NSF Postdoctoral Fellowship in Biology FY 2010

Wey Tina W, Los Angeles CA

Investigators

Abstract

This action funds an NSF Postdoctoral Research Fellowship for FY 2010. The fellowship supports a research and training plan entitled "Network and statistical analyses of animal social complexity" for Tina Wey. The host institution for this research is University of California Davis and the sponsoring scientist is Dr. Andy Sih. Social structure, the pattern of social interaction among members of a group, is thought to play an important role in determining how individual traits influence mating success. However, a comprehensive understanding of how social structure influences mating success is lacking. Social network analysis offers a quantitative approach to measuring complex patterns of interaction. This project uses a large behavioral dataset on experimentally manipulated, replicated social groups of stream water striders (Aquarius remigis) to examine the effect of social network structure on mating success. Specifically, the project addresses the following questions: 1) What are the relative effects of social network traits at multiple stages on mating success? 2) How does group network structure emerge from individual traits and influence reproductive success? 3) How do network dynamics influence mating success, and how do individuals respond to network change? 4) How does environmental variation alter the relationship between network structure and individual success? This work addresses properties of real systems (complex interactions at multiple levels and temporal dynamics) that have been difficult to analyze and is producing a predictive framework and analytical methodology that can be broadly applied to many social systems. Training objectives include developing skills in network and statistical analysis, computer programming, and scientific outreach. Project goals include developing and disseminating new analytical tools needed to study animal social complexity, while fostering interdisciplinary collaboration between experts in behavioral ecology, network analysis, and statistics. This project advances our understanding of mating success, social complexity and evolution. Expected outcomes include a workshop and free online tutorial designed to teach behavioral ecologists basic social network analysis that can be applied to diverse questions and systems.