104

Chapter 8: Simulating Mortality From Forest

Insects and Diseases

Alan A. Ager, Jane L. Hayes, and Craig L. Schmitt1

We describe methods for incorporating the effects of insects and diseases on coniferous

forests into forest simulation models and discuss options for including this capability in

the modeling work of the Interior Northwest Landscape Analysis System (INLAS) project.

Insects and diseases are major disturbance agents in forested ecosystems in the Western United States, and over time, are responsible for major changes in forest composition

and structure. Incorporating their effects into forest simulation models is difficult, especially the representation of large, episodic insect epidemics. Much empirical data on

insect mortality is available for modelers, and an array of mortality models have been

incorporated into indivdual tree growth simulators. Scaling these models to simulate

epidemics on landscapes requires, among other things, parameters that describe the

amplitudes and periodicities of pathogen/pest population cycles. Incorporating insect and

disease effects into forest simulation models makes it possible to explore ways to minimize epidemic conifer mortality and secondary interactions with other disturbances. In

addition, the inclusion of other resource goals and financial considerations makes it possible to analyze the costs and benefits of forest management activities that target stands

with high risk of mortality. We discuss options for modeling insect and disease mortality

within the INLAS project.

Keywords: Forest insects and diseases, forest stand simulation, tree mortality, landscape simulation.

Abstract

1

 Alan A. Ager is an operations research analyst, and Jane L.

Hayes is a research biological scientist, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station,

Forestry and Range Sciences Laboratory, Craig L. Schmitt is a

plant pathologist, U.S. Department of Agriculture, Forest Service,

Blue Mountains Pest Management Service Center, 1401 Gekeler

Lane, La Grande, OR 97850.
105

Simulating the potential impacts of insects and diseases on forests like those in the

Blue Mountains of northeast Oregon is challenging. Defoliators (Torgersen 2001), bark

beetles (Dendroctonus spp.) (Hayes and Daterman 2001), mistletoe (Arceuthobium spp.)

(Parks and Flanagan 2001), and root diseases (Thies 2001) all have unique population

dynamics, epidemiology, and effects on forest vegetation. Interactions among these disturbance agents as well as with management activities and physical disturbances such

as wildfire and windthrow are also significant. Collectively, insects and diseases are major determinants of forest composition and structure over time, and thus warrant serious

attention in forest planning and landscape simulation efforts (Quigley et al. 2001). Previous federal and state planning efforts may have underestimated the potential effects of

insects and diseases in projections of future forest conditions, which may have reduced

the effectiveness of these plans (Gast et al. 1991).

In this paper, we review methods to model conifer mortality caused by major forest insects and diseases within the framework of landscape planning models such as those

described in Ager (Chapter 3), Bettinger et al. (Chapter 4), and Hemstrom (Chapter 2).

Much of this work involves integrating and parameterizing existing mortality and risk

models implemented elsewhere, such as in the Forest Service Forest Vegetation Simulator (FVS) (Wykoff et al. 1982). However, major gaps exist in the area of modeling spatial spread rates data for some insect species, and the process of simulating the

complex cycles of insect populations and disease centers on a large landscape is a

challenge for any landscape planning effort. The following discussion treats forest insects

separately from forest diseases. We focused on major pests in the Blue Mountains

based on historical survey data (Gast et al. 1991) with the broad goal of summarizing

existing tools, identifying major gaps, and proposing research and development to create

a robust set of methods for modeling mortality caused by forest insects and diseases.

Extensive descriptions and reviews of insects and diseases and their effects on forest

trees in the Blue Mountains can be found in Filip et al. (1996), Gast et al. (1991), Hayes

and Daterman (2001), Parks and Flanagan (2001), Thies (2001), and Torgersen (2001).

Aerial survey maps of insect infestations provide a detailed chronology of infestations

over a 50-year period for the Blue Mountains (USDA FS 2003a).

Pertinent aspects of insect biology in the context of landscape planning models center

on the dynamics of infestations and include the periodicity and amplitude of the infestation cycles, the spatial pattern of the initial infestation centers, and the resulting damage

they cause in terms of mortality and reduced vigor. The divergent life histories of the major mortality-causing insects complicate an integrated modeling approach in landscape

planning models.

Tree-level mortality models for the major mortality-causing insects are all implemented in

FVS extensions that are described in detail elsewhere (USDA FS 2003b) There are

many case histories of modeling insect- and disease-caused mortality at the stand (e.g.,

Cameron et al. 1990, Gast et al. 1991; also see Hayes and Daterman 2001, Torgersen

2001), and to a lesser extent, landscape scale (Beukema et al. 1997, Eager and Angwin

1997, Graetz 2000, Smith et al. 2002). Landscape simulations are usually accomplished

by imputing tree lists for stands where data are incomplete. Insect mortality models can

be built ad hoc in FVS when no formal model exists by using the COMPUTE statements

and the event monitor to trigger mortality on specific host trees when stand conditions

meet an established susceptibility criterium. The existing FVS model extensions differ in

their state of validation and complexity and require many parameters to trigger outbreaks

and regulate the mortality. Recent efforts have focused on simulating multiple pests

(e.g., Roberts 2002, Roberts and Weatherby 1997), examining interactions among pests

Insect Mortality

Models

Introduction
106

(e.g., Eager and Angwin 1997), and modeling the spatial spread of insects (e.g., Smith

et al. 2002). The use of the FVS Parallel Processor (Crookston and Stage 1991) vastly

simplifies the modeling of insect spread among stands within the FVS system.

Modeling endemic insect mortality requires parameters that define stand and tree susceptibility and mortality rates among the tree type within the stand. Modeling epidemics

implies a spatial extent beyond an individual stand, and additional parameters are required to control (1) triggering of an outbreak; and (2) duration, intensity, and frequency

of occurrence (Roberts and Weatherby 1997). In the case of the westwide pine beetle

model (Beukema et al. 1997), a spatially explicit model that considers stand contagion,

parameters also are needed to control the rate of spread. Parameters needed to simulate insect epidemics are described individually below.

Stand susceptibility models use stand attributes such as average size and density of

host species and physical site factors including ecoclass, slope, aspect, and elevation

in determining susceptibility to insect outbreaks. In a few cases, spatial information such

as the distance to the nearest infestation also is considered (e.g., Shore et al. 2000). In

FVS, stand susceptibility models can be built and implemented by using FVS COMPUTE statements that calculate relevant stand metrics (Roberts and Weatherby 1997).

Outbreaks can be triggered as a function of susceptibility levels or by using assumptions

about intrinsic insect population cycles (Monserud and Crookston 1982). The resultant

mortality is dependent on other factors such as susceptibility levels and outbreak duration and intensity. Epidemic triggers can be regulated independently of endemic mortality

by changing the probability of the two levels of mortality and associated intensity of the

outbreaks. Some FVS model extensions have keywords that specify whether stands are

part of widespread or local outbreaks. Assumptions that are tailored to specific insect

pests are usually made about the interval between outbreaks and their duration. The

outbreak is manifested in mortality if susceptibility conditions are appropriate. Roberts

and Weatherby (1997) provide examples of simulating insect outbreaks by using the

FVS extensions.

Population dynamics, spread, and host availability affect duration of infestations. The

FVS insect extensions have defaults for duration. For instance, the default for Douglas-fir

beetle (Dendroctonus pseudotsugae Hopkins) pest extension (Marsden et al. 1994) is 4

years in the Blue Mountain variant. In the western spruce budworm (Choristoneura

occidentalis Freeman) extension (Crookston et al. 1990, Sheehan et al. 1989), the duration is related to a hazard rating system where low hazard generates a 5-year, moderate

a 10-year, and high a 15-year duration. Management activities that alter susceptibility

after an outbreak begins can alter the duration. Mortality of the host also affects duration

of outbreak.

Intensity is usually expressed as a function of the number of host trees killed by tree

species and diameter class per FVS cycle. Some models such as the Western Spruce

Budworm Extension can incorporate other types of damage like top kill and decreased

growth from defoliation. Intensity is modeled in concert with spread rate among stands

as part of simulating an epidemic. Damage is affected by using mortality functions in the

FVS extensions, either within an FVS extension or within outside software.

At least two methods have been applied to simulate the spread of an insect epidemic.

One approach uses Monte Carlo methods that simulate gradual growth of the infestation

among the population of stands in the simulation (Roberts and Weatherby 1997). This

approach does not consider stand contagion but rather uses random selection of stands

Triggering an Outbreak

Duration of Outbreaks

Intensity of Outbreaks

Spread

Determining

Susceptibility Levels to

Epidemic Events
107

that meet susceptibility criteria. The probability of an infestation can be changed in this

process to alter the rate at which stands become infested. Multiple probabilities can be

used in a similar Monte Carlo process to trigger low-level endemic mortality as well as

large epidemics. A more sophisticated approach to insect spread that considers stand

contagion was developed in the westwide Pine Beetle Model (Beukema et al. 1997,

Smith et al. 2002). Stands are simultaneously simulated by using the FVS parallel processor, and stand-to-stand spread of beetles is simulated.

The major tree diseases in the Blue Mountains are root disease and dwarf mistletoe.

Although dwarf mistletoe is primarily modeled as causing growth reduction, root disease

is simulated as causing mortality. Principal root diseases include Armillaria root disease

caused by Armillaria ostoyae, laminated root rot caused by Phellinus weirii (Murr.) Gilb.,

Annosus root disease caused by Heterobasidion annosum (Fr.) Bref., and black stain

root disease caused by Leptographium wageneri Kendrick M.J. Wingfield. Extensive

reviews of these diseases and their occurrences in the Blue Mountains can be found in

Hagle and Goheen (1986), Hessburg et al. (1994), Campbell and Liegel (1996), Filip et

al. (1996), and Thies (2001). Fundamental differences in the biology between insects and

diseases call for different modeling methods. Although contagion is a factor with diseases, the spread is too slow to consider as part of a landscape process (e.g., 2 feet per

year). Diseases can be modeled as endemic mortality, meaning that the mortality is

chronic, not episodic, and mortality is an intrastand or intrapolygon, rather than an

interstand or interpolygon process. In contrast to disease, the most important component in simulation models for insects is the relationship between mortality and management activities. High levels of management activities can bring about more infections and

mortality (Thies 2001), whereas in insect pests, management is largely viewed as a way

to reduce spread.

As with insects, extensive modeling capability for diseases exists in FVS (Frankel 1998,

Hawksworth et al. 1995). The western root disease model in FVS simulates the effects

of Armillaria root disease, laminated root rot, and Annosus root disease (Frankel 1998).

Considerable effort is required to build keyword files and calibrate these models for application on large landscapes. Management to control diseases (e.g., boron treatments)

can be simulated with FVS extensions. Given the slow rate of disease spread, many of

the concerns with insect pests in terms of interstand spread and cyclical epidemics are

not an issue with diseases.

The previous discussion focused on the modeling of tree mortality from insects and diseases. Depending on the overall objectives, the insect and disease considerations in

landscape planning can often be addressed by using only measures of infestation or

infection risk rather than predicting actual tree mortality. Risk models measure the longterm outlook for the effects from pests and offer a relatively simple approach to characterize forest conditions in terms of a latent potential to experience mortality, and are

often used when tree-level mortality modeling is not practical. Numerous risk rating models for insects and diseases have been developed and widely applied in coniferous forests in the intermountain West and elsewhere (see Hayes and Daterman 2001,

Hessburg et al. 1994, Lehmkuhl et al. 1994, Steele et al. 1996). These models are typically used in watershed or National Environmental Policy Act (NEPA)-related analysis to

help identify susceptible stands and assign treatment priorities. Most models output

categorical values that measure relative risk, and a few quantify risk in probabilistic

terms. Risk assessments are used to identify treatment priorities to reduce hazards from

infestations or epidemics. Many, but not all of the models, have been tested through field

validation and are published with accompanying software. Risk models have been added

Insect and Disease

Risk Models

Disease Mortality

Models
108

to FVS as event monitor applications for the mountain pine (Dendroctonus ponderosae

Hopkins) and spruce (D. rufipennis (Kirby)) beetle. There is also integrated pest risk

software that calculates multiple insect and disease risk ratings (Ager 1996, Hessburg

et al. 1994, Scott et al. 1998).

Data requirements for the risk models differ ranging from coarse photointerpreted stand

characteristics such as canopy closure to detailed stand metrics such as the basal area

of host species within a specific diameter range. In addition, many models require physiographic inputs like slope, aspect, elevation, and other physical attributes. A number of

risk models have subcomponents that independently measure risk from susceptibility to

better assess probability of mortality.

Although risk models offer a rapid way to address insect and disease considerations in

landscape planning projects, their shortcoming is that they generally do not consider

population levels and cycles, and therefore only measure the longer term risk of an infestation and mortality.

State transition models of landscape vegetation (Hemstrom et al. Chapter 2) use discrete

vegetation classes and transition probabilities to model change from succession, management, and disturbance (Kurz et al. 2000). In contrast to tree-level growth models like

FVS, the growth and mortality of individual trees is encapsulated in the transition probabilities. The use of states and transitions reduces the complexity of landscape simulations, although there remains a significant challenge to estimate and validate transition

probabilities. There are several case studies using a state and transition approach to

modeling forest landscape change by using the Vegetation Dynamics Development Tool

(VDDT) and the Tool for Exploratory Landscape Analysis (TELSA) (Kurz et al. 2000). A

prototype TELSA model built for the Upper Grande Ronde considered insect mortality

from spruce budworm and Douglas-fir beetle; and spruce beetle and mountain pine

beetle in ponderosa (Pinus ponderosa Dougl. ex Laws.) and lodgepole pine (P. contorta

Dougl. ex Loud.). Insect epidemics were simulated, and mortality was represented by

changing the vegetative state of infested stands based on host mortality. Parameters for

simulating epidemics were obtained from data on historical infestations including USDA

Forest Service, Pacific Northwest Region aerial survey maps (USDA FS 2003a) and

other historical information (e.g., Gast et al. 1991). Pertinent information for each insect

vector included periodicity of outbreaks and the percentage of host type infested during

an outbreak. Initial results from this model show how different management scenarios

change future extent and severity of insect epidemics and the effects of alternative forest

management schedules.

Alternatives to the state and transition approach are stand-level models that use individual-based tree growth models to simulate multiple stands on a landscape. Incorporating insect- and disease-caused mortality into these models is relatively straightforward.

For instance, a simple landscape simulation with insect and disease mortality can be

built by simulating all the stands in a landscape with FVS and FVS pest extensions

(Roberts and Weatherby 1997). This approach can be enhanced to consider spreading

of infestations by using the FVS parallel processing extension, as in the westwide pine

beetle model (Smith et al. 2002). When combined with the array of other FVS extensions and postprocessors (USDA FS 2003c), the multistand approach of using FVS

and the parallel processing extension provides a flexible system that can address a

variety of scenarios.

Landscape Modeling

Systems
109

More complex are the stand-alone optimization models such as the Simulation and

analysis of forests with episodic Disturbances (SafeD) model (Bettinger et al. Chapter 4,

Graetz 2000, Wedin 1999), which derive their growth equations from FVS code but do

not have direct linkages to FVS and the pest extensions. In SafeD, insect and disease

mortality was modeled as an endemic process as part of stand growth (Wedin 1999),

and epidemic or periodic mortality from insects or diseases was not considered.

Each of the methods (FVS-related software, state transitions models, landscape simulation/optimization models) for simulating vegetation change for the INLAS project requires

different amounts and kinds of development to enable modeling of insect and disease

mortality. The major tasks required to incorporate insect- and disease-caused mortality

by using FVS-related software approach (Ager Chapter 3) involve issues of local calibration and experience to run the FVS extensions for Douglas-fir beetle, western spruce

budworm, Douglas-fir tussock moth (Orgyia pseudotsugata McDunnough), and mountain

pine beetle on lodgepole pine. Additionally, ad hoc models for mountain pine beetle on

ponderosa pine, western pine beetle (D. brevicomis LeConte) on ponderosa pine, and

spruce beetle on Engelmann spruce (Picea engelmannii Parry ex Engelm.), such as

those illustrated by Roberts and Weatherby (1997) for ponderosa pine, need to be evaluated on local stand conditions. A major part of this work will be estimation of parameters

for epidemic lengths, periodicities, and spread rates for Blue Mountain conditions. For

INLAS, we will experiment with FVS insect extensions in concert with the development

of FVS-related landscape simulation tools.

Stand-alone landscape optimization models such as those described by Bettinger et al.

(Chapter 4) pose a larger problem within the context of INLAS. Although modeling endemic mortality can be accomplished by using mortality functions derived from the literature, modeling epidemics in stand-alone optimization models will require substantial

work and is probably beyond the scope of this project. A first step would be converting

FVS insect extensions to run within other stand-alone programs. Parameters are then

needed for epidemic lengths, periodicities, and spread rates for Blue Mountain conditions. With this accomplished, epidemics could be simulated much like wildfire as described by Bettinger et al. (Chapter 4), where simulations are stopped each decade to

run the FARSITE fire model (Finney Chapter 9). Insect mortality could be simulated every

cycle, with epidemic parameters carrying over from cycle to cycle. Supporting epidemic

parameters described above, including spread rate, intensity, and duration, are needed.

An alternative that would take advantage of many of the FVS insect and disease models

could be achieved by using the pest extensions in FVS to process tree lists from a

stand-alone optimization model at each cycle. Specifically the Douglas-fir beetle, western spruce budworm, and western pine beetle can be applied to tree lists generated by

SafeD and used to trigger single-cycle tree damage and mortality. Components of the

FVS insect and disease models that consider more than one cycle would need to be

incorporated into the optimization model. For instance, the scheduling of periodic outbreaks could be implemented by writing the appropriate keyword files for FVS. The integration of insect and disease mortality into forest simulation/optimization models would

provide a way to explore how different landscape goals are affected by these disturbance

agents. Both stand and landscape goals can incorporate financial or other considerations to allow the estimation of the marginal cost of reducing insect and disease effects. Landscape goals also can be combined into multiobjective goals. For instance,

stand goals would minimize susceptibility, whereas landscape goals could alter the

spatial arrangement of susceptible stands to minimize spread (see Bettinger et al.

Chapter 4). Landscape planning models can explore alternative scenarios by applying

Research Approach

Options for Different

Modeling Frameworks
110

management activities targeting specific insect pests. Results from simulations could be

applied by forest managers, pest management practitioners, and researchers concerned

with landscape planning and simulation.

State and transition models require specific transitions to represent mortality of the different insect and disease agents (Hemstrom et al. Chapter 2). Like the other modeling

approaches, the major part of this work is estimating characteristics of epidemics for

Blue Mountain conditions. We discuss approaches to estimating these parameters

below.

As mentioned earlier, a key component of any effort to model insect and disease mortality is parameters that describe the lengths, periodicities, and spread rate of epidemics

for each insect of concern for local conditions. This section presents the result of a preliminary work to quantify these parameters by using data on past infestations. Although

ultimately the size of epidemics is dependent on host type availability and secondary

factors that influence epidemic growth (e.g., weather, spatial patterns of host, natural

disturbance), realistic values must be used for epidemic cycles.

The importance of host availability and other factors is illustrated with historical conditions in the Blue Mountains. For example, it is assumed that the large historical outbreaks of western pine beetle have not been repeated in recent times owing to a

decrease in large-diameter ponderosa pine. In contrast, infestations by defoliators have

increased with the extent of defoliator host type (e.g., true firs) (e.g., Powell 1994).

Spruce beetle epidemics are often triggered by wind events that result in a large number

of downed spruce (e.g., Gast et al. 1991). Another example is Douglas-fir beetle, where

trees weakened during defoliator outbreaks seem especially susceptible to Douglas-fir

beetles (e.g., Wright et al. 1984). Hence, bark beetle activity is often observed after several years of budworm or tussock moth defoliation in the Blue Mountains.

Despite the dependence of outbreak size on host and other factors, we tried to gain

some preliminary insight into the spatiotemporal patterns of insect epidemics by surveying historical outbreaks. For instance, it would be of interest to know how epidemics are

manifested in terms of the numbers of individual infestation sites and the average size.

Using data from the annual Aerial Insect Detection Survey conducted by the USDA Forest Service Pacific Northwest Region and Oregon Department of Forestry, we summarized and examined patterns of past insect infestations in the Blue Mountains. Additional

information was obtained from Gast et al. (1991). These data clearly show the difference

between epidemic and endemic infestations, and that endemic levels for one insect may

exceed endemic levels for others (table 6, fig. 26). Bark beetles have relatively active

endemic populations in the Blue Mountains compared to defoliators, and the acres affected during an epidemic range from a twentyfold to thirtyfold increase for some species, whereas others can cause a onefold to several hundredfold increase. Endemic

levels of defoliators are so low that damage is not visible. Clearly, the defoliator cycles

are high amplitude, and in the case of spruce budworm, have a long cycle. Although

epidemics were characterized by increases in both infestation size and number of sites,

the latter appears more important than the former. For instance, the individually mapped

beetle infestations are all about 1.5 to three times larger for the epidemic versus endemic

periods, whereas the number of polygons increased by an average of six times. We note

that this difference could be an artifact of the mapping procedure. Also, the spatial arrangement of host stands could account for a major component of the size versus number contrast.

Estimating Parameters

for Insect Epidemic

Cycles
111

Table 6—Summary of aerial survey insect damage surveys showing population parametersa

Average

Population Average Average Number of Proportion mapped

Species status duration periodicity polygons of years unit Total area

– – – – – Years – – – – – Percent – – – – Acres – – – –

Douglas-fir Endemic 108 43.75 70 7,560

beetle Epidemic 8 15 661 65.25 265 175,165

Fir engraver Endemic 137 79.20 190 26,030

beetle Epidemic 5 20 951 21.80 257 244,407

Western pine Endemic 108 75.00 143 15,444

beetle Epidemic 4 16 299 25.00 364 108,836

Mountain pine Endemic 68 70.80 200 13,600

beetle in Epidemic 9 63 749 29.20 561 420,189

lodgepole

pine

Mountain pine Endemic 216 78.70 154 33,264

beetle in Epidemic 5 14 986 21.30 315 310,590

ponderosa

pine

Spruce beetle Endemic 23 85.40 225 5,175

Epidemic 6+ Variable: 129 14.60 348 44,892

disturbancerelated

Douglas-fir Endemic 0 81.10 0 0

tussock Epidemic 3 9 353 18.90 557 196,621

moth

Western spruce Endemic 0 56.60 0 0

budworm Epidemic 12 36 583 43.40 4,858 2,832,214

a

 Data were obtained between 1954 and 2001 and pertain to all forested lands in the Blue Mountains province. Low damage (BS-L and BS-1)

for western spruce budworm were not included because they do not generally indicate host mortality.
112

At a minimum, table 6 and figure 26 illustrate qualitative features of insect infestations

and illustrate the stochastic nature of this particular natural disturbance. In addition, the

data show the relative importance of modeling spatial spread and contagion among the

various insect pests. Defoliators like western spruce budworm that are capable of rapid

spread over very large areas probably do not warrant detailed modeling of spread because most or all host are infested over a short period. In contrast, insects that have

longer infestations per area affected (i.e., broad peaks, such as mountain pine beetle in

lodgepole pine and fir engraver beetle [Scolytus ventralis LeConte in true fir]) show longer

infestation periods per total acres infested, suggesting constraints to spreading are regulating these infestations more than in the western spruce budworm. Here, more detailed

spread models might be warranted.

It should be noted that the data show population status data for the Blue Mountains as a

whole, and it is possible to have localized epidemics that result in significant damage.

Douglas-fir tussock moth epidemics have characteristically developed in several discrete

and different areas within the Blue Mountains over the last century. However, in most

cases, epidemic populations of various insects and associated damage develop concurrently or occur over large areas within the Blue Mountains.

