Professor Santa Clara University Santa Clara, California
Embioptera spin silk with complex spin-step dynamics, even up to 10,000 steps per hour. A large comparative study aimed to discover patterns that might reflect lifestyles, phylogenetic relationships or other driving factors that might explain diversity. Given that webspinner adult females have the same body form no matter the taxonomic family, exploring behavioral diversity might hold clues to evolutionary diversification. The records of spinning by a few dozen species proved extremely complex and difficult to interpret. Sonification, the process of transforming data into sound, yielded a form that promised to help reveal patterns not readily apparent with more typical visual interpretations of data (graphics). Silk spinning behavior mirrored music in many ways: the physical spin-steps are like finger-positions on a musical instrument, plotting the change from one spin-step to another over time emulates placing notes onto a written score of music, and the repetitive motifs in spin-steps resembles musical motifs, such as repeated melodies in a longer composition. In this presentation, I will describe the process of analyzing data as music, play recordings of musical motifs based on silk spinning behavior, and present results of an analysis using similar methods applied by musicologists to find patterns in data.