Computational Behavioral Ecology

Abstract

Computation has fundamentally changed the way we study nature, from molecules to ecosystems. Recent advances in data collection technology, such as GPS and other mobile sensors, high definition cameras, satellite images, and genotyping, are giving biologists access to data about the natural world which are orders of magnitude richer than any previously collected. Such data offer the promise of answering some of the big questions about why animals do what they do, among other things. Unfortunately, in the domain of behavioral ecology and population dynamics, our ability to analyze data lags substantially behind our ability to collect it. In this talk I will show how computational approaches can be part of every stage of the scientific process of understanding animal sociality, from data collection (identifying individual animals from photographs by stripes and spots) to hypothesis formulation (by designing a novel computational framework for analysis of dynamic social networks).