5775 US Highway 10 W
Contact Karin Riley
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.
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.
- 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
- Research Ecologist, Forestry Sciences Lab, Rocky Mountain Research Station, Missoula, Montana
2015 - 2019
- Research Ecologist, Fire Sciences Lab, Rocky Mountain Research Station, MIssoula, Montana
- Association for Fire Ecology, Board Member (2012 - Current)
- Fire Ecology, Associate Editor (2015 - )
- Association for Fire Ecology, Vice President (2015 - 2019)
Featured Publications & Products
- Riley, Karin L.; Williams, A. Park; Urbanski, Shawn P.; Calkin, David E.; Short, Karen C.; O’Connor, Christopher D. 2019. Will landscape fire increase in the future A systems approach to climate, fire, fuel, and human drivers.
- Riley, Karin L.; Thompson, Matthew P.; Scott, Joe H.; Gilbertson-Day, Julie W. 2018. A model-based framework to evaluate alternative wildfire suppression strategies.
- Thompson, Matthew P.; Riley, Karin L.; Loeffler, Dan; Haas, Jessica R. 2017. Modeling fuel treatment leverage: Encounter rates, risk reduction, and suppression cost impacts.
- Riley, Karin L.; Loehman, Rachel A. 2016. Mid-21st- century climate changes increase predicted fire occurrence and fire season length, Northern Rocky Mountains, United States.
- Riley, Karin; Grenfell, Isaac C.; Finney, Mark A. 2016. Mapping forest vegetation for the western United States using modified random forests imputation of FIA forest plots.
- Loehman, Rachel A.; Reinhardt, Elizabeth; Riley, Karin L. 2014. Wildland fire emissions, carbon, and climate: Seeing the forest and the trees - A cross-scale assessment of wildfire and carbon dynamics in fire-prone, forested ecosystems.
- Riley, Karin L.; Abatzoglou, John T.; Grenfell, Isaac C.; Klene, Anna E.; Heinsch, Faith Ann. 2013. The relationship of large fire occurrence with drought and fire danger indices in the western USA, 1984-2008: The role of temporal scale.
- Preisler, Haiganoush K.; Riley, Karin L.; Stonesifer, Crystal S.; Calkin, Dave E.; Jolly, Matt. 2016. Near-term probabilistic forecast of significant wildfire events for the Western United States.
- Riley, Karin; Thompson, Matthew. 2017. An uncertainty analysis of wildfire modeling Chapter 13.
- Finney, Mark A.; McHugh, Charles W.; Grenfell, Isaac C.; Riley, Karin L.; Short, Karen C. 2011. A simulation of probabilistic wildfire risk components for the continental United States.
- Steelman, Toddi ; Riley, Karin . 2018. #MeToo for the wildfire community.
- Hyde, Kevin D.; Riley, Karin; Stoof, Cathelijne. 2017. Uncertainties in predicting debris flow hazards following wildfire Chapter 19.
- Riley, Karin; Thompson, Matthew; Webley, Peter; Hyde, Kevin D. 2017. Uncertainty in natural hazards, modeling and decision support: An introduction to this volume Chapter 1.
- Littell, Jeremy S.; Peterson, David L.; Riley, Karin L.; Liu, Yongqiang; Luce, Charlie H. 2016. A review of the relationships between drought and forest fire in the United States.
- Littell, Jeremy S.; Peterson, David L.; Riley, Karin L.; Liu, Yongqiang; Luce, Charles H. 2016. Fire and drought Chapter 7.
- Riley, Karin; Stonesifer, Crystal; Calkin, Dave; Preisler, Haiganoush. 2015. Assessing predictive services' 7-day fire potential outlook.
- Keane, Robert E.; Jolly, Matt; Parsons, Russell; Riley, Karin. 2015. Proceedings of the large wildland fires conference; May 19-23, 2014; Missoula, MT.
- Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A. 2015. Seeing the forest for the trees: utilizing modified random forests imputation of forest plot data for landscape-level analyses.
- Riley, Karin L.; Stonesifer, Crystal; Preisler, Haiganoush; Calkin, Dave. 2014. Predicting wildfire ignitions, escapes, and large fire activity using Predictive Service s 7-Day Fire Potential Outlook in the western USA.
- Riley, Karin L.; Grenfell, Isaac C.; Finney, Mark A.; Crookston, Nicholas L. 2014. Utilizing random forests imputation of forest plot data for landscape-level wildfire analyses.
- Woodall, Christopher W.; Domke, Grant M.; Riley, Karin L.; Oswalt, Christopher M.; Crocker, Susan J.; Yohe, Gary W. 2013. A framework for assessing global change risks to forest carbon stocks in the United States.
- Calkin, David E.; Ager, Alan A.; Thompson, Matthew P.; Finney, Mark A.; Lee, Danny C.; Quigley, Thomas M.; McHugh, Charles W.; Riley, Karin L.; Gilbertson-Day, Julie M. 2011. A comparative risk assessment framework for wildland fire management: the 2010 cohesive strategy science report.
- Finney, Mark A.; McHugh, Charles W.; Grenfell, Isaac; Riley, Karin L. 2010. Continental-scale simulation of burn probabilities, flame lengths, and fire size distribution for the United States.
|A Tree Level Model of Forests in the Western United States|
Maps of the number, size, and species of trees in forests across the western U.S. are desirable for a number of applications including estimatin ...