The Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) simulates fuel dynamics and potential fire behavior over time, in the context of stand development and management. Existing models of fire behavior and fire effects were added to FVS to form this extension. New submodels representing snag and fuel dynamics were created to complete the linkages. This report contains four chapters. Chapter 1 states the purpose and chronicles some applications of the model. Chapter 2 details the model's content, documents links to the supporting science, and provides annotated examples of the outputs. Chapter 3 is a user's guide that presents options and examples of command usage. Chapter 4 describes how the model was customized for use in different regions. Fuel managers and silviculturists charged with managing fire-prone forests can use the FFEFVS and this document to better understand and display the consequences of alternative management actions.
The Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) simulates fuel dynamics and potential fire behavior over time, in the context of stand development and management. Existing models of fire behavior and fire effects were added to FVS to form this extension. New submodels representing snag and fuel dynamics were created to complete the linkages. This report contains four chapters. Chapter 1 states the purpose and chronicles some applications of the model. Chapter 2 details the model's content, documents links to the supporting science, and provides annotated examples of the outputs. Chapter 3 is a user's guide that presents options and examples of command usage. Chapter 4 describes how the model was customized for use in different regions. Fuel managers and silviculturists charged with managing fire-prone forests can use the FFEFVS and this document to better understand and display the consequences of alternative management actions.
The Forest Vegetation Simulator (FVS) is a suite of computer modeling tools for predicting the long-term effects of alternative forest management actions. FVS was developed in the early 1980s and is used throughout the United Sates and British Columbia. The Third FVS conference, held February 13-15, 2007, in Fort Collins Colorado, contains 20 papers. They describe the use of FVS on the stand and landscape scale, and to analyze fuels management in the presence of insects and fire. Several papers compare FVS predictions of the effects of insects and disease to field measurements. FVS is continually evolving and improving in technology and capability to meet the needs of its ever increasing user community. Papers describe new methods for data acquisition and preparation for input to FVS, new economic analysis capabilities within FVS, new methods for simulating forest regeneration, new developments in calculating growth and mortality, and future plans for incorporating the effects of climate change in model simulations.
New knowledge from wildlife-habitat relationship models is often difficult to implement in a management context. This can occur because researchers do not always consider whether managers have access to information about environmental covariates that permit the models to be applied. Moreover, ecosystem management requires knowledge about the condition of habitats over large geographic regions, whereas most research projects have limited spatial inference. For example, research has revealed much about the habitat of fishers (Martes pennanti) at various research sites in California, yet this work has not been translated into practical tools that managers can use to monitor fisher habitat regionally, or to evaluate and mitigate the effects of proposed forest management on fisher habitat. This led us to create new habitat models that are intimately linked to agency approaches to forest monitoring and software tools used by forest managers to plan timber harvests and vegetation management. We created habitat models that were integrated with these approaches and tools that forest managers use for two purposes: to inventory forest resources (i.e., Forest Inventory and Analysis [FIA] plots) and to simulate the response of stands to harvest, fire, insects, disease, and other disturbances (i.e., Forest Vegetation Simulator [FVS]). In this paper we provide an example of how to assess and monitor wildlife habitat using FIA vegetation monitoring protocols. We also provide an example of how to integrate an existing FIA-based model of fisher resting habitat into FVS, software that simulates the effect of alternative silvicultural treatments on vegetation data collected from field plots. Using these tools we produce quantitative predictions of the status of resting habitat quality for fishers, and describe how it can be monitored over time. We also provide an example of the effect of vegetation treatments on predicted fisher resting habitat, which illustrates a process that can be used to understand, reduce, or mitigate the effects of these activities on fisher habitat. This work on the fisher provides one example of how habitat assessments for wildlife could be advanced if they were developed with management applicability and implementation success as a goal.
