US National Forests Research Articles

Modelling the effect of accelerated forest management on long-term wildfire activity

We integrated a widely used forest growth and management model, the Forest Vegetation Simulator, with the FSim large wildfire simulator to study how management policies affected future wildfire over 50 years on a 1.3 million ha study area comprised of a US national forest and adjacent lands. The model leverages decades of research and development on the respective forest growth and wildfire simulation models, and their integration creates a strategic forest landscape model that has a high degree of transparency in the existing user communities. The study area has been targeted for forest restoration investments in response to wildland fires that are increasingly impacting ecological conditions, conservation areas, amenity values, and surrounding communities. We simulated three alternative spatial investment priorities and three levels of management intensity (area treated) over a 50-year timespan and measured the response in terms of area burned, fire severity, wildland-urban interface exposure and timber production. We found that the backlog of areas in need of restoration on the national forest could be eliminated in 20 years when the treatment rate was elevated to a maximum of 3× the current level. However, higher rates of treatments early in the simulation created a future need to address the rapid buildup of fuels associated with understory shrub and tree regeneration. Restoration treatments over time had a large effect on fire severity, on average reducing potential flame length by up to 26% for the study area within the first 20 years, whereas reductions in area burned were relatively small. Although wildfire contributed to reducing flame length over time, area burned was only 16% of the total disturbed area (managed and burned with prescribed fire) under the 3× management intensity. Interactions among spatial treatment scenarios and treatment intensities were minimal, although inter-annual variability was extreme, with the coefficient of variation in burned area exceeding 200%. We also observed simulated fires that exceeded four times the historically recorded fire size. Fire regime variability has manifold significance since very large fires can homogenize fuels and eliminate clumpy stand structure that historically reduced fire size and maintained landscape resiliency. We discuss specific research needs to better understand future wildfire activity and the relative influence of climate, fuels, fire feedbacks, and management to achieve fire resiliency goals on western US fire frequent forests.

Cannabis legalization by states reduces illegal growing on US national forests

Ten US states and the District of Columbia have legalized cannabis as of November 2018, and have adopted other policies regarding production, consumption, and the penalties associated with it. These policy changes may have affected illegal growing operations on national forests of the United States. Using data on the number of cannabis grow sites reported on 111 national forests between 2004 and 2016 together with information about state cannabis laws and when they were implemented, we find that recreational cannabis legalization is associated with decreased reports of illegal grow operations on national forests. Laws mandating minimum sentences for illegal cannabis possession or sales are associated with fewer reported grows, as is strict regulation of cannabinoid products. Taxes on sales have positive impacts on illegal growing, while law enforcement presence has a negative effect. Counterfactual simulations for 2016 quantify the magnitudes of these policy effects.

The effects of recreational cannabis legalization on forest management and conservation efforts in U.S. national forests in the Pacific Northwest

Cannabis cultivation in US national forests has been identified as a growing environmental issue. Rational choice theory often considers law enforcement efforts as pushing this illegal activity into remote areas, including public lands, through the process of crime displacement. As such, the legalization of recreational cannabis has been prescribed as a possible solution to this environmental issue. The recent liberalization of marijuana policies across numerous states introduces the opportunity to analyze these claims. Here, utilizing regression analyses, we investigate the effects of recreational cannabis legalization and a host of relevant socio-economic and law enforcement factors in Washington and Oregon on illicit marijuana cultivation in Pacific Northwest national forests. To further investigate the regression results, structured questions were sent to a key informant of the United States Forest Service Law Enforcement and Investigations division who responded on behalf of the institution. Results demonstrate law enforcement and economic variables as significant in determining illicit cannabis cultivation in Pacific Northwest national forests, confirming the relevance of a rational choice framework. Recreational cannabis legalization is found to significantly contribute to a reduction in illicit cultivation sites in Oregonian national forests, while remaining insignificant in Washington, likely due to policy differences that are discussed.

Tradeoffs between US national forest harvest targets and fuel management to reduce wildfire transmission to the wildland urban interface

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.