Figure 26—Acres infested with major insect pests as derived from aerial survey information and Gast et al. (1991). Peak values of about

3 million acres for western spruce budworm were truncated to improve visibility of other data. Budworm damage codes for low damage

(BS-L, BS-1) were omitted.

0

200,000

400,000

600,000

800,000

1,000,000

1,200,000

1,400,000

1945 1950 1955 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005

Year

Acres infested

Douglas-fir beetle Spruce beetle

Fir engraver Mountain pine beetle-lodgepole

Mountain pine beetle-ponderosa Western pine beetle

Western spruce budworm Douglas-fir tussock moth
113

One additional factor that must be considered with these data is that aerial survey

sketch mapping has evolved over the years as new technology has been developed. For

example, this new technology has allowed more accurate portrayal of discrete pockets

of infestation, whereas in the early days of surveying, these were grouped in large polygons; thus, polygons have decreased in size and increased in number.

The goal of incorporating insect and disease mortality in landscape simulation models in

the context of INLAS is to better understand the long-term interactions of insects, disease, management, and other disturbances, and forest succession. Through the INLAS

project, we will continue to investigate the historical epidemic data and try to produce

parameters for each of the major insect pests. Work on diseases will probably be minimal given their relatively minor effect on mortality. We will explore methods to assess

uncertainty in the insect epidemic data. Given a set of reasonable parameters, epidemics will be simulated by using the simulation framework described in Ager (Chapter 3) for

the INLAS project area. These simulations will use the FVS pest extensions and will be

completed for a set of management scenarios (Barbour et al. Chapter 1). The outputs will

provide the data to examine how long-term levels of insect mortality might be affected by

different intensities and kinds of forest management at the subbasin scale.

Helpful reviews of an earlier version of this paper were provided by Don Scott and Nick

Crookston.

When you know: Multiply by: To find:

Acres 0.405 Hectares

Feet .3048 Meters

Ager, A.A. 1996. Operations manual for UPEST. Pendleton, OR: U.S. Department of

Agriculture, Forest Service, Umatilla National Forest. 16 p.

Ager, A.A. 2004. Stand-level approaches to simulating forest landscapes in the Western

U.S. In: Hayes, J.L.; Ager, A.A.; Barbour, R.J., tech. eds. Methods for integrating

modeling of landscape change: Interior Northwest Landscape Analysis System. Gen.

Tech. Rep. PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 33-40. Chapter 3.

Barbour, R.J.; Ager, A.A.; Hayes, J.L. 2004. A framework for the development and

application of INLAS: the Interior Northwest Landscape Analysis System. In: Hayes,

J.L.; Ager, A.A.; Barbour, R.J., tech. eds. Methods for integrating modeling of landscape change: Interior Northwest Landscape Analysis System. Gen. Tech. Rep.

PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station: 1-16. Chapter 1.

Bettinger, P.; Graetz, D.; Ager, A.A.; Sessions, J. 2004. The SafeD forest landscape

planning model. In: Hayes, J.L.; Ager, A.A.; Barbour, R.J., tech. eds. Methods for

integrating modeling of landscape change: Interior Northwest Landscape Analysis

System. Gen. Tech. Rep. PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 41-63. Chapter 4.

Beukema, S.J.; Greenough, J.A.; Robinson, D.C.E. [et al.]. 1997. The westwide pine

beetle model: a spatially-explicit contagion model. In: Teck, R.; Moeur, M.; Adams, J.,

comps. Proceedings: Forest Vegetation Simulator conference. Gen. Tech. Rep. INTGTR-373. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain

Research Station: 126-130.

Acknowledgments

Metric Equivalents

Literature Cited

Proposed Work
114

Cameron, D.E.; Stage, A.R.; Crookston, N.L. 1990. Performance of three mountain

pine beetle damage models compared to actual outbreak histories. Res. Pap.

INT-435. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain

Research Station. 13 p.

Campbell, S.; Liegel, L., tech. coords. 1996. Disturbance and forest health in Oregon

and Washington. Gen. Tech. Rep. PNW-GTR-381. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station and Pacific Northwest

Region; Oregon Department of Forestry; Washington Department of Natural Resources. 105 p.

Crookston, N.L.; Colbert, J.J.; Thomas, P.W. [et al.]. 1990. User’s guide to the western spruce budworm modeling system. Gen. Tech. Rep. INT-274. Ogden, UT: U.S.

Department of Agriculture, Forest Service, Intermountain Research Station. 40 p.

Crookston, N.L.; Stage, A.R. 1991. User’s guide to the parallel processing extension of

the prognosis model. Gen. Tech. Rep. INT-281. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station. 87 p.

Eager, T.J.; Angwin, P.A. 1997. Forest health assessment–Piney analysis area, Holy

Cross Ranger District, White River National Forest. In: Teck, R.; Moeur, M.; Adams,

J., comps. Proceedings: Forest Vegetation Simulator conference. Gen. Tech. Rep.

INT-GTR-373. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Research Station: 116-120.

Filip, G.M.; Torgersen, T.R.; Parks, C.A. [et al.]. 1996. Insect and disease factors in

the Blue Mountains. In: Jaindl, R.G.; Quigley, T.M., eds. Search for a solution: sustaining the land, people, and economy of the Blue Mountains. Washington, DC:

American Forests: 169-202.

Finney, M.A. 2004. Landscape fire simulation and fuel treatment optimization. In:

Hayes, J.L.; Ager, A.A.; Barbour, R.J., tech. eds. Methods for integrating modeling of

landscape change: Interior Northwest Landscape Analysis System. Gen. Tech. Rep.

PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station: 117-131. Chapter 9.

Frankel, S.J., tech. coord. 1998. Users guide to the western root disease model, version 3.0. Gen. Tech. Rep. PSW-165. Albany, CA: U.S. Department of Agriculture,

Forest Service, Pacific Southwest Research Station. 164 p.

Gast, W.R., Jr.; Scott, D.W.; Schmitt, C. 1991. Blue Mountains forest health report:

new perspectives in forest health. Portland, OR: U.S. Department of Agriculture, Forest Service, Malheur, Umatilla, and Wallowa-Whitman National Forests. [Irregular

pagination].

Graetz, D.H. 2000. The SafeD model: incorporating episodic disturbances and heuristic

programming into forest management planning for the Applegate River watershed,

southwestern Oregon. Corvallis, OR: Department of Forest Resources, Oregon State

University. 127 p. M.S. thesis.

Hagle, S.K.; Goheen, D.J. 1986. Root disease response to stand culture. In: Schmidt,

W.C., comp. Proceedings: future forests of the mountain West: a stand culture symposium. Gen. Tech. Rep. INT-GTR-243. Ogden, UT: U.S. Department of Agriculture,

Forest Service, Intermountain Research Station: 303-308.
115

Hawksworth, F.G.; Williams-Cipriani, J.C.; Eav, B.B. [et al.]. 1995. Dwarf mistletoe

impact modeling system user’s guide and reference manual. Internal Rep. MAG-95-2.

Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Forest Pest Management Methods Application Group. 120 p.

Hayes, J.L.; Daterman, G.E. 2001. Bark beetles (Scolytidae spp.) in eastern Oregon

and Washington. Northwest Science. 75: 21-30.

Hemstrom, M.; Ager, A.A.; Vavra, M. [et al.]. 2004. State and transition approach for

integrating landscape models. In: Hayes, J.L.; Ager, A.A.; Barbour, R.J., tech. eds.

Methods for integrating modeling of landscape change:

Interior Northwest Landscape Analysis System. Gen. Tech. Rep. PNW-GTR-610.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station: 17-32. Chapter 2.

Hessburg, P.F.; Mitchell, G.R.; Filip, G.M. 1994. Historical and current roles of insects

and pathogens in eastern Oregon and Washington forested landscapes. Gen. Tech.

Rep. PNW-GTR-327. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 72 p.

Kurz, W.A.; Beukema, S.J.; Klenner, W. [et al.]. 2000. TELSA: the tool for exploratory landscape analysis scenario analysis. Computers in Electronics in Agriculture.

27: 227-242.

Lehmkuhl, J.F.; Hessburg, P.F.; Everett, R.L. [et al.]. 1994. Historical and current

forested landscapes of eastern Oregon and Washington: Part I. Vegetation pattern

and insect and disease hazard. Gen. Tech. Rep. PNW-GTR-328. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 88 p.

Marsden, M.A.; Eav, B.B.; Thompson, M.K. 1994. User’s guide to the Douglas-fir

beetle impact model. Gen. Tech. Rep. RM-250. Fort Collins, CO: U.S. Department of

Agriculture, Forest Service, Rocky Mountain Research Station. 9 p.

Monserud, R.A.; Crookston, N.L. 1982. A user’s guide to the combined stand prognosis and Douglas-fir tussock moth outbreak model. Gen. Tech. Rep. INT-127. Ogden,

UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range

Experiment Station. 49 p.

Parks, C.G.; Flanagan, P.T. 2001. Dwarf mistletoes, rust diseases, and stem decays in

eastern Oregon and Washington. Northwest Science. 75: 31-37.

Powell, D.C. 1994. Effects of the 1980s western spruce budworm outbreak on the

Malheur National Forest in northeastern Oregon. R6-FI&D-TP-12-94. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Region, Forest

Insects and Diseases Group. 176 p.

Quigley, T.M.; Hayes, J.L.; Starr, G.L. [et al.]. 2001. Improving forest health and productivity in eastern Oregon and Washington. Northwest Science. 75: 234-251.

Roberts, J.C. 2002. Using a multichange agent approach with the forest vegetation

simulator on the Boise National Forest, Idaho. In: Crookston, N.L.; Havis, R.N.,

comps. Second Forest Vegetation Simulator conference. Proc. RMRS-P-25.

Ogden, UT: U.S. Department of Agriculture, Forest Service, Rocky Mountain

Research Station: 53-56.
116

Roberts, J.C.; Weatherby, J.C. 1997. Successional simulation using the Forest Vegetation Simulator and multi-pest scenarios for various levels of planning. In: Teck, R.;

Moeur, M.; Adams, J., comps. Proceedings: Forest Vegetation Simulator conference.

Gen. Tech. Rep. INT-GTR-373. Ogden, UT: U.S. Department of Agriculture, Forest

Service, Intermountain Research Station: 111-115.

Scott, D.W.; Schmitt, C.L.; Ager, A. 1998. Analyzing insect and disease risks for watershed analysis with the UPEST risk calculator program. Rep. BMZ-98-1. La Grande,

OR: U.S. Department of Agriculture, Forest Service, Wallowa-Whitman National Forest, Blue Mountains Pest Management Service Center. 18 p.

Sheehan, K.A.; Kemp, W.P.; Colbert, J.J.; Crookston, N.L. 1989. The western spruce

budworm model: structure and content. Gen. Tech. Rep. PNW-GTR-241. Portland,

OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station. 70 p.

Shore, T.L.; Safranyik, L.; Lemieux, J.P. 2000. Susceptibility of lodgepole pine

stands to the mountain pine beetle: testing of a rating system. Canadian Journal

of Forest Research. 30: 44-49.

Smith, E.; McMahan, A.J.; Eager, T. 2002. Landscape analysis of the westwide pine

beetle FVS extension. In: Crookston, N.L.; Havis, R.N., comps. Second Forest Vegetation Simulator conference. Proc. RMRS-P-25. Ogden, UT: U.S. Department of

Agriculture, Forest Service, Rocky Mountain Research Station: 62-68.

Steele, R.; Williams, R.E.; Weatherby, J.C. [et al.]. 1996. Stand hazard rating for

central Idaho forests. Gen. Tech. Rep. INT-GTR-332. Ogden, UT: U.S. Department

of Agriculture, Forest Service, Intermountain Research Station. 29 p.

Thies, W.G. 2001. Root diseases in eastern Oregon and Washington. Northwest

Science. 75: 38-45.

Torgersen, T.R. 2001. Defoliators in eastern Oregon and Washington. Northwest

Science. 75: 11-20.

U.S. Department of Agriculture, Forest Service [USDA FS]. 2003a. Forest

health protection. http://www.fs.fed.us/r6/nr/fid. (November).

U.S. Department of Agriculture, Forest Service [USDA FS]. 2003b.

http://www.fs.fed.us/foresthealth/technology/products.htm. (November).

U.S. Department of Agriculture, Forest Service [USDA FS]. 2003c.

http://www.fs.fed.us/fmsc/fvs/index.php. (November).

Wedin, H. 1999. Stand level prescription generation under multiple objectives. Corvallis,

OR: Department of Forest Resources, Oregon State University. 178 p. M.S. thesis.

Wright, L.C.; Berryman, A.A.; Wickman, B.E. 1984. Abundance of the fir engraver,

Scolytus ventralis, and the Douglas-fir beetle, Dendroctonus pseudotsugae, following

tree defoliation by the Douglas-fir tussuck moth. Canadian Entomologist. 116: 293-

305.

Wykoff, W.R.; Crookston, N.L.; Stage, A.R. 1982. User’s guide to the stand prognosis

model. Gen. Tech. Rep. INT-133. Ogden, UT: U.S. Department of Agriculture, Forest

Service, Intermountain Forest and Range Experiment Station. 112 p.
117

Chapter 9: Landscape Fire Simulation and Fuel

Treatment Optimization

Mark A. Finney1

Fuel treatment effects on the growth and behavior of large wildland fires depend on the

spatial arrangements of individual treatment units. Evidence of this is found in burn patterns of wildland fires. During planning stages, fire simulation is most often used to anticipate effects of fuel treatment units. Theoretical modeling shows that random patterns

are inefficient in changing large-fire growth rates compared to strategic designs. For

complex landscapes, computational methods are being developed to identify optimal

placement of fuel treatment units that collectively disrupt fire growth similarly to the strategic patterns. By combining these algorithms with forest simulations over long periods

(say 50 years), the long-term effects of various treatment strategies can be compared.

Keywords: Fire simulation, fire modeling, fuel treatments.

Large wildland fires are archetypal landscape phenomena. Landscapes are large land

areas that encompass properties that vary at scales finer than the landscape as a whole

(e.g., vegetation and topography). Wildland fires often encompass spatial and temporal

domains that are large compared to the landscape properties critical to their behavior

(fuels, weather, and topography). As fires advance across the landscape, they encounter

fine-scale variability in fuels, topography, and weather that produces complex patterns of

behavior and effects (see review by Finney 1999). Simulation models can accommodate

such high-frequency variation in the fire environment and thereby help us understand

movement and behavior of individual fires in complex conditions (Finney 1998). Simulation models are the main tools used to anticipate the effects management of vegetation

and forests has on large fire growth and behavior. Fire simulations, however, must be

coupled with vegetation or forest growth simulations if long-term consequences of wildland fires and management are to be addressed (Johnson et al. 1998, Keane et al. 1996,

Sessions et al. 1999). This paper will first summarize fire modeling and fuel management

techniques and then discuss methods for incorporating fire growth simulations and fuel

management optimization into landscape forest simulations.

Abstract

Introduction

1 Mark A. Finney is a research forester, U.S. Department of

Agriculture, Forest Service, Rocky Mountain Research Station,

Fire Sciences Laboratory, P.O. Box 8089, Missoula, MT 59807.
118

Wildland fire behavior has long been known to be a function of fuels, weather, and topography (Brown and Davis 1973). Fire behavior programs in use today, e.g., the fire behavior (BEHAVE) prediction and fuel modeling system (Andrews 1986), accept inputs for

these factors and predict fire behavior characteristics. Fire behavior refers to the gross

characteristics of fire, e.g., fireline intensity (kW/m, or power per unit length of the flaming front), spread rate (m/min-1), spotting distance, fuel consumption (kg/m), and whether

the fire is a surface or crown fire. These quantities are important to managing wildland

fire fighting operations, to estimating ecological effects of fires, and to designing fuel

treatments that change fire behavior. The BEHAVE program applies fire behavior models

to a given point on the ground or in one dimension.

The Fire Area Simulator (FARSITE) program extends these models to calculate fire behavior in two dimensions or across an area of land. As a result, data on fuels, weather,

and topography must be provided spatially, with weather and fuel moisture allowed to

change with time. Fire behavior across two spatial dimensions varies by the relative direction of fire spread, e.g., heading with the wind or slope, or flanking normal or backing

counter to the heading direction. Relative fire spread direction is important in determining

the variability of behaviors and effects that occur as large wildland fires move across

landscapes (Catchpole et al. 1982). Many techniques have been applied to the problem

of two-dimensional fire growth (see reviews by Finney 1998, 1999). Techniques that represent the growth and behavior of the fire edge as a vector or wave front (Finney 2002a,

Richards 1990, Sanderlin and Van Gelder 1977) produce less distortion of fire shape and

response to temporally varying conditions than techniques that model fire growth from

cell-to-cell on a gridded landscape. They are thus preferable for performing fire simulations for supporting fire management operations because they can realistically reflect

changes in fire behavior resulting from suppression, fuel, and weather changes.

Fuel management activities are designed to change the structure of wildland vegetation

and biomass distribution for the purpose of altering potential fire behavior. The prescriptions and objectives for fuel management depend on the characteristics of the vegetation

and fire regime. For forest ecosystems with low- and mixed-severity fire regimes (Agee

1998), fuel management prescriptions can be designed to improve survivability of trees

following wildland fires, restore forest structure, and improve the success of fire suppression efforts. For high-severity fire regimes in brushland and forest ecosystems, fuel management objectives can change fire behavior, slowing overall fire growth and improving fire

suppression. Fuel management techniques that have proven effective in changing wildland fire behavior and effects consist of prescribed burning (Davis and Cooper 1963,

Deeming 1990, Helms 1979, Koehler 1993, Martin et al. 1989, Pollet and Omi 2002),

thinning (Hirsch and Pengelly 1999, Keyes and O’Hara 2002), and other mechanical

manipulation of living or dead vegetation (Brown and Davis 1973, Pyne et al. 1996). Forest fuel treatments that reduce canopy fuels must often be accompanied by surface fuel

treatment; otherwise the surface fuel hazard can be increased (Alexander and Yancik

1977, van Wagtendonk 1996). There are three main targets of fuel management prescriptions that contribute to changes in discrete kinds of fire behavior (table 7).

The changes in potential fire behavior are produced at the stand level, or within the

treated area. Fire behaviors before and after treatment can be modeled by using fire behavior prediction systems such as BEHAVE (Andrews 1986) and Nexus (Scott and

Reinhardt 2001) to compare fire spread rates, intensities, and propensity for crown fire.

Although fuel management tends to produce immediate changes in fire behavior, fuel

treatment effects are only temporary. Fuel conditions change over time as a result of fuel

accretion, regrowth of understory vegetation, and ingrowth of young trees. More research

Fuel Management

Activities and

Changes to Fire

Effects and Behavior

at the Stand Level

Fire Simulations and

Their Requirements
119

is required to understand the long-term efficacy of fuel treatments on fuel conditions and

fire behavior so that scheduling of future management activities and maintenance can be

determined.

Landscape strategies for fuel treatments can be distinguished in terms of their intention

to (1) contain fires or (2) to modify fire behavior. Fire containment has been attempted by

arranging fuel treatments as fuel breaks (Agee et al. 2000, Green 1977, Omi 1996,

Weatherspoon and Skinner 1996). Fuel breaks are designed to facilitate active fire suppression at predetermined locations by indirect tactics (e.g., burnout). An alternative is to

modify fire behavior and fire progress across landscapes through strategic placement of

treatments and patterns of treatments (Brackebusch 1973; Finney 2001a, 2001b; Hirsch

et al. 2001). The latter strategy affords flexibility for integration into land management

planning and does not rely on uncertainties of success in fire suppression to mitigate fire

effects. The remainder of this paper will focus on strategic treatments.

Although behavior and effects of wildland fires can be changed within a particular treatment unit or stand, the behavior and progress of a much larger fire may not be affected

by small treatment units. Fire progression maps often reveal that small units are circumvented by large wildland fires (Dunn 1989, Salazar and Gonzalez-Caban 1987) with little

net effect on the overall growth of the fire (fig. 27). Instead, the progress of large wildland

fires is only affected by treatments that are (1) comparable to the size of the fire or (2) by

treatments that collectively disrupt the growth of fires (Brackebusch 1973, Finney 2001a,

Gill and Bradstock 1998). Examples of landscape-scale effects of fuel management are

evidenced in large national parks (e.g., Yosemite, Sequoia, and Kings Canyon) where

fire management policies have allowed free-burning fires for nearly three decades (Parsons and van Wagtendonk 1996, van Wagtendonk 1995) and in Baja, California, chaparral where little fire suppression exists (Minnich and Chou 1997). Because large fires

are of primary concern to fire and forest managers, the most important effects of fuel

treatments can only be achieved if landscape-scale considerations are incorporated into

Table 7—General relationships among fuels, prescriptions, and intended

changes to fire behavior from fuel treatments

Fuel target Prescription Change in fire behavior

Surface fuels (live grass Prescribed burning, Reduced spread rate and

and brush, and dead mechanical treatments intensity, and limit

and downed woody remove, compact, ignition of tree crowns

material) or reduce continuity of and other aerial fuels

surface fuels

Ladder fuels (small trees, Thinning (small-diameter Limit ability for fire to

 brush, low limbs) trees) and prescribed transition from surface to

burning (scorching and crown fire by separating

killing small trees and surface fuels from crown

brush) to decrease fuels

vertical continuity

between surface and

crown fuels

Canopy fuels (fine fuels like Thinning to reduce Limit spread of crown fire

 needles, and small twigs horizontal continuity of

 in tree crowns) crowns (e.g., overstory

thin)

Landscape Effects

of Fuel Management
120

the design and positioning of fuel treatments (Brackebusch 1973, Deeming 1990, Omi

1996, Omi and Kalabokidis 1998).

The effects of individual fuel treatment units on large fires must be modeled through

simulation. Aside from the minimally managed fire regimes in a few national parks and

wilderness areas, no full-scale landscape fuel management activities have been attempted. Thus, our only indications as to the effectiveness of treatments and patterns

come from theoretical and modeling activities, and occasional experience of using forest

harvest patterns for fire suppression (Bunnell 1998). Brackebusch (1973) advocated a

mosaic pattern of managed fuel patches to disrupt fire growth. Gill and Bradstock (1998)

discussed the amount of randomly arranged prescribed burns needed to disrupt fire

growth. Hirsch et al. (2001) proposed strategically locating fuel treatment units in a

“smart forest” approach to harvest scheduling and location. Theoretical work on fuel patterns (Finney 2001a, 2001b) indicates that spatial patterns of fuel treatments are critical

to fire growth rates (i.e., the rate of spread of large fires) (fig. 28). Here, random fuel treatments are very inefficient in changing overall fire growth rates. Compared to the

partially overlapped pattern, randomly arranged treatments permit fire to easily move

laterally around treatments unless large portions of the landscape are treated. This is

further illustrated by a comparison of large fire growth rates across the entire range of

treatments (fig. 29). If fire spread rate is reduced to one-fifth within the treatment unit

compared to the untreated surrounding landscape (as a direct effect of the treatment

Figure 27—Fire severity at the Hash Rock fire (August 2000) near Prineville, Oregon. A prescribed natural fire (i.e., fire use for

resource benefit) that occurred in 1995 produced important localized changes in fire behavior but had little effect on the progress

of the Hash Rock Fire as a whole.
121

Figure 28—Simulations of fire growth on different theoretical fuel patterns. Compared to (a) no treatment,

(b) random 20-percent treatment produces little effect on overall fire growth compared to (c) a theoretical

partial-overlap treatment. Random arrangements are ineffective because the fire can circumvent treatment

areas.

Figure 29—Overall fire spread rate as a function of treatment fraction for different spatial

patterns of treatment units (from Finney 2001a, 2003) reduces relative spread rate to 0.2.

