Environmental DNA dispersal from Atlantic salmon farms
Bibliographic record
Abstract
The spatial spread of genetic material is fundamental to analyses of invasive species, species dispersal, and disease surveillance. Using a quantitative environmental DNA methodology, we assessed spatial variation in Atlantic salmon ( Salmo salar) eDNA concentration, originating from four active salmon farms, along ∼55 km of narrow channels in British Columbia, Canada. We evaluated eDNA from 36 and 47 seawater samples collected at 2 and 8 m depths, respectively, at 0.3–3 km intervals along the channels. We fitted a Laplace dispersal kernel to eDNA data separately for 2 and 8 m depths. The model estimates that 95% of eDNA spread at 2 m depth was within 1.6 km upstream and 3.2 km downstream from farms relative to a prevailing current, and this was expanded at 8 m (1.8 km upstream; 3.7 km downstream). Our modeling results were robust to multiple sources of simulated uncertainty associated with sampling regime and variable eDNA shedding rates. Our results provide a benchmark for the spatial spread of biological material such as pathogens or eDNA from invasive or imperilled species in a coastal marine context. This work has implications for the interpretation of eDNA data for species surveillance and predicting disease spread.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".