Projected Market Competition for Wood Biomass between Traditional Products and Energy: A Simulated Interaction of US Regional, National, and Global Forest Product Markets

Projected Market Competition for Wood Biomass between Traditional Products and Energy: A Simulated Interaction of US Regional, National, and Global Forest Product Markets

Improved Prediction of Stream Flow Based on Updating Land Cover Maps with Remotely Sensed Forest Change Detection

The water balance in a watershed can be disrupted by forest disturbances such as harvests and fires. Techniques to accurately and efficiently map forest cover changes due to disturbance are evolving quickly, and it is of interest to ask how useful maps of different types of disturbances over time can be in the prediction of water yield. We assessed the benefits of using land cover maps produced at annual vs. five-year intervals in the prediction of monthly streamflows across 10 watersheds contained entirely within the US National Forest System. We found that annually updating land cover maps with forest disturbance data significantly improved water yield predictions using the Soil and Water Assessment Tool (SWAT; p < 0.01 improvement for both the Nash–Sutcliffe efficiency measure and the ratio of the root mean square error to the standard deviation of the measured data). Improvement related to using annually updated land cover maps was directly related to the amount of disturbance observed in a watershed. Our results lay a foundation to apply new high-resolution disturbance datasets in the field of hydrologic modeling to monitor ungauged watersheds and to explore potential water yield changes in watersheds if climate conditions or management practices were to change forest disturbance processes.

Finding exact solutions for the Geometric Firefighter Problem in practice

In the Geometric Firefighter Problem (gfp), one aims to maximize the total area shielded from a fire that radiates from a point inside a polygonal region, by constructing a subset of a given set of barriers. To decide which barriers to construct, a solution must take into account the speed of the circularly spreading fire and the barriers construction speed. A barrier is considered successfully constructed if the fire does not burn any still unconstructed point of the barrier. In this work, we consider the case where the initial set of barriers is comprised of rectilinear chords of the polygon. We present an Integer Programming (ip) model employed to solve the gfp to optimality along with procedures for preprocessing the instances, including primal algorithms and methods to reduce the problem size, as these constitute an essential step for solving harder instances. Moreover, we report on extensive experimental results that show that our ip model is an order of magnitude faster than the previous state-of-the art algorithm for the gfp. To further strain our algorithms, we introduce a new set of instances based on US national forests, which proved to be noticeably harder to solve than the previously available benchmark. An extended report on our experimental findings is presented along with a discussion that includes a restricted case where the constructed barriers must have pairwise disjoint interiors.

Introduction to the Special Section on Recreation Surveys

Surveys to estimate characteristics associated with recreational activities in the United States are local, state-based, or national. While surveys of recreational fishing are well established, surveys to make estimates for populations such as visitors to recreation sites in the US National Forests or hikers on well-established trails are becoming more common. As described by the Minnesota Department of Natural Resources, creel or angler surveys are commonly conducted by state-based agencies to measure fish, determine the number of hours fished, and count boats, fish houses, recreational craft, etc. Nationally, the Marine Recreational Information Program of the National Oceanic and Atmospheric Administration (NOAA) is intended to “provide timely, scientifically sound estimates of recreational catch and effort that fishery managers, stock assessors, and marine scientists need to ensure the sustainability of ocean resources.” This is done by using a “suite of different surveys to capture recreational catch and effort from people who fish from the shore, private boat, for hire boats (including charter boats), headboats or party boats, and guide boats” (www.st.nmfs.noaa.gov/recreational-fisheries/index).

Forest sector carbon analyses support land management planning and projects: assessing the influence of anthropogenic and natural factors

Management of forest carbon stocks on public lands is critical to maintaining or enhancing carbon dioxide removal from the atmosphere. Acknowledging this, an array of federal regulations and policies have emerged that requires US National Forests to report baseline carbon stocks and changes due to disturbance and management and assess how management activities and forest plans affect carbon stocks. To address these requirements with the best-available science, we compiled empirical and remotely sensed data covering the National Forests (one fifth of the area of US forest land) and analyzed this information using a carbon modeling framework. We demonstrate how integration of various data and models provides a comprehensive evaluation of key drivers of observed carbon trends, for individual National Forests. The models in this framework complement each other with different strengths: the Carbon Calculation Tool uses inventory data to report baseline carbon stocks; the Forest Carbon Management Framework integrates inventory data, disturbance histories, and growth and yield trajectories to report relative effects of disturbances on carbon stocks; and the Integrated Terrestrial Ecosystem Carbon Model incorporates disturbance, climate, and atmospheric data to determine their relative impacts on forest carbon accumulation and loss. We report results for several National Forests across the USA and compare their carbon dynamics. Results show that recent disturbances are causing some forests to transition from carbon sinks to sources, particularly in the West. Meanwhile, elevated atmospheric carbon dioxide and nitrogen deposition are consistently increasing carbon stocks, partially offsetting declines due to disturbances and aging. Climate variability introduces concomitant interannual variability in net carbon uptake or release. Targeting forest disturbance and post-disturbance regrowth is critical to management objectives that involve maintaining or enhancing future carbon sequestration.

