Incorporating Structured Decision Making and Alternative Sources of Data into Management of White-tailed Deer in Georgia
July 2019 - June 2022
- Clinton Moore, Co-Principal Investigator
- Gino D'Angelo, Principal Investigator
- B Boley, Co-Principal Investigator
- Amanda Van Buskirk, Student / Post Doc
- Georgia Department of Natural Resources
In Georgia, the management of deer populations across the state is challenging because of regional variation in landscapes, deer population status, property ownerships, and other factors. Sources of harvest data available to the state of Georgia primarily through self-reporting mechanisms are potentially usable for providing harvest management decision support, but these data sources have unknown biases. We will investigate the utility of these data sources under a structured decision making framework, which establishes the context for the types of data needed to support harvest decision making and their required degree of quality. This approach will help to identify analytical processes or ancillary data sources that protect the quality of decisions from influence of sampling and self-reporting biases. This work is being performed in a collaboration between the University of Georgia and the Georgia Department of Natural Resources. The research will result in recommendation of one or more candidate harvest decision support frameworks that address the goals of stakeholders and that identify priorities for the collection of data most useful for guiding management.