Federal land managers need an adaptive management framework to accommodate changing conditions and that allows them to effectively link the appropriate science to natural resource management decision-making across jurisdictional boundaries. FRAME-SIMPPLLE is a collaborative modeling process designed to accomplish this goal by coupling the adaptive capabilities of the SIMPPLLE modeling system with accepted principles of collaboration. The two essential components of the process are FRAME (Framing Research in support of the Adaptive Management of Ecosystems), which creates a collaborative problem-solving environment, and SIMPPLLE (SIMulating Patterns and Processes at Landscape Scales), which is a vegetation dynamics modeling system. The resulting collaborative modeling process allows decision makers to optimize the management of multiple resources and evaluate the likely outcome of various choices. The approach involves collaboratively engaging resource managers, modelers, and scientists in framing the science issues embedded in key natural resource management issues and then developing the SIMPPLLE modeling approach to address those issues. Through a prototype collaborative modeling effort at Mesa Verde National Park, a process has been developed for adaptive, multi-objective resource management. What is needed now is an effort to refine the approach and establish a transportable methodology that is applicable across a wide range of ecosystems. In the Northern Rockies, managers have expressed an interest in exploring this approach at Glacier National Park, the Crown of the Continent Ecosystem, and the Rocky Mountain Front. This project utilized and evaluated the FRAME-SIMPPLLE approach to (1) explore adaptive management for climate and landscape change in the Northern Rockies, (2) recommend how to foster the long-term development of such collaborative planning tools as a joint effort between the USGS and the Institute of the Environment; (3) develop graduate student mentoring opportunities focused on collaborative planning and adaptive management science, and (4) investigate the use of GIS to further landscape science and conservation, especially related to energy development.