Research to Advance Conservation

Large Carnivore
Habitat Connectivity

An urgent conservation challenge for large carnivores is identification of connectivity areas among isolated populations, and proactive efforts to reduce the potential for conflicts with humans. This is especially true for grizzly bears in the continental US. We are modeling grizzly bear movement, home ranges, range expansion, and population connectivity to meet critical conservation challenges for this iconic threatened species.

Mechanisms Driving
Spatial Behavior

Territorial behavior is a fundamental and conspicuous behavior within numerous species, but the mechanisms driving territory selection remain uncertain. We developed a mechanistic territory model that is spatially-explicit and individual-based to better understand how animals select particular territories. Application to wolves show that economical territory selection underlies wolf spatial behavior.

Large Carnivore

Estimates of carnivore abundance are an important component of conservation. For group-living, territorial carnivores, integrated models for occupancy, territories, and group size can help estimate abundance. Our approach eliminates the need for intensive field-based monitoring and introduces biological models of carnivore behavior. Application to wolves show an estimated population of >1100 wolves in Montana.

Disease Epizootics
in Sensitive Species

Diseases in wild populations are of great conservation concern. A lack of tools to help predict and proactively address risk of disease leads to reactive rather than proactive management. For example, pneumonia epizootics have immense short- and long-term impacts on bighorn sheep. Models can identify risk factors to help predict risk of die-offs, and supporting decision tools can proactively manage this risk in effort to prevent die-offs.

Decision Analysis
for Wildlife Conservation

Good decision-making is challenging but essential for wildlife conservation. Decisions in wildlife management must integrate values with science to achieve desired future conditions. Structured decision making (SDM) is a decision analytic method that breaks decision-making into logical components. Our collaborations frequently entail SDM, including for bighorn sheep, mountain goats, and mountain lions.

Rigorous Science
for Wildlife Conservation

Rigorous science that produces reliable knowledge is critical to wildlife management because it increases accurate understanding of the natural world and informs management decisions. The prevalence of studies that only generate untested hypotheses may be considered one of wildlife science’s major problems. Remedying this problem requires a common understanding of what rigorous science entails and why it is important.