Surface fuel treatments in young, regenerating stands affect wildfire severity in a mixed conifer forest, eastside Cascade Range, Washington, USA

Lyons-Tinsley, Christina; Peterson, David L.

doi:10.1016/j.foreco.2011.04.016

Cited by 34 publications

(19 citation statements)

References 33 publications

(36 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Remote‐sensing‐derived fuel models generally improved simulations, notably in disturbed areas, which is important because megafires frequently encounter previous burn scars and managed lands that may impede or accelerate fire progression. The remote sensing‐based fuels visually improved the simulated spatial distribution of burn severity, supporting studies that assert the importance of forest successional state on fire impacts (Lyons‐Tinsley and Peterson ). Current analyses are limited to areas mapped by airborne missions and depend on availability of preburn data and resources to collect postfire observations.…”

Section: Discussionsupporting

confidence: 70%

Deconstructing the King megafire

Coen

Stavros

Fites-Kaufman

2018

Ecological Applications

View full text Add to dashboard Cite

Hypotheses that megafires, very large, high-impact fires, are caused by either climate effects such as drought or fuel accumulation due to fire exclusion with accompanying changes to forest structure have long been alleged and guided policy, but their physical basis remains untested. Here, unique airborne observations and microscale simulations using a coupled weather-wildland-fire-behavior model allowed a recent megafire, the King Fire, to be deconstructed and the relative impacts of forest structure, fuel load, weather, and drought on fire size, behavior, and duration to be separated. Simulations reproduced observed details including the arrival at an inclined canyon, a 25-km run, and later slower growth and features. Analysis revealed that fire-induced winds that equaled or exceeded ambient winds and fine-scale airflow undetected by surface weather networks were primarily responsible for the fire's rapid growth and size. Sensitivity tests varied fuel moisture and amount across wide ranges and showed that both drought and fuel accumulation effects were secondary, limited to sloped terrain where they compounded each other, and, in this case, unable to significantly impact the final extent. Compared to standard data, fuel models derived solely from remote sensing of vegetation type and forest structure improved simulated fire progression, notably in disturbed areas, and the distribution of burn severity. These results point to self-reinforcing internal dynamics rather than external forces as a means of generating this and possibly other outlier fire events. Hence, extreme fires need not arise from extreme fire environment conditions. Kinematic models used in operations do not capture fire-induced winds and dynamic feedbacks so can underestimate megafire events. The outcomes provided a nuanced view of weather, forest structure, fuel accumulation, and drought impacts on landscape-scale fire behavior-roles that can be misconstrued using correlational analyses between area burned and macroscale climate data or other exogenous factors. A practical outcome is that fuel treatments should be focused on sloped terrain, where factors multiply, for highest impact.

show abstract

Section: Discussionsupporting

confidence: 70%

Deconstructing the King megafire

Coen

Stavros

Fites-Kaufman

2018

Ecological Applications

View full text Add to dashboard Cite

show abstract

“…grass and forbs) fuel loadings in the near term (McGinnis et al, 2010), which can be a significant fuel layer as it cures and becomes a combustible, continuous fuelbed (McIver and Ottmar, 2007). Additionally, intensive reforestation typically substitutes conifer biomass for shrub biomass, limiting hazardous fuels reduction unless additional efforts are employed to reduce and maintain crown continuity and surface fuel loadings (Lyons-Tinsley and Peterson, 2012). Intensive postfire hazardous fuels treatments that influence all hazardous fuel layers could have negative consequences on ecosystem function, making them an undesirable mitigation strategy.…”

Section: Management Implicationsmentioning

confidence: 99%

Modeling the direct effects of salvage logging on long-term temporal fuel dynamics in dry-mixed conifer forests

Dunn

Bailey

2015

Forest Ecology and Management

View full text Add to dashboard Cite

“…The Flick Creek fire covered the largest elevation range, but plots were principally located in lower elevations of the fire, in mixed-conifer forests of Pseudotsuga menziesii, Pinus ponderosa, and Abies grandis. Plots on the Tripod fire spanned the widest range of forest types, from Pinus contorta stands that burn predominantly with high severity, to Pseudotsuga menziesii, Pinus ponderosa, and Larix occidentalis forest types that burn more often with low and moderate severity [36][37][38]. …”

Section: Study Areamentioning

confidence: 99%

How Robust Are Burn Severity Indices When Applied in a New Region? Evaluation of Alternate Field-Based and Remote-Sensing Methods

2012

View full text Add to dashboard Cite

Abstract:Remotely sensed indices of burn severity are now commonly used by researchers and land managers to assess fire effects, but their relationship to field-based assessments of burn severity has been evaluated only in a few ecosystems. This analysis illustrates two cases in which methodological refinements to field-based and remotely sensed indices of burn severity developed in one location did not show the same improvement when used in a new location. We evaluated three methods of assessing burn severity in the field: the Composite Burn Index (CBI)-a standardized method of assessing burn severity that combines ecologically significant variables related to burn severity into one numeric site index-and two modifications of the CBI that weight the plot CBI score by the percentage cover of each stratum. Unexpectedly, models using the CBI had higher R 2 and better classification accuracy than models using the weighted versions of the CBI. We suggest that the weighted versions of the CBI have lower accuracies because weighting by percentage cover decreases the influence of the dominant tree stratum, which should have the strongest relationship to optically sensed reflectance, and increases the influence of the substrates strata, which should have the weakest relationship with optically sensed reflectance in forested ecosystems. Using a large data set of CBI plots (n = 251) from four fires and CBI scores derived from additional field-based assessments of burn severity (n = 388), we predicted two metrics of image-based burn severity, the Relative differenced Normalized Burn Ratio (RdNBR) and the differenced Normalized Burn Ratio (dNBR). Predictive models for RdNBR showed slightly better OPEN ACCESSRemote Sens. 2012, 4 457 classification accuracy than for dNBR (overall accuracy = 62%, Kappa = 0.40, and overall accuracy = 59%, Kappa= 0.36, respectively), whereas dNBR had slightly better explanatory power, but strong differences were not apparent. RdNBR may provide little or no improvement over dNBR in systems where pre-fire reflectance is not highly variable, but may be more appropriate for comparing burn severity among regions.

show abstract

Surface fuel treatments in young, regenerating stands affect wildfire severity in a mixed conifer forest, eastside Cascade Range, Washington, USA

Cited by 34 publications

References 33 publications

Deconstructing the King megafire

Deconstructing the King megafire

Modeling the direct effects of salvage logging on long-term temporal fuel dynamics in dry-mixed conifer forests

How Robust Are Burn Severity Indices When Applied in a New Region? Evaluation of Alternate Field-Based and Remote-Sensing Methods

Contact Info

Product

Resources

About