Current Research in Evolutionary Sociobiology

Our lab is interested in self-organizing systems and the complexity of emergent social systems governed by individual behavior. We use mathematical modeling to investigate possible mechanisms for the evolution of sociality. Additionally, we work to characterize traits which increase both the success and stability of organizational structures and strategies, especially those that make populations best able to survive group-level threats, such as those posed by epidemics.

Our interests in sociobiology are primarily focused on the evolution of sociality and social complexity.

1. Understanding the evolution and maintenance of observed behaviors in real-world systems: These interests focus empirically on social insects and to understand what real-world experiments tell us about these systems we use tools from game theory, linear programming, optimization theory, and dynamical systems.
2. Abstract and theoretical characterizations of the evolution and maintenance of social complexity: Rather than focusing on particular systems, we are interested in general principles of self-organization and distributed decision making under evolutionary pressures (especially from disease risks). We use simulation methods and agent based models in addition to analytic game theory, complexity theory, and analytic network theory to explore how group-level outcomes can be built by evolutionary variation in traits and selective pressure acting on individual fitness.

Related Publications

How disease constrains the evolution of social systems. Udiani, O. and N.H. Fefferman. 2020. Proceedings of the Royal Society B. 287(1932):20201284.

How Emergent Social Patterns in Allogrooming Combat Parasitic Infections Wilson, S.N., S.S. Sindi, H.Z. Brooks, M.E. Hohn, C.R. Price, A.E. Radunskaya, N.D. Williams, and N.H. Fefferman. 2020. Frontiers in Ecology and Evolution. 8:54.

Propinquity drives the emergence of network structure and density. Gallos, L., S. Havlin, G. Stanley, and N.H. Fefferman. 2019. Proceedings of the National Academy of Sciences. 116(41):20360-20365.

How Disease Risks Can Impact the Evolution of Social Behaviors and Emergent Population Organization. Williams, N.D., H.Z. Brooks, M.E. Hohn, C. R. Price, A.E. Radunskaya, S.S. Sindi, S.N. Wilson, and N. H. Fefferman. 2018. in Understanding Complex Biological Systems with Mathematics eds. A. Radunskaya, R. Segal, B. Shtylla. Association for Women in Mathematics Series, vol 14. pp 31-46. Springer.

Expanding the evolutionary theory of aging: honeybees as a test case for an optimal decision making model of senescence. Lemanski, N.J. and N.H. Fefferman. 2018. American Naturalist. 191(6):756-766.

Coordination Between the Sexes Constrains the Optimization of Reproductive Timing in Honey Bee Colonies. Lemanski, N.J. and N.H. Fefferman. 2017. Nature Scientific Reports. 7:2740.

Application of network methods for understanding evolutionary dynamics in discrete habitat. Greenbaum, G. and N.H. Fefferman. 2017. Molecular Ecology. DOI: 10.1111/mec.14059.

Simple and efficient self-healing strategy for damaged complex networks. Gallos, L. and N.H. Fefferman. 2015. Physical Reviews E. 92(5):052806.

Higher-Order Interactions: Understanding the knowledge capacity of social groups using simplicial sets. Greening, B., N. Pinter-Wollman, and N.H. Fefferman. 2015. Current Zoology. 61(1): 114–127.

Evolutionary Significance of the Role of Family Units in a Broader Social System. Greening, B. and N.H. Fefferman. 2014. Nature Scientific Reports. 4: 3608.

Revealing effective classifiers through network comparison. Gallos, L. and N.H. Fefferman. 2014. Europhysics Letters 108(3): 38001.

Strategic Mortgage Default in the Context of a Social Network: An Epidemiological Approach. Seiler, M.J., Collins, A.J., and N.H. Fefferman. Journal of Real Estate Research.

Social organization patterns can lower disease risk without associated disease avoidance or immunity. Hock, K. and N.H. Fefferman. 2012. Ecological Complexity. 12:34–42.

Violating Social Norms when Choosing Friends: How Rule-Breakers Affect Social Networks. Hock, K. and N.H. Fefferman. 2011. PLoS ONE.6(10):e26652.doi:10.1371/journal.pone.0026652

Extending the role of social networks to study social organization and interaction structure of animal groups. Hock, K. and N.H. Fefferman. 2011. Annales Zoologici Fennici. 48(6):365–370.

A Systems Approach to Studying Animal Sociality: Individual Position versus Group Organization in Dynamic Social Network Models Hock, K., K.L. Ng, and N.H. Fefferman. 2010. PLoS ONE. 5(12): e15789. doi:10.1371/journal.pone.0015789

The role of individual choice in the evolution of social complexity Fefferman, N.H. and K.L Ng. 2007. The role of individual choice in the evolution of social complexity. Annales Zoologici Fennici, 44:58-69.

Polistes Nest Founding Behavior: a Model for the Selective Maintenance of Alternative Behavioral Phenotypes Starks, P.T.B. and N.H. Fefferman. 2006. Polistes Nest Founding Behavior: a Model for the Selective Maintenance of Alternative Behavioral Phenotypes. Annales Zoologici Fennici, 43:456-467.

A Modeling Approach to Swarming in Honey Bees Fefferman, N.H., and P.T.B. Starks. 2006. A Modeling Approach to Swarming in Honey Bees. Insectes Sociaux, 53(1):37-45.