Predicting increasing high severity area burned for three forested regions in the western United States using extreme value theory

Predicting increasing high severity area burned for three forested regions in the western United States using extreme value theory

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Predicting increasing high severity area burned for three forested regions in the western United States using extreme value theory

Highlights

West-wide, the number of fires with high severity hectares >200 has increased since 1984.

In most years, temperature and moisture deficit explain high severity area burned.

In extreme years, regionally specific controls explain high severity fire area burned.

Abstract

More than 70 years of fire suppression by federal land management agencies has interrupted fire regimes in much of the western United States. The result of missed fire cycles is a buildup of both surface and canopy fuels in many forest ecosystems, increasing the risk of severe fire. The frequency and size of fires has increased in recent decades, as has the area burned with high severity in some ecosystems. A number of studies have examined controls on high severity fire occurrence, but none have yet determined what controls the extent of high severity fire. We developed statistical models predicting high severity area burned for the western United States and three sub-regions—the Northern Rocky Mountains, Sierra Nevada Mountains, and Southwest. A simple model with maximum temperature the month of fire, annual normalized moisture deficit and location explains area burned in high severity fire in our west-wide model, with the exception of years with especially large areas burned with high severity fire: 1988, 2002. With respect to mitigation or management of high severity fire, understanding what drives extreme fire years is critical. For the sub-regional models, topography, spring temperature and snowpack condition, and vegetation condition class variables improved our prediction of high severity burned area in extreme fire years. Fire year climate is critical to predicting area burned in high severity fire, especially in extreme fire years. These models can be used for scenario analyses and impact assessments to aid management in mitigating negative impacts of high severity fire.

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© 2018 Published by Elsevier B.V.

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Superforest

via ScienceDirect Publication: Forest Ecology and Management https://ift.tt/2zaqiu8

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