The Rocky Mountain Research Work Unit 4151 provides knowledge and guidelines required to sustain ecosystem integrity, improve forest health, and enhance social values in the Central and Northern Rocky Mountains, including Montana, east-central Idaho, northwest Wyoming, and northern Utah.
ONGOING STUDIES
Biocontrol & Weeds
Biological control in managing noxious weed invasions in western forests of the U.S, in cooperation with Switzerland, France, Republic of Georgia, Bulgaria and Ukraine
Lodgepole Pine Research
Long-term study of lodgepole pine stands on the Tenderfoot Creek Experimental Forest, typical fire-prone forest in Northern Rocky Mountains
Riparian Research
Determine how changes in riparian plant species composition have altered ecosystem dynamics
Tree Physiology
Determine effects of management treatments and interruption of natural disturbance processes on forest physical and chemical process dynamics (e.g., water, nitrogen, carbon)
Selected Research
RM-4151 scientists are actively involved in the development of scientific knowledge to support natural resource management. Partnerships with universities, state and federal agencies are an integral component of this research.
Key Clients/Collaborators
National Forests in Montana and Idaho, University of Montana, Montana State University, Forest Health Management, Region 1; USDA FS Air Resource Managers, Bureau of Land Management, Switzerland, France, Republic of Georgia, Bulgaria and Ukraine.
Whitebark Pine Research
Understanding the natural regeneration process and how fire may be used to return whitebark pine communities to earlier successional stages
Western Larch Research
Research for managing the valuable western larch species on the Coram Experimental Forest, established in 1933
DECISION MAKING TOOLS
Landscape-scale Modeling
SIMPPLLE is a software application created by RM-4151 designed to simulate patterns and processes at landscape scales. This spatially explicit, object-oriented modeling approach integrates various levels of knowledge, and ultimately facilitates an understanding of landscape dynamics through time. Multiple simulations can provide a prediction of general trends for processes on a specific landscape.
![[Photograph]: Seasonal image of Montana.](rm/ecology/common/images/front_cover/spring.jpg)
