Effects of aquaculture on wild fish populations: a synthesis of data
Bibliographic record
Abstract
The potential adverse environmental effects of aquaculture have been the subject of considerable attention in both the media and the scientific literature. We undertook a synthesis of the published scientific literature, primarily concerning Atlantic salmon (Salmo salar), to assess the current data available regarding these potential effects. No data are available to test for the direct effects of aquaculture organisms on the demographics of wild fish populations. However, seven studies show that escaped salmon in the wild have lower fitness, as measured by survival and reproductive success, than native salmon. Thirteen other studies, encompassing 91 different traits, provide strong evidence of phenotypic differences between farmed and wild salmon, presumably because of artificial selection in the aquaculture environment. An additional 10 studies have documented significant genetic differences between farmed salmon and the wild fish with which they will interact, or potentially interact. Given the paucity of data regarding actual population consequences of escaped farmed fish on wild populations, and the documented differences between the two types of fish, it seems prudent to treat farmed fish as exotic species with potentially negative consequences for wild populations, particularly when the latter are of conservation concern.Key words: aquaculture, Atlantic salmon, artificial selection, fitness, introgression.
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 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".