Climate Change and Fire

Background

The North American boreal biome (NAB) is warming at 2–4 times the mean global rate, contributing to increasing wildfire activity. The degree to which this trend alters biome-level feedbacks to global climate depends on how strongly bottom-up feedbacks between fire and vegetation dampen the effects of climate drivers.

Accurate fire weather forecasting is essential for effective wildfire management, particularly in regions increasingly affected by extreme fire activity such as British Columbia and Alberta, Canada.

Increased frequency, severity, and duration of droughts and increased wildfire severity are impacting many conifer forests globally. Reforestation in these changing disturbance regimes requires tree seedlings capable of establishing in hotter and drier climates.

Cloud-to-ground (CG) lightning is a major source of summer wildfire ignition in the western United States (WUS). However, future projections of lightning are uncertain since lightning is not directly simulated by most global climate models. To address this issue, we use convolutional neural network (CNN)-based parameterizations of daily June-September CG lightning.

Area burned by wildfire has increased in western US forests and elsewhere over recent decades coincident with warmer and drier fire seasons. However, high–severity fire—fire that kills all or most trees—is arguably a more important metric of fire activity given its destabilizing influence on forest ecosystems and direct and indirect impacts to human communities.

Drought, wildfire, wind, insects, and pathogens can interact across space and time to shape forest ecosystems. Although subdisciplines in ecology have long studied individual disturbances, their interactions remain poorly understood, particularly under climate change. Further, inconsistent terminology used to describe these interactions compounds this gap.

Annual wildfire area in California has rapidly grown in recent decades, with increasingly negative impacts on people. The fire season is also lengthening, with an earlier onset. This trend has been hypothesized to be driven by anthropogenic warming, but it has yet to be quantitatively attributed to climate drivers.

Dangerous fire weather is increasing under climate change, but there is limited knowledge of how this will affect fire intensity, a critical determinant of the socioecological effects of wildfire.

Warming temperatures and increasingly variable precipitation patterns are reducing winter snowpack and critical late-season streamflows. Here, we used two models (LANDIS-II and DHSVM) in linked simulations to evaluate the effects of wildfire and forest management scenarios on future snowpack and streamflow dynamics.