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Key Findings and Messages from the Go Big or Go Home? Project

Year of Publication
2018
Publication Type

About Go Big or Go Home?: The goals of this research project were to analyze how public land managers and stakeholders in Oregon’s east Cascades can plan and manage at landscape scales using scientific research and participatory simulation modeling (Envision). To learn more, visit: gbgh.forestry.oregonstate.edu

Forest Service Managers' Perception of Landscapes and Computer Models

Year of Publication
2018
Publication Type

About Go Big or Go Home?: The goals of this research project were to analyze how public land managers and stakeholders in Oregon’s east Cascades can plan and manage at landscape scales using scientific research and participatory simulation modeling (Envision). To learn more, visit: gbgh.forestry.oregonstate.edu

Policy Scenarios for fire-adapted communities: Understanding stakeholder risk-perceptions, using Fuzzy Cognitive Maps

Year of Publication
2017
Publication Type

Collaborative groups are most effective when the varied stakeholder groups within them understand the risks of wildfire and take proactive steps to manage these risks. Implementing policies for fire risk mitigation and adaptation, however, remains difficult because risks and policy alternatives are not understood or supported uniformly across diverse stakeholders.

The Fire Weather Accuracy and Lightning Ignition Probability System

Year of Publication
2015
Publication Type

Weather forecasts can help identify environmental conditions conducive to prescribed burning or to increased fire danger. These conditions are important components of fire management tools such as fire ignition potential maps, fire danger rating systems, fire behavior predictions, and smoke dispersion modeling.

Developing a post-processor to link the Forest Vegetation Simulator (FVS) and the Fuel Characteristic Classification System (FCCS)

Year of Publication
2015
Publication Type

In this project, we developed a Forest Vegetation Simulator (FVS, JFSP Project #) post-processor (FVS2FCCS) to convert FVS simulated treelist and surface fuel data into Fuel Characteristics Classification System (FCCS, JFSP Project #98-1-1-06) fuelbed format (.xml) that can be read and processed by the FCCS to create estimates of surface fire behavior, including reaction intensity (Btu ft-2 min

Latent resilience in ponderosa pine forest: effects of resumed frequent fire

Year of Publication
2013
Publication Type

Ecological systems often exhibit resilient states that are maintained through negative feedbacks. In ponderosa pine forests, fire historically represented the negative feedback mechanism that maintained ecosystem resilience; fire exclusion reduced that resilience, predisposing the transition to an alternative ecosystem state upon reintroduction of fire.