Alan A. Ager

Understanding Ungulate Herbivory—Episodic Disturbance Effects on Vegetation Dynamics: Knowledge Gaps and Management Needs

Abstract Herbivory by wild and domestic ungulates is a chronic disturbance that can have dramatic effects on vegetation dynamics. Herbivory effects, however, are not easily predicted under different combinations of episodic disturbance such as fire, timber harvest, drought, and insect defoliation. This lack of predictability poses a substantial obstacle to effective management of ungulate herbivory. Traditional models of vegetation transition in forested ecosystems have ignored the influences of ungulate herbivory, while research on effects of herbivory have typically excluded other disturbances. Of the 82 contemporary studies on ungulate herbivory we examined, only 15 (18%) considered the interactions of herbivory with episodic disturbances. Moreover, only 26 (32%) evaluated vegetation response to ungulate herbivory beyond the simplistic treatment levels of herbivory versus no herbivory. Only 31 (38%) used a repeated-measures design of sampling responses over 3 or more time periods. Finally, just 7 (9%) explicitly made inferences to large landscapes such as watersheds, which are often used for management planning. We contend that useful landscape research on herbivory must examine the interactions of ungulate grazing with other disturbance regimes at spatial extents of interest to forest and rangeland managers and under varying ungulate densities and species. We identify herbivory models that could accommodate such information for forested landscapes in western North America. Such models are essential for identifying knowledge gaps, designing future studies, and validating relations of ungulate herbivory on landscapes where episodic disturbances are common, such as those of western North America.

A comparative risk assessment framework for wildland fire management: the 2010 cohesive strategy science report

The FLAME Act of 2009 requires the U.S. Department of Agriculture Forest Service and the U.S. Department of Interior to submit to Congress a Cohesive Wildfire Management Strategy. In this report, we explore the general science available for a risk-based approach to fire and fuels management and suggest analyses that may be applied at multiple scales to inform decisionmaking and tradeoff analysis. We discuss scientific strengths and limitations of wildfire risk assessment frameworks, including the benefit of broad scalability as demonstrated by four recent case studies. We further highlight the role of comparative risk assessment, which extends the analysis to include the decision space available to managers and stakeholders to allow them to explore the tradeoffs between alternative courses of action. We identify scientific limitations of the analytical protocol and discuss questions of how to better address climate change, smoke modeling issues, and socioeconomic vulnerability, and how to better quantify treatment effectiveness. Key challenges are: achieving a balance between retaining analytical flexibility at regional and sub-regional planning scales while simultaneously retaining data and methodological consistency at the national scale, and identifying and aligning regional and national priorities to inform multi-objective strategy development. As implementation proceeds, the analytical protocol will no doubt be modified, but the contents of this report comprise a rigorous and transparent framework for comparative risk assessment built from the best available science.

Mitigating spatial differences in observation rate of automated telemetry systems

Wildlife ecologists are increasingly interested in determining spatial distributions and habitat use of ungulates from locations estimated from both conventional and automated telemetry systems (ATS). If the performance of an ATS causes spatial versus random variation in probability of obtaining an acceptable location (observation rate), analysis of habitat selection is potentially biased. We define observation rate as the percentage of acceptable locations (i.e., those that meet signal strength, signal-to-noise ratios, geometric dilution of precision criteria) of the total locations attempted. An ATS at the Starkey Experimental Forest and Range (Starkey) in Oregon tracks movements of elk (Cervus elaphus), mule deer (Odocoileus hemionus), and cattle. We detected localized variation in observation rate of stationary radiocollars in 1993. Subsequently, we devised a method to estimate observation rate at various spatial scales using animal location data over 4 years (1992-95 ; n = 907,156 location attempts) to determine if the variation was spatial or random. We formulated 5 variants of a general linear model to obtain estimates of spatial variation in observation rate. All 5 models assumed spatially correlated error terms estimated from isotropic semivariograms. Three models included environmental variables as covariates correlated with observation rate. Models then were compared based on mean error, coefficient of determination, and residual plots. Random variation accounted for 47-53%, and spatial variation accounted for 38-45% of the variation in observation rate. One model was selected to demonstrate application of the correction to mitigate spatial bias in observation rate. Our results demonstrate the utility of semivariograms to detect and quantify spatial variation in observation rate of animal locations determined from an ATS.

