Effects of the group’s mix of sizes and personalities on the emergence of alternative mating systems in water striders
Bibliographic record
Abstract
Although much work has analysed how individual behavioural plasticity and adaptations to ecological conditions (e.g. density, sex-ratio, resource distribution) shape mating systems, few studies have assessed the relative importance of multiple factors in explaining why mating systems vary from one sub-population to the next even in the same ecological conditions. Differences among groups in their phenotypic composition, such as their average phenotype, within-group variation in phenotype, or the phenotype of individuals occupying key social roles might shape the mating system emerging at the group level and explain some portion of mating system variability. Here, we take advantage of the mating system flexibility of stream water striders (Aquarius remigis) to investigate how phenotypic composition affects the mating system emerging at the group level. Groups exhibited stable mating systems varying from scramble polygyny with intense sexual conflict, to systems with a clear dominant male guarding a “harem” of females. We found that male size asymmetries and the personality of the largest individuals within groups had important effects on the group’s mating system. The group’s average male and female personality, size, and social plasticity also explained some of the variation in mating systems. Our study is one of the first to quantify significant relationships between group phenotypic composition and mating system variability.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".