Gene–environment interactions influence feeding and anti‐predator behavior in wild and transgenic coho salmon
Bibliographic record
Abstract
Environmental conditions are known to affect phenotypic development in many organisms, making the characteristics of an animal reared under one set of conditions not always representative of animals reared under a different set of conditions. Previous results show that such plasticity can also affect the phenotypes and ecological interactions of different genotypes, including animals anthropogenically generated by genetic modification. To understand how plastic development can affect behavior in animals of different genotypes, we examined the feeding and risk-taking behavior in growth-enhanced transgenic coho salmon (with two- to threefold enhanced daily growth rates compared to wild type) under a range of conditions. When compared to wild-type siblings, we found clear effects of the rearing environment on feeding and risk-taking in transgenic animals and noted that in some cases, this environmental effect was stronger than the effects of the genetic modification. Generally, transgenic fish, regardless of rearing conditions, behaved similar to wild-type fish reared under natural-like conditions. Instead, the more unusual phenotype was associated with wild-type fish reared under hatchery conditions, which possessed an extreme risk averse phenotype compared to the same strain reared in naturalized conditions. Thus, the relative performance of genotypes from one environment (e.g., laboratory) may not always accurately reflect ecological interactions as would occur in a different environment (e.g., nature). Further, when assessing risks of genetically modified organisms, it is important to understand how the environment affects phenotypic development, which in turn may variably influence consequences to ecosystem components across different conditions found in the complexity of nature.
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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) | 0.000 | 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 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".