Compared to patterns that require overlap among treatments, the random treatment pattern

produces little reduction in overall fire spread rate until relatively large proportions of the

landscape are treated (because fire goes around the treated patches).
122

prescription) 35-percent reduction in large fire growth rates is achieved by treating about

10 percent of the landscape in the strategic pattern compared to 50 percent in a random

pattern (fig. 29). The strategic pattern is clearly more efficient (per area treated) than a

random spatial arrangement of treatments. In nature, fire patterns created by free-burning

fires in the large national parks and Baja (Minnich and Chou 1997, Parsons and van

Wagtendonk 1996, van Wagtendonk 1995) obstruct fire growth because large percentages of the landscape are maintained by previous fires, despite the random locations of

those fires and previously burned areas.

The effects of fuel and forest management activities on fire behavior are not restricted to

the stand that is treated. Behavior characteristics of large wildland fires can be altered

outside the treated area because of the way fire behavior changes depending on the

relative fire spread direction. These constitute an “off-site” effect of treatments that are

seen as changes in overall fire growth rate (fig. 28), flanking and backing fire burning with

lower fireline intensity on the lee-side of treatment units (fig. 30), and in moderated fire

effects on the lee-side of fuel changes (fig. 31). Such landscape-scale effects on large

fires become important to the patch sizes and proportions of areas burned with different

severities.

Despite the potential benefits of fuel management at the stand and landscape levels,

limitations on the amounts and locations of treatment suggest that these activities must

be carefully chosen to achieve the greatest effect and benefit. The problem might be

approached as an optimization of effects given constraints on locations, amounts, and

prescriptions that can be applied. Application of spatial optimization and strategies in

forest management (Baskent 1999, Baskent and Jordan 1996, Snyder and ReVelle 1996)

and fire management (Finney 2001a, Hirsch et al. 2001, Hof et al. 2000, Wilson and

Baker 1998) is becoming more common. For a simple theoretical landscape consisting

of two fuel types on flat terrain, a pattern of rectangular fuel treatment units can be optimized for size and placement (Finney 2001a). Such patterns are optimal in terms of

efficiency and effectiveness in reducing large-fire growth rates compared to random fuel

patterns (Finney 2001b, 2003). However, there are no analytical solutions to the optimization of fuel treatment locations on real landscapes that are complex in terms of fuels,

topography, and weather. For real landscapes, where fuels, topography, and weather all

differ, an optimization of this kind is complicated by the spatial and temporal nature of

fire and its movement through a pattern of fuel treatments.

An optimization algorithm is under development for helping choose the placement of fuel

treatments on real landscapes (Finney 2002b). One process now being considered consists of two steps: (1) use fire growth algorithms to identify the fastest travel routes

across a landscape, and (2) use heuristic algorithms to optimize the locations and sizes

of fuel treatments to block these routes. The fastest travel routes produced by fire growth

algorithms suggest initial places for optimal placement of fuel treatments for delaying fire

growth. The procedure requires the construction of a gridded landscape containing information on fuels and topography (fig. 32a). Specific weather conditions associated with

the conditions targeted for fuel treatment performance, including wind direction, windspeed, humidity, and temperature are used to compute the fire behavior at each cell.

Each cell contains fire spread rates in all directions assuming an elliptical fire shape

(Finney 2002a) so that fire growth across the landscape can be computed from a generic

ignition source. The fire growth algorithm is based on minimum fire travel time methods

from graph theory (Finney 2002a, Moser 1991) that efficiently calculate fire growth and

behavior for each cell (node) on the landscape. The paths producing the minimum fire

travel time can then be processed to identify the “influence paths” or routes of fire travel

Effects of Spatial

Locations and

Patterns of

Landscape Fuel

Treatments
123

Figure 30—Landsat 7 image of the Rodeo fire in Arizona

(June 21, 2002) showing interior fire fronts around arrowshaped islands within the main fire. These occur where

fire fronts join after circumventing the islands and are a

landscape-scale effect of varying fuels and fire behavior.

Figure 31—A ridge within the

Alder Creek fire (Montana 2000)

showing offsite effect of rocky

areas (arrows) on fire effects

and behavior. Crown fire moved

from lower left to upper right and

could not burn areas on lee side

of rocky patches (photo by Colin

Hardy, USDA FS, Missoula Fire

Sciences Lab).
124

Figure 32a—Fuels and terrain data showing

fire growth contours (progression in 1-hour

time step from north to south).

Figure 32b—Fire influence paths calculated

from fire growth algorithm. Given the

ignition configuration (bottom of landscape),

fire burning through paths of high influence

(red) ultimately burns more land area than

areas around them. These suggest places

to place fuel treatment units because a

large effect would be achieved by slowing

fire spread through those areas compared

to surrounding areas.

Figure 32c—Fuel treatments (fuchsia color)

optimized by using a genetic algorithm for

this landscape. Treatments cause fire

growth to take twice as long as it would

without treatments to cross this landscape

while occupying about 15 percent of the

total land area.
125

that account for the most area burned later in time (fig. 32b). These paths are the starting locations for treatment units because of the large influence that blocking those paths

has on area burned. The exact number, sizes, and patterns of those treatments, however, must be obtained through the use of a heuristic algorithm (fig. 32c).

Heuristic algorithms are used to find spatially optimal fuel treatment unit sizes and

locations. At present, a genetic algorithm (Goldberg 1989) is being developed for evaluating collections of fuel treatment units to determine their effectiveness and efficiency

at changing overall fire growth rates. The challenging part of this problem is the sequential nature of fire movement. Fuel treatment units located upwind divert fire growth and

change the priorities for fuel treatments downwind (sizes and locations). Furthermore,

the optimal spatial pattern is not necessarily composed of locally optimal treatment

units. In other words, the importance of each unit is only realized in context of the entire

pattern. An approach to this problem involves the use of recursion, starting the algorithm

at downwind locations and allowing it to recurse toward the ignition location. At each

location, a population of “best” treatment units is selected based on the best populations

from previous locations (i.e., upwind or closer to the ignition). The performance of individual treatment patterns is assessed by using the fire growth algorithm to compare fire

travel times among treatment alternatives. The genetic algorithm (GA) is used to refine

the population of individual treatment units within a horizontal strip, where each treatment

unit has characteristics of vertical location and size. Ultimately, the optimal solution is

selected from the treatments that produce the overall best effect. The algorithm consists

of the following steps:

• Evaluate the fire growth by using the minimum travel time algorithm for the landscape

without treatment.

• Divide the landscape into a series of strips of random width running perpendicular to

the main fire spread direction.

• Starting with the downwind strip (i.e., farthest from the ignition), use GA to optimize

the fuel treatment locations and unit sizes for each of the fuel treatment configurations obtained from the GA on previous strips. Applying the GA to each strip requires

recursion into preceding strips to find the optimal treatment locations and sizes.

Each treatment configuration in each strip is evaluated by using the minimum travel

time algorithm.

• Within each strip, create populations of treatment locations and sizes to evaluate

and improve by using the GA. Treatment unit sizes are obtained by infilling the fire

growth contours from a starting point (e.g., an influence path) by using the differential

spread rate owing to treatment.

• Pick the best overall treatment pattern from all strips that maximize the fire travel

time across the landscape as a whole.

The above algorithm is being developed for handling spatial constraints on treatment area

and local treatment effectiveness (i.e., within a given stand and stand type). So far, the

algorithm appears to identify fuel treatment units that efficiently retard overall fire growth

(fig. 32c).
126

Long-term consequences of forest and fuel management activities on wildland fire behavior can only be understood by either large-scale experimentation or through simulation

modeling. Until experimental or operational treatment areas have been established on

the ground and monitored, simulation modeling will be the only method available.

Many landscape simulation approaches are currently used for spatially modeling fire and

long-term future forest development (Johnson et al. 1998, Jones and Chew 1999, Keane

et al. 1997, Mladenoff and He 1999, Sessons et al. 1996, Thompson et al. 2000). Some

of these have been proposed for modeling effects of treatments and for optimizing the

scheduling of fuel treatments. At present, these simulations do not permit control for fuel

treatment spatial patterns. As the above analysis of simple landscape patterns suggests, however, fuel treatments at the landscape scale have topological effects that are

critical to changing fire growth. Improvements to landscape simulations include the prescription, scheduling, and location of treatments dynamically in response to unpredicted

disturbances (fire, insects, etc.). Furthermore, the simulation must have fine-scale resolution of landscape units, as either grids (raster) or small polygons, to retain the fine

resolution of spatially variable fire effects (Finney 1999).

The intent of a new modeling effort is to modify the simulation approach (Simulation and

Analysis of Forests with Episodic Disturbances [SafeD]) described by Sessions et al.

(1999) and Johnson et al. (1998) to incorporate a spatial optimization for fuel treatments

(Finney 2002b). The SafeD model has been used previously to examine how fuelbreaks

performed in the presence of wildfire and forest change (Johnson et al. 1998, Sessions

et al. 1999). Currently, SafeD (Graetz 2000) is a spatially explicit simulation/optimization

tool that features a stand prescription generator (Wedin 1999), forest growth-and-yield

modeling by using the Forest Vegetation Simulator (FVS), a heuristic method of allocating activities across a landscape with multiple constraints, and a spatially explicit fire

growth model FARSITE (Finney 1998). Together, these models allow for scheduling of

fuel and harvesting treatments, simulation of wildfire events and effects, growth and mortality of vegetation, surface and crown fuel development, and specification of stand- and

landscape-level objectives. The landscape goal-seeking component of SafeD couples

heuristic techniques with goal programming to find near-optimal sets of stand and landscape prescriptions. Multiple stand management objectives can be specified for the

simulations. Mechanical and prescribed fire treatment effects are modeled in SafeD by

manipulation of tree lists (lists of density by size and species of trees) and surface fuel

components. Wildfire effects are created by fireline intensity maps created by FARSITE

simulations that are activated by the SafeD model.

Several additions to the SafeD model will be required to permit spatial optimization of fuel

treatments. Optimal fuel treatment locations will be determined by inclusion of a spatial

treatment algorithm (e.g., Finney 2002b).

A project funded by the Joint Fire Science Program (http://www.nifc.gov/joint_fire_sci/

jointfiresci.html) will make use of the SafeD simulation system to address landscape

fuel treatment scheduling and potential effects for several study areas. These study areas are located in the Blue Mountains in eastern Oregon (one of the INLAS study sites),

Sanders County in western Montana, the Sierra National Forest in California, and southern Utah. The landscapes were chosen as samples of different ecosystems, fire

regimes, mixtures of landownership, and fuel and forest management issues and constraints to examine, in a practical sense, how the outcomes of landscape fuel treatment

programs can be expected to differ. A series of simulations for these landscapes will be

performed to address the following questions:

Research

Applications

Integration of Fire

and Landscape

Simulations
127

• How important is fuel treatment topology to the potential effects of treatments on real

landscapes?

• For different fuel treatment amounts and patterns, what fuel treatment effects (e.g.,

fire sizes, burned area, severity) can be expected with no constraint on treatment

location or prescription?

• What fuel treatment effects are possible given current restrictions on fuel and forest

management activities?

• What are the tradeoffs in fuel treatment effectiveness possible by relaxing some of

the constraints?

The results of this project are intended to lead to practical methods for guiding fuel treatment planning across landscapes and for helping identify constraints on needed management activities through cooperation among the many competing interests in wildland

management.

The fire behavior models presently available can be used to simulate fire growth, behavior, and effects at the landscape scale. Effects of fuel treatments on changes in fire behavior can be modeled for a variety of prescriptions and environmental conditions. The fire

simulations also have been used to examine spatial effects of fuel treatment patterns,

suggesting that fuel treatment topology can be important to effects on fire growth and

behavior. Fire growth simulation and heuristic algorithms are being combined as a means

to find optimal patterns of treatments in highly variable conditions found on real landscapes. These optimizations are to be combined with landscape simulation and scheduling programs to examine likely effects of spatial fuel treatment programs on wildland fire

behaviors and effects at the landscape scale.

This work was partly funded by the Joint Fire Science Program and the USDA Forest

Service, Rocky Mountain Research Station, Fire Sciences Laboratory, Fire Behavior

Research Work Unit in Missoula, Montana.

When you know: Multiply by: To find:

Meters (m) 3.28 Feet

Kilograms (kg) 2.205 Pounds

Kilowatts per meter (kW/m) 0.2889 British thermal unit 

per foot per second

Agee, J.K. 1998. Fire strategies and priorities for forest health in the Western United

States. In: Proceedings of the 13th fire and forest meteorology conference. Fairfax, VA:

International Association of Wildland Fire, USA: 297-303.

Agee, J.K.; Bahro, B.; Finney, M.A. [et al.]. 2000. The use of fuelbreaks in landscape

fire management. Forest and Ecology Management. 127: 55-66.

Alexander, M.E.; Yancik, R.F. 1977. The effect of precommercial thinning on fire potential in a lodgepole pine stand. Fire Management Notes. 38(3): 7-9, 20.

Andrews, P.L. 1986. BEHAVE: fire behavior prediction and fuel modeling system–BURN

subsystem. Part 1. Gen. Tech. Rep. INT-194. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 130 p.

Baskent, E.Z. 1999. Controlling spatial structure of forested landscapes: a case study

towards landscape management. Landscape Ecology. 14: 83-97.

Conclusions

Acknowledgments

English Equivalents

Literature Cited
128

Baskent, E.Z.; Jordan, G.A. 1996. Designing forest management to control spatial

structure of landscapes. Landscape and Urban Planning. 34: 55-74.

Brackebusch, A.P. 1973. Fuel management: a prerequisite not an alternative to fire

control. Journal of Forestry. 71(10): 637-639.

Brown, A.A.; Davis, K.P. 1973. Fire control and use. 2nd ed. New York: McGraw-Hill

Book Company. 686 p.

Bunnell, D. 1998. Old-growth lodgepole pine and the Little Wolf Fire. In: Close, K.;

Bartlette, R., eds. Proceedings of the 1994 interior West fire council meeting and

program. Fairfax, VA: International Association of Wildland Fire, USA: 155-160.

Catchpole, E.A.; de Mestre, N.J.; Gill, A.M. 1982. Intensity of fire at its perimeter.

Australian Forest Research. 12: 47-54.

Davis, L.S.; Cooper, R.W. 1963. How prescribed fire affects wildfire occurrence. Journal

of Forestry. 61: 915-917.

Deeming, J.E. 1990. Effects of prescribed fire on wildfire occurrence and severity. In:

Walstad, J.D.; Radosevich, S.R.; Sandberg, D.V., eds. Natural and prescribed fire in

Pacific Northwest forests. Corvallis, OR: Oregon State University Press: 95-104.

Chapter 8.

Dunn, A.T. 1989. The effects of prescribed burning on fire hazard in the chaparral: toward a new conceptual synthesis. In: Berg, N.H., tech. coord. Proceedings of the

symposium on fire and watershed management. Gen. Tech. Rep. PSW-109. Albany,

CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research

Station: 23-29.

Finney, M.A. 1998. FARSITE: Fire Area Simulator–model development and evaluation.

Res. Pap. RMRS-RP-4. Fort Collins, CO: U.S. Department of Agriculture, Forest

Service, Rocky Mountain Research Station. 47 p.

Finney, M.A. 1999. Mechanistic modeling of landscape fire patterns. In: Mladenoff, D.J.;

Baker, W.L., eds. Spatial modeling of forest landscape change: approaches and applications. Cambridge, United Kingdom: Cambridge University Press: 186-209.

Finney, M.A. 2001a. Design of regular landscape fuel treatment patterns for modifying

fire growth and behavior. Forest Science. 47(2): 219-228.

Finney, M.A. 2001b. Spatial strategies for landscape fuel treatments. In: Bento, J.;

Botelho, H., eds. Workshop on tools and methodologies for fire danger mapping: proceedings of a workshop. Vila Real, Portugal: Universidad de Traj-os-montes el AltoDouro, Departamento Forestal: 157-163.

Finney, M.A. 2002a. Fire growth using minimum travel time methods. Canadian Journal

of Forest Research. 32: 1420-1424.

Finney, M.A. 2002b. Use of graph theory and genetic algorithms for finding optimal fuel

treatment locations. In: Viegas, D.X., ed. Proceedings of the 4th international conference on fire research [CD ROM]. Rotterdam, The Netherlands: Millpress Science

Publishers.

Finney, M.A. 2003. Calculation of fire spread rates across random landscapes. International Journal of Wildland Fire. 12(2): 167-174.
129

Gill, A.M.; Bradstock, R.A. 1998. Prescribed burning: patterns and strategies. In: 13th

conference on fire and forest meteorology. Fairfax, VA: International Association of

Wildland Fire, USA: 3-6.

Goldberg, D.E. 1989. Genetic algorithms in search, optimization and machine learning.

Boston, MA: Addison-Wesley Publishing Co. 432 p.

Graetz, D.H. 2000. The SafeD model: incorporating episodic disturbances and heuristic

programming into forest management planning for the Applegate River watershed,

southwestern Oregon. Corvallis, OR: Oregon State University. 127 p. M.S. thesis.

Green, L.R. 1977. Fuelbreaks and other fuel modification for wildland fire control. Agric.

Handb. 499. Washington, DC: U.S. Department of Agriculture, Forest Service. 79 p.

Helms, J.A. 1979. Positive effects of prescribed burning on wildfire intensities. Fire Management Notes. 40(3): 10-13.

Hirsch, K.; Kafka, V.; Tymstra, C. [et al.]. 2001. Fire-smart forest management:

a pragmatic approach to sustainable forest management in fire-dominated ecosystems. The Forestry Chronicle. 77(2): 357-363.

Hirsch, K.; Pengelly, I. 1999. Fuel reduction in lodgepole pine stands in Banff National

Park. In: Neuenschwander, L.F.; Ryan, K.C., tech eds. Proceedings of the joint fire

sciences conference and workshop. Boise, ID: University of Idaho: 250-256.

Hof, J.; Omi, P.N.; Bevers, M.; Laven, R.D. 2000. A timing oriented approach to spatial

allocation of fire management effort. Forest Science. 46(3): 442-451.

Johnson, K.N.; Sessions, J.; Franklin, J.; Gabriel, J. 1998. Integrating wildfire into

strategic planning for Sierra Nevada forests. Journal of Forestry. 96(1): 42-49.

Jones, J.G.; Chew, J.D. 1999. Applying simulation and optimization to evaluate the

effectiveness of fuel treatments for different fuel conditions at landscape scales. In:

Neuenschwander, L.F.; Ryan, K.C., tech. eds. Proceedings of the joint fire science

conference and workshop. Boise, ID: University of Idaho: 89-95.

Keane, R.E.; Morgan, P.; Running, S.W. 1996. FIRE-BGC—a mechanistic ecological

process model for simulating fire succession on coniferous forest landscapes of the

northern Rocky Mountains. Res. Pap. RP-INT-484. Ogden, UT: U.S. Department of

Agriculture, Forest Service, Intermountain Research Station. 122 p.

Keyes, C.R.; O’Hara, K.L. 2002. Quantifying stand targets for silvicultural prevention of

crown fires. Western Journal of Applied Forestry. 17(2): 101-109.

Koehler, J.T. 1993. Prescribed burning: a wildfire prevention tool? Fire Management

Notes. 53-54(4): 9-13.

Martin, R.E.; Kauffman, J.B.; Landsberg, J.D. 1989. Use of prescribed fire to reduce

wildfire potential. In: Berg, N.H., tech. coord. Proceedings of the symposium on fire

and watershed management. Gen. Tech. Rep. PSW-109. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific Southwest Research Station: 17-22.
130

Minnich, R.A.; Chou, Y.H. 1997. Wildland fire patch dynamics in the chaparral of southern California and northern Baja California. International Journal of Wildland Fire. 7:

221-248.

Mladenoff, D.; He, H.S. 1999. Design, behavior and application of LANDIS, an objectoriented model of forest landscape disturbance and succession. In: Mladenoff, D.J.;

Baker, W.L., eds. Spatial modeling of forest landscape change: approaches and applications. Cambridge, United Kingdom: Cambridge University Press: 125-162.

Moser, T.J. 1991. Shortest path calculation of seismic rays. Geophysics. 56(1): 59-67.

Omi, P.N. 1996. Landscape-level fuel manipulations in Greater Yellowstone: opportunities and challenges. In: Greenlee, J., ed. The ecological implications of fire in Greater

Yellowstone. Proceedings of the 2nd biennial conference on the Greater Yellowstone

ecosystem. Fairfax, VA: International Association of Wildland Fire, USA: 7-14.

Omi, P.N.; Kalabokidis, K.D. 1998. Fuels modification to reduce large fire probability.

In: Viegas, D.X., ed. 3rd international conference on forest and fire research and 14th

conference on fire and forest meteorology. Industrial, Portugal: ADAI–Associacao para

o Desenvolvimento da Aerodinamica: 2073-2088. Vol 2.

Parsons, D.J.; van Wagtendonk, J.W. 1996. Fire research and management in the

Sierra Nevada. In: Halvorson, W.L.; Davis, G.E., eds. Science and ecosystem

management in the national parks. Tucson, AZ: University of Arizona Press: 25-48

Chapter 3.

Pollet, J.; Omi, P.N. 2002. Effect of thinning and prescribed burning on crown fire

severity in ponderosa pine forests. International Journal of Wildland Fire. 11(1): 1-10.

Pyne, S.J.; Andrews, P.L.; Laven, R.D. 1996. Introduction to wildand fire. 2nd ed. New

York: John Wiley and Sons, Inc. 769 p.

Richards, G.D. 1990. An elliptical growth model of forest fire fronts and its numerical

solution. International Journal of Numerical Methods in Engineering. 30: 1163-1179.

Salazar, L.A.; Gonzalez-Caban, A. 1987. Spatial relationship of a wildfire, fuelbreaks,

and recently burned areas. Western Journal of Applied Forestry. 2(2): 55-58.

Sanderlin, J.C.; Van Gelder, R.J. 1977. A simulation of fire behavior and suppression

effectiveness for operation support in wildland fire management. In: Proceedings of the

1st international conference on mathematical modeling. St. Louis, MO: [Publisher unknown]: 619-630.

Scott, J.H.; Reinhardt, E.D. 2001. Assessing crown fire potential by linking models

of surface and crown fire behavior. Res. Pap. RMRS-RP-29. Fort Collins, CO: U.S.

Department of Agriculture, Forest Service, Rocky Mountain Research Station. 59 p.

Sessions, J.; Johnson, K.N.; Franklin, J.F.; Gabriel, J.T. 1999. Achieving sustainable

forest structures on fire-prone landscapes while pursuing multiple goals. In: Mladenoff,

D.J.; Baker, W.L., eds. Spatial modeling of forest landscape change: approaches and

applications. Cambridge, United Kingdom: Cambridge University Press: 210-255.

Sessons, J.; Johnson, K.N.; Sapsis, D. [et al.]. 1996. Methodology for simulating

forest growth, fire effects, timber harvest, and watershed disturbance under different

management regimes. In: Sierra Nevada Ecosystem Project; final report to Congress.

Addendum. Davis, CA: University of California, Centers for Water and Wildland

Resources: [Pages unknown].
131

Snyder, S.; ReVelle, C. 1996. The grid packing problem: selecting a harvesting pattern

in an area with forbidden regions. Forest Science. 42(1): 27-34.

Thompson, W.A.; Vertinsky, I.; Schreier, H.; Blackwell, B.A. 2000. Using forest fire

hazard modeling in multiple use forest management planning. Forest Ecology and

Management. 134: 163-176.

van Wagtendonk, J.W. 1995. Large fires in wilderness areas. Gen. Tech. Rep. INTGTR-320. In: Brown, J.K.; Mutch, R.W.; Spoon, C.W.; Wakimoto, R.H., tech. coords.

