobcat and puma lacked a significant correlation between H/O isotopes in hair and local waters, and also exhibited an isotopic decoupling of δ(18)O(h) and δD(h). Conversely, strong δD and δ(18)O coupling was found for key prey, eastern cottontail rabbit (Sylvilagus floridanus; hair) and white-tailed deer (Odocoileus virginianus; collagen, bone phosphate). CONCLUSIONS/SIGNIFICANCE: Puma and bobcat hairs do not adhere to expected pattern of H and O isotopic variation predicted by precipitation isoscapes for North America. Thus, using bulk hair, felids cannot be placed on δ(18)O and δD isoscapes for use in forensic investigations. The effective application of isotopes to trace the provenance of feline carnivores is likely compromised by major controls of their diet, physiology and metabolism on hair δ(18)O and δD related to body water budgets. Controlled feeding experiments, combined with single amino acid isotope analysis of diets and hair, are needed to reveal mechanisms and physiological traits explaining why felid hair does not follow isotopic patterns demonstrated in many other taxa.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".