Wildfire is an ever present, natural process shaping landscapes. Having the ability to accurately measure and predict wildfire occurrence and impacts to ecosystem goods and services, both retrospectively and prospectively, is critical for adaptive management of landscapes.
Ongoing challenges to understanding how hazard exposure and disaster experiences influence perceived risk lead us to ask: Is seeing believing? We approach risk perception by attending to two components of overall risk perception: perceived probability of an event occurring and perceived consequences if an event occurs.
Many forest ecosystems are thought to be at risk of ecological collapse, which is broadly defined as an abrupt, long-lasting, and widespread change in ecosystem state and dynamics that has major negative impacts on biodiversity and key ecosystem services. However, there is currently a limited ability to accurately predict the risk of collapse for a given forest ecosystem.
A lengthening of the fire season, coupled with higher temperatures, increases the probability of fires throughout much of western North America. Although regional variation in the frequency of fires is well established, attempts to predict the occurrence of fire at a spatial resolution <10 km2 have generally been unsuccessful.
Wildfire risk in temperate forests has become a nearly intractable problem that can be characterized as a socioecological “pathology”: that is, a set of complex and problematic interactions among social and ecological systems across multiple spatial and temporal scales.
Forests sequester carbon from the atmosphere, helping mitigate climate change. In fire-prone forests, burn events result in direct and indirect emissions of carbon. High fire-induced tree mortality can cause a transition from a carbon sink to source, but thinning and prescribed burning can reduce fire severity and carbon loss when wildfire occurs.
We assessed wildfire mitigation activities in the wildland-urban interface (WUI) of New Mexico to identifywhich strategies are most effective. First, we modeledhow fuel treatments change wildfire behavior in 12 WUI areas.The second element of our analysis used data from over 2,000assessments of home wildfire hazard to better understand howthose hazards are distributed and change over time.
We present a method and case study to predict and map the likelihood of wildfires spreading to the urban interface through statistical analysis of past fire patterns using 15 000 lines from 677 fires with known ignition points and date and random potential end points on the urban interface of Sydney, Australia.
The increasing extent of wildfires has prompted investigation into alternative fire management approaches to complement the traditional strategies of fire suppression and fuels manipulation. Wildfire prevention through ignition reduction is an approach with potential for success, but ignitions result from a variety of causes.
Research across a variety of risk domains finds that the risk perceptions of professionals and the public differ. Such risk perception gaps occur if professionals and the public understand individual risk factors differently or if they aggregate risk factors into overall risk differently.