Single generation exposure to a captive diet: a primer for domestication selection in a salmonid fish?
Bibliographic record
Abstract
Abstract Millions of wild animals in captivity are reared on diets that differ in their uptake and composition from natural conditions. Few studies have investigated whether such novel diets elicit unintentional domestication selection in captive rearing and supplementation programs. In highly fecund salmonid fishes, natural and captive mortality is highest in the first few months of exogenous feeding. This high early mortality might be a potent driver of unintentional selection because wild fish normally forage on live prey whereas they are fed almost exclusively pellet feed in captivity: fish that do not adapt pellet feed well under captive conditions experience reduced growth and/or die. We tested this hypothesis by generating a large number of families from F 1 captive and wild fish originating from the same three populations and then rearing them each on pellet and natural, live, drifting feed for three months at the beginning of exogenous feeding. We found that captive fish of every population grew faster than wild fish in all diet treatments. Populations exhibited an idiosyncratic response to diet treatment, with two populations exhibiting faster growth on a pellet diet versus the natural diet but another population exhibiting similar growth in both diet treatments. Fish exposed to a natural diet also exhibited higher survival relative to those given a pellet diet. Captive and wild fish did not differ in survival, regardless of population of origin. Overall, we found evidence that rapid domestication selection associated with a single generation exposure to a novel captive diet generates genetically-based changes to individual fitness (e.g., growth and survival) in a wild fish.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".