Migration and the Genetic Covariance between Habitat Preference and Performance
Bibliographic record
Abstract
Studies of the genetic covariance between habitat preference and performance have reported conflicting outcomes ranging from no covariance to strong covariance. The causes of this variability remain unclear. Here we show that variation in the magnitude of genetic covariance can result from variability in migration regimes. Using data from walking stick insects and a mathematical model, we find that genetic covariance within populations between host plant preference and a trait affecting performance on different hosts (cryptic color pattern) varies in magnitude predictably among populations according to migration regimes. Specifically, genetic covariance within populations is high in heterogeneous habitats where migration between populations locally adapted to different host plants generates nonrandom associations (i.e., linkage disequilibrium) between alleles at color pattern and host preference loci. Conversely, genetic covariance is low in homogeneous habitats where a single host exists and migration between hosts does not occur. Our results show that habitat structure and patterns of migration can strongly affect the evolution and variability of genetic covariance within populations.
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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 | 0.001 |
| 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".