Scientists & Staff

Karin 11-2020

Karin Riley

Research Ecologist
5775 US Highway 10 W
Missoula, MT, 59808-9361
Phone: 406-329-4806

Contact Karin Riley


Current Research

Much of my current research focuses on better understanding the relationship between climate and wildfire, and how this relationship might shift with climate change. In addition, I am interested in how spatial planning can be utilized to inform fire and landscape management options.

Research Interests

Much of my current research focuses on better understanding the relationship between climate and wildfire, and how this relationship might shift with climate change. I also use machine learning algorithms to create tree-level models of US forests. In addition, I am interested in how spatial planning can be utilized to inform fire and landscape management options.

Why This Research is Important

Wildland fire has a dual nature. In fire-adapated ecosystems, fire is a natural process that maintains the health of the ecosystem. However, fires may also negatively impact highly valued resources such as homes, watersheds, and habitat, even costing human lives. We can leverage tools such as simulation models, machine learning, and statistical analysis to better understand our forests and wildland fires. In so doing, we can assist land managers in using fires to restore ecosystems where the opportunity exists and help to create ecosystems that will be resilient to climate change.

Education

  • University of Montana, Phd Geosciences, 2012
  • Humboldt State University, Master Of Science Environmental Systems, 2001
  • Harvard University, Bachelor Of Arts Earth and Planetary Science, 1996

Professional Experience

  • Research Ecologist, Forestry Sciences Lab, Rocky Mountain Research Station, Missoula, Montana 2015 - 2019
  • Research Ecologist, Fire Sciences Lab, Rocky Mountain Research Station, MIssoula, Montana

Professional Organizations

  • Association for Fire Ecology (2012 - Current)
    Inclusivity, Journal, and Conference
  • Fire Ecology
  • Association for Fire Ecology (2015 - 2019)

Featured Publications & Products

Publications & Products

National Research Highlights

A subset of the landscape in Montana’s Swan Valley (top panel). The lower panel shows the plot IDs for the best-matching plot for each pixel of the same landscape, with each color representing a unique plot. In the left half of the imagery, the landscape is dominated by a checkerboard pattern, the legacy of extensive timber harvest on private lands, and less extensive harvest on public lands. On the right side of the imagery, vegetation is dominated by topographic gradients in a mountainous landscape. The model was able to pick up these patterns, with the outline of the checkerboard visible in the left half of the lower panel, and the topographic gradients visible in the clustering of the plots on the right half of the panel. U.S. Department of Agriculture Forest Service.

A Tree Level Model of Forests in the Western United States

Year: 2016

Maps of the number, size, and species of trees in forests across the western U.S. are desirable for a number of applications including estimating terrestrial carbon resources, tree mortality following wildfires, and for forest inventory; however, detailed mapping of trees for large areas is not feasible with current technologies. Forest Service scientists used a statistical method called random forests for matching forest plot data with biophysical characteristics of the landscape to populate entire landscapes with a limited set of forest plot inventory data.

Last modified: Monday, May 18, 2020