Upcoming Event: Oden Institute Seminar

Network Approaches in Spatial Ecology

Tim Keitt, Professor, UT Austin - Department of Integrative Biology

Abstract

Complexity in ecology emerges from processes that operating at multiple scales in time and space. This complexity can often be modeled in terms of networks that capture key relationships. A common theme in my lab over the past 20 years are network representations of spatial processes and linking these to population, community, and evolutionary dynamics. I will present several examples of this work, some primarily theoretical and others emphasizing theory-data fusion. Our recent work has modeled the invasion of North American waterways by the zebra mussel, an exotic pest introduced from Europe that has cause billions of dollars of damage to filtration systems. In developing this model, we asked: How can we estimate complex, latent spatial and demographic processes from sparse and noisy data? The answer illustrates the importance of leveraging theoretical knowledge of dynamics to constrain estimation problems.

Biography

Dr. Timothy Keitt grew up in North Florida, where he developed a passion for observing nature while tagging along on field trips with his father, an avid, life-long birder. He studied zoology as an undergraduate at the University of Florida and later received his PhD in ecology and evolutionary biology from the University of New Mexico. In graduate studies, he discovered a parallel passion for computer science, and has made his career combining these interests. He held postdoctoral fellow appointments at the Santa Fe Institute and the National Center for Ecological Analysis and Synthesis. The major question of his research is how environmental variation in time and space, manifest at multiple scales, influences the dynamics of populations, communities and ecosystems. To these ends, he employs mathematical and computer modeling, statics and field studies. Recent work includes field studies of bird populations responding to changing climate and landscape fragmentation, and the application of machine learning to environmental monitoring with sensor networks. He is a professor of Integrative Biology at the University of Texas at Austin, where he teaches ecological theory and field ornithology.