Local Adaptation along Smooth Ecological Gradients Causes Phylogeographic Breaks and Phenotypic Clustering
Bibliographic record
Abstract
Coalescent theory has provided a basis for evolutionary biologists to build sophisticated methods for inferring population history from variation in genetic markers, but these methods leave out a major conceptual cornerstone of modern evolutionary theory: natural selection. I provide the first quantitative analysis of the effects of selection on genealogical patterns in a continuously distributed population in which the selective optimum for a trait linked to the marker varies gradually and continuously across the landscape. Simulations show that relatively weak selection for local adaptation can lead to strong phylogeographic structure, in which highly divergent genealogical groups (i.e., clades) are geographically localized and differentially adapted, and dramatically increased standing variation (e.g., coalescence time) compared to neutral expectations. This pattern becomes more likely with increasing population size and with decreasing dispersal distances, mutation rates, and mutation sizes. Under some conditions, the system alternates between a nearly neutral behavior and a behavior in which highly divergent clades are locally adapted. Natural selection on markers commonly used in phylogeographic studies (such as mitochondrial DNA) presents a major challenge to the inference of biogeographic history but also provides exciting opportunities to study how selection affects both between- and within-species biodiversity.
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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".