Disentangling the mechanisms of signal evolution in Tyrannidae flycatchers, part II: plumage elaboration evolved with migration behavior, but is also affected by diet, climate, and drift
Bibliographic record
Abstract
Animal coloration is an important communication signal that varies among taxa and affects survival and reproduction. Species-specific color is influenced by a variety of factors including phylogeny, predation, sexual selection, light and resource availability, ecological context, and/or species recognition. Tyrant flycatchers are useful to study color evolution because they are the largest family of birds, occur across broad environmental gradients, and although many genera are monomorphic with drab plumage, some are very colorful. Given the complexity of factors involved, the mechanisms influencing plumage color evolution in Tyrant flycatchers likely involve multiple drivers. In the second of our two-part paper on signal evolution in this avian family, we harnessed a large plumage color database of female and male Tyrannidae species (n = 399) to test the relative importance of geography (climate, latitude), ecology (migration behavior, forest cover, diet), and heterospecific proximity on plumage color evolution. From phylogenetically controlled analyses, we found that female color was largely driven by climate and male color was more exaggerated in migratory species. Sexual dichromatism was also affected by climate and diet, and was more pronounced in migratory species, possibly as a result of color loss in females. Pairwise comparisons between heterospecific color differences and geographic distance were generally weak and consistent with expectations under drift, which contrasted our song results (presented in Part I), but analyses at finer taxonomic scales revealed color may be used for conspecific recognition in some genera. Together with our paper on Tyrannidae song evolution, the color results reflect the importance of testing multiple drivers of signal evolution at different taxonomic scales because flycatcher color variation may have arisen through genetic drift, from a loss of female color in migratory species, and for species recognition in some genera. Future work could formally test the correlation between song and color variation, and use stochastic character mapping to confirm if Tyrannidae dichromatism resulted from female color loss in migratory species.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.000 | 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".