Methods for integrated modeling of landscape change: Interior Northwest Landscape Analysis System.

The Interior Northwest Landscape Analysis System (INLAS) links a number of resource, disturbance, and landscape simulations models to examine the interactions of vegeta-tive succession, management, and disturbance with policy goals. The effects of natural disturbance like wildfire, herbivory, forest insects and diseases, as well as specific management actions are included. The outputs from simulations illustrate potential changes in aquatic conditions and terrestrial habitat, potential for wood utilization, and socioeconomic opportunities. The 14 chapters of this document outline the current state of knowledge in each of the areas covered by the INLAS project and describe the objectives and organization of the project. The project explores ways to integrate the effects of natural disturbances and management into planning and policy analyses; illustrate potential conflicts among current policies, natural distrubances, and management activities; and explore the policy, economics, and ecological constraints associated with the application of effective fuel treatments on midscale landscapes in the interior Northwest. Abstract The concept of a process for evaluating policy direction and management options for subbasin-size landscapes in the interior West evolved from the Pacific Northwest Research Stations Research Initiative for Improving Forest Ecosystem Health and Productivity in Eastern Oregon and Washington. The Interior Northwest Landscape Analysis System (INLAS) project was initiated to explore this concept and began with meetings of resource managers and scientists from various disciplines and institutions. This group suggested ways to build an integrated set of tools and methods for addressing resource management questions on large, multiowner landscapes. The papers in this volume are the outcome of these meetings and document our initial approach to developing an integrated landscape analysis framework. Collectively, the papers illustrate the diversity of methods for modeling different resources and reflect the inherent complexity of linking models to create a functional framework for integrated resource analysis. We are still a long way from a perfect tool, the linkages among the chapters are not always apparent, and integration issues have not been consistently addressed. We cannot yet address the interrelationships between many key natural and anthropomorphic processes on large landscapes. We also found that integration forced scientists to generalize relationships and to summarize detailed research findings in order to incorporate their disciplines at the landscape scale of the INLAS framework. With a growing interest in integrated natural resource modeling, we concluded that, despite the fact that we have not solved all the problems associated with integrating information from different scientific disciplines, …

Network analysis of wildfire transmission and implications for risk governance

We characterized wildfire transmission and exposure within a matrix of large land tenures (federal, state, and private) surrounding 56 communities within a 3.3 million ha fire prone region of central Oregon US. Wildfire simulation and network analysis were used to quantify the exchange of fire among land tenures and communities and analyze the relative contributions of human versus natural ignitions to wildfire exposure. Among the land tenures examined, the area burned by incoming fires averaged 57% of the total burned area. Community exposure from incoming fires ignited on surrounding land tenures accounted for 67% of the total area burned. The number of land tenures contributing wildfire to individual communities and surrounding wildland urban interface (WUI) varied from 3 to 20. Community firesheds, i.e. the area where ignitions can spawn fires that can burn into the WUI, covered 40% of the landscape, and were 5.5 times larger than the combined area of the community core and WUI. For the major land tenures within the study area, the amount of incoming versus outgoing fire was relatively constant, with some exceptions. The study provides a multi-scale characterization of wildfire networks within a large, mixed tenure and fire prone landscape, and illustrates the connectivity of risk between communities and the surrounding wildlands. We use the findings to discuss how scale mismatches in local wildfire governance result from disconnected planning systems and disparate fire management objectives among the large landowners (federal, state, private) and local communities. Local and regional risk planning processes can adopt our concepts and methods to better define and map the scale of wildfire risk from large fire events and incorporate wildfire network and connectivity concepts into risk assessments.