Proceedings: symposium on fire in wilderness and park management. Odgen, UT:

U.S. Department of Agriculture, Forest Service, Intermountain Research Station:

113-116.

van Wagtendonk, J.W. 1996. Use of a deterministic fire growth model to test fuel treatments. In: Sierra Nevada Ecosystem Project; final report to Congress. Assessments

and scientific basis for management options. Davis, CA: University of California, Centers for Water and Wildland Resources: 1155-1165. Vol. 2.

Weatherspoon, C.P.; Skinner, C.N. 1996. Landscape-level strategies for forest fuel

management. In: Sierra Nevada Ecosystem Project; final report to Congress. Assessments and scientific basis for management options. Davis, CA: University of California, Centers for Water and Wildland Resources: 1471-1492. Vol 2.

Wilson, J.S.; Baker, P.J. 1998. Mitigating fire risk to late-successional forest reserves

on the east slope of the Washington Cascade Range, USA. Forest Ecology and Management. 110: 59-75.
132

Chapter 10: Connection to Local Communities

Gary J. Lettman and Jeffrey D. Kline1

The socioeconomic health of La Grande and other northeastern Oregon communities

traditionally has been linked to the region’s forests, which have provided economic activity related to timber outputs as well as recreation and other nontimber values. Forest

management changes within the Interior Northwest Landscape Analysis System (INLAS)

project area can affect socioeconomic changes in the region. This research will evaluate

the regional economic impacts of current and alternative forest management alternatives

implemented within the INLAS project area and describe prevailing attitudes and values

toward forestry and forest management among the region’s residents. The research will

contribute to understanding the socioeconomic consequences of current and alternative

forest management scenarios and can assist forest managers and policymakers in identifying potential compatibilities regarding joint production of multiple timber and nontimber

forest outputs.

Keywords: Forest economics, input/output models, local economies, eastern Oregon.

The socioeconomic health of La Grande and other northeastern Oregon communities

traditionally has been linked to the region’s forests. Historically, lumber and wood products industries contributed significantly to the region’s economic base. More recently,

other forest resource-based industries, such as recreation and tourism, also have been

recognized as important contributors to local economies. However, a two-thirds reduction

in timber harvests in eastern Oregon (Oregon Department of Forestry 2001), coupled with

poor economic conditions for the region’s agriculture (Barney and Worth 2001), has led

to increased concerns regarding the socioeconomic health of northeastern Oregon’s

communities. Current county-level unemployment rates in the region are between 8

and 16 percent (Bureau of Labor Statistics 2002). Alternative forest management scenarios could alter forest conditions and resource outputs in ways that result in both economic impacts to communities economically dependent on forestry activities, as well as

Abstract

Overview

1 Gary J. Lettman is a principal forest economist, Oregon

Department of Forestry, 2600 State Street, Salem, OR 97301; and

Jeffrey D. Kline is a research forester, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station,

Forestry Sciences Laboratory, 3200 SW Jefferson Way, Corvallis,

OR 97331.
133

in quality-of-life impacts that affect residents and visitors who recreate in the region’s

forests.

Although assessments of alternative forest management practices often have focused

on evaluating regional economic impacts resulting from timber outputs, Oregonians also

increasingly recognize forests as important cultural resources. Recent population growth

coupled with growth of nonforestry economic sectors has reduced the proportion of

Oregonians who are directly involved with the economic aspects of forests and forestry

(Kline and Armstrong 2001). These and other socioeconomic changes have led to greater

environmental orientations toward forests (Schindler et al. 1993, Steel et al. 1994). Recent statewide surveys, for example, suggest that Oregonians place high values on

clean air and water, wilderness, and wildlife (Davis et al. 1999). Growing urban populations also can increase demands for outdoor recreation. In another survey, Oregonians

cited natural beauty and recreation opportunities as the attributes they most value about

living in the state (Oregon Business Council 1993). Similar changes in public values and

attitudes toward forests have been observed nationally (Bengston 1994, Davis et al.

1991, Egan and Luloff 2000, Schindler et al. 1993).

How attitudes and values regarding forests might change over time relative to concerns

for other issues of regional or statewide interest can reveal the degree to which local

communities will trade off forest values of different types with other public objectives.

Recent survey data gathered during the ongoing economic turndown, e.g., suggest that

Oregonians currently rate economic issues, such as education funding and the recession, as more important than forest management and environmental issues (Davis et al.

2001). Understanding the socioeconomic consequences of current and alternative forest

management scenarios in the Interior Northwest Landscape Analysis System (INLAS)

project area is important to evaluating resulting regional and statewide impacts. However,

understanding Oregonians’ attitudes and values regarding forests, and how they change

over time, is important to evaluating what range of forest practices and policies will be

politically feasible in the future. Together, the two types of information provide a socioeconomic context for evaluating what forest management alternatives are appropriate and

can assist managers and policymakers in identifying potential compatibilities regarding

joint production of multiple forest outputs.

The objectives of this research are to (1) build and calibrate economic impact models for

state, county, and local economies to analyze the economic effects of current and alternative forest management scenarios; and (2) describe attitudes and values among the

region’s residents toward forests and forest management and consider what changes in

these might mean for public forest management and policy in the future.

The planned research involves two principal tasks: (1) evaluate the economic impacts of

alternative forest management scenarios and (2) describe and examine public attitudes

and values toward forests.

The economic impacts of alternative forest management scenarios will be examined

by using output data describing the volume of timber and other forest commodities produced under different scenarios as input data into economic models describing local

and regional economic activity. Harvested timber volume and other forest commodity

Objectives

Research Approach

Evaluate Economic

Impacts
134

measures will be estimated from tree lists data produced by INLAS vegetation models

at each modeling interval. The analysis will describe community and regional economic

impacts resulting from different levels of timber volume and other forest commodities

produced under the alternative INLAS forest management scenarios tested.

Two types of economic models could be used to examine the economic impacts of current and alternative forest management scenarios. The first is a commercially available

economic modeling system such as the Impact Analysis for Planning (IMPLAN) social

accounting and economic impact system (Lindall and Olson 1993). This approach would

enable relatively quick and easy development of input/output models, after updating and

validating county-level data supplied with the modeling system. Such models provide

“snapshots in time” of local economies, and their resulting multipliers can be used to

evaluate economic impacts of changes in forest management practices. A disadvantage

to using these models is that analyses can be satisfactorily done only at the county

level, not for individual communities. Such models also may not fully account for informal

economic activity, such as undocumented trade and unreported income, which may be

characteristics of some forest-based activities involving recreation and nontimber forest

products for example.

A second approach is to develop economic impact models by using community or regional economic surveys. Unlike commercially available modeling systems, surveybased models could be constructed for individual communities of interest. However, their

disadvantage is their greater complexity and higher cost. Constructing survey data models involves obtaining data on the impacts of local purchases and sales of each economic sector to demands in all other economic sectors, including imports purchased

and exports sold.

The choice between using a commercially available modeling system, such as IMPLAN,

versus using a survey-based approach will depend on assessing available funding and

staffing resources at the outset relative to information needs of the greater INLAS research effort. The IMPLAN system currently is being used in socioeconomic assessments in Wallowa, Union, and Grant Counties, and opportunities may exist to build on

this ongoing work.

Analyzing only the short-term impacts of alternative forest management scenarios on

local and regional economies, and only in terms of dollar flows, provides an incomplete

picture of the socioeconomic effects of different forest management activities on nearby

communities. For example, user values for fish and wildlife resources, recreation values

for activities like fishing and hiking, and preservation values for the forest are examples of

nonfinancial economic values that should be considered in evaluating future management

activities. Measuring residents’ willingness to pay for biodiversity and other nonmarket

values through surveys is beyond the scope of work foreseen for INLAS. However, there

are many examples of such analyses in published economics literature (Lettman 2001).

These will be reviewed and summarized to illustrate some of the values people may hold

for biodiversity and nonmarket forest outputs not generally included in financial-based

economic analyses.

Examining Public

Attitudes and Values
135

Additionally, telephone survey and focus group data already collected for the Oregon

Department of Forestry (Davis et al. 2001) will be examined to help improve understanding of the attitudes and values of people in local communities toward forests and natural

resource issues, and how these values might change over time. Because the data were

collected for seven different regions in Oregon, including northeast Oregon, it will be possible to examine attitudes and values toward forest and natural resource management

issues at the regional level and to compare regional and statewide focus group and survey results. In particular, survey results will be summarized for the northeast Oregon

counties of Baker, Grant, Umatilla, Union, and Wallowa, and compared to results statewide.

The review and summary of public attitudes and values will not be linked directly to other

INLAS models. Rather, they will provide background information describing the social

context in which forest management and policy decisions are made.

The research will produce analyses of the regional economic impacts of alternative forest

management scenarios and describe public attitudes and values toward forests. In particular, the economic impact analyses will produce economic impact multipliers and

other quantitative results, whereas the examination of public attitudes and values will

produce qualitative literature reviews, survey results, and other descriptive information.

Specific products will include two reports: one report describing the regional economic

impacts of current and alternative forest management and fire planning scenarios, as well

as the technical aspects of the economic impact approaches taken; and one report describing public values and attitudes toward forests and forest management, which form

the socioeconomic context in which management and policymaking will take place.

Users of the information produced by this research will include the Governor of Oregon,

the Oregon Departments of Forestry and Economic and Community Development, local

community officials, national forest planners, and others concerned with the impacts of

forest management on economic development and community stability.

Barney and Worth, Inc. 2001. Inland Northwest economic adjustment strategy,

2001. Olympia, WA: Washington Department of Community, Trade, and Economic

Development. 74 p.

Bengston, D.N. 1994. Changing forest values and ecosystem management. Society

and Natural Resources. 7(6): 515-533.

Bureau of Labor Statistics. 2002. Local area unemployment statistics. Washington,

DC. http://www.bls.gov/. (27 June 2003).

Davis, A.; Hibbits, T.; McCaig, P. 1999. Oregonians discuss forest values, management goals and related issues. Portland, OR: Forest Resources Institute. 19 p.

Davis, A.; Hibbits, T.; McCaig, P. 2001. A forestry program for Oregon: Oregonians

discuss their options on forest management and sustainability. Portland, OR: Davis,

Hibbitts and McCaig, Inc. 72 p.

Davis, L.S.; Ruth, L.W.; Teeguarden, D.; Henly, R.K. 1991. Ballot box forestry.

Journal of Forestry. 89(12): 10-18.

Egan, A.F.; Luloff, A.E. 2000. The exurbanization of America’s forests: research in rural

social science. Journal of Forestry. 98(3): 26-30.

Literature Cited

Products and Users
136

Kline, J.D.; Armstrong, C. 2001. Autopsy of a forestry ballot initiative: characterizing

voter support for Oregon’s Measure 64. Journal of Forestry. 99(5): 20-27.

Lettman, G.J., coord. 2001. Elliott State Forest management plan revision: connection

to state and local economies. Salem, OR: Oregon Department of Forestry. 158 p.

Lindall, S.A.; Olson, D.C. 1993. Micro IMPLAN user’s guide: version 91-F. Stillwater,

MN: Minnesota IMPLAN Group, Inc. 417 p.

Oregon Business Council. 1993. Oregon values and beliefs: summary. Portland, OR:

39 p.

Oregon Department of Forestry. 2001. Oregon timber harvest reports, 1990-2000.

Salem, OR. 3 p.

Schindler, B.; List, P.; Steel, B.S. 1993. Managing federal forests: public attitudes in

Oregon and nationwide. Journal of Forestry. 91(7): 36-42.

Steel, B.S.; List, P.; Shindler, B. 1994. Conflicting values about federal forests:

a comparison of national and Oregon publics. Society and Natural Resources.

7(2): 137-153.
137

Chapter 11: Conflicts and Opportunities in

Natural Resource Management: Concepts,

Tools, and Information for Assessing Values

and Places Important to People

Roger N. Clark1

The world today, in general, and natural resource management, in particular, seem to be

about ever-increasing conflicts. As human populations grow, diversify, and move about

the landscape, concerns mount about the impacts of people on water, forests, fish, wildlife, and other people. Strategies for resolving these impacts often result in polarized,

either-or remedies, which lead to land use restrictions or closures. Controversy grows as

people feel inappropriately excluded from areas and places they have used for years if

not generations. In this paper, a number of concepts and approaches are briefly described for identifying and evaluating the values and places important to people. The work

proposed as part of the Interior Northwest Landscape Analysis System project focuses

on human population dynamics and the relationship between human uses and values

and natural resources, with recreation used as a case example. This information, if used

in the context of integrated planning, management, and research should help to develop

and implement strategies for sustaining a more diverse array of biophysical and social

options at multiple spatial and temporal scales.

Keywords: Recreation, integration, resource conflicts, population dynamics.

The past 50 years have seen continuing and emerging conflicts in what people value and

how they wish to use natural resources (Allen and Gould 1986). As our population grows

and diversifies, demands on forests and other natural resources increase. Alarms are

sounded from many quarters about the negative effects of people on a variety of values

that accrue from public and private lands. Also as scientific information expands, new

questions arise about the interactions (both positive and negative) between people and

Abstract

Introduction

1 Roger N. Clark is a research social scientist, U.S. Department

of Agriculture, Forest Service, Pacific Northwest Research

Station, Pacific Wildland Fire Sciences Laboratory, 400 N 34th St.,

Suite 201, Seattle, WA 98103.
138

the natural resources upon which we depend for our survival and lifestyles. Just how real

these problems are is subject to debate. Opposing interest groups’ perspectives, concerns about the ideological positions of managers and scientists, and conflicting data

make the public even more skeptical about who can be trusted to deal with the complex

problems we face.

Many people are dissatisfied with how decisions are made about management of lands

they care about (Wondolleck 1988, Wondolleck and Yaffee 2000). Management of roads

and trails, riparian areas, and threatened and endangered species increasingly leads to

difficult problems where the perception often prevails that people must go. This perception can lead to restrictions and closures that limit public access to resources such as

valued places for recreation. Taking care of one system (i.e., social, biophysical, or economic) often leads to disenfranchising another. Polarization leads to either-or solutions to

complex problems. This often leads to less than optimal solutions with clear winners and

losers. Better ways are needed to identify not only the conflicts but also the compatibilities between biophysical and social values and uses. Many have argued that until we

embrace people as being a part of ecosystems, rather than apart from, we will continue

to breed conflict rather than accommodation (Clark et al. 1999).

Conflicts regarding forest values typically involve the interaction among three key elements: people (their distribution, values, organization, and behavior), places (both the

geographic and symbolic sense), and processes (both ecological processes as well as

human activities and institutions that affect people, places, and their interactions)

(Stankey and Clark 1992). As we seek to better understand these conflicts and to more

effectively fashion solutions that prevent or at least mitigate them, it is important that we

understand how different management programs will affect each element. Conversely, we

need to understand how changes in these elements can affect management programs.

For example, how do changes in forest conditions affect employment opportunities in

rural communities or the availability of recreation sites? How do changes in local populations or land use rules affect adjacent forests and forest management activities?

The work described in this paper focuses on ways to better understand the relationship

between people and natural resources. What people value, their perspectives and perceptions, and what they actually do and where they do it must be considered. Approaches, tools, and information are needed to help managers, scientists, and citizens

work through problem framing and problemsolving to identify and implement options that

are less polarizing than at present (Wondolleck 1988; Yankelovich 1991, 1999).

The Interior Northwest Landscape Analysis System (INLAS) project is intended to assemble and apply concepts, frameworks, models, and other tools to enable resource

managers to address complex biophysical and social values and uses at multiple

scales. Some concepts and tools already exist, whereas others are needed to enable

scientists and managers to better understand what concerns people have and how they

can be better included in planning and management processes.

The work described in this paper will address three components: (1) What frameworks

and concepts exist that can be applied to understand the relations between human concerns, values, and uses and biophysical conditions and processes? (2) What changes

are occurring in the human population and what significance might that have for use and

management of the area? and (3) How can places that are important to people for things

such as recreation be identified, described, and evaluated with respect to other biophysical resources and uses?
139

There are various frameworks and concepts that provide ways to identify, understand,

and evaluate the values and places important to people and how these interact with other

resources. Several such concepts that seem to have value for the INLAS project are

briefly described here.

Periodically, particular words and phrases take on a special if uncertain significance to

people. Integration is one such example. It is used in many circles and implies certain

conditions or actions to those who use it. In research, we frequently cite the need for

“better integration,” or the desire for “integrated approaches” or “integrated teams.” Nevertheless, exactly what makes something integrated remains elusive. In the absence of

some clarity about and shared expectations for what we expect from integration, we run

the risk of perpetuating another round of confusing rhetoric and meaningless slogans

best suited to bumper stickers (Clark et al. 1999).

A more holistic understanding about human-natural resource interactions is needed.

Such understanding will provide the foundation for developing and implementing integrated resource management programs and practices. There are many reasons why

integrated approaches are increasingly desired.

• The world is complex. Either-or approaches are no longer tenable and can be

unnecessarily divisive (owls vs. jobs, timber vs. recreation, fish vs. dams, riparian

restoration vs. public access or recreation use). We need to embrace a wide range

of values and uses to find ways to reject either-or solutions to complex problems.

To understand multifaceted systems, we need models and approaches that allow

us to isolate and explain the interactions within and among its parts. As we attend

to biological and physical factors, we also must deal with the social, cultural, economic and institutional aspects of environmental values and uses. However, these

things cannot only be considered after the fact as add-ons or things to mitigate for

or against.

• Substantive areas (basic processes, problems, issues, policies) require it.

Integrated approaches are about complex processes, connections, and interrelationships. Stewardship and sustainability involve relationships between people,

their environments, and processes that link them. Disciplinary, fragmented research

(even if in sum all the parts are included) does not add up to understanding the

complexity of the whole.

• Traditional institutions often fragment rather than unite. Such institutional

behavior exists in education, management, and research organizations. Diverse

perspectives are valid, and if we can tie them together, we will reveal new knowledge

and provide answers to complex questions facing society.

This project focuses on improving understanding of how systems (biophysical, ecological, human) interact and the effects one has on the other. Lack of such knowledge leads

to loss of options as a tyranny of small decisions are made to resolve perceived problems as conflicts occur between the biophysical and social systems. Ideology rather

than science often guides such decisions. Past research and development have generally been disciplinary where experts start from world views, beliefs, etc. within like

disciplines. We have an opportunity to better understand how these complex systems

function together. This will lead to better understanding of when, where, and how multiple

uses can be allowed without unacceptable adverse effects of one on the other.

Component 1:

Frameworks and

Concepts

Interactions and

Integration
140

For example, the recreation resource is unusual because it represents the combination

of most, if not all, physical and biological resources and their management. Past management has tended to focus primarily on recreation and other public uses apart from all

other resources. Expanding recreational and other opportunities for the public and addressing potential conflicts require an improved understanding of the complex system of

which recreation is a part (Clark 1987).

There are various questions to be addressed regarding the interactions between people

and natural resource values and uses. The basic question is under what conditions can

public access and use of high-quality recreation settings and sites be provided without

adverse effects on biophysical conditions and functions such as in riparian areas? To

understand this, we need to better appreciate how these systems interact. How do

these interactions vary at different spatial and temporal scales? What is acceptable

both from a biophysical and social perspective? Moreover, we need improved frameworks

and knowledge about the cumulative effects on and from recreation use and management, as well as on and from riparian use and management (Clark and Gibbons 1991).

Inadequately framed problems are a major obstacle to designing successful projects to

better understand human-natural resource interactions (Bardwell 1991; Clark et al. 1999,

in press; Senge 1990). Several things that might be considered to improve effective problem framing are briefly described below.

It is important not to commit to a particular direction until one gets the questions right.

This means that we need to step back from individual or disciplinary definitions and join

with other interests to ensure that we are not solving the “wrong” problem. We must

learn from one another about how we define landscapes so that we can jointly determine opportunities and redefine problems and then develop explicit questions to drive

joint actions.

To be effective, problem framing and resolution must include diverse perspectives and

value systems. Because landscape values and meanings are highly variable, there is no

“correct” definition. Although this suggests that diversity may be an obstacle, it may be

an opportunity as well. What can unite us is recognition of the power of both individual

and collective perspectives. Processes that are inclusive increase the possibility of improved understanding, greater representativeness in public participation, an opportunity

to learn, and eventually identifying better ways to get desired outcomes (Wondolleck

1988).

A number of things make designing and implementing integrated approaches hard to do

(Clark et al. 1999, in press). Ideologies and beliefs (world views) condition how we think

and act (Socolow 1976). Such ways of thinking can become problematic if not dealt with

constructively, but can enrich dialogue and problemsolving if embraced upfront. Striving to

get answers and solutions before clarifying the questions and problems often derails the

best intended efforts (Bardwell 1991). Scientific language and expertise make it difficult

for interested citizens to easily engage in processes and activities that affect them.

Technology can be a means to desired ends but can be a hindrance if the wrong questions are under study.

Problem framing is difficult and often inadequate to identify new questions and understanding. A major challenge is to understand the needs and questions to be addressed

before lines are drawn on maps and data collection started. Such problem framing is the

Problem Framing Is a

Critical First Step and

Must Be Ongoing
141

most important, yet least well-done step, particularly if all interested parties are not included up front. Problem framing must account for the world views and ideologies people

have, or these will limit or preclude effectiveness in the longer run. Problem framing must

be iterative and adaptive; it takes time and patience. If done well, clear and shared expectations will result.

To be effective, problem framing must account for diverse ways of knowing and diverse

forms of knowledge. In this sense, scientific knowledge is only one component. It is

necessary but not sufficient for understanding relationships between biophysical and

social systems.

A central problem facing INLAS is to determine the scale of an area to understand the

people-resource interactions (Clark et al. 1999, Jensen and Bourgeron 2001). Landscapes such as that represented by INLAS, and places within them, have meanings to

people at every conceivable scale. Which is the “right” scale depends (Clark et al., in

press). It takes on a different meaning for people who live in the region or beyond vs.

those who live nearby. It differs for people who may care about but never visit the area.

And for people who actually set foot on the land and visit the area, there may be strong

attachments to particular places. The appropriate scale from a human perspective may

not match nicely with biophysical considerations, at least within present planning and

scientific approaches.

There is no one right definition for what a landscape is or the scale(s) appropriate for

understanding relationships between humans and natural resources. Various needs and

questions will define the appropriateness of landscape meanings and scales of analysis.

Sometimes these needs are defined by scientists, and at other times by resource managers, and at still others by citizens. Technical definitions are important for technical

analyses but not necessarily important to everyone; they often are a means to unclear

ends.

In a sense, the meanings that landscapes hold are determined by those viewing the

landscape or by interacting with it in other ways. Each meaning is different, not better or

worse. To fully understand the values and meanings landscapes produce requires that

analyses be inclusive of the people that interact with the landscape in diverse ways.

People think and act at multiple scales for many reasons (Stankey and Clark 1992).

There is no one way to divide time and space that will account for the multiple values,

concerns, and uses that people bring to the understanding of natural resources. Some

ways to think about how landscapes can be considered from a social science perspective are briefly described below.

• A suite of values is of importance to people. There are a number of values that

are important to people as they think about and use forests and other landscapes.

These include commodity, public use, amenity, environmental quality, spiritual, and

health values. Such values are attached to landscapes by different types of people

and at different scales. For example, recreation can be thought of as people using

microsites such as campsites or as driving for pleasure across larger landscapes.

Moreover, the array of values often blends biophysical, economic, and social domains

in different combinations across space, people, and time. This means that to understand the meaning and importance of these values requires expertise beyond the

biophysical sciences.

Landscapes Are in the

Eye of the Beholder2

2

 This section is adapted from Clark et al. (in press) and Stankey

and Clark (1992).
142

• People organize in many ways. There are a variety of ways to think about how

people (individuals) are combined at different scales and how a social organizational

hierarchy can be described. These include individuals, family and household groups,

neighborhoods, communities, counties/boroughs, states/provinces, nations, and

ultimately, the globe. The interests people hold in the landscape at different scales

and the decisions they make about how they interact with the landscape may cut

across these different levels. Each level or scale is characterized by different

emergent properties, such that the next higher scale is not simply an aggregation of

the units at the next lower scale. There are often mismatches between these

organizational units and biophysical scales that will need to be reconciled before any

analysis begins if an integrated solution is desired.

