Simple Spatial Modeling Tool for Prioritizing Prescribed Burning Activities at the Landscape Scale

Hiers, J. Kevin; Laine, Stephen C.; Bachant, J. J.; Furman, James H.; Greene, Weldon W.; Compton, Vernon

doi:10.1111/j.1523-1739.2003.00381.x

Cited by 48 publications

(42 citation statements)

References 10 publications

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“…The treatment of wildlands for fire hazard reduction is both costly (e.g., Hiers et al, 2003;Keane et al, 2003;Lynch and Mackes, 2003) and controversial. However, in areas of high risk, such as the ponderosa pine type where return times for fire are short (Everett et al, 2000) or where extensive contiguous forest can produce fires exceeding 100,000 acres, it is imperative that some sort of action be taken.…”

Section: Discussionmentioning

confidence: 99%

Applying landscape principles to fire hazard reduction

Loehle

2004

Forest Ecology and Management

145

108

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Fire spreads in a specifically spatial manner, which suggests the applicability of percolation models to the risk reduction problem. It is shown that under fairly general conditions a threshold exists below which a landscape becomes essentially fireproof. Arranging treated acres into a grid, analogous to bulkheads on a ship, drastically reduces the acreage that must be treated to achieve a fireproof condition. Such compartmentation of the landscape yields a much higher leverage (ratio of acres saved to acres treated). Certain landscape features create updrafts that spread fire particularly far. Treating fuels in such areas yields high leverage. Fire shadow effects were replicated by the simulation and showed a possible mechanism for amplifying treatment effectiveness. Either fuel reduction programs or commercial forestry can be used to achieve hazard reduction without excessive costs if spatial aspects of fire spread are taken into account. #

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Section: Discussionmentioning

confidence: 99%

Applying landscape principles to fire hazard reduction

Loehle

2004

Forest Ecology and Management

145

108

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“…Previous work on decision support systems specifically for forest restoration is limited. Several studies have created spatial prioritization systems by combining a number of ecological and operational data into GIS overlays (Hiers et al 2003, Sisk et al 2006. The system developed for the national fire plan's prioritization system (Keane et al 2007) derived HRV departure indices that could be used to prioritize restoration activities.…”

Section: Discussionmentioning

confidence: 99%

Restoration of fire in managed forests: a model to prioritize landscapes and analyze tradeoffs

Ager

Vaillant

McMahan³

2013

Ecosphere

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Abstract. Ongoing forest restoration on public lands in the western US is a concerted effort to counter the growing incidence of uncharacteristic wildfire in fire-adapted ecosystems. Restoration projects cover 725,000 ha annually, and include thinning and underburning to remove ladder and surface fuel, and seeding of fire-adapted native grasses and shrubs. The backlog of areas in need of restoration combined with limited budgets requires that projects are implemented according to a prioritization system. The current system uses a stand-scale metric that measures ecological departure from pre-settlement conditions. Although conceptually appealing, the approach does not consider important spatial factors that influence both the efficiency and feasibility of managing future fire in the post-treatment landscape. To address this gap, we developed a spatial model that can be used to explore different landscape treatment configurations and identify optimal project parameters that maximize restoration goals. We tested the model on a 245,000 ha forest and analyzed tradeoffs among treatment strategies as defined by fire behavior thresholds, total area treated, and the proportion of the project area treated. We assumed the primary goal as the protection and conservation of old growth ponderosa pine trees from potential wildfire loss. The model located optimal project areas for restoration and identified treatment areas within them, although the location was dependent on assumptions about acceptable fire intensity within restored landscapes, and the total treated area per project. When a high percentage of stands was treated (e.g., .80%), the resulting project area was relatively small, leaving the surrounding landscape at risk for fire. Conversely, treating only a few stands with extreme fire behavior (,20%) created larger projects, but substantial old growth forests remained susceptible to wildfire mortality within the project area. Intermediate treatment densities (35%) were optimal in terms of the overall reduction in the potential wildfire mortality of old growth. The current work expands the application in spatial optimization to the problem of dry forest restoration, and demonstrates a decision support protocol to prioritize landscapes and specific areas to treat within them. The concepts and model can be applied to similar problems in spatial ecology.

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“…We chose to examine how these stakeholders prioritize land, and the rationales behind those priorities, specifically to explicate the priorities and rationales that are often only implicit as multiple stakeholders negotiate around the question of when and where to burn. Unearthing this process will improve the likelihood that management objectives will be understood, supported, and met (Hiers et al 2003). We compared prescribed burning priorities of these two groups with priorities identified by nonpractitioners, i.e., ecologists who have knowledge of the landscape and ecosystem, but who are not directly involved in burning, and therefore not culpable for the potential outcomes of burning.…”

Section: Introductionmentioning

confidence: 99%