It has long been a challenge to quantify the variation in dynamic motions to understand how those displays function in animal communication. The traditional approach is dependent on labor-intensive manual identification/annotation by experts. However, the recent progress in computational techniques provides researchers with toolsets for rapid, objective, and reproducible quantification of dynamic visual displays. In the present study, we investigated the effects of diet manipulation on dynamic visual components of male courtship displays of Rabidosa rabida wolf spiders using machine learning algorithms. Our results suggest that (i) the computational approach can provide an insight into the variation in the dynamic visual display between high- and low-diet males which is not clearly shown with the traditional approach and (ii) males may plastically alter their courtship display according to the body size of females they encounter. Through the present study, we add an example of the utilization of recent computational techniques for understanding the evolution of animal behaviors.

Raw data - We recorded male courtship with a Photron Fastcam 1024 PCI 100k high-speed camera (Photron USA, San Diego, CA, USA) and a Sony DCR-HC65 NTSC Handycam (Sony Electronics Inc., USA). Then, we analyzed the movement of the foreleg and pedipalps during the selected courtship bouts using ProAnalyst Lite software (Xcitex Inc., Woburn, Massachusetts, USA). We first set the x-axis and y-axis by where the pedipalp tip was in contact with the substrate (y-position 0) and most posterior point of the abdomen (x-position 0) at the beginning of the courtship bout. When the foreleg or pedipalps did not move during the courtship bout, the location of the joint was recorded by the location of the parts at the cocked position. In the case of the image being blurred, the location of blurred points was guessed based on the previous or subsequent frames or other parts in the current frame.