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Ecology and behavior predict an evolutionary trade-off between song complexity and elaborate plumages in antwrens (Aves, Thamnophilidae)
- Source :
- Evolution; international journal of organic evolutionLITERATURE CITED. 75(10)
- Publication Year :
- 2020
-
Abstract
- The environment can impose constraints on signal transmission properties such that signals should evolve in predictable directions (Sensory Drive Hypothesis). However, behavioral and ecological factors can limit investment in more than one sensory modality leading to a trade-off in use of different signals (Transfer Hypothesis). In birds, there is mixed evidence for both sensory drive and transfer hypothesis. Few studies have tested sensory drive while also evaluating the transfer hypothesis, limiting understanding of the relative roles of these processes in signal evolution. Here, we assessed both hypotheses using acoustic and visual signals in male and female antwrens (Thamnophilidae), a species-rich group that inhabits diverse environments and exhibits behaviors, such as mixed-species flocking, that could limit investment in different signal modalities. We uncovered significant effects of habitat (sensory drive) and mixed-species flocking behavior on both sensory modalities, and we revealed evolutionary trade-offs between song and plumage complexity, consistent with the transfer hypothesis. We also showed sex- and trait-specific responses in visual signals that suggest both natural and social selection play an important role in the evolution of sexual dimorphism. Altogether, these results support the idea that environmental (sensory drive) and behavioral pressures (social selection) shape signal evolution in antwrens.
- Subjects :
- Male
Modalities
Ecology
Flocking (behavior)
Ecology (disciplines)
Sensory system
Biology
Trade-off
Biological Evolution
Sexual dimorphism
Stimulus modality
Phenotype
Genetics
Animals
Female
Passeriformes
Vocalization, Animal
General Agricultural and Biological Sciences
Ecology, Evolution, Behavior and Systematics
Selection (genetic algorithm)
Ecosystem
Subjects
Details
- ISSN :
- 15585646
- Volume :
- 75
- Issue :
- 10
- Database :
- OpenAIRE
- Journal :
- Evolution; international journal of organic evolutionLITERATURE CITED
- Accession number :
- edsair.doi.dedup.....1a6efcb46699ffbc35d7789b7c3563df