A new heuristic for capturing the complexity of multimodal signals

Many animal signals are inherently multimodal, engaging more than one of the receiver's sensory systems simultaneously, and it is the interaction between the two modalities that determines the signal's function (s) and efficacy. It is hence necessary to quantify the effect of each modality relative to the other in order to fully understand animal communication. We have developed a new heuristic to aid in the identification and interpretation of the many distinct ways in which signals in multiple sensory modalities interact. Our approach represents natural variation in signal production for each modality and uses these to generate three-dimensional receiver response surface plots that map the relationships among the signal components and receiver behavior. We accommodate the extant hypotheses for the interactions between modalities, each of which makes a clear prediction about the shape of the response surface, and extend previous theory by considering new phenomena.