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US public land management agencies are faced with multiple, often conflicting objectives to meet management targets and produce a wide range of ecosystem services expected from public lands. One example is managing the growing wildfire risk to human and ecological values while meeting programmatic harvest targets for economic outputs mandated in agency budgets. Studies examining strategic management tradeoffs on federal lands and program efficiencies are rare. In this study we used the 79 western US national forests to examine tradeoffs between forest management scenarios targeting wildfire risk to the wildland urban interface (WUI) and those meeting agency convertible volume production targets. We quantified production frontiers to measure how the efficiency of meeting harvest volume targets is affected by prioritizing treatments to areas that transmit fire to the WUI. The results showed strong tradeoffs and scale effects on production frontiers, and more importantly substantial variation among planning areas and national forests. Prioritizing treatments to reduce fire transmission to the WUI resulted in an average harvest volume reduction of about 248 m3 per ha treated. The analysis also identified opportunities where both management objectives can be achieved. This work represents the first large-scale tradeoff analysis for key management goals in forest and fuel management programs on national forests.

Natural resource managers need better estimates of water storage and supply in forested landscapes. These estimates would aid planning for management activities that maintain and enhance forest health and productivity and help prepare forested landscapes for a changing climate. In particular, low soil moisture in combination with high evaporative demands can induce significant stresses on forests, increasing vulnerability to attacks of insect and disease, as well as increasing wildfire risk. Although high-resolution soils data exist for much of the Pacific Northwest, regional-scale datasets that identify forested areas potentially vulnerable to soil moisture-related drought do not exist. In this study, we used readily available spatial datasets depicting available water supply, soil depth, and evapotranspiration to model the likelihood that soils experience prolonged summer drying. To calibrate the model, we examined soil profile descriptions, lab data, and soil moisture curves for 25 sites throughout the Pacific Northwest and estimated the average annual number of days that soil moisture drops to levels at or below the permanent wilting point, a theoretical lower limit of plant-available water. Using this approach, we found statistically significant relationships between the independent variables and broad classes of soil moisture levels representing the highest and lowest levels of plant-available moisture. We then used these relationships to create a landscape-level droughty soil index for the Pacific Northwest. We expect that this approach can be further developed to include additional soil moisture data outside Washington and Oregon and enhanced with other explanatory variables such as topographic position, elevation, and vegetation type. With the addition of vegetation-related data, in particular, the current modeling approach can aid in identifying vulnerable landscapes in the context of managing for increased forest resiliency in the Pacific Northwest.

In this report we provide a framework for assessing cross-boundary wildfire exposure and a case study application in the western U.S. The case study provides detailed mapping and tabular decision support materials for prioritizing fuel management investments aimed at reducing wildfire exposure to communities located proximal to national forests. The work was motivated by a number of factors, including a request from U.S. Department of Agriculture Undersecretary James Hubbard (Natural Resources and Environment) to assess community wildfire risk specifically from Forest Service lands, language in the 2018 omnibus bill (Public Law 115-141) calling for a national assessment of wildfire risk to communities, and newer shared stewardship initiatives (Clavet 2018). We used national FSim simulation outputs to (1) estimate cross-boundary wildfire among major land types (Federal, State, private); (2) quantify structure exposure to all western communities; (3) map sources of community wildfire exposure (firesheds); (4) characterize firesheds in terms of management opportunity and fuels; and (5) prioritize communities based on integration of exposure and fireshed characteristics. The study revealed that 1,812 communities in the western U.S. could potentially be significantly impacted by future wildfires (more than 1 structure per year on average). Ignitions on national forest lands will most likely affect 516 of these 1,812 communities (more than one structure per year on average). Of the total exposure, ignitions on national forest lands will expose an estimated 4,000 structures (21 percent of total) in the western U.S. per year on average. Due to administrative restrictions on national forest lands, only about half of the total exposure from national forest lands (2,200 structures) originates on lands where mechanical treatments and prescribed fire are either allowed or ecologically appropriate. The framework can guide future efforts aimed at quantifying community and other cross-boundary exposure situations, and the outputs can be used to help identify shared stewardship projects, and prioritize fuel and other management activities within public land management agencies.

