This visual training aid is designed to provide Photoload users a tool to increase the accuracy of fuel loading estimations when using the Photoload technique. The Photoload Sampling Technique (RMRS-GTR-190) provides fire managers a sampling method for obtaining consistent, accurate, inexpensive, and quick estimates of fuel loading. It is designed to require only one hour of training, but the accuracy of the estimates can be increased with additional training and visual calibration. This training tool is designed to help users estimate loadings of the six common surface fuel components used in the Photoload method (1 hr, 10 hr, 100 hr, and 1000 hr downed, dead woody fuels and live and dead shrubs and herbaceous fuels). Users estimate the loadings of the fuels in the photographs in this document using the Photoload sampling technique and then compare their estimates to the actual loadings that are given on the page following each photograph. Each photograph set contains a photograph of the fuelbed, a photograph of the stand, and a table of laboratory measured loadings. The photographed fuelbeds are in both natural and disturbed sites.

Fire managers need better estimates of fuel loading so they can more accurately predict the potential fire behavior and effects of alternative fuel and ecosystem restoration treatments. This report presents a new fuel sampling method, called the photoload sampling technique, to quickly and accurately estimate loadings for six common surface fuel components (1 hr, 10 hr, 100 hr, and 1000 hr downed dead woody, shrub, and herbaceous fuels). This technique involves visually comparing fuel conditions in the field with photoload sequences to estimate fuel loadings. Photoload sequences are a series of downward-looking and close-up oblique photographs depicting a sequence of graduated fuel loadings of synthetic fuelbeds for each of the six fuel components. This report contains a set of photoload sequences that describe the range of fuel component loadings for common forest conditions in the northern Rocky Mountains of Montana, USA to estimate fuel loading in the field. A companion publication (RMRS-RP-61CD) details the methods used to create the photoload sequences and presents a comprehensive evaluation of the technique.

This report describes a new set of standard fire behavior fuel models for use with Rothermels surface fire spread model and the relationship of the new set to the original set of 13 fire behavior fuel models. To assist with transition to using the new fuel models, a fuel model selection guide, fuel model crosswalk, and set of fuel model photos are provided.

A new era in wildland fuel sciences is now evolving in such a way that fire scientists and managers need a comprehensive understanding of fuels ecology and science to fully understand fire effects and behavior on diverse ecosystem and landscape characteristics. This is a reference book on wildland fuel science; a book that describes fuels and their application in land management. There has never been a comprehensive book on wildland fuels; most wildland fuel information was put into wildland fire science and management books as separate chapters and sections. This book is the first to highlight wildland fuels and treat them as a natural resource rather than a fire behavior input. Moreover, there has never been a comprehensive description of fuels and their ecology, measurement, and description under one reference; most wildland fuel information is scattered across diverse and unrelated venues from combustion science to fire ecology to carbon dynamics. The literature and data for wildland fuel science has never been synthesized into one reference; most studies were done for diverse and unique objectives. This book is the first to link the disparate fields of ecology, wildland fire, and carbon to describe fuel science. This just deals with the science and ecology of wildland fuels, not fuels management. However, since expensive fuel treatments are being planned in fire dominated landscapes across the world to minimize fire damage to people, property and ecosystems, it is incredibly important that people understand wildland fuels to develop more effective fuel management activities.

This reference work encompasses the current, accepted state of the art in the science of wildfires and wildfires that spread to communities, known as wildland-urban interface (WUI) fires. 171 author contributions include accepted knowledge on these topics from throughout the world, all written by the leading researchers, experts, practitioners, and academics. This encyclopedia is an invaluable reference for newcomers to the field, as well as researchers, students, developers, and professionals who are interested in exploring this dynamic area. General Sections include: Combustion Coordination System Locations Fire Whirls Firebrands and Embers Incident Management Team (IMT) Support Locations Incident Response Support Locations On-the-Incident Locations Soot and Effects on Wildland/WUI Fire Behavior Weathering Effects on Fire Retardant Wood Treatments Wildland Firefighting Locations Wildland Fuel Treatments

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.