Meeting Abstract
In honey bees, a worker bee that returns from a foraging trip will indicate to her nestmates in the hive where she has found food by performing a stereotypical behavior, the waggle dance. In this waggle dance bees encode the direction and the distance to the food source. Researchers can eavesdrop on these dances, extract the vectors from hive to food resource, and assess the landscape for its ability to feed pollinators. In other words, we can use bees as bioindicators for landscape health. Up to now, researchers have decoded these dances by hand from video. However, recently a group in Japan (Okubo et al. (2019) Apidiolgie 50:243–252) has published a method for decoding dances from video automatically using particle image velocimetry (PIV). This method of dance decoding has the potential to use waggle dance data on a large scale. Unfortunately, the researchers used proprietary software for the PIV. Here we show how we re-implemented the method using free and open software. Our implementation using OpenPIV and Okubo et al.‘s scripts works well at identifying waggle runs from video recorded waggle dances. Furthermore, we show that the automatically decoded waggle runs are largely concordant with the gold-standard of manually extracting the vector information. This open and free implementation should provide a useful resource for researchers studying bee foraging.
