Computational approaches to HD

We are interested in incorporating analytics to develop and apply innovative computational approaches to help inform management of natural resources. We have been developing new approaches to better understand wildlife-based recreators and conservationist behaviors.

Traditional surveys are often not able to capture all the information necessary to understand sportsperson participation, and high rates of surveying can lead to reduced response rates as sportspersons are burdened with continually answering multiple surveys. We are leading efforts to move beyond traditional approaches to use data mining techniques on data already available to natural resource organizations (i.e., license sales, stamp sales, magazine subscriptions, memberships) to better inform underlying patterns driving sportsperson behavior. This approach, which we have termed “computational human dimensions”, shows promise in answering many unresolved questions in human dimensions research.