• People act at multiple spatial scales. These include microsites, areas (e.g.,

a grove of trees, meadows), drainages, watersheds, landscapes (e.g., the Upper

Grande Ronde), regions (e.g., the Blue Mountains), continents, and the globe. It is

important to consider such ways of defining scales because different social, cultural,

and institutional properties may emerge at each scale. Appropriate scales may be

defined by the processes at work, interactions within and between components of

complex biophysical and social systems, and policy and scientific needs.

• Human lives and activities consider multiple temporal scales. Ways of defining time include the past, today, tomorrow, weeks, seasons, years, decades, and

generations. These may or may not coincide with how time is considered by

specialists concerned with biophysical phenomena. Differences between biological

and social scales of significance are frequently at the root of conflict—such as when

forest plans are considered over a 50-year timeframe but budgets are appropriated

annually. Considerations of time often influence how acceptable people believe forest

management practices to be. Who can wait, e.g., for newly harvested forests to

become old growth when people only live for a few decades?

• Beware the ecological fallacy when drawing conclusions about people.

Meanings cannot simply be aggregated upward; people may define an entire watershed as a suitable place for timber harvesting, yet hold claims to spiritual, aesthetic,

and recreational meanings at the site level. What may be true at a higher scale, such

as the county level, may not be so at lower scales, such as the communities in the

county; the attributes of a transportation system may not apply to the individual

roads within; qualities of a dispersed recreation area may differ when one looks at

specific sites; and the distribution of meanings across a landscape cannot necessarily be summed to arrive at an overall assignment of landscape meanings. It is

likely in many cases that different processes work at different scales. The perspectives people have when they think at different scales influence judgments about the

appropriateness and acceptability of change. In addition, what may be acceptable at

one scale may not be so at another.

In the INLAS project, recreation will be used as a case example for understanding the

relationship between human uses and values and other resource uses and values. Recreation was chosen because of manager interest and the existence of methods for identifying recreation places people use.

Many of the concepts from the wildlife habitat literature (Thomas 1979) apply to recreation (Clark 1987, 1988). Several of these might be considered when managing for recreation habitats. Understanding these concepts could help managers evaluate the potential

effects of alternative strategies and prescriptions on recreational opportunities (Clark and

Stankey 1979).

Habitats for People
143

• People have “home ranges.” Resident populations tend to center recreation in the

community; other users are migratory (tourists) and frequent sites well beyond their

home ranges. The size of the home range is influenced by the relative availability of

recreational opportunities desired by the population, competition among users for

these opportunities, and mode and duration of travel.

• People use definable “travel corridors.” Natural topographic features and humancreated corridors channel air, water, critters, and people. The intersection of corridors

(water crossings, power corridors, dams) or flows within them often reveals conflicts

and compatibilities between public values and uses and other resource values.

Access in general is constrained by travel routes (roads and trails) and by physicalbiological conditions, such as steep slopes, dense vegetation, and bodies of water.

Knowledge of present and potential travel corridors should help predict the effects of

management practices on recreational use patterns.

• People are “territorial.” They form strong attachments to favorite and often-visited

places and usually do not wish to see them changed. It is important to identify the

location and characteristics of such sites before any on-the-ground management

occurs.

• “Hiding cover” is particularly important at campsites. People generally want privacy

and quiet, and they try to separate themselves from other parties and from evidence

of other resource uses. This seems to be as true for people in moderately developed

areas as it is for people who prefer dispersed settings and wilderness.

• “Critical habitat” might be defined as a combination of attributes considered

absolutely necessary for some types of recreation values and uses.

• “Edges” seem to influence recreational use. For example, sites near natural or

artificial openings and riparian and coastal areas all appear to be used more

frequently than other locations.

• People like “diversity” in the sites they visit and the activities they engage in.

• Site “preferences” may differ from actual “requirements.” Requirements are elements

essential to recreation; preferences add quality to a recreational experience.

However, preferences for some people may be requirements for others.

• Habitats are “dynamic,” and both natural changes and human-caused disturbances

influence the nature of recreational settings. Indeed, the type and location of

recreation activities can change with physical alterations. Such change can be

managed both spatially and temporally to achieve desired goals.

• “Adaptation” occurs as recreation habitats are changed. Users can choose to stay in

such areas and alter their expectations or move on (thus becoming “displaced”) if the

changes exceed their accepted limits. Although either outcome may be appropriate,

the potential consequences of both should be evaluated to avoid destruction of

irreplaceable opportunities.

These concepts can help us think about how people relate to landscapes at multiple

scales and improve our ability to understand the effects of policy options and management practices on existing and potential public values and uses.
144

People form strong opinions about places and the characteristics of places at multiple

scales. They also are concerned about the appropriateness of resource management

uses (in time and space) (Clark and Stankey 1979). Legacies on the land from past management (road management, area closures, timber harvesting) affect judgments in different ways. It is hard for some people to relate to large landscapes when they are

concerned about favorite places. Place attributes and meanings (at multiple scales) influence choices people make (Clark and Downing 1985). However, the meanings people

attach to specific places, and which define critical habitat needs, are often not correlated

with certain types of biogeographical features mapped by biologists.

A variety of factors influence recreation use patterns (Clark 1988). Some of these are

described below.

• The places where people choose to recreate are important. Most people tend to have

special places they visit repeatedly (Clark et al. 1984). Often these are places people

used as children and those where they now take their children. These places may be

large landscapes or small sites. Favorite and often-visited sites are definable, and

people form strong attachments to them (Clark et al. 1984, Clark and Stankey 1986).

In many areas, recreationists have established their own campsites, and they are

concerned about the relation between other resource uses and these sites; many

want their favorite campsites protected from the effects of logging (or other resource

uses) (Clark and Downing 1985, Clark and Stankey 1986, Clark et al. 1984).

• The type of access is the key to most recreation and strongly influences use

patterns. For example, as a group, people who recreate in roaded forest lands want

roads of various designs and standards, but they do not need to be paved in all

cases.

• Site attributes affect, in many often predictable ways, how recreationists make

choices (McCool et al. 1985, Stankey and McCool 1985). Some attract (scenery) or

detract (bugs and poisonous snakes); some facilitate (road pullouts) or constrain

(steep terrain) (Clark and Stankey 1986). Attributes that have been determined to be

particularly important in dispersed areas include water (marine, riparian, lakes,

streams), trees (of various species, densities, and age), flat areas, naturalness (or

natural appearing), and privacy from others not in one’s own party (much like wilderness users). Knowledge of these attributes aids in determining what is possible,

desirable, or necessary at a particular location to protect, enhance, or create

opportunities for recreation.

Recreation (both in terms of our choice of activity and places) often plays a major role in

where people choose to live and take vacations. Relatively easy access to diverse natural environments explains why many people have chosen to reside where they do. The

forests, lakes, streams, mountains, and all the associated wildlife provide a rich backdrop for the diverse recreation people seek. Special places and favorite activities provide

the temporary retreat from pressures at work and at home.

So when managers of public (and in some cases private) lands consider changing

what users have known and valued about those special places, users become alarmed.

People remember other places that have been lost for one reason or another (Clark and

Stankey 1979). Many questions come to mind: What will the changes mean to one’s

family? How long will it take before one can go there again? Do managers know about

Settings and Places

Important to People
145

the places people like and why they like them? Can favorite places be protected? These

and other questions are important because the places people value are more than rock,

dirt, and trees that can easily be replaced. They have special meaning that even the best

manager cannot easily discern (Downing and Clark 1979).

Natural resource management programs are considered to be sustainable when they are

ecologically sound, economically feasible, and socially acceptable. Social acceptability

is an essential aspect of any successful implementation effort. The social acceptability

judgment process is critical to the efforts to manage natural resource systems on an

integrated, multiple-value basis. For instance, any given practice is likely evaluated on

the basis of potential alternatives as well as the consequences of any given alternative

on other resources, values, and benefits. If a proposal to limit public access to riparian

corridors, e.g., is presented solely as a means of restoring aquatic habitat, some particular patterns of acceptability will emerge. However, if the proposal also includes the

impacts such closures will have on historical recreation, then it is likely that some other

pattern of acceptability will emerge. At present, such multiresource issues typically lack

full consideration of social acceptability assessments, with the result that public opposition increases.

Understanding is limited about the factors affecting the formation of acceptability judgments, their resistance to change, and the conditions that lead to change. A conventional premise is that public judgments are primarily influenced by the level and accuracy

of the technical and scientific information held by different citizen interests, or that they

are predominantly the reflection of adverse aesthetic judgments. Existing research on

social acceptability indicates that judgments are the product of a complex, multifaceted,

and dynamic process, of which information—in the technical-scientific sense—or aesthetic appearances are only a part. The judgment formation process is greatly affected

by the belief systems of individuals. In addition, the trust associated with individuals or

organizations making decisions can have a major effect on what is and is not acceptable.

The nature and extent of change acceptable to recreationists and other forest users differs (Clark and Stankey 1979; Stankey et al. 1985, 2003). People seem to have different

expectations for “macro” versus “micro” sites, and the microsite seems more susceptible

to adverse change; i.e., management activities acceptable in the general area (such as

evidence of logging or roads or restoration activities) may be considered intolerable at a

campsite.

Acceptance of change varies both in time and space and depends on many factors

(Kakoyannis et al. 2001, Shindler et al. 2002). Judgments about the acceptability of

change depend on its nature, extent, cause, and location with respect to specific areas,

the meanings people attach to landscapes at different scales, and places people value.

Acceptability—of What,

for Whom, Why

The research community has a significant role in helping create a more socially acceptable brand of forest management. Not that there is an insufficient amount of either

theoretical research or applied research already to draw from. What is in short supply,

however, is (1) well-defined, manager-friendly frameworks for conducting more socially

acceptable processes and (2) the institutional will (i.e., commitment, time, and resources) for experimentation and implementation (Shindler et al. 2002).
146

The Pacific Northwest is experiencing rapid and far-reaching population changes

(McCool et al. 1997). Population growth and redistribution affect both urban and rural

areas. Accompanying this growth and change is a climate of increasing conflict over the

region’s once-abundant natural resources. Much of this conflict centers on changing

societal values and expectations regarding the things public lands should produce

(McGranahan 1999). Moreover, there is increased competition for the commodities,

amenities, and recreational opportunities provided by those public lands.

Given this dynamic and challenging context, it is important to understand both how the

population is changing and the potential implications these changes have for the management of forest lands in the Pacific Northwest (Troy 1998). As certain communities

shift from rural to suburban or urban, what changes are likely to occur in attitudes and

public uses regarding natural resource issues? What are the factors that are driving migration from urban to rural areas? Are the motivations for in-migration to rural communities driven by economic concerns or by the amenities of small towns and natural

resources?

The fundamental concept driving the analysis of population dynamics is that changes in

the makeup of human populations will be accompanied by changes in the attitudes and

uses of residents toward the management of forest lands whether public or private. In

addition, these changing attitudes and uses will have a profound influence on the actions

of management agencies. Making the connection between attitudes, public uses, and

changing social conditions will help managers respond to and anticipate the needs of

local and regional residents. Ultimately this type of knowledge can help managers respond to challenges and opportunities at various geographic scales and for various user

groups.

This assessment will provide a detailed description of the population dynamics in the

region and selected areas such as INLAS. Ways to understand, articulate, and display

the multiple and interrelated changes occurring within the region will be explored. Data

from sources such as the U.S. Census and Internal Revenue Service will be used to

develop graphical and interaction-oriented approaches to describe the population dynamics. Adopting this approach will allow for an analysis of the factors driving more localized

changes as well as an examination of how local areas might influence and be influenced

by regional population dynamics. The graphical approach will enhance our ability to engage in a broader dialogue regarding the nature of these changes.

Beyond a basic description, there is a need to address why the observed changes

matter. Thus, a second focus will produce a series of propositions regarding how the

changing character of the region’s population may influence shifts in acceptability of

forest management practices. Making this link between population dynamics, public

uses, and attitudes will require the use of existing data as well as the possible collection of new information on resident attitudes toward natural resource management if time

allows. This second product also will involve a focused examination of specific subregions within Oregon and Washington, including INLAS. The choice of communities will

be made to highlight issues for areas that are currently experiencing rapid change along

with those that have relatively slower rates of change.

Component 2:

Population

Dynamics3

3

 This work is being conducted by Theron Miller and Steve McCool

at the University of Montana’s School of Forestry in conjunction

with the author.
147

Population change in rural areas has significant implications for the acceptability of various land management actions (e.g., treatment of fuels, use of fire, and management of

wildlife). Where public lands are intermingled with private, rapidly developing lands, there

are significant questions about how newly arriving individuals, with potentially different

ties to public landscapes than long-term residents, will be attached to these landscapes,

and how those attachments may affect acceptability of forest management.

In addition, population growth and redistribution have implications for demand of recreational opportunities provided on public lands. Because the in-migrating population may

have characteristics different from existing residents, their patterns of participation in

recreation may differ. As a result, the character and distribution of the supply of existing

facilities and opportunities may no longer be adequate for the “new” population.

Beyond the benefits to individuals directly involved in management, this type of analysis

could help provide an avenue for involvement of community leaders and concerned citizens. The process of understanding the many social changes to an area can facilitate

both community learning and assist in efforts of problemsolving.

As described earlier, knowing the sites people use in forests is important for understanding the potential interactions between this use and other resource values and uses. In

this project, we will focus on recreation as one example of human use taking place in the

INLAS area.

Recreational uses often compete with timber, wildlife, fisheries, and other resource

uses for the same sites (Clark 1988, Clark et al. 1984). An understanding of the relationships between recreation and other uses of forested lands is required for effective multiresource management. Important questions needing answers include: Who are the

visitors of specific areas? What are the activities in which they engage? When do they

engage in these activities? Where do they engage in these activities? What site characteristics influence where they go? What are the effects on recreation in areas where

other resource uses are managed and vice versa? How important are these effects from

the perspective of the public and land managers? What concepts, frameworks, and management tools exist or might be developed to help mitigate adverse effects?

Knowing the importance forest visitors attach to particular features of recreational settings (called “site attributes”) is the foundation of effective recreation management. Without information about these attributes, land managers cannot maintain or enhance desirable

qualities, nor can they prevent or mitigate damage to recreational values as a result of

other forest uses, such as timber management. There is a need for a better understanding of what attributes can be avoided and positive effects enhanced. Attributes constitute

the features that define an area or site as a recreational resource. Knowing what these

attributes are, their relative importance to recreationists participating in different activities

or seeking different experiences, and the sensitivity of the attributes to change is essential input to integrated resource management.

Alterations in settings induced by nonrecreational resource uses can greatly change the

type of recreational opportunities available. Conversely, maintaining the essential attributes of a particular recreational opportunity setting might represent a significant constraint on other uses. For example, a management objective to maintain semiprimitive or

primitive recreation opportunities would limit the nature and extent of timber harvest activities appropriate in the area (Clark and Stankey 1979). Understanding these interdependencies is essential to the integration of different resource allocations and to minimizing

conflict (Clark and Gibbons 1991, Clark and Stankey 1986).

Component 3:

Place–Based

Analyses of

Recreation Use
148

We must understand the complex system of which recreation is a part. There remains,

however, a lack of comprehensive knowledge and site-specific guidelines to facilitate

effective integration of recreation and other resource uses at multiple temporal and spatial scales. Part of the problem is the limitation of knowledge about just where people go

and what the characteristics are of those places. In this project, the author and colleagues developed and applied methods for several watersheds in eastern Washington

that will be used to locate and characterize sites used by the public in parts of the

INLAS area.

This assessment of places that people use will include:

• Locate specific places along formal and informal roads in several subareas of the

INLAS project area where there is trace evidence of public use (including but not

limited to recreation).

• Use a global positioning system to establish the location of sites identified.

• Complete a written description of the sites.

• Take photos that can be used to classify the site and its surroundings (at the

microlevel and macrolevel).

• Describe and document the relationship between the sites identified and evidence of

resource management activities.

• Create geographical information system data layers to allow analysis of the

interrelationships between public use and other forest values and uses and forest

management activities.

Knowledge of important recreation sites and their attributes will assist managers in

evaluating the consequences of changes because of other resource uses on dispersed

recreation opportunities (Brown et al. 1978, Clark and Stankey 1986). Such information

will aid in developing strategies to prevent or mitigate undesirable impacts on biophysical

resources while taking advantage of positive changes to provide a desired range of public

benefits.

This work will provide three major types of products:

• Syntheses of available frameworks and concepts and how they might be used in the

context of integrated research and development and management at multiple scales

in areas such as INLAS.

• Empirical information about regional and local population migration and a framework

to evaluate the potential effects of population changes on places people use and their

acceptance of management practices.

• A description of specific places for parts of INLAS that are used by the public. This

will be useful as a stand-alone product, but its best use will be in the context of an

integrated approach to assessing the interactions between biophysical and social

values and uses in areas such as INLAS.

It is yet to be determined how this information will be integrated with other biophysical

information.

Expected Outcomes

and Products
149

Both public and private resource policymakers and managers should find the information

useful for designing, implementing, and evaluating options at multiple scales. The primary beneficiaries of this research effort will be natural resource managers of federal,

state, and private lands. They will benefit from a clearer understanding of the dynamic

populations and attitudes within the areas that they operate and the types of places that

are important to existing and future populations. This will be particularly helpful for managers in areas currently experiencing rapid population changes and conflicts between

human and other uses. Managers in other areas could use the results of this research to

anticipate future changes.

The ultimate beneficiary of this information is the public who depends on the resource

values and uses provided by areas such as those represented by INLAS.

Whether intended or not, almost all forest management activities affect public values and

uses. The effects of management are not necessarily negative and largely depend on

people’s preferences and expectations. However, effective multiresource management

demands an understanding of the interactions among public and other uses.

In addition, changes in human populations have significant implications for the use and

management of diverse natural resources. It is not just how many people are leaving the

area or moving in but what values and expectations they have for nearby as well as distant forests and rangelands.

Furthermore, it is critical to have detailed, place-based analysis of human and natural

resource interactions. Information about public use—the where, who, when, why, and

how—enables planning processes to consider human and natural resource interactions

at multiple spatial and temporal scales.

From this brief overview, it seems evident that a holistic, systems perspective is needed

to help integrate public uses such as recreation with other resources. The recreation

resource, in particular, is unusual, compared to some resources, in that it is represented

by the combination of all other physical and biological resources and how they are managed. The complex interrelationships among these resources have important implications for recreational opportunities and use (Clark et al. 1984).

The questions posed earlier can be resolved with a more holistic perspective that recognizes the nature of potential onsite interactions between public uses and other resources. Past management has focused primarily on public uses such as recreation

apart from other uses. Expanding opportunities for the future and addressing the potential for onsite conflicts and ways to resolve them require an improved understanding of

the complex system of which human concerns are an integral part. The overriding question is not whether human values and uses should be integrated with other resource

uses, but where, when, and how such integration can be achieved.

It is critical that approaches developed to understand these interactions consider people

and their uses at multiple scales. We must begin to make connections between biophysical and human systems, or we will continue to fall victim to extreme, polarized,

solutions to resolving complex problems (Clark and Gibbons 1991).

Almost everything resource managers do, whether planned or not, will affect opportunities for the public. People react to this reality as they anticipate or discover undesirable

changes in areas and at sites they value. Professionals must be sensitive to how what

they do affects people and places people value. Failure to do so could easily lead to

further polarization and loss of manager credibility as well as support for agency or landowner programs.

Users of Information

Conclusions
150

Unfortunately, there are few specific guidelines and little detailed information to facilitate

such integration and few tested approaches for managing potentially incompatible uses

at specific locations. There are, however, a variety of concepts and frameworks that can

be used to address some of the questions listed earlier. These tools will provide aids to

help managers, citizens, and scientists work through problemsolving for complex and

controversial issues; rarely, however, will they provide definite answers.

Allen, G.M.; Gould, E.M., Jr. 1986. Complexity, wickedness, and public forests. Journal

of Forestry. 84(4): 20-23.

Bardwell, L. 1991. Problem-framing: a perspective on environmental problem-solving.

Environmental Management. 15(5): 603-612.

Brown, P.J.; Driver, B.L.; McConnell, C. 1978. The opportunity spectrum concept and

behavioral information in outdoor recreation resource supply inventories: background

and application. In: Lund, G.H.; LaBau, V.J.; Ffolliott, P.F.; Robinson, D.W., tech.

coords. Integrating inventories of renewable natural resources: Proceedings of the

workshop. Gen. Tech. Rep. RM-55. Fort Collins, CO: U.S. Department of Agriculture,

Forest Service, Rocky Mountain Forest and Range Experiment Station: 73-84.

Clark, R.N. 1987. Recreation management: a question of integration. Western Wildlands. 13(1): 20-23.

Clark, R.N. 1988. Enhancing recreation opportunities in silvicultural planning. In:

Schmidt, W.C., comp. Proceedings: future forests of the mountain West: a stand

culture symposium. Gen. Tech. Rep. INT-243. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station: 61-69.

Clark, R.N.; Downing, K.B. 1985. Why here and not there: the conditional nature of

recreation choice. In: Stankey, G.H.; McCool, S.F., comps. Proceedings, symposium

on recreation choice behavior. Gen. Tech. Rep. INT-GTR-184. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment

Station: 61-70.

Clark, R.N.; Gibbons, D.R. 1991. Recreation. In: Meehan, W.R., ed. Influences of forest

and rangeland on salmonid fishes and their habitats. Spec. Publ. 19. Bethesda, MD:

American Fisheries Society: 459-481. Chapter 13.

Clark, R.N.; Koch, R.W.; Hogans, M.L. [et al.]. 1984. The value of roaded, multiple use

areas as recreation sites in three national forests of the Pacific Northwest. Res. Pap.

PNW-319. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Forest and Range Experiment Station. 40 p.

Clark, R.N.; Kruger, L.E.; McCool, S.F.; Stankey, G.H. [In press]. Landscape perspectives. Res. Pap. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station.

Clark, R.N.; Stankey, G.H. 1979. The recreation opportunity spectrum: a framework for

planning, management, and research. Gen. Tech. Rep. PNW-98. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station. 32 p.

Clark, R.N.; Stankey, G.H. 1986. Site attributes—a key to managing wilderness and

dispersed recreation. In: Proceedings: national wilderness research conference. Gen.

Tech. Rep. GTR-INT-212. Ogden, UT: U.S. Department of Agriculture, Forest Service,

Intermountain Research Station: 509-515.

Literature Cited
151

Clark, R.N.; Stankey, G.H.; Brown, P.J. [et al.] 1999. Toward an ecological approach:

integrating social, economic, cultural, biological and physical considerations. In:

Johnson, N.C.; Malk, A.J.; Sexton, W.T.; Szaro, R., eds. Ecological stewardship: a

common reference for ecosystem management. Oxford, United Kingdom: Elsevier

Science Ltd. 3: 297-318.

Downing, K.B.; Clark, R.N. 1979. Users’ and managers’ perceptions of dispersed recreation impacts: a focus on roaded forest lands. In: Ittner, R.; Potter, D.R.; Agee, J.K.;

Anschell, S., eds. Recreational impact on wildlands: Proceedings of a conference.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region; U.S. Department of the Interior, National Park Service, Pacific Northwest Region:

18-23.

Jensen, M.E.; Bourgeron, P.S., eds. 2001. A guidebook for integrated ecological

assessments. New York: Springer-Verlag, Inc. 536 p.

Kakoyannis, C.; Shindler, B.; Stankey, G.H. 2001. Understanding the social acceptability of natural resource decisionmaking processes by using a knowledge base

modeling approach. Gen. Tech. Rep. PNW-GTR-518. Portland, OR: U.S. Department

of Agriculture, Forest Service, Pacific Northwest Research Station. 40 p.