Policy, practice, and partnerships for climate change adaptation on US national forests

Climate change presents a challenge to land management agencies tasked with managing landscapes to protect natural resources and provide key goods and services in the face of ecological change, complexity, and uncertainty. Land management agencies, like the U.S. Forest Service, have developed multi-faceted strategies that utilize concepts like resilience and ecological integrity to guide adaptation. To address an extant research need, we conducted a qualitative case study, consisting of interviews with Forest Service staff in the Rocky Mountain Region, to explore how local federal land managers approach adaptation. Our goals were to understand what impacts managers are finding salient, perceptions of current agency strategies, and aspects of policy and practice that support effective adaptation planning. Interview participants anticipate impacts to disturbance regimes, wildlife species, and human uses. Participants intend to draw on agency policies, like its climate change scorecard and its land management planning regulations. However, the participants note that ambiguous concepts, uncertainty, and institutional variables make adaptation planning challenging in practice. A major theme apparent in the interviews was the use of partnerships with a range of other entities to address climate change. Ambiguity associated with concepts like resilience and ecological integrity allow them to function as boundary concepts; however, this ambiguity makes it challenging for managers to operationalize these concepts. These findings revealed that climate change adaptation is leading to and revealing the need for broader governance change. Moving forward, it will be crucial to adjust current governance structures to support long-term partnerships adept at translating scientific knowledge into actions and implementing complex boundary concepts.

Economic Opportunities and Trade-Offs in Collaborative Forest Landscape Restoration

We modeled forest restoration scenarios to examine socioeconomic and ecological trade-offs associated with alternative prioritization scenarios. The study examined four US national forests designated as priorities for investments to restore fire resiliency and generate economic opportunities to support local industry. We were particularly interested in economic trade-offs that would result from prioritization of management activities to address forest departure and wildfire risk to the adjacent urban interface. The results showed strong trade-offs and scale effects on production possibility frontiers, and substantial variation among planning areas and national forests. The results pointed to spatially explicit priorities and opportunities to achieve restoration goals within the study area. However, optimizing revenue to help finance restoration projects led to a sharp reduction in the attainment of other socioecological objectives, especially reducing forest departure from historical conditions. The analytical framework and results can inform ongoing collaborative restoration planning to help stakeholders understand the opportunity cost of specific restoration objectives. This work represents one of the first spatially explicit, economic trade-off analyses of national forest restoration programs, and reveals the relative cost of different restoration strategies, as well scale-related changes in production frontiers associated with restoration investments.

Towards improving wildland firefighter situational awareness through daily fire behaviour risk assessments in the US Northern Rockies and Northern Great Basin

Wildland firefighters must assess potential fire behaviour in order to develop appropriate strategies and tactics that will safely meet objectives. Fire danger indices integrate surface weather conditions to quantify potential variations in fire spread rates and intensities and therefore should closely relate to observed fire behaviour. These indices could better inform fire management decisions if they were linked directly to observed fire behaviour. Here, we present a simple framework for relating fire danger indices to observed categorical wildland fire behaviour. Ordinal logistic regressions are used to model the probabilities of five distinct fire behaviour categories that are then combined with a safety-based weight function to calculate a Fire Behaviour Risk rating that can plotted over time and spatially mapped. We demonstrate its development and use across three adjacent US National Forests. Finally, we compare predicted fire behaviour risk ratings with observed variations in satellite-measured fire radiative power and we link these models with spatial fire danger maps to demonstrate the utility of this approach for landscape-scale fire behaviour risk assessment. This approach transforms fire weather conditions into simple and actionable fire behaviour risk metrics that wildland firefighters can use to support decisions that meet required objectives and keep people safe.

Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar measurements. Two sets of models are generated, the first relating ground estimates of AGB to airborne laser scanning (ALS) measurements and the second set relating ALS estimates of AGB (generated using the first model set) to GLAS measurements. GLAS then, is used as a sampling tool within a hybrid estimation framework to generate stratum-, state-, and national-level AGB estimates. A two-phase variance estimator is employed to quantify GLAS sampling variability and, additively, ALS-GLAS model variability in this current, three-phase (ground-ALS-space lidar) study. The model variance component characterizes the variability of the regression coefficients used to predict ALS-based estimates of biomass as a function of GLAS measurements. Three different types of predictive models are considered in CONUS to determine which produced biomass totals closest to ground-based national forest inventory estimates - (1) linear (LIN), (2) linear-no-intercept (LNI), and (3) log-linear. For CONUS at the national level, the GLAS LNI model estimate (23.95±0.45Gt AGB), agreed most closely with the US national forest inventory ground estimate, 24.17±0.06Gt, i.e., within 1%. The national biomass total based on linear ground-ALS and ALS-GLAS models (25.87±0.49Gt) overestimated the national ground-based estimate by 7.5%. The comparable log-linear model result (63.29±1.36Gt) overestimated ground results by 261%. All three national biomass GLAS estimates, LIN, LNI, and log-linear, are based on 241,718 pulses collected on 230 orbits. The US national forest inventory (ground) estimates are based on 119,414 ground plots. At the US state level, the average absolute value of the deviation of LNI GLAS estimates from the comparable ground estimate of total biomass was 18.8% (range: Oregon, −40.8% to North Dakota, 128.6%). Log-linear models produced gross overestimates in the continental US, i.e., >2.6x, and the use of this model to predict regional biomass using GLAS data in temperate, western hemisphere forests is not appropriate. The best model form, LNI, is used to produce biomass estimates in Mexico. The average biomass density in Mexican forests is 53.10±0.88t/ha, and the total biomass for the country, given a total forest area of 688,096km2, is 3.65±0.06Gt. In Mexico, our GLAS biomass total underestimated a 2005 FAO estimate (4.152Gt) by 12% and overestimated a 2007/8 radar study's figure (3.06Gt) by 19%.

Analyzing the transmission of wildfire exposure on a fire-prone landscape in Oregon, USA

We develop the idea of risk transmission from large wildfires and apply network analyses to understand its importance on a 0.75 million ha US national forest. Wildfires in the western US frequently burn over long distances (e.g., 20–50km) through highly fragmented landscapes with respect to ownership, fuels, management intensity, population density, and ecological conditions. The collective arrangement of fuel loadings in concert with weather and suppression efforts ultimately determines containment and the resulting fire perimeter. While spatial interactions among land parcels in terms of fire spread and intensity have been frequently noted by fire managers, quantifying risk and exposure transmission has not been attempted. In this paper we used simulation modeling to quantify wildfire transmission and built a transmission network consisting of land designations defined by national forest management designations and ownership. We then examined how a forest-wide fuel management program might change the transmission network and associated metrics. The results indicated that the size, shape, and fuel loading of management designations affected their exposure to wildfire from other designations and ownerships. Manipulating the fuel loadings via simulated forest fuel treatments reduced the wildfire transmitted among the land designations, and changed the network density as well. We discuss how wildfire transmission has implications for creating fire adapted communities, conserving biodiversity, and resolving competing demands for fire-prone ecosystem services.

Climate, trees, pests, and weeds: change, uncertainty, and biotic stressors in eastern US national park forests

Climate, trees, pests, and weeds: change, uncertainty, and biotic stressors in eastern US national park forests

Wildfire exposure and fuel management on western US national forests

Substantial investments in fuel management activities on national forests in the western US are part of a national strategy to reduce human and ecological losses from catastrophic wildfire and create fire resilient landscapes. Prioritizing these investments within and among national forests remains a challenge, partly because a comprehensive assessment that establishes the current wildfire risk and exposure does not exist, making it difficult to identify national priorities and target specific areas for fuel management. To gain a broader understanding of wildfire exposure in the national forest system, we analyzed an array of simulated and empirical data on wildfire activity and fuel treatment investments on the 82 western US national forests. We first summarized recent fire data to examine variation among the Forests in ignition frequency and burned area in relation to investments in fuel reduction treatments. We then used simulation modeling to analyze fine-scale spatial variation in burn probability and intensity. We also estimated the probability of a mega-fire event on each of the Forests, and the transmission of fires ignited on national forests to the surrounding urban interface. The analysis showed a good correspondence between recent area burned and predictions from the simulation models. The modeling also illustrated the magnitude of the variation in both burn probability and intensity among and within Forests. Simulated burn probabilities in most instances were lower than historical, reflecting fire exclusion on many national forests. Simulated wildfire transmission from national forests to the urban interface was highly variable among the Forests. We discuss how the results of the study can be used to prioritize investments in hazardous fuel reduction within a comprehensive multi-scale risk management framework.

