The Opportunistic Serpent: Male Garter Snakes Adjust Courtship Tactics to Mating Opportunities
Bibliographic record
Abstract
Reproductive males encounter potential mates under a range of circumstances that influence the costs, benefits or feasibility of alternative courtship tactics. Thus, males may be under strong selection to flexibly modify their behaviour. Red-sided garter snakes (Thamnophis sirtalis parietalis) in Manitoba overwinter in communal dens, and court and mate in large aggregations in early spring. The number of males within a courting group varies considerably, as do the body sizes of both males and females. We manipulated these factors to set up replicated courtship groups in outdoor arenas, and analysed videotapes of 82 courtship trials to quantify courting behaviours of male snakes. Larger and more heavy-bodied males courted more vigorously than did their smaller, thinner-bodied rivals, and large females attracted more intense courtship. The major effect, however, involved the number of rival males competing for copulation. Males in large groups not only reduced their overall vigour of courtship, but also modified their tactics in such a way as to benefit from the courtship activities of rival males. That is, they devoted less energy to inducing female receptivity (which requires energy-expensive caudocephalic waving) and more effort to behaviour (tail-searching) that enhanced their own probability of mating if the female gaped her cloaca. This social parasitism reveals an unsuspected plasticity and complexity in the behavioural tactics of reproducing male snakes.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".