McCool, S.F.; Burchfield, J.A.; Allen, S.D. 1997. Social assessment of the basin. In:

Quigley, T.M.; Arbelbide, S.J., tech. eds. An assessment of ecosystem components

in the interior Columbia basin and portions of the Klamath and Great Basins. Gen.

Tech. Rep. PNW-GTR-405. Portland, OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station: 1873-2000. Chapter 7. Vol. 4. (Quigley,

T.M., tech. ed.; Interior Columbia Basin Ecosystem Management Project: scientific

assessment).

McCool, S.F.; Stankey, G.H.; Clark, R.N. 1985. Choosing recreation settings: processes, findings, and research directions. In: Stankey, G.H.; McCool, S.F., comps.

Proceedings: symposium on recreation choice behavior. Gen. Tech. Rep. INT-GTR184. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest

and Range Experiment Station: 1-8.

McGranahan, D.A. 1999. Natural amenities drive rural population change. Agric. Econ.

Rep. 781. Washington, DC: U.S. Department of Agriculture, Food and Rural Economics Division, Economic Research Service. 24 p.

Senge, P.M. 1990. The fifth discipline: the art and practice of the learning organization.

New York: Currency Doubleday. 423 p.

Shindler, B.; Brunson, M.; Stankey, G.H. 2002. Social acceptability of forest conditions and management practices: a problem analysis. Gen. Tech. Rep. PNW-GTR537. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 68 p.

Socolow, R.H. 1976. Failures of discourse: obstacles to the integration of environmental

values into natural resource policy. In: Tribe, L.H.; Schelling, C.S.; Voss, J., eds.

When values conflict: essays on environmental analysis, discourse, and decision.

Cambridge, MA: Ballinger Publication Co.: 1-33.

Stankey, G.H.; Clark, R.N. 1992. Social aspects of new perspectives in forestry: a problem analysis. The Pinchot Institute for Conservation Monograph Series. Milford, PA:

Grey Towers Press. 33 p.
152

Stankey, G.H.; Clark, R.N.; Bliss, J. 2003. Fostering compatible forest resource management: the conditional nature of social acceptability. In: Monserud, R.A.; Haynes,

R.W.; Johnson, A.C., eds. Compatible forest management. Dordrecht, The Netherlands: Kluwer Press: 453-480.

Stankey, G.H.; Cole, D.N.; Lucas, R.C. [et al.]. 1985. The limits of acceptable change

(LAC) system for wilderness planning. Gen. Tech. Rep. INT-176. Ogden, UT: U.S.

Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 37 p.

Stankey, G.H.; McCool, S.F., comps. 1985. Proceedings: symposium on recreation

choice behavior. Gen. Tech. Rep. INT-GTR-184. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 106 p.

Thomas, J.W., tech. ed. 1979. Wildlife habitats in managed forests: the Blue Mountains of Oregon and Washington. Agric. Handb. 533. Washington, DC: U.S. Department of Agriculture, Forest Service. 512 p.

Troy, L.R. 1998. Recent human migration to the interior Columbia basin and implications

for natural resource management. Missoula, MT: University of Montana. 75 p. M.S.

thesis.

Wondolleck, J.M. 1988. Public lands conflict and resolution: managing national forest

disputes. New York: Plenum Press. 263 p.

Wondolleck, J.M.; Yaffee, S.L. 2000. Making collaboration work: lessons from innovation in natural resource management. Washington, DC: Island Press. 277 p.

Yankelovich, D. 1991. Coming to public judgment: making democracy work in a complex world. Syracuse, NY: Syracuse University Press. 290 p.

Yankelovich, D. 1999. The magic of dialogue: transforming conflict into cooperation.

New York: Simon and Schuster. 236 p.
153

Chapter 12: Analysis and Modeling of ForestLand Development at the Wildland/Urban

Interface

Jeffrey D. Kline1

Population growth and resulting land use changes are becoming increasingly important

factors in forest management and fire planning as forests are converted to residential and

other developed uses. This part of the Interior Northwest Landscape Analysis System

(INLAS) project examines low-density residential and other development at the wildland/

urban interface in the area surrounding the INLAS project area. The research contributes

to an integrated analysis of fire risk by describing where humans are located on the forest landscape, how they are likely to manage the portion of the landscape they occupy,

how the spatial distribution of humans will change in the future, and what their expectations will be regarding forest management and policy and fire planning.

Keywords: Wildland/urban interface, urbanization, land use change.

Increasingly important factors in forest management and fire planning are population

growth and the impacts resulting land use changes can have on forests as they are

converted to residential and other developed uses. In-migration of people to rural areas

in the Pacific Northwest is resulting in increasing numbers of residences on forest landscapes. Forest-land conversion to developed uses essentially is a permanent change

resulting in the interspersion of nonforest land uses with forest, and often fragmenting

forest landscapes into smaller parcels of land. These processes can result in longer

lasting ecological and economic impacts than forest cutting and fire, where regrowth

and succession may overcome temporary loss of forest. Ecological impacts can include

direct loss of habitat or changes in habitat quality. Economic impacts can include less

intensive forest management for commercial timber resulting in reduced economic output on private lands. Analysis and modeling of existing and potential low-density residential and other development at the wildland/urban interface can anticipate where these

Abstract

Overview

1 Jeffrey D. Kline is a research forester, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station,

Forestry Sciences Laboratory, 3200 SW Jefferson Way, Corvallis,

OR 97331.
154

changes are likely to occur in the future. Such research can contribute to an integrated

analysis of fire risk by describing where humans are located on the forest landscape,

how they are likely to manage the portion of the landscape they occupy, how the spatial

distribution of humans will change in the future, and what their expectations will be regarding forest management and policy and fire planning.

What researchers and policymakers refer to as the wildland/urban interface is characterized by relatively low-density residential and other development on forest landscapes.

Researchers and policymakers hypothesize that such development has the potential to

increase the threat of wildfire associated with increased human habitation and activity in

forests (Lorensen et al. 1993). Many forestry analysts also feel that increasing numbers

of residences located in forested landscapes are leading to increasing costs owing to

wildfire and overburdening firefighting resources that are redirected to save homes instead of containing fires (Milloy 2000). Along with the potential for increased wildfire

threat and increased firefighting costs is the increased potential for significant loss of life

and property. The 2001 fire season in the Pacific Northwest provided numerous examples

of the particular challenges associated with fighting forest fires near homes (e.g., Cockle

2001, Larabee 2001, Quinn 2001).

In addition to these direct implications for fire planning, low-density residential and other

development on forested landscapes can have fewer direct implications regarding forest

management. For example, researchers believe that forest lands located within the

wildland/urban interface become less productive as a result of their fragmentation into

smaller and smaller management units, potentially diminishing the economies of scale

in timber production (Row 1978). Forest tract size has been negatively correlated with

the likelihood of commercial timber management (Thompson et al. 1981) and the propensity of forest owners to harvest timber (Cleaves and Bennett 1995). Lower harvest rates

and less likelihood of commercial timber management also have been correlated with

increasing population densities (Barlow et al. 1998, Wear et al. 1999).

As people migrate into forested areas, the characteristics and forest management objectives of newer more urban-minded forest-land owners also may change. It is believed that

many nonindustrial private forest-land owners are motivated by amenity, recreation, and

other nontimber objectives in addition to or in place of timber production objectives when

making forest management decisions (Binkley 1981; Bowes et al. 1984; Dennis 1989,

1990; Englin and Klan 1990; Hyberg and Holthausen 1989; Kuuluvainen et al. 1996; Max

and Lehman 1988; Newman and Wear 1993; Strang 1983; Swallow and Wear 1993).

Such nontimber objectives have been shown to be important factors motivating nonindustrial private forest-land owners in the Pacific Northwest (Johnson et al. 1997; Kline et al.

2000a, 2000b). Smaller forest tract sizes and changing characteristics of forest-land

owners can alter the manner in which private forest lands are managed and affect the

potential range of management and policy options available to forest managers and

policymakers regarding fire-risk reduction on private forest lands.

A potential secondary impact of development at the wildland/urban interface is overall

changes in people’s values and attitudes toward forestry. A growing number of social

scientists believe that the Nation is experiencing rapid and significant changes in forest

values (Bengston 1994) and attitudes concerning forest management (Davis et al. 1991,

Schindler et al. 1993). Researchers observe that increasing migration of urbanites to

rural areas is resulting in a shift in forest values and a push for forestry policies and practices that reflect changing forest values (Egan and Luloff 2000). Increasing development

A Brief Literature

Review
155

at the wildland/urban interface may be accompanied by a declining empathy toward timber industries and increasing demands for outdoor recreation and the protection of forest

amenities and wildlife. Research suggests that these processes could be taking place in

the Pacific Northwest (Kline and Armstrong 2001). Such changes could have implications regarding the political climate in which forest management and policy and fire planning decisions are made.

A common approach to multidisciplinary landscape-level analysis of socioeconomic and

ecological processes has been to treat humans largely as exogenous to the forest landscape. Land use change analyses commonly have been used in multidisciplinary studies to delineate discrete forest and nonforest or forest and urban land use categories for

integration with other landscape-level models describing socioeconomic and ecosystem

processes and conditions (see, e.g., Bockstael 1996, Kline et al. 2001, Turner et al.

1996). Similar discrete treatments of land use can be found in Bradshaw and Muller

(1998), Chomitz and Gray (1996), Helmer (2000), and Nelson and Hellerstein (1997).

These models generally use spatially referenced land use data to estimate logit or probit

regression models describing the timing and location of changes among discrete land

use categories.

For many applications, a discrete treatment of land use may be appropriate when the

processes under study are relatively insensitive to low levels of human habitation of land.

However, in other applications, when socioeconomic and ecological processes may be

sensitive to a range of human habitation, discrete land use categories may inadequately

characterize the spatial and temporal interactions of humans as agents affecting the

landscape-level processes under study. In the case of wildfire threat on forested landscapes, relatively low-density human habitation can be of particular interest. Wear and

Bolstad (1998) offer an alternative to discrete land use change analysis by describing the

“spatial diffusion” of human populations throughout a landscape. They use data describing building densities to identify explanatory variables useful in predicting building densities. Although Wear and Bolstad (1998) ultimately use their spatial diffusion model to

project changes among discrete land use categories, Kline et al. (in press) show that

their methods can be adapted to describe potential future building density scenarios that

also can serve as inputs into landscape-level models.

The objectives of the research are to (1) develop empirical spatial models of low-density

residential and other development at the wildland/urban interface for select areas in eastern Oregon, (2) use the empirical models to describe likely future development scenarios

based on projections of future population growth and in-migration, and (3) integrate potential future development scenarios with other INLAS submodels describing ecological

conditions and processes and fire risk. The research is intended to provide information

concerning (1) what socioeconomic and geographic factors have contributed to increased

in-migration in eastern Oregon; (2) how these factors have influenced the spatial distribution of people; and (3) how institutional factors, such as land use zoning, have affected

that spatial distribution.

Empirical models describing historical and future low-density residential and other

development at the wildland/urban interface will be estimated for select areas in eastern

Oregon. Model estimation will rely on building density data based on aerial photointerpretation similar to that described in Azuma et al. (1999) for western Oregon. The Oregon

Department of Forestry currently is working to gather building density data for eastern

Oregon. When available, these data will enable analysis and modeling of building density

by using the methods of Wear and Bolstad (1998) and Kline et al. (in press). Empirical

models will be estimated describing historical land use or building density changes as a

Objectives

Research Approach
156

function of socioeconomic and geographic variables. The empirical models will be used

to project future building density scenarios based on projected changes in socioeconomic variables, such as population, included in the models. The projections will be used

to create geographic information system maps (GIS) describing future building density

scenarios, enabling projections to be integrated with other INLAS submodels describing

ecological conditions and processes and wildfire threat.

The analytical method will closely follow methods used by Kline et al. (in press) to project potential future building density scenarios for western Oregon as part of the Coastal

Landscape Analysis and Modeling Study (CLAMS) (Spies et al. 2002). In that analysis,

a negative binomial model was estimated describing the spatial distribution and rate of

change in historical building densities in western Oregon as a function of a gravity index

of development pressure, existing building densities, slope, elevation, and existing land

use zoning. A gravity index was used to describe the spatial proximity of land to existing

cities of varying population sizes. The resulting empirical model was used to project

pixel-level changes in building densities based on projected future population growth of

cities included in the gravity index computation. The projected building density changes

were applied to a 1995 building density map to describe the future spatial distributions of

buildings for successive modeling periods (fig. 33). The building density maps are key

inputs in other socioeconomic and ecological submodels comprising CLAMS.

If historical building density data are not available, analysis and modeling will be accomplished by using existing socioeconomic data available from the U.S. Bureau of the Census and other sources to develop empirical models of human migration (e.g., Amacher et

al. 1998, McGranahan 1999, Swanson 1986). Analysis will focus on describing historical

spatial variation in population densities and other socioeconomic variables, and in describing potential future changes in the spatial distributions of people across the INLAS

study landscape. Landscape-level projections of future spatial distributions of people

would be accomplished by simulating future forest-land development scenarios based on

existing land use zoning maps and projections of future population (e.g., Bradshaw and

Muller 1998, ECONorthwest 2000). Projections of future populations will be obtained from

published U.S. Census figures or estimated from in-migration models. This alternative

analysis would result in GIS maps describing future population density scenarios, enabling projections to be integrated with other INLAS submodels describing ecological

conditions and processes and wildfire threat.

Anticipated products include relatively fine-scale GIS maps of potential future low-density

residential and other development at the wildland/urban interface for select regions of

eastern Oregon, including the INLAS study area. The maps will be used both as standalone products and for integration with other INLAS submodels describing ecological

conditions and processes and fire risk. For example, the maps will identify where forest

land is most likely to be taken out of active management for timber production, enabling

timber production submodels to account for a potentially diminishing forest-land base.

The maps also will be used to identify locations within the INLAS study area where wildfire poses the greatest risk of significant loss of life and property, which may have implications for the types and locations of potential management prescriptions proposed and

analyzed by INLAS researchers.

In addition to maps of potential low-density development will be descriptive analysis and

projections regarding potential changes in the socioeconomic characteristics of the

population of eastern Oregon, including the INLAS study area. Analysis will include discussion regarding the potential impacts of socioeconomic change on regional public

Products
157

demands regarding outdoor recreation and forest amenities, and public perceptions and

attitudes regarding forest management and policy and fire planning goals and strategies.

This analysis would be largely descriptive and contribute to providing the socioeconomic

context in which forest management and policy and fire planning will take place. Other

anticipated products include at least one technical journal article describing the analytical approach and one nontechnical report describing the analysis and its implications for

forest management and policy and fire planning.

Figure 33—Base year and projected building density categories in western Oregon created for the Coastal Landscape Analysis and

Modeling Study. Note: Based on negative binomial model projections of building density change applied to 1995 base year map. Existing

urban development in 1995 base year shown in gray.
158

The users of the information produced by this research include national forest and land

management agencies; state agencies; nonprofit organizations concerned with forests,

fire, and land use change; and researchers seeking to integrate land use change information into landscape-level analyses of ecological conditions and processes. Geographic information system maps of potential future low-density residential and other

development at the wildland/urban interface for select regions of eastern Oregon will

serve as key inputs into other INLAS models of ecological conditions and processes.

Amacher, G.S.; Cruz, W.; Grebner, D.; Hyde, W.F. 1998. Environmental motivations

for migration: population pressure, poverty, and deforestation in the Philippines. Land

Economics. 74(1): 92-101.

Azuma, D.L.; Birch, K.R.; DelZotto, P. [et al.]. 1999. Land use change on non-federal

land in western Oregon, 1973-1994. Salem, OR: Oregon Department of Forestry. 55 p.

Barlow, S.A.; Munn, I.A.; Cleaves, D.A.; Evans, D.L. 1998. The effect of urban sprawl

on timber harvesting. Journal of Forestry. 96(12): 10-14.

Bengston, D.N. 1994. Changing forest values and ecosystem management. Society and

Natural Resources. 7: 515-533.

Binkley, C.S. 1981. Timber supply from private nonindustrial forests. Bull. 92. New

Haven, CT: School of Forestry and Environmental Studies, Yale University. 97 p.

Bockstael, N.E. 1996. Modeling economics and ecology: the importance of a spatial

perspective. American Journal of Agricultural Economics. 78: 1168-1180.

Bowes, M.D.; Krutilla, J.V.; Sherman, P.B. 1984. Forest management for increased

timber and water yields. Water Resources Research. 20: 655-663.

Bradshaw, T.K.; Muller, B. 1998. Impacts of rapid urban growth on farmland conversion: application of new regional land use policy models and geographical information

systems. Rural Sociology. 63: 1-25.

Chomitz, K.M.; Gray, D.A. 1996. Roads, land use, and deforestation: a spatial model

applied to Belize. The World Bank Economic Review. 10: 487-512.

Cleaves, D.A.; Bennett, M. 1995. Timber harvesting by nonindustrial private forest landowners in western Oregon. Western Journal of Applied Forestry. 10(2): 66-71.

Cockle, R. 2001. Northeast Oregon town threatened. The Oregonian. August 17.

http://www.oregonlive.com/news/oregonian/index.ssf?/xml/story.ssf/

html_standard.xsl?/base/front_page/9980493443448189.xml. (10 September).

Davis, L.S.; Ruth, L.W.; Teeguarden, D.; Henly, R.K. 1991. Ballot box forestry. Journal of Forestry. 89(12): 10-18.

Dennis, D. 1989. An economic analysis of harvest behavior: integrating forest and ownership characteristics. Forest Science. 35: 1088-1104.

Dennis, D.F. 1990. A probit analysis of the harvest decision using pooled time-series

and cross-sectional data. Journal of Environmental Economics and Management.

18: 176-187.

ECONorthwest. 2000. Research report 1: density, development patterns, and definition of alternatives. Prepared for Willamette Valley Alternative Futures, Eugene, OR.

On file with: ECONorthwest, 99 West 10th, Suite 400, Eugene, OR 97401.

Users

Literature Cited
159

Egan, A.F.; Luloff, A.E. 2000. The exurbanization of America’s forests: research in rural

social science. Journal of Forestry. 98(3): 26-30.

Englin, J.E.; Klan, M.S. 1990. Optimal taxation: timber and externalities. Journal of

Environmental Economics and Management. 18: 263-275.

Helmer, E.H. 2000. The landscape ecology of tropical secondary forest in montane

Costa Rica. Ecosystems. 3: 98-114.

Hyberg, B.T.; Holthausen, D.M. 1989. The behavior of nonindustrial private forest landowners. Canadian Journal of Forest Research. 19: 1014-1023.

Johnson, R.L.; Alig, R.J.; Moore, E.; Moulton, R.J. 1997. Nonindustrial private landowners’ view of regulation. Journal of Forestry. 59: 23-28.

Kline, J.D.; Alig, R.J.; Johnson, R.L. 2000a. Forest owner incentives to protect

riparian habitat. Ecological Economics. 33(1): 29-43.

Kline, J.D.; Alig, R.J.; Johnson, R.L. 2000b. Fostering the production of nontimber

services among forest owners with heterogeneous objectives. Forest Science.

46(2): 302-311.

Kline, J.D.; Armstrong, C. 2001. Autopsy of a forestry ballot initiative: characterizing

voter support for Oregon’s Measure 64. Journal of Forestry. 99(5): 20-27.

Kline, J.D.; Azuma, D.L.; Moses, A. [In press]. Modeling the spatially dynamic distribution of humans in the Oregon (USA) Coast Range. Landscape Ecology.

Kline, J.D.; Moses, A.; Alig, R.J. 2001. Integrating urbanization into landscape-level

ecological assessments. Ecosystems. 4(1): 3-18.

Kuuluvainen, J.; Karppinen, H.; Ovaskainen, V. 1996. Landowner objectives and

nonindustrial private timber supply. Forest Science. 42: 300-308.

Larabee, M. 2001. Fire brings urban peril into focus. The Oregonian. August 12. http://

www.oregonlive.com/news/oregonian/index.ssf?/xml/story.ssf/html_standard.xsl?/

base/front_page/9975309381909169.xml. (10 September).

Lorensen, T.; Birch, K.; Lettman, G. 1993. Wildfire prevention and control in areas of

residential forest land development: an analysis of fire data. Tech. Bull. Salem, OR:

Public Affairs Office, Oregon Department of Forestry. [Pages unknown].

Max, W.; Lehman, D.E. 1988. A behavioral model of timber supply. Journal of Environmental Economics and Management. 15: 71-86.

McGranahan, D.A. 1999. Natural amenities drive rural population change. Agric. Econ.

Rep. 781. Washington, DC: U.S. Department of Agriculture, Economic Research

Service. 24 p.

Milloy, R.E. 2000. Population trends heighten West’s fire woes. New York Times.

August 10: Sect. A: 10.

Nelson, G.C.; Hellerstein, D. 1997. Do roads cause deforestation? Using satellite images in econometric analysis of land use. American Journal of Agricultural Economics. 79: 80-88.

Newman, D.H.; Wear, D.N. 1993. Production economics of private forestry: a comparison of industrial and nonindustrial forest owners. American Journal of Agricultural

Economics. 75: 674-684.
160

Quinn, B. 2001. Crews abandon 10 homes to Quartz Fire. The Oregonian. August 14.

http://www.oregonlive.com/news/oregonian/index.ssf?/xml/story.ssf/

html_standard.xsl?/base/front_page/99779015127150166.xml. (10 September).

Row, C. 1978. Economies of tract size in timber growing. Journal of Forestry. 78:

576-582.

Schindler, B.; List, P.; Steel, B.S. 1993. Managing federal forests: public attitudes in

Oregon and nationwide. Journal of Forestry. 91(7): 36-42.

Spies, T.A.; Reeves, G.H.; Burnett, K.M. [et al.]. 2002. Assessing the ecological

consequences of forest policies in a multi-ownership province in Oregon. In: Liu, J.;

Taylor, W.W., eds. Integrating landscape ecology into natural resource

management. New York: Cambridge University Press.

Strang, W.J. 1983. On the optimal forest harvesting decision. Economic Inquiry.

11: 576-583.

Swallow, S.K.; Wear, D.N. 1993. Spatial interactions in multiple-use forestry and substitution and wealth effects for the single stand. Journal of Environmental Economics

and Management. 25: 103-120.

Swanson, L.L. 1986. What attracts new residents to nonmetro areas? Res. Rep. 56.

Washington, DC: U.S. Department of Agriculture, Economic Research Service. 15 p.

Thompson, R.; Thompson, P.; Jones, J.G. 1981. Classifying nonindustrial private forest land by tract size. Journal of Forestry. 81: 288-291.

Turner, M.G.; Wear, D.N.; Flamm, R.O. 1996. Land ownership and land-cover change

in the southern Appalachian Highlands and the Olympic Peninsula. Ecological Applications. 6: 1150-1172.

Wear, D.N.; Bolstad, P. 1998. Land-use changes in southern Appalachian landscapes:

spatial analysis and forecast evaluation. Ecosystems. 1: 575-594.

Wear, D.N.; Liu, R.; Foreman, J.M.; Sheffield, R. 1999. The effects of population

growth on timber management and inventories in Virginia. Forest Ecology and Management. 118(1-3): 107-115.
161

Chapter 13: Evaluating Forest Products as Part

of Landscape Planning

R. James Barbour, Douglas Maguire, and Ryan Singleton1

The probability that harvest activities will occur on any piece of ground is a function of the

accessibility of the ground (both physically and administratively), the costs of implementing the treatment, and the value of the removed material. We describe the concept of

combining these three attributes to develop a utilization index that can be used to display where on a landscape timber harvest might be most fruitfully used to alter stand

structural conditions. Displaying the three component parts of this index allows managers to understand that a particular polygon on the landscape is either a good candidate

for timber removal or not. At least in theory, these same techniques could be applied to

the collection of any number of nontimber forest products.

