Field Test of the Self‐Preserving <scp>eDNA</scp> Filter and the Importance of Calibration When Changing Methods During Long‐Term Monitoring
Bibliographic record
Abstract
ABSTRACT Filtering water is currently the primary field method used for collecting aquatic environmental DNA (eDNA). One of the drawbacks of filtering is the need to transfer the filter from the filter housing to a preservative‐filled container in the field. New products are being developed to avoid this handling step, but comparative studies are needed to ensure that the results produced by new protocols are transferable within and across eDNA monitoring programs. To meet this need, we evaluated two filter preservation methods (self‐preserving filter housing vs. ethanol) of the 5.0‐μm polyethersulfone (PES) filter membrane in a field trial typical of stream fisheries eDNA sampling. We compared DNA detection and yield for free‐swimming rainbow trout, Oncorhynchus mykiss (Walbaum, 1792), from streams in Washington, United States, and British Columbia, Canada, while accounting for the effects of two environmental covariates: stream discharge and water temperature. As these streams were part of an ongoing fisheries eDNA monitoring program, we also compared these methods to the original protocol, which used a 0.45‐μm cellulose nitrate (CN) filter membrane and ethanol preservative. We found that the self‐preserving filter housings collected and preserved eDNA well and provided similar results to identical filters preserved in ethanol. The 5.0‐μm PES filters preserved in ethanol significantly outperformed the original protocol in terms of both DNA detection and yield, highlighting the importance of calibration of eDNA results when changing sampling methods during an ongoing monitoring program.
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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 | 0.001 |
| 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".