The social, demographic and cognitive features of bottlenose dolphins (Tursiops sp.) show remarkable parallels with primates, offering a powerful method for examining how large brains, extensive maternal care, behavioral flexibility and prolonged developmental periods evolved. In this project the investigators examine the social and ecological factors related to dolphin female reproduction and development using innovative techniques in both computer modeling and biological sampling. The investigators will examine what factors contribute to female calving success, why dolphins have such a long juvenile period, and what patterns of information (cultural) transmission in the population favor such behavioral plasticity. They have also initiated a study that involves collecting blow samples (fluid exhaled from the blowhole) and have already extracted DNA from blow. These samples will also be used for hormone and fatty acid assays, opening up exciting new avenues for the non-invasive study of reproduction, stress, maturation and diet. The attributes of the project include: (1) the size and unprecedented detail of the 25-year longitudinal dataset; (2) the creation of an extensive integrated relational database with a web platform; (3) the computational modeling for analyzing complex multi-dimensional associations in the context of a large social network; (4) the natural variation in social, ecological, and reproductive parameters; (5) the new direction in developing non-invasive biological sampling techniques; and (6) the scientific value of studying a species on par with primates. The inter-disciplinary nature of this collaboration will foster innovation and intellectual exchange across multiple disciplines, advancing our understanding of complex animal societies. The project supports five graduate and approximately 22 undergraduate students from Biology and Computer Science. The database will be broadly accessible through our website and will serve as an educational tool and as a foundation for design of similar long-term data warehouses. Thus, the next generation biologists will be better equipped to integrate computer science approaches and database technology.
