Whether ignited by lightning or by Native Americans, fire once shaped many North American ecosystems. Euro-American settlement and 20th-century fire suppression practices drastically altered historic fire regimes, leading to excessive fuel accumulation and uncharacteristically severe wildfires in some areas and diminished flammability resulting from shifts to more fire-sensitive forest species in others. Prescribed fire is a valuable tool for fuel management and ecosystem restoration, but the practice is fraught with controversy and uncertainty. Here, we summarize fire use in the forests and woodlands of North America and the current state of the practice, and explore challenges associated with the use of prescribed fire. Although new scientific knowledge has reduced barriers to prescribed burning, societal aversion to risk often trumps known, long-term ecological benefits. Broader implementation of prescribed burning and strategic management of wildfires in fire-dependent ecosystems will require improved integration of science, policy, and management, and greater societal acceptance through education and public involvement in land-management issues.

https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.1890/120329

Prescribed fire in North American forests and woodlands: history, current practice, and challenges

In recent years, advances in computational power have led to an increase in attempts to model the behaviour of wildland fires and to simulate their spread across landscape. The present series of articles endeavours to comprehensively survey and precis all types of surface fire spread models developed during the period 1990–2007. The present paper surveys models of a simulation or mathematical analogue nature. Most simulation models are implementations of existing empirical or quasi-empirical models and their primary function is to convert these generally one-dimensional models to two dimensions and then simulate the propagation of a fire perimeter across a modelled landscape. Mathematical analogue models are those that are based on some mathematical concept (rather than a physical representation of fire spread) that coincidentally represents the spread of fire. Other papers in the series survey models of a physical or quasi-physical nature, and empirical or quasi-empirical nature. Many models are extensions or refinements of models developed before 1990. Where this is the case, these models are also discussed but much less comprehensively.

Wildland surface fire spread modelling, 1990–2007. 3: Simulation and mathematical analogue models

Every year worldwide some extraordinary wildfires occur, overwhelming suppression capabilities, causing substantial damages, and often resulting in fatalities. Given their increasing frequency, there is a debate about how to address these wildfires with significant social impacts, but there is no agreement upon terminology to describe them. The concept of extreme wildfire event (EWE) has emerged to bring some coherence on this kind of events. It is increasingly used, often as a synonym of other terms related to wildfires of high intensity and size, but its definition remains elusive. The goal of this paper is to go beyond drawing on distinct disciplinary perspectives to develop a holistic view of EWE as a social-ecological phenomenon. Based on literature review and using a transdisciplinary approach, this paper proposes a definition of EWE as a process and an outcome. Considering the lack of a consistent “scale of gravity” to leverage extreme wildfire events such as in natural hazards (e.g., tornados, hurricanes and earthquakes) we present a proposal of wildfire classification with seven categories based on measurable fire spread and behavior parameters and suppression difficulty. The categories 5 to 7 are labeled as EWE.

/pdf/defining-extreme-wildfire-events-difficulties-challenges-and-24i8xxa7jx.pdf

Defining Extreme Wildfire Events: Difficulties, Challenges, and Impacts

Innovations in machine learning and cloud-based computing were merged with historical remote sensing and field data to provide the first moderate resolution, annual, percent cover maps of plant functional types across rangeland ecosystems to effectively and efficiently respond to pressing challenges facing conservation of biodiversity and ecosystem services. We utilized the historical Landsat satellite record, gridded meteorology, abiotic land surface data, and over 30,000 field plots within a Random Forests model to predict per-pixel percent cover of annual forbs and grasses, perennial forbs and grasses, shrubs, and bare ground over the western United States from 1984 to 2017. Results were validated using three independent collections of plot-level measurements, and resulting maps display land cover variation in response to changes in climate, disturbance, and management. The maps, which will be updated annually at the end of each year, provide exciting opportunities to expand and improve rangeland conservation, monitoring, and management. The data open new doors for scientific investigation at an unprecedented blend of temporal fidelity, spatial resolution, and geographic scale.

