Establishing Silphids in the invertebrate DNA toolbox: a proof of concept
Bibliographic record
Abstract
Environmental DNA (eDNA) analyses are an increasingly popular tool for assessing biodiversity. eDNA sampling that uses invertebrates, or invertebrate DNA (iDNA), has become a more common method in mammal biodiversity studies where biodiversity is assessed via diet analysis of different coprophagous or hematophagous invertebrates. The carrion feeding family of beetles ( Silphidae: Coleoptera , Latreille (1807)), have not yet been established as a viable iDNA source in primary scientific literature, yet could be useful indicators for tracking biodiversity in forested ecosystems. Silphids find carcasses of varying size for both food and reproduction, with some species having host preference for small mammals; therefore, iDNA Silphid studies could potentially target small mammal communities. To establish the first valid use of iDNA methods to detect Silphid diets, we conducted a study with the objective of testing the validity of iDNA methods applied to Silphids using both Sanger sequencing and high throughput Illumina sequencing. Beetles were collected using inexpensive pitfall traps in Alberta, Michigan in 2019 and 2022. We successfully sequenced diet DNA and environmental DNA from externally swabbed Silphid samples and diet DNA from gut dissections, confirming their potential as an iDNA tool in mammalian studies. Our results demonstrate the usefulness of Silphids for iDNA research where we detected species from the genera Anaxyrus , Blarina , Procyon , Condylura, Peromyscus, Canis, and Bos . Our results highlight the potential for Silphid iDNA to be used in future wildlife surveys.
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".