Landscape heterogeneity shapes species distributions, interactions, and fluctuations. Historically, in dry forest ecosystems, low canopy cover and heterogeneous fuel patterns often moderated disturbances like fire. Over the last century, however, increases in canopy cover and more homogeneous patterns have contributed to altered fire regimes with higher fire severity. Fire management strategies emphasize increasing within-stand heterogeneity with aggregated fuel patterns to alter potential fire behavior. Yet, little is known about how such patterns may affect fire behavior, or how sensitive fire behavior changes from fuel patterns are to winds and canopy cover. Here, we used a physics-based fire behavior model, FIRETEC, to explore the impacts of spatially aggregated fuel patterns on the mean and variability of stand-level fire behavior, and to test sensitivity of these effects to wind and canopy cover. Qualitative and quantitative approaches suggest that spatial fuel patterns can significantly affect fire behavior. Based on our results we propose three hypotheses: (1) aggregated spatial fuel patterns primarily affect fire behavior by increasing variability; (2) this variability should increase with spatial scale of aggregation; and (3) fire behavior sensitivity to spatial pattern effects should be more pronounced under moderate wind and fuel conditions.

As scientists and managers seek to understand fire behavior in conditions that extend beyond the limits of our current empirical models and prior experiences, they will need new tools that foster a more mechanistic understanding of the processes driving fire dynamics and effects. Here we suggest that process-based models are powerful research tools that are useful for investigating a large number of emerging questions in wildland fire sciences. These models can play a particularly important role in advancing our understanding, in part, because they allow their users to evaluate the potential mechanisms and interactions driving fire dynamics and effects from a unique perspective not often available through experimentation alone. For example, process-based models can be used to conduct experiments that would be impossible, too risky, or costly to do in the physical world. They can also contribute to the discovery process by inspiring new experiments, informing measurement strategies, and assisting in the interpretation of physical observations. Ultimately, a synergistic approach where simulations are continuously compared to experimental data, and where experiments are guided by the simulations will profoundly impact the quality and rate of progress towards solving emerging problems in wildland fire sciences.

This review focused on the primary literature that described, modeled, or predicted the probability of postfire mortality in ponderosa pine (Pinus ponderosa) and Douglas-fir (Pseudotsuga menziesii). The methods and measurements that were used to predict postfire tree death tended to fall into two general categories: those focusing on measuring important aspects of fire behavior, the indirect but ultimate cause of mortality; and those focusing on tissue damage due to fire, the direct effect of fire on plant organs. Of the methods reviewed in this paper, crown scorch volume was the most effective, easiest to use, and most popular measurement in predicting postfire mortality in both conifer species. In addition to this direct measure of foliage damage, several studies showed the importance and utility of adding a measurement of stem (bole) damage. There is no clear method of choice for this, but direct assessment of cambium condition near the tree base is widely used in Douglas-fir. Only two ponderosa pine studies directly measured fine root biomass changes due to fire, but they did not use these measurements to predict postfire mortality. Indirect measures of fire behavior such as ground char classes may be the most practical choice for measuring root damage. This review did not find clear postfire survivability differences between the two species. The literature also does not show a consistent use of terminology; we propose a standard set of terms and their definitions.

Landscape-level bark beetle (Coleoptera: Curculionidae, Scolytinae) outbreaks occurred in Arizona ponderosa pine (Pinus ponderosa Dougl. ex Law.) forests from 2001 to 2003 in response to severe drought and suitable forest conditions. We quantified surface fuel loadings and depths, and calculated canopy fuels based on forest structure attributes in 60 plots established 5 years previously on five national forests. Half of the plots we sampled in 2007 had bark beetle-caused pine mortality and half did not have mortality. Adjusting for differences in pre-outbreak stand density, plots with mortality had higher surface fuel and lower canopy fuel loadings 5 years after the outbreak compared with plots without mortality. Total surface fuels averaged 2.5 times higher and calculated canopy fuels 2 times lower in plots with mortality. Nearly half of the trees killed in the bark beetle outbreak had fallen within 5 years, resulting in loadings of 1000-h woody fuels above recommended ranges for dry coniferous forests in 20% of the mortality plots. We expect 1000-h fuel loadings in other mortality plots to exceed recommended ranges as remaining snags fall to the ground. This study adds to previous work that documents the highly variable and complex effects of bark beetle outbreaks on fuel complexes.