Divergent Host Plant Adaptation and Reproductive Isolation between Ecotypes of <i>Timema cristinae</i> Walking Sticks
Bibliographic record
Abstract
Theoretical and empirical studies have demonstrated that divergent natural selection can promote the evolution of reproductive isolation. Three unresolved questions concern the types of reproductive barriers involved, the role of geography, and the factors determining the extent of progress toward complete speciation. Here I synthesize studies of Timema cristinae host plant ecotypes to address these issues. The approach is to compare the magnitude of multiple reproductive barriers among different ecological and geographic scenarios, where pairs of populations within each scenario are the unit of replication. Application of this approach to T. cristinae revealed that divergent host adaptation can promote the evolution of diverse reproductive barriers, including those that are not inherently ecological. Gene flow in parapatry tended to constrain divergence, with the notable exception of the reinforcement of sexual isolation. Thus, geography affected progress toward speciation but did not influence all reproductive barriers in the same way. Studies of any single pair of taxa often capture only certain stages of the speciation process. For example, reproductive isolation between T. cristinae ecotypes is incomplete, and so only the stages before the completion of speciation have been examined. Studies of more divergent taxa within the genus are required to determine the factors that complete speciation.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".