The hidden costs of aquaculture : impacts on wild Pacific salmon in British Columbia
Bibliographic record
Abstract
Salmon aquaculture has expanded significantly along the coast of British Columbia over the past several decades, contributing to food security and rural economies. However, this growth has coincided with widespread declines in wild Pacific salmon populations. A growing body of research points to disease transmission and ecological stressors from open-net pen farms particularly those situated along key migration corridors and near spawning habitats as contributing factors. While biological and experimental studies have highlighted these risks, they often focus on specific species or localized areas, limiting generalization. This thesis estimates the causal impact of salmon farms on wild Pacific salmon across British Columbia. Using stream-level salmon escapement data and geospatial records of aquaculture operations, we construct a spatial exposure framework linking salmon farms to river mouths of salmon spawning streams. Employing two-way fixed effects models controlling for stream, species, and year, we find that each additional salmon farm within 10 km of stream mouths significantly reduces wild salmon returns by approximately 638 fish (p < 0.05). These negative effects are consistent across species, with particularly strong impacts observed for Pink and Chinook salmon. This research provides the first province-wide, stream-level econometric analysis of aquaculture impacts on wild Pacific salmon returns. The results underscore the ecological risks posed by spatial overlap between aquaculture infrastructure and salmon migration corridors, and support the development of spatially informed regulatory policies aimed at safeguarding wild salmon populations in British Columbia.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".