Alleles underlying larval foraging behaviour influence adult dispersal in nature
Bibliographic record
Abstract
The dispersal and migration of organisms have resulted in the colonisation of nearly every possible habitat and ultimately the extraordinary diversity of life. Animal dispersal tendencies are commonly heterogeneous (e.g. long vs. short) and non-random suggesting that phenotypic and genotypic variability between individuals can contribute to population-level heterogeneity in dispersal. Using laboratory and field experiments, we demonstrate that natural allelic variation in a gene underlying a foraging polymorphism in larval fruit flies (for), also influences their dispersal tendencies as adults. Rover flies (for(R) ; higher foraging activity) have consistently greater dispersal tendencies and are more likely to disperse longer distances than sitter flies (for(s) ; lower foraging activity). Increasing for expression in the brain and nervous system increases dispersal in sitter flies. Our study supports the notion that variation in dispersal can be driven by intrinsic variation in food-dependent search behaviours and confirms that single gene pleiotropic effects can contribute to population-level heterogeneity in dispersal.
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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 | 0.001 | 0.003 |
| 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; both teacher heads agree on what is shown here.
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".