Keywords: Timber management, harvesting, financial analysis, wood utilization.

Outputs from the Interior Northwest Landscape Analysis System (INLAS) modeling

framework (Barbour et al. Chapter 1) will help policymakers, managers, and the public

understand the capacity of subbasin-sized landscapes (about 500,000 acres, or about

202 300 hectares) located in the interior Northwest to deliver ecological, social, and economic benefits including the potential to remove timber and nontimber forest products.2

Abstract

Introduction

1 R. James Barbour is a research forest products technologist,

U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station, Forestry Sciences Laboratory, 620 SW Main,

Suite 400, Portland, OR 97205. Douglas Maguire is an associate

professor of silviculture, and Ryan Singleton is a research

forester, Department of Forest Science, Oregon State University,

Corvallis, OR 97331.

2 Nontimber forest products (also referred to as special forest

products) are defined as “species harvested from forests for

other than timber commodities” (Vance et al. 2001). They can

include “nonwoody species, such as mushrooms, ferns, and

other understory plants; nonwoody parts of trees, such as

cones, fruits, bark, foliage, and sap; and woody material such

as firewood, poles, and boughs” (von Hagen and Fight 1999).
162

The INLAS framework tracks the vegetation on individual landscape units (polygons) and

projects the quality and abundance of various resources under different management

policies while considering dynamic disturbance processes (Hemstrom et al. Chapter 2,

Bettinger et al. Chapter 4).

The goal of the INLAS utilization analysis is to develop a simple metric that is useful for

displaying the quality and abundance of timber and nontimber forest products under different policy goals. We call this metric the “utilization potential” and use it to integrate

information about the economic costs of harvesting, the administrative and physical ease

of accessing each polygon, and the types and values of materials removed. The utilization potential under alternative management scenarios depends on both the current

stand conditions and the long-term stand growth responses to proposed silvicultural

treatments. The utilization analysis will characterize the quality and quantity of current

timber and nontimber forest products, and when possible also project their future quality

and quantity in response to proposed treatments.

Four questions make up the primary focus of the INLAS utilization analysis:

1. What is the product potential3

 for materials removed from each stand (polygon) under

alternative management scenarios?

2. Will the various management scenarios require financial subsidies?

3. What is the accessibility of timber and nontimber forest products on each polygon?

4. What is the utilization potential4 for each polygon?

We will address secondary questions indirectly through integration with the other discipline areas covered by the INLAS project. As the project develops, these questions may

change in scope and complexity, but they will initially include:

1. What road network is necessary for utilization and what hazards (e.g., fires, sediment,

resource damage) are associated with this network? (Links to vegetation, wildlife, and

aquatics discipline areas).

2. How does active management affect the amount or duration of smoke associated with

planned and unplanned fires? (Links to vegetation and disturbance discipline areas).

3. How does the collection of nontimber forest products contribute to the local economy?

(Links to sociocultural and economics discipline areas).

4. How do various management scenarios influence the abundance and accessibility of

nontimber forest products? (Links to vegetation and sociocultural discipline areas).

5. How do proposed treatments enhance or degrade production of nontimber forest products? (Links to vegetation and sociocultural discipline areas).

A key objective of the INLAS project is to use existing models as much as possible.

The INLAS utilization module will use available models and methodology to evaluate (1)

accessibility, (2) product potential, (3) financial return, and (4) utilization potential (composite of 1 through 3) for timber and nontimber forest products for each polygon on the

Research Objectives

Research Approach

3

 The suitability of harvested materials for manufacturing a variety

of timber and nontimber forest products.

4

 Utilization combines product potential, accessibility, and financial

return.
163

landscape. Models are available to describe the mechanics of timber harvest, the finances of harvesting and processing, the impacts of harvesting on other resources

and ecological processes, wood utilization, and the subsequent economic impacts of

wood processing industries. Comparable information does not currently exist for most

nontimber forest products. This information gap leads to an apparent emphasis on timber

over nontimber forest products in this section. Where possible we will incorporate available information on nontimber forest products into the INLAS framework. We hope to

highlight those areas where additional research about nontimber forest products is

needed and use our analysis of wood utilization to demonstrate how this information

could be used for integrated landscape modeling.

The potential economic value of all forest products is influenced by road access, the

costs associated with harvesting, and transportation to markets. Geographical information system (GIS) layers are available with current road locations, polygon delineation,

topographic features, and sensitive areas. We will define the physical accessibility of

each polygon as the distance from the centroid of the polygon to the nearest road. Likewise, we will determine the haul distance from each polygon to one of three major exit

points from the watershed. The physical access information will point out the need for

new roads by indicating where the distance to the nearest road exceeds a predetermined

threshold level. For nontimber forest products, travel times will include both the time required to drive to the closest access point for each polygon plus an estimate of the time

required to walk from the closest road access to collection sites. Under some policy

goals, administrative access to certain polygons is restricted or prohibited. In those

cases we will reduce or eliminate accessibility to them accordingly.

We will compile information into an index and display it graphically as a set of maps that

indicate access to both timber and nontimber resources. Prescription design and management scenarios can make use of this information, and the implications for utilization

potential and product values can also be evaluated during allocation of treatments across

the subbasin. Assigning specific polygons to classes of hauling/travel distances or administratively restricted access will provide a simple method to summarize the results of

the GIS analysis.

Our analyses will include the expected performance of harvested materials in various

primary-manufacturing applications. Projections of the volume and characteristics of

wood removed under each management scenario will allow evaluation of alternative configurations of industrial facilities that might develop over the coming decades. The wood

processing facilities that use materials from the Upper Grande Ronde basin, however, are

likely to draw resources from a much broader geographic area, so it will not be possible

to estimate the size of the industry that treatments might support.

Tree lists generated by the vegetation simulators (Hemstrom et al. Chapter 2, Bettinger

et al. Chapter 4) will identify both the trees selected for removal and those slated for

retention under each management scenario. We will use information on the residual

stands to evaluate future timber volume and quality. For harvested material we will use

existing methods to estimate the harvesting costs (Hartsough et al. 2001), and both the

quantity (Wycoff et al. 1982) and characteristics (Barbour and Parry 2001, Barbour et al.

1997, Parry et al. 1996) of wood removed under different management alternatives. Surveys of delivered log prices (e.g., Log Lines 2003) to existing facilities will supply the

initial input prices for financial analyses.

Accessibility for

Extraction of Forest

Products

Wood Utilization
164

We will combine elements of existing models, e.g., FEEMA (Fight and Chmelik 1999),

with new programming solutions and tree-level information from the vegetation simulators

(Hemstrom et al. Chapter 2, Bettinger et al. Chapter 4) to develop estimates of both potential yields of and financial returns from various wood product options.

The system will pass tree lists from the vegetation simulators included in the INLAS

framework to a tool for characterizing wood product potential and conducting financial

analyses. Storage of results in a database will allow production of customized tabular

outputs. Combining these results with GIS data on road systems and land allocation will

result in maps illustrating where different types of wood material are located, the financial

costs associated with removing it, and the biophysical or sociopolitical constraints on

removing it (fig. 34).

Output tables will include information on the means and variability of initial and residual

stand conditions, size and volume of merchantable and submerchantable trees removed

during treatments, log diameter, species distribution, and financial return. The tremendous amount of data generated from each scenario evaluated by using the INLAS process makes the creation of a succinct set of tables essential. Final formats will reflect

user needs, with one possible format shown in figure 35. This format was used for a recent analysis of current and projected future conditions in the state of Montana (Barbour

et al., 2004).

A set of idealized maps (fig. 36) provides an example of spatially explicit graphical results for a hypothetical landscape with four polygons. These four simple maps provide

estimates of (1) accessibility, (2) wood product potential, (3) financial return, and (4)

utilization potential (an index arrived at by combining 1 through 3). Accessibility is a

function of road density or road proximity, physical characteristics of the land, and land

use designation. Wood product potential is derived from cut-tree lists and a set of rules

describing the types of material that the local industry can process. Financial return is

the difference between the estimated dollar costs of harvesting, hauling, handling, and

processing the raw material and the selling price of the end products. The utilization

potential is a composite measure calculated from the other three that provides a visual

display of the current status of the landscape in terms of the potential for wood utilization.

In the example shown here, the northwest (upper left) polygon on this landscape has low

accessibility, moderate wood product potential, and a low financial return. Perhaps it is a

steep unroaded area where trees are of moderate size. Financial return is low because

expensive logging systems—helicopters or long-span skyline systems—are required,

and the material removed is not particularly valuable. As a result, the utilization potential

of this polygon is low. Managers might want to consider strategies that would not require

removal of wood from this polygon. The northeast polygon might represent a different flat

part of the unroaded area where there are many large shade-tolerant trees that are slated

for removal because of disease concerns or a desire to enhance regeneration of seral

species. Even though this is an unroaded area, the trees are large enough to justify their

removal with helicopters, which lowers financial return. As a result, the utilization potential for wood products is moderate. The southwest polygon is a flat roaded area with

sensitive soils, where fuel reduction treatments are desired and trees are small. Financial return is moderate because the cost of removing trees is low, but soil mitigation

adds to total harvesting costs. As a result, utilization potential is low. Finally, the southeast quadrant is a flat roaded area with no operational restrictions, so the harvesting
165

Figure 34—Steps in analytical process for the utilization module (adapted from Christensen et al. 2002

fig. 1).
166

Figure 35—Potential formats for tabular reports (adapted from Christensen et al. 2002 figs. 2 and 3).
167

Figure 36—Example of geographic information system output for a highly simplified landscape with four polygons.

costs are low; the trees are moderate in size, so the financial return is good. The utilization potential of this polygon is good. This might be the type of area where wood removals would prove most successful.

In practice, this system will account for many different constraints on operations, product

characteristics, and land or stand conditions. At a glance it will provide an idea of the

suitability of different parts of the landscape for treatments that involve removal of wood

products at different points in time. It will also provide a visual method for diagnosing why

particular polygons or groups of polygons are either desirable or undesirable in terms of

wood removals. In many instances, such qualitative visual displays will produce sufficient

detail. In others, they will help analysts identify places where quantitative information is

needed. Tabular reports can then be used to provide that detail.

Current information on nontimber forest products is sparse. An initial task is to identify

the set of potentially important nontimber forest products found in the Upper Grande

Ronde watershed. Alternative products may be added or substituted as the project develops. The analyses will supply information on current demand for each of the targeted

Utilization of Nontimber

Forest Products
168

nontimber forest products. We also want to understand the contribution of different stand

structures to providing a given quantity and quality of each nontimber forest product. The

information will be summarized as the amount of material available by type, and where

possible, its estimated economic value.

We will project nontimber forest product presence and abundance from known relations

with stand structure and site or habitat type. Information to establish predictive models

will be collected from the literature, and the models will be developed or refined from published and unpublished data that have not yet been incorporated into models. To the

degree that existing information allows, the nontimber forest products module will provide

tabular and graphical outputs similar to those for timber.

The primary outputs from this analysis will be sets of tables and maps that are suitable

for evaluating different management scenarios. Maps will graphically display the product

potential, net financial return, relative accessibility, and overall utilization potential of

timber and nontimber forest products for individual polygons or groups of polygons in a

more qualitative fashion. Maps that illustrate outcomes will allow us to graphically display results more concisely, although less precisely, than the tabular format. These will

be useful to groups who want a general picture of utilization potential and how it changes

over time but do not need quantitative information. Often the same groups who are interested in tabular outputs will first look to maps to gain a general understanding of where

the commodities they care about are most abundant. Some examples of these users

are members of the public interested in utilization of wood, gathering of nontimber forest

products, or forest conditions after treatments; policymakers who evaluate broad policy

goals and want information on the materials generated by treatments or the costs of

implementing treatments; and others interested in wood utilization or collection of

nontimber forest products.

Tabular displays of data are intended to provide information to a variety of user groups

who need quantitative information. These groups might include managers or planners

who want information about wood or nontimber product outputs generated under different

management scenarios; forest operators who bid on contracts to implement treatments;

and wood processors or purchasers of nontimber forest products who need estimates of

characteristics and volumes of materials available.

We anticipate that the nature of the outputs developed to describe utilization potential

will evolve as we work with users and clients to implement the ideas presented in this

paper. Our goal is to develop an easily understandable and useful method for evaluating

the potential for use of timber and nontimber forest products that can be integrated with

other resource outputs from subbasins in the interior Northwest, and to do that, collaboration with users is essential.

Products and Audience
169

Barbour, R.J.; Ager, A.A.; Hayes, J.L. 2004. A framework for the development and

application of INLAS: the Interior Northwest Landscape Analysis System. In: Hayes,

J.L.; Ager, A.A.; Barbour, R.J., tech. eds. Methods for integrated modeling of landscape change: Interior Northwest Landscape Analysis System. Gen. Tech. Rep.

PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station: 1-16. Chapter 1.

Barbour, R.J.; Fight, R.D.; Christensen, G.A.; Pinjuv, G.L.; Nagubadi, V. 2004. Thinning and prescribed fire and projected trends in wood product potential, financial return, and fire hazard in Montana. Gen. Tech. Rep. PNW-GTR-606. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 78 p.

Barbour, R.J.; Johnston, S.; Hayes, J.P.; Tucker, G.F. 1997. Simulated stand characteristics and wood product yields from Douglas-fir plantations managed for ecosystem

objectives. Forest Ecology and Management. 91: 205-219.

Barbour, R.J.; Parry, D.L. 2001. Log and lumber grades as indicators of wood quality in

20- to 100-year-old Douglas-fir trees from thinned and unthinned stands. Gen. Tech.

Rep. PNW-GTR-510. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 22 p.

Bettinger, P.; Graetz, D.; Ager, A.A.; Sessions, J. 2004. The SafeD forest landscape

planning model. In: Hayes, J.L.; Ager, A.A.; Barbour, R.J., tech. eds. Methods for

integrated modeling of landscape change: Interior Northwest Landscape Analysis

System. Gen. Tech. Rep. PNW-GTR-610. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station: 41-63. Chapter 4.

Christensen, G.A.; Fight, R.D.; Barbour, R.J. 2002. Simulating fire hazard reduction,

wood flow and economics of fuel treatments with FVS, FEEMA, and FIA data. In:

Crookston, N.L.; Havies, R.N., comps. Second Forest Vegetation Simulator conference. Proc. RMRS-P-25. Ogden, UT: U.S. Department of Agriculture, Forest Service,

Rocky Mountain Research Station: 91-103.

Fight, R.D.; Chmelik, J.T. 1999. Analysts guide to FEEMA for financial analysis of

ecosystem management activities. Gen. Tech. Rep. FPL-GTR-111. Madison, WI:

U.S Department of Agriculture, Forest Service, Forest Products Laboratory. 5 p.

Hartsough, B.R.; Zhang, X.; Fight, R.D. 2001. Harvesting cost model for small trees in

natural stands in the interior Northwest. Forest Products Journal. 51(4): 54-61.

Hemstrom, M.; Ager, A.A.; Vavra, M. [et al.]. 2004. State and transition approach for

integrating landscape models. In: Hayes, J.L.; Ager, A.A.; Barbour, R.J., tech. eds.

Methods for integrated modeling of landscape change: Interior Northwest Landscape

Analysis System. Gen. Tech. Rep. PNW-GTR-610. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station: 17-32. Chapter 2.

Literature Cited
170

Log Lines. 2003. Monthly price reports. Mount Vernon, WA: Log Lines Price Reporting

Service. 10 p.

Parry, D.L.; Filip, G.M.; Willits, S.A.; Parks, C.G. 1996. Lumber recovery and deterioration of beetle-killed Douglas-fir and grand fir in the Blue Mountains of eastern Oregon. Gen. Tech. Rep. PNW-GTR-376. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station. 24 p.

Vance, N.C.; Borsting, M.; Pilz, D.; Freed, J. 2001. Special forest products: species

information guide for the Pacific Northwest. Gen. Tech. Rep. PNW-GTR-513. Portland,

OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station. 169 p.

von Hagen, B.; Fight, R.D. 1999. Opportunities for conservation-based development of

nontimber forest products in the Pacific Northwest. Gen. Tech Rep. PNW-GTR-473.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 18 p.

Wycoff, W.R.; Crookston, N.L.; Stage, A.R. 1982. User’s guide to the stand prognosis

model. Gen. Tech. Rep. INT-133. Ogden, UT: U.S. Department of Agriculture, Forest

Service, Intermountain Forest and Range Experiment Station. 112 p.
171

Chapter 14: Bibliography

Marti Aitken and Alan A. Ager1

This chapter consists of a bibliography listing and index to recently published literature

relating to the Interior Northwest Landscape Analysis System (INLAS) project area. The

bibliography is intended to provide background information about the natural and socioeconomic research that has been conducted in the project area. It is not a complete

compendium of literature cited within the chapters of this general technical report.

The bibliography was developed by searching public and academic library databases in

Oregon, Washington, and Idaho for literature specifically related to the INLAS study

area. We also used DigiTop, the digital desktop library for the U.S. Department of Agriculture. The library emphasizes products focused on scientific research and provides

access to databases, journals, newspapers, statistics, and other important digital information resources. The Thomson Institute for Scientific Information (ISI) Web of Knowledge was the primary platform used.

The INLAS study area is located in the Upper Grande Ronde watershed, in the Blue

Mountains of northeast Oregon (fig. 37). The Upper Grande Ronde watershed is one of

three hydrologic unit codes (HUC4) subwatersheds in the Grande Ronde basin and is

approximately 178 000 ha. Because authors seldom reference the Upper Grande Ronde

in their keywords, broader geographic references were used. These terms included

Blue Mountains, Wallowa-Whitman National Forest, Umatilla National Forest, and

Union County. Even broader-scale geographic references such as northeastern Oregon,

or eastern Oregon were found to be too broad to be useful. Additional citation information was gathered through the Grande Ronde Model Watershed Program (GRMWP)

Introduction

1

 Marti Aitken is a resource information manager, and

Alan A. Ager is an operations research analyst, U.S. Department of Agriculture, Forest Service, Forestry and Range

Sciences Laboratory, 1401 Gekeler Lane, La Grande, OR 97850.
172

Figure 37—The INLAS study area in relation to the Grande Ronde watershed and the Blue Mountains.
173

and from direct contact with local researchers and specialists. The GRMWP is composed of local representatives and agency personnel involved with the multiple uses of

natural resources within the basin, and coordinates policy for the development, implementation, monitoring, and maintenance of the model watershed for the Grande Ronde

River basin.

The complete search turned up more than 500 references. This bibliography contains the

highlights of the search and consists of 358 citations dated from 1960 through April

2003. These citations cover a broad range of topics and have been grouped into the following 10 disciplines addressed in the INLAS project: aquatics, fire, grazing, herbivory,

insects/disease, modeling, socioeconomics, utilization, vegetation, wildlife, and general.

Citations addressing multiple disciplines (e.g., environmental impact analysis) can be

found under the general grouping. Citations also have been grouped into three geographic

categories: Upper Grande Ronde, Grande Ronde, and Blue Mountains. Geographic

groupings are based on the best available information about the research locations. The

intent was to reference as many citations as possible to the Upper Grande Ronde watershed. Citations that could not be georeferenced to the Upper Grande Ronde watershed

were georeferenced either to the Grande Ronde watershed, or to the Blue Mountains,

depending on the information available.

Publications include journal articles, government publications, reports, theses, and

books. Although the study area includes the Starkey Experimental Forest and Range,

we avoided duplicating references available through the Starkey Experimental Forest

and Range Web site (http://www.fs.fed.us/pnw/starkey/publications/index.shtml). The

Web site lists numerous publications related to ungulate behavior, habitat, and management. This bibliography also does not contain hydrologic and water quality references

available through the Oregon Department of Water Resources Web site (http://

www.wrd.state.or.us/surface_water/index.shtml) or the Oregon Department of Environmental Quality (http://www.deq.state.or.us/wq/TMDLs/TMDLs.htm).

Unfortunately, publications listed below are not on file or available for use at any central

location. Libraries, especially those serving as federal depositories, are the first and best

source for information. Listed theses and dissertations are available from the individual

schools.

Citations are listed alphabetically by author, date, and title. The [brackets] around a date

means the approximate year (exact date was not found on the publication).
174

Aquatics

Anderson et al. 1993

Bach 1995

Ballard 1998a

Ballard 1998b

Ballard 1999

Baxter 2002

Benner 1999

Beschta et al. 1991

Betts and Wisseman 1995

Bohle 1994

Bryant 1982

Bryce and Clarke 1996

Bryson 1993

Buckhouse and Gaither 1982

Bull and Carter 1996

Carlson 1989

Carmichael 1993

Carmichael and Boyce 1986

Chen 1996

Chen et al. 1998a

Chen et al. 1998b

Clifton et al. 1999

Cordova 1995

Corrarino and Brusven 1983

Diebel 1997

Dwire 2001

Ebersole 1994

Ebersole et al. 2002

Filip et al. 1989a

Fowler et al. 1979

Gill 1994

Helvey and Tiedemann 1978

Higgins et al. 1988

Higgins et al. 1989

Howell 2001

Huntington 1994

James 1984

Keefe et al. 1994

Keefe et al. 1995

Knight 1977

Lytjen 1998

Maloney et al. 1999

Marcot et al. 1994

McHugh 2003

McIntosh 1992

McIntosh 1995

McIntosh et al. 1994a

McIntosh et al. 1994b
175

McIntosh et al. 1995

McIver and Starr 2001

McLemore and Meehan 1988

Meays 2000

Mobrand et al. 1995

Moffat et al. 1990

Neitzel and Frest 1992

Noll et al. 1987

Northwest Power Planning Council 1990

Oregon Department of Fish and Wildlife [1988]

Oregon Department of Fish and Wildlife [1990]

Oregon Department of Fish and Wildlife [1993-1996]

Oregon Department of Fish and Wildlife [1994]

Oregon Department of Fish and Wildlife [1999]

Oregon Department of Transportation 1984

Parker et al. [1995]

Porath et al. 2002

Price 1998

Rieman et al. 2001

Robichaud and Brown 1999

Smith 1975a

Steel 1999

Tiedemann et al. 1988

Torgersen et al. 1999

U.S. Army Corps of Engineers 1999

U.S. Department of Agriculture, Forest Service 1992a

U.S. Department of Agriculture, Forest Service 1992b

U.S. Department of Agriculture, Forest Service 1994c

U.S. Department of Agriculture, Natural Resources Conservation Service and U.S.

