Douglas B. Rideout

Toward a Unified Economic Theory of Fire Program Analysis with Strategies for Empirical Modeling

Recent United States federal wildland fire policy documents including the 2001 policy update (US Department of Agriculture and US Department of the Interior 2001) call for integrated approaches to the national fire program. An important theme of these inter-agency policies is to encourage planning and budgeting across the major fire program components (e.g., suppression, fuels, prevention) in a consistent way. This means, for example, that planning and budgeting for the fuels (suppression) component is informed by the planning and budgeting of the suppression (fuels) component. In this chapter we specify the economic structure of a planning and budgeting system, as opposed to a component-by-component analysis. This structure shows, for example, that budgeting a federal system by program component is unlikely to promote efficiency. The structure also shows that the components can be managed in concert to capitalize on the complementary impacts they are likely to have on each other. Implementing a unified theory in planning constitutes a major challenge across uncharted waters. Current planning approaches are largely based upon component specific models and budgeting is often executed as incremental adjustment to precedent. This chapter reaches beyond by deriving the essential principles of an integrated fire system in support of cost effective planning and budgeting. While some of our analytics used to derive the principles are complex, we do not intend to imply that budgeting systems need to reflect such complexity: only the essential principles. Previous planning and budgeting models have focused on individual program components such as fuels management, suppression, or prevention with no direct or simultaneous consideration of the other components. This means that managing and budgeting the system of components in concert has been largely unattainable. Current models were not intended to directly address how the plans for initial attack (fuels treatment) are affected by a simultaneous consideration

COMPARING FIRE PROTECTION AND IMPROVEMENT VALUES AT FOUR MAJOR US NATIONAL PARKS AND ASSESSING THE POTENTIAL FOR GENERALIZED VALUE CATEGORIES

A new approach was used to elicit relative values of a variety of natural and cultural resources to estimate the extent that managers thought these resources would be enhanced or harmed by wildfire. This method, while based on economic principles of utility, does not involve monetary valuation. The method is illustrated by elicitation of relative values of different forest types, wildlife habitat and archaeological/cultural resources from resource professionals and managers in Grand Canyon, Rocky Mountain, Sequoia-Kings Canyon and Yellowstone National Parks. While these elicitations were independently performed for each park, the relative protection and improvement values of the various resources are remarkably similar. This similarity may reflect the common and well-focused mandate that national parks operate under. The management implications of the protection and improvement values of natural and cultural resources for wildland fire management at these and other national parks are discussed. Keywords Disturbance, Grand Canyon, Rocky Mountain, Sequoia-Kings Canyon, value elicitation, wildland fire, Yellowstone Language: en

Optimal Allocation Of Initial Attack Resources To Multiple Wildfire Events

Increased scrutiny of federally funded programs combined with changes in fire management reflects a demand for new fire program analysis tools. We formulated an integer linear programming (ILP) model for initial attack resource allocation that operates in a performance-based, cost-effectiveness analysis (CEA) environment. The model optimizes the deployment of initial attack resources for a user-defined set of fires that a manager would like to be prepared for across alternative budget levels. The model also incorporates fire spread, multiple ignitions, simultaneous ignitions, and monitoring of resources on a landscape. It also evaluates the cost effectiveness of alternate firefighting resources and alternative pre-positioning locations. Fires that escape initial attack are costly during the extended attack phase of fire management. To address this within the scope of initial attack, we constructed and analyzed alternative objective functions that incorporate a proxy for internalizing the cost of fires that escape initial attack. This type of model can provide the basis for a wider scale formulation with the potential to measure an organizations performance and promote a higher level of accountability and efficiency in fire programs. Keywords fire escape, initial attack, integer linear programming, optimal deployment, performance, wildland fire Language: en

Valuing fire planning alternatives in forest restoration: using derived demand to integrate economics with ecological restoration.

Assessing the value of fire planning alternatives is challenging because fire affects a wide array of ecosystem, market, and social values. Wildland fire management is increasingly used to address forest restoration while pragmatic approaches to assessing the value of fire management have yet to be developed. Earlier approaches to assessing the value of forest management relied on connecting site valuation with management variables. While sound, such analysis is too narrow to account for a broad range of ecosystem services. The metric fire regime condition class (FRCC) was developed from ecosystem management philosophy, but it is entirely biophysical. Its lack of economic information cripples its utility to support decision-making. We present a means of defining and assessing the deviation of a landscape from its desired fire management condition by re-framing the fire management problem as one of derived demand. This valued deviation establishes a performance metric for wildland fire management. Using a case study, we display the deviation across a landscape and sum the deviations to produce a summary metric. This summary metric is used to assess the value of alternative fire management strategies on improving the fire management condition toward its desired state. It enables us to identify which sites are most valuable to restore, even when they are in the same fire regime condition class. The case study site exemplifies how a wide range of disparate values, such as watershed, wildlife, property and timber, can be incorporated into a single landscape assessment. The analysis presented here leverages previous research on environmental capital value and non-market valuation by integrating ecosystem management, restoration, and microeconomics.

