This dataset is a product of the PNW QWRA 2025. The purpose of the PNW QWRA 2025 is to provide foundational information about wildfire risk across the Pacific Northwest Region (which encompasses the states of Oregon and Washington). Analytics from the QWRA are used to guide vegetation management, fire response, and community planning at multiple scales.

A QWRA considers several different components, each resolved spatially across the region, including:

• likelihood of a fire burning,

• the intensity of a fire if one should occur,

• the exposure of assets and resources based on their locations, and

• the susceptibility of those assets and resources

Data users are encouraged to refer to the PNW QWRA 2023 Methods Report for full details: https://oe.oregonexplorer.info/externalcontent/wildfire/PNW_QWRA_2023Methods.pdf

The PNW QWRA 2025 evaluated risk to eight highly-valued resources and assets (HVRAs): People and Property, Infrastructure, Drinking Water, Timber, Ecological Integrity, Wildlife Habitat, Agriculture, and Recreation. This data layer, Ecological Integrity cNVC, represents risk integrated across all Ecological Integrity sub-HVRAs. The Ecological Integrity HVRA is intended to capture the quality and condition of ecosystems and how they respond to wildfires. Sub-HVRAs were divided into forested and non-forested types, and unique methods were applied to those two classes. The forested Ecological Integrity process evaluated existing structural conditions and assesses whether wildfire moves forest structure towards or away from desired restoration targets and was evaluated on forested lands where fire-mediated ecological integrity was presumed to be a land management objective. The framework and methods are described in detail in Laughlin et al. (2023), DeMeo et al. (2018), and Haugo et al. (2015). Sub-HVRAs included:

1. Early-seral forests

2. Mid-seral forests, closed canopy

3. Mid-seral forests, open canopy

4. Late-seral forests, open canopy

5. Late-seral forests, closed canopy

Assessing wildfire risk to rangeland Ecological Integrity required that we classify existing vegetation into sub-HVRAs based on factors that influence vegetation susceptibility to wildfire. To do so, we used the concepts of threat-based land management (Johnson et al., 2019), as captured in threat-based ecostate maps (Creutzburg, 2022) to characterize existing rangeland condition. The resulting ecostates were classified based on the dominant vegetation (i.e. - shrub, grass, trees) and the relative proportion of percent cover of perennial forbs & grasses to annual forbs & grasses using data from the Rangeland Analysis Platform (U.S. Department of Agriculture, Agricultural Research Service, 2022). The spatial extent of rangeland sub-HVRAs was defined using data from the National Land Cover Database (NLCD; Rigge et al., 2020).

Sub-HVRAs included:

1. Class A: Good and Intermediate Condition Shrubland – areas with more than 10% shrubs and the proportion of perennials is greater than annuals in the herbaceous layer

2. Class B: Good and Intermediate Condition Grasslands – areas with less than 10% shrubs and the proportion of perennials is greater than annuals in the herbaceous layer

3. Class C: Poor Condition Shrubland – areas with more than 10% shrubs and the proportion of annuals is greater than perennials in the herbaceous layer

4. Class D: Poor Condition Grassland – areas with less than 10% shrubs and the proportion of annuals is greater than perennials in the herbaceous layer

5. Juniper: early to mid-encroachment, Good and Intermediate Condition Understory – tree cover (assumed to be encroaching juniper) is 5% - 20% canopy cover and the proportion of perennials is greater than annuals in the herbaceous layer.

6. Juniper: early to mid-encroachment, Poor Condition Understory – tree cover (assumed to be encroaching juniper) is 5% - 20% canopy cover and the proportion of annuals is greater than perennials in the herbaceous layer.

7. Juniper: late encroachment, Good and Intermediate Condition Understory – tree cover (assumed to be encroaching juniper) is more than 20% canopy cover and the proportion of perennials is greater than annuals in the herbaceous layer.

8. Juniper: late encroachment, Poor Understory – tree cover (assumed to be encroaching juniper) is more than 20% canopy cover and the proportion of annuals is greater than perennials in the herbaceous layer.

Risk is estimated within the QWRA framework by integrating wildfire hazard with HVRA susceptibility (Scott et al., 2013). Risk is calculated for each pixel separately based on the fire hazard data for that pixel and based on which HVRAs are present. Fire impacts to each HVRA are characterized by the estimated change in value, a unitless approximation of whether the HVRA is beneficially or adversely affected by fire and to what magnitude. Accordingly, risk is expressed as net value change (NVC). Net value change is first calculated for all pixels across a sub-HVRA. The NVC for each HVRA is then calculated by summing the NVC of all its constituent sub-HVRAs. Positive values indicate that wildfire is likely to have beneficial impacts on the HVRA while negative values indicate that the net outcomes are likely to be adverse. Risk is calculated based on a very wide range of plausible weather conditions, much wider than the range under which we have typically experienced large fires in the past. The specific conditions under which a wildfire occurs will determine the outcomes. When interpreting QWRA risk results, bear in mind that fire will not always be beneficial in areas with positive NVC values and, likewise, it may be possible to experience beneficial fire in areas with negative NVC values.

Primary Data Contact: Ian Rickert, Regional Fire Planner, Forest Service R6/R10, ian.rickert@usda.gov

Citations:

Scott, J.H., Thompson, M.P., Calkin, D.E., 2013. A wildfire risk assessment framework for land and resource management (No. RMRS-GTR-315). U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Ft. Collins, CO. https://doi.org/10.2737/RMRS-GTR-315

Finney, M.A., McHugh, C.W., Grenfell, I.C., Riley, K.L., Short, K.C., 2011. A simulation of probabilistic wildfire risk components for the continental United States. Stoch Environ Res Risk Assess 25, 973–1000. https://doi.org/10.1007/s00477-011-0462-z