Across the western United States, decades of fire exclusion combined with past management history have contributed to the current condition of extensive areas of high-density, shade-tolerant coniferous stands that are increasingly prone to high-severity fires. Here, we report the modeled effects of constructed defensible fuel profile zones and group selection treatments on crown fire potential, flame length, and conditional burn probabilities across 11 land allocation types for an 18 600 ha study area within the northern Sierra Nevada, California. Fire modeling was completed using FlamMap and FARSITE based on landscape files developed with high-resolution aerial (IKONOS) imagery, ground-based plot data, and integrated data from ARCFUELS and the Forest Vegetation Simulator. Under modeled 97th percentile weather conditions, average conditional burn probability was reduced between pre- and post-treatment landscapes. A more detailed simulation of a hypothetical fire burning under fairly severe fire weather, or “problem fire”, revealed a 39% reduction in final fire size for the treated landscape relative to the pre-treatment condition. To modify fire behavior at a landscape level, a combination of fuel treatment strategies that address topographic location, land use allocations, vegetation types, and fire regimes is needed.

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Ladder fuels carry fire from the forest floor to the canopy and thereby may turn low-intensity fires into severe canopy fires. Attempts at assessing ladder fuels have been either expensive and spatially limited quantified approaches or unrepeatable and variable expert opinion strategies. We have developed a mixed semiquantitative, semiqualitative approach using a flow chart that systematizes observations and constrains judgments and decisionmaking. The ladder fuel hazard assessment (LaFHA) approach leads to ladder hazard ratings and some quantified observed data; it can be repeated across a very large area at relatively low cost and, because of the systematic and constrained approach, produces results that are mostly consistent and repeatable. Key attributes assessed are clumping of low aerial fuels, height to live crown base, and maximum gaps in vertical fuel ladders. Three field seasons of testing and implementing the LaFHA approach resulted in almost 4,000 observations. For the study area in the northern Sierra Nevada, California, more than a quarter of sites were rated high hazard and about 40% more were moderate risk. Data are presented on heights to live crown base and maximum gaps for each of the rated hazard categories.

Many statistics are available to compare distributions. Some are limited to nominal data while others, such as skew, Kullback-Leibler, Kolmogorov-Smirnov and the Gini coefficient, are useful for providing information about ordered distributions. While many of these tests are useful for determining properties of data in histograms, there has not been a test until now that allows for the detection of differences between distributions, describes the difference and is sensitive to the location of the departures. Such a test could be critical for comparing pre-and post-event distributions, such as a change in the distribution of biomass due to fire, for example, or for comparing data from different locations, such as soil size distributions, and even for evaluating economic disparity or examining differences in age demographics. We present a new statistic, a departure index, which allows a test distribution to be compared with any reference distribution. The resulting index contains information about the location, magnitude and direction of departure from the reference distribution to the test distribution. The departure index in turn provides a standardized response range that allows for a comparison of results from different analyses. A case study of actual fire data demonstrates the sensitivity and range of the test.