THE EVOLUTION OF TRADE-OFFS: EFFECTS OF INBREEDING ON FECUNDITY RELATIONSHIPS IN THE CRICKET GRYLLUS FIRMUS
Bibliographic record
Abstract
The evolution of traits is modulated by their interrelationships with each other, particularly when those relationships result in a fitness trade-off. In this paper we explore the consequences of genetic architecture on functional relationships between traits. Specifically, we address the consequences of inbreeding on these relationships. We show that the linear regression between two traits will not be affected if there is no dominance genetic variance in either trait, whereas the intercept but not the slope of the regression will change if there is dominance genetic variance in one trait only. We test the latter hypothesis using fecundity relationships in the cricket Gryllus firmus. Data from pedigree analysis and an inbreeding experiment show that there is significant dominance genetic variance in fecundity, but not head width (an index of body size) or dorsal longitudinal muscle (DLM) mass. Fecundity increases with head width, but decreases with DLM mass. As predicted, the intercepts of the regressions of fecundity on these two morphological traits decrease with inbreeding, but there is little or no change in slope. Gryllus firmus is wing dimorphic, with the macropterous (LW) morph having a lower fecundity than the micropterous (SW) morph. We hypothesize that the difference in fecundity arises primarily because of a competition for resources in the LW females between DLM maintenance (i.e., mass) and egg production. As a consequence, we predict that the fecundity within each morph should decline linearly with the inbreeding coefficient at the same rate in both morphs. The result of this will be a change in the relative fitness of the two morphs, that of the SW morph increasing with inbreeding. This prediction is supported. These results indicate that trade-offs will evolve and such changes will affect evolutionary trajectories by altering the pattern of relationships among fitness components.Corresponding Editor: D. Wheeler
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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 | 0.001 | 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".