Social network position experiences more variable selection than weaponry in wild subpopulations of forked fungus beetles
Bibliographic record
Abstract
1. The phenotypic expression and fitness consequences of behaviors that are exhibited during social interactions are especially sensitive to their local social context. This context-dependence is expected to generate more variation in the sign and magnitude of selection on social behavior than that experienced by static characters like morphology. Relatively few studies, however, have examined selection on behavioral traits in multiple populations. 2. We estimated sexual selection in the wild to determine if the strength and form of selection on social phenotypes is more variable than that on morphology. 3. We compared selection gradients on social network position, body size, and weaponry of male forked fungus beetles (Bolitotherus cornutus) as they influenced mating success across nine natural subpopulations. 4. Male horn length consistently experienced positive sexual selection. However, the sign and magnitude of selection on individual measures of network centrality (strength and betweenness) differed significantly among subpopulations. Moreover, selection on social behaviors occurred at local scale (“soft selection”), whereas selection on horn length occurred at the metapopulation scale (“hard selection”). 5. These results indicate that an individual with a given social phenotype could experience different fitness consequences depending on the network it occupies. While individuals seem to be unable to escape the fitness effects of their morphology, they may have the potential to mediate the pressures of selection on behavioral phenotypes by moving among subpopulations or altering social connections within a network.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".