Meeting Abstract
Although social structures vary spatially and temporally, traditional sampling approaches are often unable to fully capture this heterogeneity. In this study, we integrate recent technological advances in network theory and automated data loggers to reveal the dynamics of spatial associations in free-living California ground squirrels (Otospermophilus beecheyi). O. beecheyi are facultatively social rodents that forage above ground, but rest and seek refuge from predators in below-ground burrow systems. As part of a long-term study, we regularly live trapped and released O. beecheyi at our field site in northern California. Upon first capture of each individual, we inserted a Passive Integrated Transponder (PIT) tag beneath its skin. This tag provides a reliable lifetime ‘barcode’ for permanent identification. Here we deployed automated sensors to monitor each time a squirrel passed through a burrow entrance. Specifically, PIT tag readers (antenna loops) were placed inside of each burrow entrance. Data loggers were deployed at two distinct locations at the study site and recorded movements continuously for almost a year. Readers logged movements of individual squirrels (as presence-absence events) at a temporal resolution of one minute. Social network analysis of these data revealed that spatial associations vary across multiple temporal scales (e.g., hour to hour, day to day, month to month). Our results therefore uncover short and long-term dynamics of spatial associations within these free-living mammals. These data have important implications for understanding disease, parasite and information transmission across spatially and temporally dynamic networks.
