Brian is a quantitative ecologist and population biologist who is interested in supporting good decisions in natural resource management. Brian’s work combines field research, quantitative methods, and structured-decision making skills to help understand how landscapes influence wildlife populations and support value-based wildlife management decisions in an inclusive and transparent framework. Brian has a B.S. in Biological Sciences (2011), a Ph.D. in Ecology from Auburn University (2017), and post-doctoral experience from the Alabama and Florida Cooperative Fish and Wildlife Research Units. Brian previously worked for the U.S. Geological Survey at the Fort Collins Science Center and Conservation Science Partners. At USGS, a key product he developed was PopEquus, a website application that can simulate wild horse populations and help understand trade-offs among management alternatives. Current research projects involve applied management problems related to ungulates, Mojave desert tortoises, and wild horses in the Great Basin ecoregion.
Nathan is a large mammal ecologist interested in population ecology and the effects of density dependence on movement, demography, population dynamics, and competition (intra- and interspecific). Nathan’s research leverages movement and demographic datasets to inform conservation and management decisions for large, herbivorous mammals. Nathan holds a B.S. in Natural Resources-Wildlife Conservation and Management from the University of Arizona (2013), and an M.S. (2019) and Ph.D. (2024) in Natural Resources and Environmental Science from the University of Nevada, Reno. Nathan’s current research is focused on migratory behavior of ungulates in the Great Basin. His current work is done in co-production with state (Nevada Department of Wildlife) and federal agencies (U.S. Geological Survey Corridor Mapping Team).
We are continuing to build out the lab and will be hiring graduate students to help with projects as they emerge. Check out funded student and post-doc opportunities are here!