Piloting environmental DNA for fisheries monitoring in the upper Peace River watershed
Bibliographic record
Abstract
Applications of environmental DNA (eDNA) represent one of the most significant recent advances in aquatic species monitoring. eDNA has the potential to dramatically increase the effectiveness and efficiency of fisheries monitoring across large geographic areas and particularly for species that have traditionally been difficult to survey. The Williston Reservoir and its surrounding watershed in northern British Columbia is a vast and heavily disturbed aquatic ecosystem where fish stocks have been difficult to monitor with traditional survey techniques. Although eDNA has many potential benefits, the validation process required in a novel environment can be a barrier to adoption. Primer choice and validation, study design and laboratory workflows are critical considerations for eDNA studies and must be evaluated when developing a novel approach in a particular geographic area. My research advanced the validation of species-specific eDNA assays for six prominent pelagic species in the Williston Reservoir and a generic, metabarcoding primer set that was effective in detecting the diversity of fish in the surrounding streams and rivers. The species-specific approach included the validation of four published assays and the development of novel assays for detecting lake trout (Salvelinus namaycush) and peamouth (Mylocheilus caurinus). Lake trout and bull trout (Salvelinus confluentus) are very closely related species that are sympatric throughout much of northwestern North America. The development of a novel lake trout assay that did not cross amplify bull trout eDNA is an important achievement for species-specific eDNA monitoring. Reservoir samples were collected from above and below the thermocline during the summer when the reservoir was stratified to identify species-specific patterns of eDNA distribution throughout the water column. Species detections in the reservoir were comparable for species-specific and metabarcoding assays when compared against gillnet catches in the reservoir. Abundant species that exhibit diel vertical migrations were detected by eDNA and gillnets at all depths. eDNA copy numbers detected were higher for samples with greater abundance and biomass of each species caught in the gillnets. Samples collected from tributaries around the reservoir were tested with metabarcoding primers and species detections were compared to results from a species-specific assay for Arctic grayling and a snorkel survey. Metabarcoding results were comparable to those from the Arctic grayling eDNA study and the snorkels survey, although the metabarcoding methods in this study were less sensitive due to a reduced amount of sample replication. Piloting eDNA in the Williston Reservoir and surrounding watershed has provided valuable insights into eDNA sampling design and the overall workflow for future eDNA studies in the region.,
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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 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".