Innovation in rangeland monitoring: annual, 30 m, plant functional type percent cover maps for U.S. rangelands, 1984–2017

The Monitoring Trends in Burn Severity project is a comprehensive fire atlas for the United States that includesperimetersandseveritydataforallfiresgreaterthanaparticularsize(,400hainthewesternUS,and,200hain the eastern US). Although the database was derived for management purposes, the scientific community has expressed interest in its research capacity. As with any derived data, it is critical to understand inherent limitations to maximise the utility of the dataset without compromising the inferences. The classified severity product in particular is of limited use to research due to a lack of both consistency in developing class thresholds and empirical relationships with ecological metrics. Here we review the products available and their development process, and characterise and quantify the limitations of the classified burn severity data product based on the use of highly variable and subjective classification thresholds. We suggest a framework for overcoming these limitations by developing a more robust classified product that will support ecological management and applications. This framework utilises field data to develop consistent, ecologically based thresholds that incorporate existing ecoregion classifications from LANDFIRE or other fire management frameworks already widely integrated into planning efforts. Additional keywords: dNBR, Landsat, MTBS, RdNBR.

/pdf/limitations-and-utilisation-of-monitoring-trends-in-burn-2ljsnimxvh.pdf

Limitations and utilisation of Monitoring Trends in Burn Severity products for assessing wildfire severity in the USA

A new decision support tool, the Wildland Fire Decision Support System (WFDSS) has been developed to support risk-informed decision-making for individual fires in the United States. WFDSS accesses national weather data and forecasts, fire behavior prediction, economic assessment, smoke management assessment, and landscape databases to efficiently formulate and apply information to the decision making process. Risk-informed decision-making is becoming increasingly important as a means of improving fire management and offers substantial opportunities to benefit natural and community resource protection, management response effectiveness, firefighter resource use and exposure, and, possibly, suppression costs. This paper reviews the development, structure, and function of WFDSS, and how it contributes to increased flexibility and agility in decision making, leading to improved fire management program effectiveness.

/pdf/developing-the-us-wildland-fire-decision-support-system-89inu92dne.pdf

Developing the US Wildland Fire Decision Support System

https://www.fs.fed.us/rm/pubs_other/rmrs_2013_ryan_k001.pdf

LANDFIRE - A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning

There is currently no spatial wildfi re spread and growth simulation model used commonly across New Zealand or Australia. Fire management decision-making would be enhanced through the use of spatial fi re simulators. Various groups from around the world met in January 2006 to evaluate the applicability of different spatial fi re spread applications for common use in both New Zealand and Australia. Devel- opers and researchers from Canada, the United States, and Australia were invited to apply Prometheus, FARSITE, and other similar models to New Zealand and Australian wildfi res in grass, scrub, and forested fuel types. Although the lack of site-specifi c fuel models and weather data were a concern, coarse spatial and temporal data inputs proved adequate for modeling fi res within a reasonable margin of error. The choice of grass models proved less important than expected since spread rates were easily manipulated through moisture content values during calibration. The fi nal modeled perimeters are affected by several user inputs that are impossible to separate from model error. These various inputs exist to allow experienced users to approximate local environmental variability as closely as possible to obtain successful outputs. Rather than attempt to quantify direct comparisons, local users concluded it was more important to choose an application that provides an appropriate level of functionality, that is compatible with current data and fi re management systems, and that can be easily modifi ed to use unique and varied fi re spread equations. Prometheus and FARSITE performed very well and will be further investigated to understand how each might be customized for use with local fi re spread models. This paper describes the process and results of testing some existing fi re growth simulation models for use on fiin New Zealand and Australia.

https://www.fs.fed.us/rm/pubs/rmrs_p041/rmrs_p041_201_212.pdf

Applying fire spread simulators in New Zealand and Australia: Results from an international seminar

In response to federal wildfire policy changes, risk-informed decision-making by way of improved decision support, is increasingly becoming a component of managing wildfires As fire incidents escalate in size and complexity, the Wildland Fire Decision Support System (WFDSS) provides support with different analytical tools as fire conditions change We demonstrate the application of WFDSS information and tools to assess risk management cycle elements by using a case study wildfire from the 2013 fire season; the Gold Pan Fire, Bitterroot National Forest, Montana, USA Examples of the scalability of the WFDSS, its ability to gain quick situational awareness, and an evaluation of fire behavior potential and burn probability with respect to Highly Valued Resources and Assets, is shown for the Gold Pan Fire as an emerging incident that evolved into a complex wildfire, supported with sophisticated analyses to assist decision-making

https://www.fs.fed.us/rm/pubs/rmrs_p073/rmrs_p073_320_323.pdf

Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA

Tonja S. Opperman

Papers

Developing the US Wildland Fire Decision Support System

LANDFIRE - A national vegetation/fuels data base for use in fuels treatment, restoration, and suppression planning

Applying fire spread simulators in New Zealand and Australia: Results from an international seminar

Applying the Wildland Fire Decision Support System (WFDSS) to support risk-informed decision making: The Gold Pan Fire, Bitterroot National Forest, Montana, USA