Reclassifying the Wildland–Urban Interface Using Fire Occurrences for the United States

Quantification of Bioaccessible and Environmentally Relevant Trace Metals in Structure Ash from a Wildland-Urban Interface Fire

Wildfires at the wildland-urban interface (WUI) are increasing in frequency and intensity, driven by climate change and anthropogenic ignitions. Few studies have characterized the variability in the metal content in ash generated from burned structures in order to determine the potential risk to human and environmental health. Using inductively coupled plasma optical emission spectroscopy (ICP-OES) and inductively coupled plasma mass spectrometry (ICP-MS), we analyzed leachable trace metal concentration in soils and ash from structures burned by the Marshall Fire, a WUI fire that destroyed over 1000 structures in Boulder County, Colorado. Acid digestion revealed that ash derived from structures contained 22 times more Cu and 3 times more Pb on average than surrounding soils on a mg/kg basis. Ash liberated 12 times more Ni (mg/kg) and twice as much Cr (mg/kg) as soils in a water leach. By comparing the amount of acid-extractable metals to that released by water and simulated epithelial lung fluid (SELF), we estimated their potential for environmental mobility and human bioaccessibility. The SELF leach showed that Cu and Ni were more bioaccessible (mg of leachable metal/mg of acid-extractable metal) in ash than in soils. These results suggest that structure ash is an important source of trace metals that can negatively impact the health of both humans and the environment.

Assessing the impact of wildfires on property values in wildland-urban intermix and interface in Colorado: A hedonic approach

In this article, we investigate the impact of wildfire on property values in wildland-urban intermix (WUIM) and wildland-urban interface (WUIF) in Colorado. We construct fire indices accounting for the nonlinear impact of wildfires, and evaluate the effects of different fire attributes-proximity, frequency, and scale-on property values in a hedonic price framework using housing transactions data and wildfire data in Colorado from 2000 to 2016. We find a substantial difference in the impact of wildfires on property values between WUIM and WUIF. Specifically, larger fires depreciate property values in WUIM, but increase property values in WUIF. In addition, we find that small fires lead to a negative impact on property values in both WUIM and WUIF, which is comparable with larger fires. Our findings provide policymakers novel information in making more efficient wildfire management plans.

A Systematic Review of Applications of Machine Learning Techniques for Wildfire Management Decision Support

Wildfires threaten and kill people, destroy urban and rural property, degrade air quality, ravage forest ecosystems, and contribute to global warming. Wildfire management decision support models are thus important for avoiding or mitigating the effects of these events. In this context, this paper aims at providing a review of recent applications of machine learning methods for wildfire management decision support. The emphasis is on providing a summary of these applications with a classification according to the case study type, machine learning method, case study location, and performance metrics. The review considers documents published in the last four years, using a sample of 135 documents (review articles and research articles). It is concluded that the adoption of machine learning methods may contribute to enhancing support in different fire management phases.

Timing of Tree Density Increases, Influence of Climate Change, and a Land Use Proxy for Tree Density Increases in the Eastern United States

Long-term observations inform relationships among changes in vegetation, climate, and land use. For the eastern United States, I compared the timing of tree change, comprised of density and diversity increases, with the timing of climate change, as measured by change point detection of the Palmer Modified Drought Index (PMDI) that accounts for water balance, in two prairie ecological provinces, four grassland landscapes, and four forest landscapes. Historical evidence supplied documentation of tree density increases between approximately 1860 and 1890 in the two prairie provinces of grasslands bordering eastern forests. Additionally, because timing of tree increases paralleled when land area reached ≥25% agricultural use, I categorized grassland and forest landscapes that increased to ≥25% agricultural area during 1860, 1880, 1900, and 1920. One change point detection method identified no significant PMDI change points during the 1800s. The other method found the southern prairie province, bordering eastern forests, had change points of 1855 and 1865 during an interval of relative dryness. Only two of four grassland landscapes, and one of four forest landscapes had change points, which occurred during relative dryness or were continuous with historical variation. Inconsistent changes in moisture availability did not provide correlations with comprehensive tree increases, but land use change corresponded with tree changes based on timing, magnitude and direction of change, and mechanism. The agricultural threshold may provide the critical missing component that allows progression in analysis of land use change effects on vegetation.

A 13-Year Approach to Understand the Effect of Prescribed Fires and Livestock Grazing on Soil Chemical Properties in Tivissa, NE Iberian Peninsula

The high density of fuel accumulated in the Mediterranean ecosystems due to land abandonment results in high severity fires. Traditional fire practices and livestock grazing have played an important role in shaping the structure and composition of Mediterranean landscapes, and both can be efficient tools to manage them now that land abandonment is widespread. Attempts at controlling forest fires are essential for landscape management practices that, in their turn, seek to maintain a specific species composition. Against this backdrop, this study aims to determine the short- and long-term effects of the combined management practices of prescribed fires and goat grazing on the chemical properties of soils in Tivissa, Tarragona (NE Iberian Peninsula). Forty-two samples were collected in a 4 × 18 m plot before the prescribed fire of 2002 (1), immediately after the 2002 prescribed fire (PF) (2), one year after the 2002 PF (3), three years after the 2002 PF (4), and thirteen years after the 2002 PF (5). Soil samples were taken at each sampling point from the top layer (0–5 cm), sieved to obtain a <2 mm fraction, and soil pH, EC, Total C, total N, available P, K+, Ca2+, and Mg2+ were determined. The results indicate that the short-term effects of fire are more relevant than those attributable to the livestock over the long term due to the low grazing intensity of less than one goat per ha. The long-term effects of prescribed fires were not visible in the research, suggesting that they recovered after burning with all their functions intact and with enhanced levels of natural fertility. Combined land management practices of prescribed fire and livestock grazing did not affect soil chemical properties. The applied management enhanced soil fertility and boosted the ecosystem’s resilience.

Classifying Large Wildfires in the United States by Land Cover

Fire is an ecological process that also has socio-economic effects. To learn more about fire occurrence, I examined relationships between land classes and about 12,000 spatially delineated large wildfires (defined here as uncontrolled fires ≥200 ha, although definitions vary) during 1999 to 2017 in the conterminous United States. Using random forests, extreme gradient boosting, and c5.0 classifiers, I modeled all fires, first years (1999 to 2002), last years (2014 to 2017), the eastern, central, and western United States and seven ecoregions. The three classifiers performed well (true positive rates 0.82 to 0.94) at modeling all fires and fires by year, region, and ecoregion. The random forests classifier did not predict to other time intervals or regions as well as other classifiers and models were not constant in time and space. For example, the eastern region overpredicted fires in the western region and models for the western region underpredicted fires in the eastern region. Overall, greater abundance of herbaceous grasslands, or herbaceous wetlands in the eastern region, and evergreen forest and low abundance of crops and pasture characterized most large fires, even with regional differences. The 14 states in the northeastern United States with no or few large fires contained limited herbaceous area and abundant crops or developed lands. Herbaceous vegetation was the most important variable for fire occurrences in the western region. Lack of crops was most important for fires in the central region and a lack of pasture, crops, and developed open space was most important for fires in the eastern region. A combination of wildlands vegetation was most influential for most ecoregions, although herbaceous vegetation alone and lack of pasture, crops, and developed open space also were influential. Despite departure from historical fire regimes, these models demonstrated that herbaceous vegetation remains necessary for fires and that evergreen forests in particular are fire-prone, while reduction of vegetation surrounding housing developments will help provide a buffer to reduce large fires.