Divergence genetics analysis reveals historical population genetic processes leading to contrasting phylogeographic patterns in co‐distributed species
Bibliographic record
Abstract
Coalescent samplers are computational time machines for inferring the historical demographic genetic processes that have given rise to observable patterns of spatial genetic variation among contemporary populations. We have used traditional characterizations of population structure and coalescent-based inferences about demographic processes to reconstruct the population histories of two co-distributed marine species, the frilled dog whelk, Nucella lamellosa, and the bat star, Patiria miniata. Analyses of population structure were consistent with previous work in both species except that additional samples of N. lamellosa showed a larger regional genetic break on Vancouver Island (VI) rather than between the southern Alexander Archipelago as in P. miniata. Our understanding of the causes, rather than just the patterns, of spatial genetic variation was dramatically improved by coalescent analyses that emphasized variation in population divergence times. Overall, gene flow was greater in bat stars (planktonic development) than snails (benthic development) but spatially homogeneous within species. In both species, these large phylogeographic breaks corresponded to relatively ancient divergence times between populations rather than regionally restricted gene flow. Although only N. lamellosa shows a large break on VI, population separation times on VI are congruent between species, suggesting a similar response to late Pleistocene ice sheet expansion. The absence of a phylogeographic break in P. miniata on VI can be attributed to greater gene flow and larger effective population size in this species. Such insights put the relative significance of gene flow into a more comprehensive historical biogeographic context and have important implications for conservation and landscape genetic studies that emphasize the role of contemporary gene flow and connectivity in shaping patterns of population differentiation.
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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 | 0.001 |
| 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".