Experimental trait mismatches uncover specificity of evolutionary links between multiple signaling traits and their interactions in hummingbirds*
Bibliographic record
Abstract
Many animal signals co-occur, and these signals may coevolve due to their interactive properties. Previous work has demonstrated ecological drivers of evolutionary relationships between signals and the environment, which leads to questions about why specific signal pairs evolved among species that possess multiple signals. We asked whether the coloration of different species was optimized for presentation with its natural behavioral display. We investigated this in "bee" hummingbirds, where males exhibit angle-dependent structurally-colored plumage and a stereotyped courtship (shuttle) display, by experimentally creating mismatches between the behavior and plumage of five species and quantifying how these mismatches influenced male color appearance during a display. Specifically, we photographed the plumage from a given species as we moved its feathers through the position-and-orientation-specific courtship display path of other species and quantified the resulting color appearance during the display in order to compare the mismatched color appearance to each species' natural color appearance. We found that mismatches significantly altered display flashiness (% change in coloration during displays) compared to the natural plumage-behavior pairings, and that such departures in flashiness were predicted by differences in shuttle behaviors alone. These results illustrate a tight evolutionary relationship between shuttle displays and color flashiness in these hummingbirds. Further, we found that interspecific variation in male plumage, behavior, and natural color appearance predicted deviations between natural and mismatched flashy color appearance. Altogether, our work provides a new method for testing signal coevolution and highlights the complex evolutionary relationships between multiple signals and their interactions.
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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 | 0.000 | 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 | 0.001 |
| 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".