Proportion of prey consumed can be determined from faecal DNA using real‐time PCR
Bibliographic record
Abstract
Reconstructing the diets of pinnipeds by visually identifying prey remains recovered in faecal samples is challenging because of differences in digestion and passage rates of hard parts. Analysing the soft-matrix of faecal material using DNA-based techniques is an alternative means to identify prey species consumed, but published techniques are largely nonquantitative, which limits their usefulness for some applications. We further developed and validated a real-time PCR technique using species-specific mitochondrial DNA primers to quantify the proportion of prey in the diets of Steller sea lions (Eumetopias jubatus), a pinniped species thought to be facing significant diet related challenges in the North Pacific. We first demonstrated that the proportions of prey tissue DNA in mixtures of DNA isolated from four prey species could be estimated within a margin of ∼ 12% of the percent in the mix. These prey species included herring Clupea palasii, eulachon Thaleichthyes pacificus, squid Loligo opalescens and rosethorn rockfish Sebastes helvomaculatus. We then applied real-time PCR to DNA extracted from faecal samples obtained from Steller sea lions in captivity that were fed 11 different combinations of herring, eulachon, squid and Pacific ocean perch rockfish (Sebastes alutus), ranging from 7% to 75% contributions per meal (by wet weight). The difference between the average percentage estimated by real-time PCR and the percentage of prey consumed was generally <12% for all diets fed. Our findings indicate that real-time PCR of faecal DNA can detect the approximate relative quantity of prey consumed for complex diets and prey species, including cephalopods and fish.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".