A Probabilistic Landscape Analysis Supporting the Management of Unplanned Ignitions at Sequoia and Kings Canyon National Parks

Fire management policy in the United States has evolved to encourage fire managers to address the full range of beneficial and detrimental effects of unplanned ignitions. We developed a probability-based fire risk and benefit simulation approach to support wildland fire management at Sequoia and Kings Canyon National Parks (SEKI) in a manner consistent with the SEKI fire management plan. The approach integrated fire behavior, fire spread probability, and resource values to estimate the spatial distribution of expected fire net benefits for any ignition point in a landscape context. We simulated probabilistic fire footprints from each burnable cell and evaluated them for their potential to provide ecosystem benefits or to require risk mitigation. The expected net benefits of igniting a cell were stored in the ignition cell to provide a landscape-level perspective. We provide results that reflect the fire planning weather conditions of concern to demonstrate how the sensitivity of the results can reflect weather influences. The results provided a preprocessed “playbook” type reference guide to fire management. The results can be quickly accessed and intuitively interpreted and were used to promote interagency cooperation in managing the Tehipite fire on northern SEKI and on the Sierra National Forest.

Sustainable development and the great sage-grouse

The invasion of non-native grasses, pinyon-juniper encroachment, drought and climate change have resulted in larger, more intense fires in the western United States’ sagebrush-steppe ecosystem. The U.S. Fish and Wildlife Service identified these factors as the primary threat to sagebrush obligate species, particularly the endemic greater sage-grouse. A large portion of primary sage-grouse conservation areas reside on the U.S. Department of the Interior federal lands. In 2015, the DOI issued Secretarial Order 3336 that directed the development of a comprehensive science-based strategy to reduce the threat of large-scale rangeland fires to greater sage-grouse habitat and the sage-steppe ecosystem. This study reports the results of using the STARFire planning and budgeting system to respond to Section 7(b) iii-Fuels, Action Item #4 of the secretarial order. This study demonstrates the capabilities of STARFire to apply the latest science and technology using a risk-based approach to conduct a wildfire risk analysis and improve the targeting of fuels reduction programs on a landscape-scale study across the Northern Great Basin of the United States.

Comparing Alternative Budget Allocation Models To Support Strategic Wildland Fire Program Analysis Across Us National Parks

Hazard fuel reduction and wildland fire preparedness programs are two important budgeting compo nents in the US National Park Service strategic wildland fire planning. During the planning process, each national park independently conducts analysis to understand the benefits from investing in each program to mitigate fire risks and improve ecosystem benefits. The national program analysis imports the cost-effective frontiers of investment in both programs from each national park. The national program then allocates cost-effective funding to the parks and implements required national policies while minimizing disruption to current programs of work. In this study, we test and compare two alternative modeling methods for budget allocation between the fuel treatment and preparedness programs responding to changes in funding levels nationally. One approach uses a nonlinear programming model (NLP) to maximize the benefits of investments in both programs with a set of feasibility constraints. The other approach uses a simulation-based gradient method to manage program budget changes. Both approaches are designed to focus on national level program efficiency while mitigating potential program disruptions; however, different approaches suggest different budgeting allocation strategies. This study compares the trade-offs between efficiency and the level of disruption of different budget allocation methods. Discoveries could help managers to select and implement an efficient and viable analytical system to study the value of funding increases, the cost of budget reductions, and guide landscape allocations. It will also identify national impacts by accumulating allocations to individual units across the national parks in the United States.

Using Benefit Transfer to Estimate Average Relative Marginal Values for Wildland Fire Program Planning

We developed a set of generalized value categories and average relative marginal values using resource and valuation information collected at seven federal land management planning units in the USA. The categories and average values are intended to be used for rapid strategic wildland fire program planning or as foundation values for a more extended planning effort. To divide the original information into logical and statistically valid value categories, we used a k-means cluster analysis combined with expert knowledge of how each resource type is managed with respect to fire. After we established the value categories, we performed a regression tree analysis to estimate an average relative marginal value for each category under different combinations of ecosystem condition and fireline intensity. Average values for each category are as expected and the regression tree fits are excellent with R2 values ranging from .895 to .948. The results of this study can be used to identify general resource types for planning or other valuation analyses and they provide a low cost way to transfer nonmarket value information between similar planning sites.