Atlantic salmon farms are a likely source of <i>Tenacibaculum maritimum</i> infection in migratory Fraser River sockeye salmon
Bibliographic record
Abstract
Abstract Infectious disease from domestic hosts, held for agriculture, can impact wild species that migrate in close proximity, potentially reversing selective advantages afforded by migration. For sockeye salmon in British Columbia, Canada, juveniles migrate past numerous Atlantic salmon farms from which they may acquire a number of infectious agents. We analyse patterns of molecular detection in juvenile sockeye salmon for one bacterial pathogen, Tenacibaculum maritimum , known to cause disease in fish species around the globe and to cause mouthrot disease in farmed Atlantic salmon in BC. Our data show a clear peak in T. maritimum detections in the Discovery Islands region of BC, where sockeye migrate close to salmon farms. Using well established differential-equation models to describe sockeye migration and T. maritimum infection spread, we fit models to our detection data to assess support for multiple hypotheses describing farm- and background-origin infection. Despite a data-constrained inability to resolve certain epidemiological features of the system, such as the relative roles of post infection mortality and recovery, our models clearly support the role of Discovery-Islands salmon farms in producing the observed patterns. Our best models (with 99.8% empirical model support) describe relatively constant (background) infection pressure, except around Discovery-Islands salmon farms, where farm-origin infection pressure peaked at 12.7 (approximate 95% CI: 4.5 to 31) times background levels. Given the evidence for farm-origin transfer of T. maritimum to Fraser-River sockeye salmon, the severity of associated disease in related species, and the imperilled nature of Fraser River sockeye generally, our results suggest the need for a more precautionary approach to managing farm/wild interactions in sockeye salmon.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".