Design and Governance of Multiparty Monitoring under the USDA Forest Service's Collaborative Forest Landscape Restoration Program

Project-level monitoring is a necessary component of forest restoration and has historically been neglected. The 2009 Forest Landscape Restoration Act, which created the Collaborative Forest Landscape Restoration Program (CFLRP), authorizes funding for collaboratively designed restoration projects on US National Forests. It is the only statute requiring that the US Department of Agriculture Forest Service conduct project-level monitoring, specifically requiring collaboratively designed and implemented multiparty monitoring for 15 years after a CFLRP project begins. We conducted research to understand the design of these monitoring programs, their purposes, and their associated governance structures. Our goal was to investigate how this innovative aspect of the CFLRP is proceeding in the early years of the program and to set the stage for longitudinal research on this aspect of the CFLRP. We conducted and systematically analyzed semistructured interviews with 45 participants, including federal and nonfederal partners, from the first 10 CFLRP projects. We found that monitoring programs are being designed for a variety of purposes, such as tracking ecological impacts, maintaining trust with stakeholders, supporting “adaptive” planning documents meant to cover multiple years of treatment, and “telling the story” of these projects in terms of social and economic impacts to communities. Governance structures include formal roles and responsibilities for participants but lack formal processes for incorporating monitoring data into long-term project planning. Major challenges relate to the timing requirements of the CFLRP legislation, a lack of capacity among all parties in terms of time and expertise, navigation of the distinction between research and monitoring, and the design of adaptive planning documents to cover activities for multiple years over large landscapes.

How the eastern US National Forests were formed

As a landscape ecologist conducting research on eastern forests for the US Forest Service (e.g., www.nrs.fs.fed.us/atlas), I was eager to learn about how the eastern National Forests came to be, as these forests now play such an important part of the natural world and provide a large carbon sink. The book did not disappoint and I'm confident that it will be informative and interesting to a large swath of people with interests in the eastern US landscape or environmental history.

Visitor Preferences for Campfires in US National Forest Developed Campgrounds

Visitor Preferences for Campfires in US National Forest Developed Campgrounds

A sample design for globally consistent biomass estimation using lidar data from the Geoscience Laser Altimeter System (GLAS)

BackgroundLidar height data collected by the Geosciences Laser Altimeter System (GLAS) from 2002 to 2008 has the potential to form the basis of a globally consistent sample-based inventory of forest biomass. GLAS lidar return data were collected globally in spatially discrete full waveform “shots,” which have been shown to be strongly correlated with aboveground forest biomass. Relationships observed at spatially coincident field plots may be used to model biomass at all GLAS shots, and well-established methods of model-based inference may then be used to estimate biomass and variance for specific spatial domains. However, the spatial pattern of GLAS acquisition is neither random across the surface of the earth nor is it identifiable with any particular systematic design. Undefined sample properties therefore hinder the use of GLAS in global forest sampling.ResultsWe propose a method of identifying a subset of the GLAS data which can justifiably be treated as a simple random sample in model-based biomass estimation. The relatively uniform spatial distribution and locally arbitrary positioning of the resulting sample is similar to the design used by the US national forest inventory (NFI). We demonstrated model-based estimation using a sample of GLAS data in the US state of California, where our estimate of biomass (211 Mg/hectare) was within the 1.4% standard error of the design-based estimate supplied by the US NFI. The standard error of the GLAS-based estimate was significantly higher than the NFI estimate, although the cost of the GLAS estimate (excluding costs for the satellite itself) was almost nothing, compared to at least US$ 10.5 million for the NFI estimate.ConclusionsGlobal application of model-based estimation using GLAS, while demanding significant consolidation of training data, would improve inter-comparability of international biomass estimates by imposing consistent methods and a globally coherent sample frame. The methods presented here constitute a globally extensible approach for generating a simple random sample from the global GLAS dataset, enabling its use in forest inventory activities.