CAREER: Myco-fluidics -- Mathematics at the interface of fluid dynamics and fungal biology

University Of California-Los Angeles, Los Angeles CA

Investigators

Abstract

This project combines mathematical modeling and physical experiments to study the dispersal and growth of fungi and to predict how fungi will respond to our changing Earth. The mathematical work in this project includes probability theory, optimization, dynamical systems, fluid mechanics, and the synthesis of new models. The central biological questions addressed are: (i) How do adaptive fungal networks form and how are they optimized for mixing and transport? (ii) How does the flow in these networks self-organize to eliminate congestion? (iii) What adaptations are used by fungi to control their spore dispersal? This project will develop interdisciplinary teaching and research methods connecting physics, genetics and the environment. Teaching and research are integrated through the interdisciplinary training of graduate and undergraduate students in mathematics and biology. New undergraduate mathematical modeling seminars and classes that emphasize societal impacts will be developed. Undergraduate researchers will be mentored to make key research contributions. Humans, mammals, fish, reptiles and plants represent only a razor's edge of the Earth's immense biodiversity. Most of the Earth's multicellular species are undescribed and lie inside of plants or buried in the soil and undergrowth. Millions of these undescribed species are thought to be fungi. Increasing our knowledge of these species is important because emerging fungal diseases pose a danger to society by threatening our forests, crops and wildlife. This project will provide mechanistic models of adaptation in fungal networks and the physical processes involved in fungal dispersal. These models will provide a platform for predicting which fungi are capable of adapting and dispersing into new habitats and the rate at which they will do so. The discovered strategies used by fungal transport networks can be applied to scheduling problems in a variety of other settings such as traffic or data networks.