A Burning Problem: Social Dynamics of Disaster Risk Reduction through Wildfire Mitigation

Disasters result from hazards affecting vulnerable people. Most disasters research by anthropologists focuses on vulnerability; this article focuses on natural hazards. We use the case of wildfire mitigation on United States Forest Service lands in the northwestern United States to examine social, political, and economic variables at multiple scales that influence fire hazard and risk reduction treatments and their effectiveness. Variables highlighted include policy direction to prioritize wildfire risk reduction in the wildland-urban interface, laws and policies that make treating fuels in some national forest land management allocations challenging, social and political constraints on using prescribed fire, agency budget and target pressures, and integrating fire hazard reduction into forest management projects having multiple objectives. These variables compromise the effectiveness of wildfire mitigation treatments. Understanding the social dynamics of natural hazard mitigation is important because they affect its outcomes, creating differential exposure to natural hazards—one component of social vulnerability. Interdisciplinary research to identify how the social dynamics of natural hazard mitigation influence hazard reduction outcomes can contribute to more informed and effective approaches to disaster risk reduction.

The Science and Opportunity of Wildfire Risk Assessment

Wildfire management within the United States continues to increase in complexity, as the converging drivers of (1) increased development into fire-prone areas, (2) accumulated fuels from historic management practices, and (3) climate change potentially magnify threats to social and ecological values (Bruins et al., 2010; Gude et al., 2008; Littell et al., 2009). The need for wildfire risk assessment tools continues to grow, as land management agencies attempt to map wildfire risk and develop strategies for mitigation. Developing and employing wildfire risk assessment models can aid management decision-making, and can facilitate prioritization of investments in mitigating losses and restoring fire on fire prone landscapes. Further, assessment models can be used for monitoring trends in wildfire risk over space and across time.

ArcFuels10 system overview

Fire behavior modeling and geospatial analyses can provide tremendous insight for land managers as they grapple with the complex problems frequently encountered in wildfire risk assessments and fire and fuels management planning. Fuel management often is a particularly complicated process in which the benefits and potential impacts of fuel treatments need to be demonstrated in the context of land management goals and public expectations. The fuel treatment planning process is complicated by the lack of data assimilation among fire behavior models and weak linkages to geographic information systems (GIS), corporate data, and desktop office software. ArcFuels10 is a streamlined fuel management planning and wildfire risk assessment system that creates a trans-scale (stand to large landscape) interface to apply various forest growth and fire behavior models within an ArcGIS platform to design and test fuel treatment alternatives. The new version of ArcFuels has been implemented on Citrix at the Forest Service Enterprise Production Data Center, eliminating the need for desktop GIS, improving connectivity to the corporate geospatial databases housed at the data centers, and enabling sharing of information among Forest Service employees. This overview introduces ArcFuels10 and the tools available within the system. Further information, including download information, demonstration data, and a tutorial, can be found at http://www.fs.fed.us/wwetac/arcfuels/index.html.

ArcFuels User Guide and Tutorial: for use with ArcGIS 9

Fuel management planning can be a complex problem that is assisted by fire behavior modeling and geospatial analyses. Fuel management often is a particularly complicated process in which the benefits and potential impacts of fuel treatments need to be demonstrated in the context of land management goals and public expectations. Fire intensity, likelihood, and effects can be analyzed for multiple treatment alternatives. Depending on the goal, the effect of treatments on wildfire impacts can be considered at multiple scales, from a single forest stand or planning unit to a watershed to a national forest to the Nation as a whole. The fuel treatment planning process is complicated by the lack of data assimilation among fire behavior models and by weak linkages to geographic information systems, corporate data, and desktop office software. ArcFuels is a streamlined fuel management planning and wildfire risk assessment system. ArcFuels creates a trans-scale (stand to large landscape) interface to apply various forest growth and fire behavior models within an ArcGIS? platform to design and test fuel treatment alternatives. It eliminates a number of tedious data transformations and repetitive processes that have plagued the fire operations and research communities as they apply the models to solve fuel management problems. This User Guide and Tutorial includes an overview of ArcFuels and its functionality, a tutorial highlighting all the tools within ArcFuels, and fuel treatment planning scenarios. There is also a section for obtaining, formatting, and setting up ArcFuels for use with your own data. It is assumed that the reader has basic familiarity with the Forest Vegetation Simulator (forest growth and yield program) and FlamMap (landscape fire behavior model).