RoL:FELS:RAISE: Integrating Statistical Physics and Nonlinear Dynamics to Understand Emergent Synchrony and Phase Transitions in Biological Systems

点击翻译按钮获取中文摘要

This research will use ideas from statistical physics to examine the transitions to synchrony (events operating in unison) across space in biological systems. Tools in physics developed primarily to explain how magnetism arises at large scale from alignment at small scale will be employed to develop detail-independent explanations for the emergence of synchrony. The work aims to determine general rules that govern the propagation of information or changes in biological systems from short-range interactions to large scales, with an emphasis on ecological systems. Phenomena in this category range from synchrony across space of oscillations in predator and prey systems to synchrony in dynamics of neural activity in the brain. Synchrony is strongly linked to extinction risk, which may either be beneficial (as in epidemic burnout) or detrimental (as for threatened species). Similarly, synchronous neural dynamics may have large implications for human health. This work addresses several fundamental questions in the life sciences: What are general rules that determine patterns of synchrony in identical biological oscillators with nearest-neighbor coupling? How do heterogeneities and system size affect the rules governing the appearance and maintenance of synchrony in coupled biological oscillators? How do correlations in randomly-determined effects across space or time affect the appearance and maintenance of synchrony in coupled biological oscillators? The project will involve junior researchers at the undergraduate, graduate, and postdoctoral levels. The investigators plan to organize an interdisciplinary workshop that will include leading and junior researchers in ecology and physics as well as other areas of biology.This project aims to build upon previous research demonstrating that the transitions in the two-dimensional Ising model of theoretical physics map onto models of spatial population dynamics on a lattice and can be used to explain data for the yield of individual trees across space and time in a pistachio orchard. The goal of the project is to elucidate a detail-independent explanation for the synchrony across space that is prevalent at many scales of biological systems. However, real biological systems have significant heterogeneities, so this work aims both to build on extensions and modifications of the Ising model as well as to investigate other models. The work will depend on extensive simulations and analysis of models from statistical physics. The overall goal of finding detail-independent universal explanations of large-scale synchronous dynamics will advance understanding of ecological systems as well as a range of other biological systems.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.