Overview: Social insect colonies show a decentralized system of the division of labor and its related task allocation. Both are resulting from multi-level interactions among members of the colony and between the colony and the environment, as the size of colony increases. Social insect biologists face the challenge of integrating the individual and colony levels of organization. Mathematical models have begun to show how colony-level patterns of division of labor result from simple individual behavioral rules. However, these models do not integrate the dierent levels of interactions in a colony nor do they consider the in uence of a dynamically changing environment. In addition they lack validation and parameterization through data. Intellectual Merit: The goal of this collaborative research is to develop a general integrated multi-scale dynamical network modeling framework for social insects. Rigorous mathematics will be integrated with extensiveeld and laboratory data to study the complex adaptive system of social insect societies. We will explore: 1. How the underlying topology of the interaction network of a colony evolves and adapts at dierent scales of the organization; 2. How to characterizes the crucial feedback mechanisms linking both structure and dynamics of the division of labor in a dy- namical environment and 3. How the decentralized social insect system based on many independent and simple individual interactions leads to highly complex dynamics with great network properties such as scalability, robustness/ exibility and simplicity. We will use nonlinear dierential equa- tions, spatial stochastic processes and kinetic equations to model at the colony level, the individual level and at a spatial and task continuum level, respectively. Dynamical systems concepts will be applied to ODEs, DDEs, PDEs to investigate the dynamics of the resulting multi-scale dynamical network models. The collaboration between the PIs represents a strong team eort with individual backgrounds in mathematics, behavioral ecology and social insect biology and a track record for transdisciplinary research. Broader Impacts: This research project lives at the intersection of social science, life sciences and applied mathematics. Our modeling framework of social insects provides not only a powerful sys- tem for examining how network dynamics contribute to the evolution of complex biological systems but also a great opportunity to explore how behavior evolves within complex systems in general. The methods developed may apply in many domains outside of biology, including network routing, optimization theory and robotics. We will develop a template to integrate interdisciplinary learning for social sciences students, life sciences students and applied mathematics students through shared research projects at the undergraduate and/or graduate student level. In addition, summer research projects will be connected to the Mathematical and Theoretical Biology Institute directed by Pro- fessor Castillo-Chavez providing minority students with arst-hand research experience. Suitable research projects will be integrated into a new undergraduate mathematical biology course that contributes to the establishment of new math major/minor at ASU, Polytechnic Campus. The PIs will give lectures related to their research in the student camp to promote careers in STEM among young women and the educator camp Bridging Science& Fun thru Biology and Math for high school teachers.
Effective start/end date9/15/138/31/17


social insects
research projects
insect colonies
Biological Sciences
social sciences
college students
insect biology
cooperative research
high schools
stochastic processes
mathematical models