Revisiting Wildland Fire Fuel Quantification Methods: The Challenge of Understanding a Dynamic, Biotic Entity

Abstract

Abstract:Wildland fires are a function of properties of the fuels that sustain them. These fuels are themselves a function of vegetation, and share the complexity and dynamics of natural systems. Worldwide, the requirement for solutions to the threat of fire to human values has resulted in the development of systems for predicting fire behaviour. To date, regional differences in vegetation and independent fire model development has resulted a variety of approaches being used to describe, measure and map fuels. As a result, widely different systems have been adopted, resulting in incompatibilities that pose challenges to applying research findings and fire models outside their development domains. As combustion is a fundamental process, the same relationships between fuel and fire behaviour occur universally. Consequently, there is potential for developing novel fuel assessment methods that are more broadly applicable and allow fire research to be leveraged worldwide. Such a movement would require broad cooperation between researchers and would most likely necessitate a focus on universal properties of fuel. However, to truly understand fuel dynamics, the complex biotic nature of fuel would also need to remain a consideration-particularly when looking to understand the effects of altered fire regimes or changing climate.

Mixed‐severity wildfire and habitat of an old‐forest obligate

“…However, based on the findings of this study and many others (see review by Duff et al. ), we contend that fire models that continue to use fuel models that rate older forests with higher relative fire behavior will likely overestimate fire severity and inflate estimated loss of old forests in the Pacific Northwest. An alternative is to consider forest fuels in a more holistic manner and alternative age–flammability models (Kitzberger et al.…”

“…Running fire models for our study area based on conditions during the Douglas Complex and Big Windy Fires would be a worthwhile exercise to evaluate model predictions relative to the actual behavior of those fires. However, based on the findings of this study and many others (see review by Duff et al 2017), we contend that fire models that continue to use fuel models that rate older forests with higher relative fire behavior will likely overestimate fire severity and inflate estimated loss of old forests in the Pacific Northwest. An alternative is to consider forest fuels in a more holistic manner and alternative age-flammability models (Kitzberger et al 2012, Duff et al 2017.…”

“…, Duff et al. ). Where this view may be correct is in dry forests with historically very frequent fire‐return intervals (<10 yr), and contemporary increased fuel continuity has resulted from fire exclusion and led to increased sizes of high‐severity patches when fires burn under extreme weather (Reilly et al.…”

“…B/A index < 1 indicates that the forest type (suitable or unsuitable) burned at the severity class less than would have been expected by chance, and B/A index > 1 indicates forest type burned at the class more than by chance alone. (Kitzberger et al 2012, Duff et al 2017. Where this view may be correct is in dry forests with historically very frequent fire-return intervals (<10 yr), and contemporary increased fuel continuity has resulted from fire exclusion and led to increased sizes of high-severity patches when fires burn under extreme weather (Reilly et al 2017).…”

Quantifying Spatiotemporal Post‐Disturbance Recovery Using Field Inventory, Tree Growth, and Remote Sensing

“…Recovery rates following disturbances may ultimately depend on multiple interacting factors, such as disturbance frequency, type, intensity, pre-disturbance stand conditions, and the presence of biological legacies, as well as the local site factors such as topography or soils (Bartels et al, 2016;Buma, 2015;Cary et al, 2009;Foster et al, 1998;Frazier et al, 2015;Johnstone et al, 2011;Turner et al, 1999;Yang et al, 2017). The spatiotemporal variations in disturbances and recovery affect long-term landscape structure and function of forests (Miranda et al, 2016) and many forest ecosystem services such as carbon/energy/water budgets and climate change Liu et al, 2005;Randerson et al, 2006;Raymond et al, 2015;Welp et al, 2007), biodiversity conservation (Haslem et al, 2011), wildland fuels (Duff et al, 2017), and surface runoff and soil erosion (Wittenberg et al, 2007). Therefore, a thorough evaluation of post-disturbance vegetation recovery is essential for long-term planning in sustainable forestry (Bastos et al, 2011;Bourbonnais et al, 2017;Miranda et al, 2016;Wang et al, 2009;Wittenberg et al, 2007).…”