Hydrocarbon divergence and reproductive isolation in Timema stick insects
Bibliographic record
Abstract
BACKGROUND: Individuals commonly prefer certain trait values over others when choosing their mates. If such preferences diverge between populations, they can generate behavioral reproductive isolation and thereby contribute to speciation. Reproductive isolation in insects often involves chemical communication, and cuticular hydrocarbons, in particular, serve as mate recognition signals in many species. We combined data on female cuticular hydrocarbons, interspecific mating propensity, and phylogenetics to evaluate the role of cuticular hydrocarbons in diversification of Timema walking-sticks. RESULTS: Hydrocarbon profiles differed substantially among the nine analyzed species, as well as between partially reproductively-isolated T. cristinae populations adapted to different host plants. In no-choice trials, mating was more likely between species with similar than divergent hydrocarbon profiles, even after correcting for genetic divergences. The macroevolution of hydrocarbon profiles, along a Timema species phylogeny, fits best with a punctuated model of phenotypic change concentrated around speciation events, consistent with change driven by selection during the evolution of reproductive isolation. CONCLUSION: Altogether, our data indicate that cuticular hydrocarbon profiles vary among Timema species and populations, and that most evolutionary change in hydrocarbon profiles occurs in association with speciation events. Similarities in hydrocarbon profiles between species are correlated with interspecific mating propensities, suggesting a role for cuticular hydrocarbon profiles in mate choice and speciation in the genus Timema.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".