Predicting wildfire disasters presents a major challenge to the field of risk science, especially when fires propagate long distances through diverse fuel types and complex terrain. A good example is in the western US where large tracts of public lands routinely experience large fires that spread from remote wildlands into developed areas and cause structure loss and fatalities. In this paper we provide the first comprehensive assessment of where public wildlands potentially contribute wildfire exposure to communities in the 11 western US states. We used simulation modeling to map and characterize the composition of the source landscapes (firesheds) and recipient communities in terms of fuels, fire behavior and forest management suitability. The information was used to build a prototype investment prioritization framework that targets highly exposed communities where forest and fuel management activities are feasible. We found that simulated wildfires ignited on national forests can potentially affect about half of the communities in the western US (2560 out of 5118), with 90% of exposure affecting the top 20% of the communities (n = 516). Firesheds within national forests, defined as areas that have the potential to expose communities to fire, were estimated at 35 million ha (62% of the total national forest area), and were almost three times larger than the affected community lands. Large contiguous areas of wildfire transmission were evident on a number of national forests. Only 22% of the fireshed area is forested, fire-adapted, and lies within land management designations that allow mechanical fuels management. The methods demonstrate how cross-boundary exposure can be factored into prioritizing federal investments in hazardous fuels reduction on national forests in concert with community protection measures. The results can also help scale wildfire governance systems to match the geography of risk from large wildfire events, which augments existing assessments that do not explicitly identify the source of risk to communities.

Ecological departure, or how much landscapes have changed from a natural range of variation (NRV), has become a key metric in forest planning and restoration efforts. In this study we define forest restoration need as the specific change in structural stage abundance necessary to move landscapes into the NRV. While most restoration projects in the forested ecosystems of the Pacific Northwest, USA (Oregon and Washington) have embraced this paradigm, our understanding of what treatments to apply where, when, and at what magnitude is evolving and continues to be refined. We build on a body of existing LANDFIRE/Fire Regime Condition Class (FRCC) work on ecological departure to assess the ecological departure of all forested landscapes in the region. Moreover, we assess departure in moister forests west of the Cascade crest, and compare them with fire-dependent forests east of the crest and in southwest Oregon. These “moister Westside” forests have received relatively less attention in a fire ecology context, and we hypothesize restoration needs there are quite different. We show a substantial need for disturbance-related treatments in the drier fire-dependent portion of this region (east of the Cascade crest plus southwest Oregon), with over half of this treatment type falling on Federally-administered land. On the Westside the need for succession is more pronounced. The lack of pronounced disturbance need west of the Cascade crest suggests restoration there may require strategies more nuanced than in the fire-dependent zone.

Widespread habitat degradation and uncharacteristic fire, insect, and disease outbreaks in forests across the western United States have led to highly publicized calls to increase the pace and scale of forest restoration. Despite these calls, we frequently lack a comprehensive understanding of forest restoration needs. In this study we demonstrate a new approach for evaluating where, how much, and what types of restoration are needed to move present day landscape scale forest structure towards a Natural Range of Variability (NRV) across eastern Washington, eastern Oregon, and southwestern Oregon. Our approach builds on the conceptual framework of the LANDFIRE and Fire Regime Condition Class programs. Washington–Oregon specific datasets are used to assess the need for changes to current forest structure resulting from disturbance and/or succession at watershed and regional scales. Across our analysis region we found that changes in current structure would be needed on an estimated 4.7 million+ ha (40% of all coniferous forests) in order to restore forest structure approximating NRV at the landscape scale. Both the overall level and the type of restoration need varied greatly between forested biophysical settings. Regional restoration needs were dominated by the estimated 3.8+ million ha in need of thinning and/or low severity fire in forests that were historically maintained by frequent low or mixed severity fire (historical Fire Regime Group I and III biophysical settings). However, disturbance alone cannot restore NRV forest structure. We found that time to transition into later development structural classes through successional processes was required on approximately 3.2 million ha (over 25% of all coniferous forests). On an estimated 2.3 million ha we identified that disturbance followed by succession was required to restore NRV forest structure. The results of this study are intended to facilitate the ability of local land managers to incorporate regional scale, multi-ownership context into local forest management and restoration. Meeting the region-wide restoration needs identified in this study will require a substantial increase in the pace and scale of restoration treatments and coordination amongst governments, agencies, and landowners. 2014 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-SA license

Any theoretical treatment of a problem concerning our environment, such as our present concern, namely that of deducing the parameterization of an ocean-carbon model by inverse methods, must be based on some kind of model. In reality of course, the natural phenomena are so complex and our data so few that all such problems are indeterminate (i.e. have more than one solution that is consistent with the data). However, only by adopting models, and thereby, by definition, imposing a reduction on the complexity of reality do overdetermined systems arise, and also only by adoption of models can we hope to make efficient use of the available data and information. It is obvious that whether or not the results will be of interest depends on how well our model captures the essence of the phenomena in nature which it seeks to describe.