Partitioning the effects of isolation by distance, environment, and physical barriers on genomic divergence between parapatric threespine stickleback
Bibliographic record
Abstract
Genetic divergence between populations is shaped by a combination of drift, migration, and selection, yielding patterns of isolation-by-distance (IBD) and isolation-by-environment (IBE). Unfortunately, IBD and IBE may be confounded when comparing divergence across habitat boundaries. For instance, parapatric lake and stream threespine stickleback (Gasterosteus aculeatus) may have diverged due to selection against migrants (IBE), or mere spatial separation (IBD). To quantitatively partition the strength of IBE and IBD, we used recently developed population genetic software (BEDASSLE) to analyze partial genomic data from three lake-stream clines on Vancouver Island. We find support for IBD within each of three outlet streams (unlike prior studies of lake-stream stickleback). In addition, we find evidence for IBE (controlling for geographic distance): the genetic effect of habitat is equivalent to geographic separation of ∼1.9 km of IBD. Remarkably, of our three lake-stream pairs, IBE is strongest where migration between habitats is easiest. Such microgeographic genetic divergence would require exceptionally strong divergent selection, which multiple experiments have failed to detect. Instead, we propose that nonrandom dispersal (e.g., habitat choice) contributes to IBE. Supporting this conclusion, we show that the few migrants between habitats are a nonrandom subset of the phenotype distribution of the source population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".