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Sexual selection and 'species recognition' revisited: serial processing and order-of-operations in mate choice
1Department of Biology, California State University Northridge, 18111 Nordhoff Street, Northridge, CA 91330-8303, USA.
Proceedings. Biological Sciences
|March 23, 2022
Summary
Mating signals are evaluated in a specific order. Early signal components aid species recognition with low variation, while later components indicate mate quality with higher variation, revealing an
Area of Science:
- Evolutionary biology
- Animal behavior
- Bioacoustics
Background:
- Mating signals were initially viewed as species recognition traits, later expanded to include sexual selection and mate choice.
- The dual function of signals (recognition vs. quality) was proposed to stem from female preference functions but lacked empirical testing.
- Contrasting properties of recognition (stereotyped, low variation) and quality (condition-dependent, high variation) signals pose a challenge.
Purpose of the Study:
- To test the hypothesis that different mating signal components are evaluated sequentially: first for recognition, then for quality.
- To investigate the relationship between signal variation, female preference, and phylogenetic signal in cricket calls.
Main Methods:
- Analysis of intraspecific variation in male cricket call components.
- Characterization of female preference function shapes for these components.
- Assessment of phylogenetic signal across different call components.
Main Results:
- Early-processed signal components exhibit low intraspecific variation, closed female preference functions, and low phylogenetic signal.
- Later-processed signal components show high intraspecific variation, open preference functions, and high phylogenetic signal.
- These patterns support a sequential 'order-of-operations' in mating signal evaluation.
Conclusions:
- Mating signal processing follows a distinct sequence, prioritizing species recognition before mate quality assessment.
- This 'order-of-operations' model provides a framework for understanding signal evolution across diverse taxa and sensory modalities.
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