Detection of brook trout in spatiotemporally separate locations using validated eDNA technology
Bibliographic record
Abstract
Abstract Brook trout are a species of conservation concern in Southwestern Ontario, Canada, and effective monitoring of their populations is crucial for making informed management decisions. Electrofishing is a traditional, yet invasive, method that allows for fish abundance estimation. Environmental DNA (eDNA) is an emerging molecular tool that presents a non-invasive alternative to electrofishing. This study was a collaborative effort between researchers in academia, industry, and an NGO, with the following objectives: 1) compare eDNA detections with electrofishing when monitoring brook trout populations in a site of known occupancy, 2) compare existing eDNA collection methods, and 3) extend eDNA surveys to regions of unknown occupancy that could be of conservation concern (Hanlon Creek and Twelve Mile Creek, Ontario). First, eDNA sampling methods were validated with standard electrofishing. Water samples were filtered in tandem at each site using two commercially available eDNA samplers. The results suggest a significant difference in total eDNA capture and incidence of PCR inhibitors between the two autosamplers. Brook trout eDNA was detected at all locations in Hanlon Creek in September and November, as well as 5/6 sampling locations in Twelve Mile Creek. Brook trout signal in Hanlon Creek was stronger in November compared to September 2019, suggesting possible spawning activity. Brook trout eDNA was also detected in Twelve Mile Creek where brook trout were previously unreported. This study provides a technical validation for the use of eDNA in brook trout monitoring and illustrates the opportunity to use eDNA surveys in regulated settings to complement and improve conventional biomonitoring methods for the management of elusive species.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".