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Data and code from: Computational analyses of dynamic visual courtship display reveal diet-dependent male signaling in Rabidosa rabida wolf spiders

Authors: Choi, Noori; Wilgers, Dustin; Hebets, Eileen;

Data and code from: Computational analyses of dynamic visual courtship display reveal diet-dependent male signaling in Rabidosa rabida wolf spiders

Abstract

Male courtship signals exhibit significant variation influenced by genetic, environmental, and ecological factors. Investigating the evolutionary significance of the variations in the complex male courtship signals, which often consist of multiple components with distinct functions, requires clear identification and quantification of their structural organization. Traditional, manually defined ethograms can be subjective and inconsistent, even with the knowledge and experience of trained experts, leading to challenges in reproducible and consistent comparative analysis. To address these limitations, this study investigates the impact of diet manipulation on the dynamic visual components of multimodal courtship displays in male Rabidosa rabida wolf spiders. By adopting a bottom-up ethogram using the Gaussian Hidden Markov Model (GHMM) and employing both unary and binary similarity measures, we aim to develop automated tools for behavior annotation and quantitatively compare dynamic visual components (i.e., foreleg movements) during male courtship. We revealed that (i) the structural organization of foreleg movements defined by the GHMM is comparable to the previously described by human observers, (ii) combining unary similarity measures with binary similarity measures is a powerful approach for animal communication studies, and (iii) previous foraging history of males influence the morphology and movement of forelegs during the multimodal courtship signals of R. rabida males. Our findings will enhance our understanding of the evolution of complex male courtship signals by providing a standardized framework for future research.

Funding provided by: U.S. National Science FoundationROR ID: https://ror.org/021nxhr62Award Number: Funding provided by: University of Nebraska–LincolnROR ID: https://ror.org/043mer456Award Number:

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Keywords

Gaussian Hidden Markov Model, Machine learning, courtship display, Wolf spiders, Schizocosa, Dynamic visual motions, diet manipulation, Signal similarity

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average