Telemetric and video assessment of female response to male vocal performance in a lek-mating manakin
Bibliographic record
Abstract
Sexual signals play an important role in mate attraction. In this study, we explore male vocal behavior and female mate attraction in long-tailed manakins, tropical lekking birds where males perform cooperative displays to attract females, and males provide only gametes to choosy females. We monitored female visitation at 37 sites using two techniques: video recordings and automated radiotelemetry. Simultaneously, we used digital recorders to sample male vocal behavior, quantifying vocal output as well as frequency matching and temporal synchrony in male–male duets. We compared male vocal performance to the rate at which females visited male display sites. Video data revealed that both male vocal output and the temporal synchrony of male–male duets were positively related to female visitation, matching our expectations. Telemetry data, in contrast, revealed no such relationship. Our results suggest that telemetry data may yield biased estimates of patterns of female choice, because the tracked females may not adequately represent the pool of potential female visitors to leks. We also demonstrate that male vocal behavior and female visitation vary, in concert, with time of day, peaking in the early morning, with a pronounced drop in the mid-day heat. We compare these results with those of another study, of the same species, in a montane environment with cooler daytime temperatures.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".