Environmental DNA bioassays corroborate field data for detection of overwintering species at risk Blanding’s turtles (<i>Emydoidea blandingii</i>)
Bibliographic record
Abstract
Environmental DNA (eDNA) is gaining traction in conservation ecology as a powerful tool for detecting species at risk. We developed a quantitative polymerase chain reaction assay to detect a DNA amplicon fragment of the mitochondrial nicotinamide adenine dinucleotide locus of the Blanding’s turtle (Emydoidea blandingii) for detecting overwintering individuals. Seventy-eight water samples were collected from 17 wetland sites in Ontario, Canada. We used traditional field data to identify a priori positive and negative control sites. Fifty percent of positive control sites amplified. Detection was related to the number of individuals estimated from field observations in at least one region surveyed. Positive control sites had lower total dissolved solids and electrical conductivity in relation to negative control sites. Shedding rates were within the same order of magnitude for brumating and active turtles. We recommend collecting additional samples at a larger number of locations to maximize detection. Recommended sampling design changes may overshadow the additional effects of water chemistry and low eDNA shedding rates. eDNA offers tremendous potential to practitioners conducting species at risk assessments in environmental consulting by providing a faster, more efficient method of detection compared with traditional surveys.
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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 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".