Department of Agriculture, Forest Service 1996

U.S. Department of Energy, Bonneville Power Administration 1997

U.S. Department of the Interior, Bureau of Land Management, Baker Resource Area

Office 1993

U.S. Department of the Interior, Bureau of Reclamation, Pacific Northwest Region 1982

U.S. Department of the Interior, Geological Survey 1989

Van Cleve and Ting 1960

Walters et al. 1994

Watershed Sciences, LLC 2000

Wellman et al. 1993

Wells 1975

White et al. 1981

Widner 1991

Wissmar et al. 1994a

Wissmar et al. 1994b

Wondzell 2001

Fire and fuels

Agee 1994

Diaz-Avalos 1998

Diaz-Avalos et al. 2001
176

Filip and Yang-Erve 1997

Hall 1976

Hall 1977

Hall 1980

Heyerdahl 1997

Heyerdahl et al. 1996

Heyerdahl et al. 2001

Huff et al. 1995

Johnson [1998]

Langston 1995

Lehmkuhl et al. 1994

Maruka 1994

McIver and Starr 2000

McIver and Starr 2001

Mohr and Both 1996

Mutch et al. 1993

Olson 2000

Ottmar and Sandberg 2001

Petersen and Mohr 1984

Reed 1998

Robichaud and Brown 1999

Shindler and Reed 1996

Skovlin 1996

Skovlin and Thomas 1995

Thies and Niwa 2001

Tiedemann et al. 2000

Wickman 1992

Williamson 1999

Wissmar et al. 1994b

General

Anderson et al. 1993

Bauer 2000

Berggren 1983

Bormann et al. 1994

Clarke and Bryce 1997

Clarke et al. 1997

Everett 1994

Everett et al. 1994

Gast et al. 1991

Harvey et al. 1994

Jensen and Bourgeron 1994

Hessburg et al. 1994

Jaindl and Quigley 1996

Johnson et al. 1994

Keith 1991

Langston 1994

Langston 1995

Langston 2000

Marcot et al. 1994
177

Mutch et al. 1993

Oliver et al. 1994

Robbins and Wolf 1994

Starr et al. 2001

Tanaka et al. 1995

Thomas et al. 1976

U.S. Department of Agriculture, Forest Service 1992a

U.S. Department of Agriculture, Forest Service 1994b

U.S. Department of Agriculture, Forest Service 1998

U.S. Department of Agriculture, Forest Service 2002

U.S. Department of the Interior, Bureau of Land Management and U.S. Department of 

Agriculture, Forest Service 1990

Union Soil and Water Conservation District 1995

Whitney 1999

Williams 2000

Wissmar et al. 1994b

Grazing

Bryant 1982

Bull and Hayes 2000

Clark 1996

Cook et al. 1996

Edgerton and Smith 1971

Gebauer 1998

Gillen et al. 1985

Heyerdahl et al. 2001

Holechek et al. 1980

Holechek et al. 1981

Holechek et al. 1982a

Holechek et al. 1982b

Holechek et al. 1983

Holechek et al. 1987

Holechek and Vavra 1983

Irwin et al. 1994

Knight 1977

Maloney et al. 1999

McInnis et al. 1990

McIntosh et al. 1994a

McIntosh et al. 1994b

Moser and Witmer 2000

Porath et al. 2002

Quigley et al. 1991

Riggs et al. 2000

Roath and Krueger 1982

Sanderson et al. 1988

Sheehy 1987

Skovlin 1967

Skovlin et al. 1976

Sneva and Hyder 1962

Svejcar and Vavra 1985a
178

Svejcar and Vavra 1985b

Vavra and Phillips 1979

Vavra and Phillips 1980

Herbivory

Bryant 1993

Clark 1996

Cook et al. 1996

Gebauer 1998

Irwin et al. 1994

Moser and Witmer 2000

Parks et al. 1998

Riggs et al. 2000

Sheehy 1987

Skovlin 1967

Insects and disease

Aho 1974

Aho and Hadfield 1975

Beckwith and Stelzer 1979

Bull et al. 1992a

Bull et al. 1995

Delucchi 1976

Downing et al. 1977

Ferguson 1994

Filip et al. 1987

Filip et al. 1989b

Filip et al. 1989c

Filip et al. 1992

Filip et al. 1996

Filip and Parks 1987

Filip and Parks 1991

Filip and Yang-Erve 1997

Grimble and Beckwith 1992-1994

Grimble et al. 1993

Hayes and Daterman 2001

Hayes and Ragenovich 2001

Helvey and Tiedemann 1978

Hessburg et al. 1994

Kemp et al. 1986

LaBonte et al. 2001

Langston 1995

Lehmkuhl et al. 1994

Lundquist et al. 1996

Mason 1996

Mason and Paul 1988

Mason and Paul 1996

Mason and Wickman [1988]

McIver et al. 1997
179

Murphy and Croft 1990

Parks and Bull 1997

Parks and Flanagan 2001

Parks and Hoffman 1991

Parks et al. 1999

Parry et al. 1996

Powell 1994

Roush 1978

Ryan 1983

Ryan 1985

Ryan 1997

Swetnam et al. 1995

Thies 2001

Thies and Niwa 2001

Tiedemann et al. 2000

Torgersen 2001

Torgersen and Bull 1995

Wickman 1976

Wickman 1988

Wickman 1992

Wickman et al. 1980

Youngblood and Wickman 2002

Zack et al. 1979

Modeling

Baxter 1993

Bettinger et al. 1996a

Bettinger et al. 1996b

Chen 1996

Chen et al. 1998a

Chen et al. 1998b

Diaz-Avalos 1998

Diaz-Avalos et al. 2001

Hemstrom et al. 2002

Higgins et al. 1988

Hitchcock and Ager 1992

Kemp et al. 1986

Lundquist and Beatty 1999

Lundquist and Beatty 2002

McHugh 2003

McInnis et al. 1990

Sneva and Hyder 1962

Wells 1975

White et al. 1981

Social and economic

Applegate and O’Donnell 1994

Barklow 1987

Bormann et al. 1994

Braun 1991
180

Buan and Lewis 1991

Davis et al. 1991

Delucchi 1976

Downing et al. 1977

Duncan 1998

Ebert 1987

Evans 1991

Gildemeister 1998

Hall 1977

Hall and Bigler-Cole 2001

Haynes et al. 2001

Hermens and Turner 1985

Johnson [1997]

Keith 1991

Langston 1995

Langston 2000

Quigley 1992

Reed 1998

Shindler et al. [2002]

Shindler and Reed 1996

Starr and Quigley 1992

U.S. Department of the Interior, Bureau of Reclamation, Pacific Northwest Region 1982

Wells 1975

Williams 1976

Wissmar et al. 1994a

Womack 1982

Utilization

Aho 1974

Aho and Hadfield 1975

Bull and Carter 1996

Bull et al. 1997

Clausnitzer [1993]

Cochran and Barrett 1993

Cochran and Barrett 1995

Cochran and Dahms [1998]

Cochran and Seidel 1995

Coulter 1999

Filip et al. 1987

Filip et al. 1989c

Geist et al. 1989

Gill 1994

Haynes et al. 2001

Ince 1982

Klock and Lopushinsky 1980

Lennette 1999

Lundquist and Beatty 1999

Lundquist et al. 1996

McIntosh et al. 1994a

McIntosh et al. 1994b
181

McIver and Starr 2000

McIver and Starr 2001

Oester et al. 1995

Parry et al. 1996

Peterson and Hibbs 1989

Quigley 1992

Quigley et al. 2001

Reed 1998

Seidel 1982

Seidel and Head 1983

Shindler and Reed 1996

Skovlin et al. 1989

Tiedemann et al. 1988

Wickman 1978

Wickman 1986

Wickman et al. 1980

Williams 1988

Wilson et al. 2001

Wissmar et al. 1994a

Youngblood 2000

Vegetation

Beck 1996

Bohle 1994

Brady 2001

Brookshire 2000

Buckhouse and Gaither 1982

Bull et al. 2001b

Case 1995

Chen et al. 1998b

Clausnitzer 1979

Clausnitzer [1993]

Crowe and Clausnitzer 1997

Diaz-Avalos 1998

Diaz-Avalos et al. 2001

Dwire 2001

Ferguson 1994

Filip et al. 1989a

Filip and Yang-Erve 1997

Franklin and Dyrness 1973

Ganskopp 1978

Gebauer 1998

Hall 1973

Hall 1974

Hall 1976

Hall 1977

Hall 1980

Harrod 2001

Hemstrom 2001

Hemstrom et al. 2002
182

Hines 1998

Hines and Bradshaw 1997

Huntington 1994

Irwin et al. 1994

Johnson 1981

Johnson [1993]

Johnson [1998]

Johnson and Clausnitzer 1992

Lehmkuhl et al. 1994

Lennette 1999

Lundquist and Beatty 1999

Lundquist et al. 1996

Lytjen 1998

Mannan 1982

Maruka 1994

Moser and Witmer 2000

Oester et al. 1995

Olson 2000

Otting 1998

Parks et al. 1998

Parks and Schmitt 1997

Powell 1999

Reed 1998

Riegel 1989

Riggs et al. 2000

Shirley and Erickson 2001

Skovlin 1996

Skovlin et al. 1976

Skovlin and Thomas 1995

Smergut 1991

Tiedemann et al. 2000

Wissmar et al. 1994a

Wissmar et al. 1994b

Wood 1971

Youngblood 2001

Wildlife

Bolon 1994

Bryant 1993

Bull 1980

Bull 1984

Bull 1987

Bull 2000

Bull 2001

Bull [In press]

Bull and Anderson 1978

Bull and Beckwith 1993

Bull and Blumton 1997

Bull and Blumton 1999

Bull and Carter 1996
183

Bull and Collins 1993

Bull and Collins 1996

Bull and Hayes 2000

Bull and Hayes 2001

Bull and Hayes 2002

Bull and Heater 1995

Bull and Heater 2000

Bull and Heater 2001

Bull and Henjum 1990

Bull and Holthausen 1993

Bull et al. 1987

Bull et al. 1989

Bull et al. 1990

Bull et al. 1992a

Bull et al. 1992b

Bull et al. 1995

Bull et al. 1997

Bull et al. 2000

Bull et al. 2001a

Bull et al. 2001b

Bull and Meslow 1988

Bull and Shepherd 2003

Bull and Skovlin 1982

Bull and Wales 2001a

Bull and Wales 2001b

Cook et al. 1996

Cook et al. 1999

Ebert 1987

Edgerton and Smith 1971

Goggans 1985

Hitchcock and Ager 1992

Irwin et al. 1994

Korfhage et al. 1980

Leckenby 1984

Mannan 1982

Marcot et al. 1994

McCluskey 1976

Moore and Henny 1984

Moser and Witmer 2000

Nowak 1999

Noyes et al. 1996

Parks and Bull 1997

Parks et al. 1998

Parks et al. 1999

Pelren 1996

Pelren and Crawford 1999

Riggs et al. 2000

Sallabanks et al. 2002

Sheehy 1987

Sheehy and Slater 1998
184

Skovlin et al. 1989

Skovlin and Vavra 1979

Smith 1975a

Smith 1975b

Smith 1982

Snyder 2001

Thomas et al. 1976

Thomas et al. 1979

Thomas et al. 1986

Torgersen and Bull 1995

Wales 2001

Upper Grande Ronde

Anderson et al. 1993

Bach 1995

Ballard [1998a]

Bettinger et al. 1996b

Bohle 1994

Brookshire 2000

Bryce and Clarke 1996

Bull 1980

Bull 1984

Bull 1987

Bull 2000

Bull 2001

Bull [In press]

Bull and Anderson 1978

Bull and Beckwith 1993

Bull and Blumton 1997

Bull and Blumton 1999

Bull and Carter 1996

Bull and Collins 1993

Bull and Collins 1996

Bull and Hayes 2000

Bull and Hayes 2001

Bull and Hayes 2002

Bull and Heater 1995

Bull and Heater 2000

Bull and Heater 2001

Bull and Henjum 1990

Bull and Holthausen 1993

Bull and Meslow 1988

Bull et al. 1987

Bull et al. 1989

Bull et al. 1990

Bull et al. 1992a

Bull et al. 1992b

Bull et al. 1995

Bull et al. 1997

Bull et al. 2000
185

Bull et al. 2001b

Bull and Shepherd 2003

Bull and Skovlin 1982

Case 1995

Chen 1996

Chen et al. 1998a

Chen et al. 1998b

Clark 1996

Delucchi 1976

Dwire 2001

Edgerton and Smith 1971

Filip et al. 1987

Filip et al. 1989a

Filip et al. 1992

Filip and Parks 1987

Filip and Parks 1991

Ganskopp 1978

Gildemeister 1998

Gill 1994

Hemstrom et al. 2002

Hines 1998

Holechek et al. 1980

Holechek et al. 1981

Holechek et al. 1982a

Holechek et al. 1982b

Holechek et al. 1983

Holechek et al. 1987

Holechek and Vavra 1983

Knight 1977

Lytjen 1998

Mason and Paul 1988

Mason and Wickman [1988]

McHugh 2003

McIntosh 1992

McLemore and Meehan 1988

Otting 1998

Parks and Bull 1997

Parks et al. 1999

Parks and Schmitt 1997

Skovlin et al. 1976

Svejcar and Vavra 1985a

Swetnam et al. 1995

Torgersen and Bull 1995

U.S. Department of Agriculture, Forest Service 1992a

U.S. Department of Agriculture, Forest Service 1992b

U.S. Department of Agriculture, Forest Service 1994a

U.S. Department of Agriculture, Forest Service 1994b

U.S. Department of Agriculture, Forest Service 1994c

U.S. Department of Agriculture, Forest Service 1998

U.S. Department of Agriculture, Forest Service 2002
186

Union Soil and Water Conservation District 1999

Wickman 1976

Wickman 1978

Wickman 1986

Wickman 1988

Wickman et al. 1980

Youngblood 2000

Youngblood and Wickman 2002

Grande Ronde

Ballard 1998b

Ballard 1999

Bauer 2000

Baxter 2002

Beschta et al. 1991

Bryson 1993

Carmichael 1993

Carmichael and Boyce 1986

Cook et al. 1999

Corrarino and Brusven 1983

Diebel 1997

Duncan 1998

Filip et al. 1989b

Filip et al. 1989c

Hermens and Turner 1985

Hines and Bradshaw 1997

Huff et al. 1995

Huntington 1994

James 1984

Keefe et al. 1994

Keefe et al. 1995

Lennette 1999

Maruka 1994

McIntosh et al. 1994b

McIntosh et al. 1995

Mobrand et al. 1995

Neitzel and Frest 1992

Noll et al. 1987

Northwest Power Planning Council 1990

Oregon Department of Fish and Wildlife [1988]

Oregon Department of Fish and Wildlife [1990]

Oregon Department of Fish and Wildlife [1994]

Oregon Department of Fish and Wildlife [1999]

Oregon Department of Transportation 1984

Parker et al. [1995]

Ryan 1983

Ryan 1985

Ryan 1997

Sheehy and Slater 1998

Smergut 1991
187

Smith 1975a

Steel 1999

U.S. Army Corps of Engineers 1999

U.S. Department of Agriculture, Natural Resources Conservation Service and U.S.

Department of Agriculture 1996

U.S. Department of Energy, Bonneville Power Administration 1997

U.S. Department of the Interior, Bureau of Land Management 1993

U.S. Department of the Interior, Bureau of Land Management and U.S. Department of

Agriculture, Forest Service 1990

U.S. Department of the Interior, Geological Survey 1989

Union Soil and Water Conservation District 1995

Van Cleve and Ting 1960

Walters et al. 1994

Watershed Sciences, LLC 2000

Wells 1975

White et al. 1981

Whitney 1999

Wissmar et al. 1994a

Wissmar et al. 1994b

Blue Mountains

Agee 1994

Aho 1974

Aho and Hadfield 1975

Applegate and O’Donnell 1994

Barklow 1987

Baxter 1993

Beck 1996

Beckwith and Stelzer 1979

Benner 1999

Bettinger et al. 1996a

Betts and Wisseman 1995

Bolon 1994

Brady 2001

Braun 1991

Bryant 1982

Bryant 1993

Buan and Lewis 1991

Buckhouse and Gaither 1982

Bull et al. 2001a

Bull and Wales 2001a

Bull and Wales 2001b

Clarke and Bryce 1997

Clarke et al. 1997

Clausnitzer [1993]

Clausnitzer 1979

Clifton et al. 1999

Cochran and Barrett 1993

Cochran and Barrett 1995

Cochran and Dahms [1998]
188

Cochran and Seidel 1995

Cook et al. 1996

Cordova 1995

Coulter 1999

Crowe and Clausnitzer 1997

Diaz-Avalos 1998

Diaz-Avalos et al. 2001

Downing et al. 1977

Ebersole 1994

Ebersole et al. 2002

Ebert 1987

Evans 1991

Everett 1994

Everett et al. 1994

Ferguson 1994

Ferguson 2001

Filip et al. 1996

Filip and Yang-Erve 1997

Fowler et al. 1979

Franklin and Dyrness 1973

Gast et al. 1991

Gebauer 1998

Geist 1977

Geist et al. 1989

Geist and Strickler 1978

Gillen et al. 1985

Goggans 1985

Grimble and Beckwith 1992-1994

Grimble et al. 1993

Hall 1973

Hall 1974

Hall 1976

Hall 1977

Hall 1980

Hall and Bigler-Cole 2001

Harrod 2001

Harvey et al. 1994

Hayes and Daterman 2001

Hayes and Ragenovich 2001

Haynes et al. 2001

Helvey and Tiedemann 1978

Hemstrom 2001

Hessburg et al. 1994

Heyerdahl 1997

Heyerdahl et al. 1996

Heyerdahl et al. 2001

Higgins et al. 1988

Higgins et al. 1989

Hitchcock and Ager 1992

Howell 2001
189

Ince 1982

Irwin et al. 1994

Jaindl and Quigley 1996

Jensen and Bourgeron 1994

Johnson 1994

Johnson 1981

Johnson [1997]

Johnson [1998]

Johnson and Clausnitzer 1992

Johnson et al. 1994

Keith 1991

Klock and Lopushinsky 1980

Korfhage et al. 1980

Kreger and Roschke 1991

LaBonte et al. 2001

Langston 1994

Langston 1995

Langston 2000

Leckenby 1984

Lehmkuhl et al. 1994

Lundquist and Beatty 1999

Lundquist and Beatty 2002

Lundquist et al. 1996

Mannan 1982

Marcot et al. 1994

Mason 1996

Mason and Paul 1996

McInnis et al. 1990

McIver et al. 1997

McIver and Starr 2000

Mohr and Both 1996

Moore and Henny 1984

Moser and Witmer 2000

Murphy and Croft 1990

Mutch et al. 1993

Nowak 1999

Oester et al. 1995

Oliver et al. 1994

Olson 2000

Ottmar and Sandberg 2001

Parks and Hoffman 1991

Parks and Flanagan 2001

Parks et al. 1998

Parry et al. 1996

Pelren and Crawford 1999

Petersen and Mohr 1984

Peterson and Hibbs 1989

Porath et al. 2002

Powell 1994

Powell 1999
190

Price 1998

Quigley 1992

Quigley et al. 1991

Quigley et al. 2001

Reed 1998

Riegel 1989

Riggs et al. 2000

Roath and Krueger 1982

Robbins and Wolf 1994

Robichaud and Brown 1999

Sallabanks et al. 2002

Seidel 1982

Seidel and Head 1983

Sheehy 1987

Shindler and Reed 1996

Shirley and Erickson 2001

Skovlin 1967

Skovlin 1996

Skovlin and Thomas 1995

Skovlin and Vavra 1979

Skovlin et al. 1989

Smith 1975b

Smith 1982

Sneva and Hyder 1962

Starr and Quigley 1992

Starr et al. 2001

Svejcar and Vavra 1985b

Tanaka et al. 1995

Thies and Niwa 2001

Thies 2001

Thomas et al. 1976

Thomas et al. 1979

Thomas et al. 1986

Tiedemann et al. 1988

Tiedemann et al. 2000

Torgersen 2001

Trauba 1975

U.S. Department of Agriculture, Soil Conservation Service and Oregon State University

Agricultural Experiment Station 1985

U.S. Department of the Interior, Bureau of Reclamation, Pacific Northwest Region 1982

U.S. Department of the Interior, Geological Survey 1996

Vavra and Phillips 1979

Vavra and Phillips 1980

Wales 2001

Wickman 1992

Widner 1991

Williams 1976

Williams 1988

Williams 2000

Williamson 1999
191

Wilson et al. 2001

Womack 1982

Wondzell 2001

Wood 1971

Youngblood 2001

Zack et al. 1979
192

Agee, J.K. 1994. Fire and weather disturbances in terrestrial ecosystems of the eastern Cascades. Gen. Tech. Rep. PNW-GTR-320. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 52 p. (Everett, R.L.,

assessment team leader, Eastside forest ecosystem health assessment; Hessburg,

P.F., science team leader and tech. ed., Volume III: assessment).

Aho, P.E. 1974. Defect estimation for grand fir in the Blue Mountains of Oregon and

Washington. Res. Pap. PNW-175. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Forest and Range Experiment Station. 12 p.

Aho, P.E.; Hadfield, J.S. 1975. How to estimate defect in grand fir in the Blue Mountains of Oregon and Washington. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Forest and Range Experiment Station. 10 p.

Anderson, J.W.; Beschta, R.L.; Boehne, P.L. [et al.]. 1993. A comprehensive approach to restoring habitat conditions needed to protect threatened salmon species

in a severely degraded river—the Upper Grande Ronde River anadromous fish habitat

protection, restoration and monitoring plan. In: Tellman, B.; Cortner, H.J.; Wallace,

M.G. [et al.], tech. coords. Riparian management: common threads and shared interests. A western regional conference on river management strategies: Proceedings of

a western regional conference on river management strategies. Gen. Tech. Rep. RM226. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station: 175-179.

Applegate, S.; O’Donnell, T., eds. 1994. Talking on paper: an anthology of Oregon

letters and diaries. Corvallis, OR: Oregon State University Press. 324 p.

Bach, L. 1995. River basin assessment—Upper/Middle Grande Ronde River and

Catherine Creek. Portland, OR: Oregon Department of Environmental Quality. [Pages

unknown].

Ballard, T. [1998a]. 1994-1998 Grande Ronde River basin water quality monitoring report for the Upper Grande Ronde, Lower Grande Ronde, Wallowa and Imnaha subbasins. Unpublished report. On file with: Grande Ronde Model Watershed, 10901

Island Avenue, La Grande, OR 97850.

Ballard, T. 1998b. Grande Ronde basin water quality monitoring report for six key

subwatersheds. Portland, OR: U.S. Department of Energy, Bonneville Power

Administration. Unpublished report. On file with: Grande Ronde Model Watershed,

10901 Island Avenue, La Grande, OR 97850.

Ballard, T. 1999. Grande Ronde River Basin, 1994-1998, water quality monitoring report.

La Grande, OR: Union and Wallowa Soil and Water Conservation Districts and

Grande Ronde Model Watershed Program. 211 p.

Barklow, I. 1987. From trails to rail: the post offices, stage stops, and wagon roads of

Union County, Oregon. Enterprise, OR: Enchantments Publication of Oregon. 300 p.

Bauer, S.B. 2000. Grande Ronde River basin monitoring program review. Boise, ID:

Pocket Water, Inc. Unpublished report. Submitted to Grande Ronde Basin Partnership. On file with: Grande Ronde Model Watershed, 10901 Island Ave., La Grande,

OR 97850.
193

Baun, C.M.; Lewis, R. 1991. The first Oregonians: an illustrated collection of essays

on traditional lifeways, federal-Indian relations, and the state’s native people today.

Portland, OR: Oregon Council for the Humanities. 128 p.

Baxter, C.V. 2002. Fish movement and assemblage dynamics in a Pacific Northwest

riverscape. Corvallis, OR: Oregon State University. 174 p. Ph.D. dissertation.

Baxter, P.A. 1993. Utilizing GIS to analyze collections of the Eagle Cap Wilderness

flora of northeastern Oregon. Pullman, WA: Washington State University. 60 p. M.S.

thesis.

Beck, A.P. 1996. 4,400 years of vegetation change at Twin Lakes, Wallowa Mountains,

northeastern Oregon. Pullman, WA: Washington State University. 51 p. M.A. thesis.

Beckwith, R.C.; Stelzer, M.J. 1979. The duration of cold storage and eclosion of the

Douglas-fir tussock moth. Annals of the Entomological Society of America. 72(1):

158-161.

Benner, D.A. 1999. Evaporative heat loss of the upper Middle Fork of the John Day

River, northeastern Oregon. Corvallis, OR: Oregon State University. 142 p. M.S.

thesis.

Berggren, B.J. 1983. The minerology and morphology of loess derived soils along a

traverse in northeastern Oregon. Corvallis, OR: Oregon State University. 147 p. M.S.

thesis.

Beschta, R.L.; Platts, W.S.; Kauffman, J.B. [et al.]. 1991. Field review of fish habitat

improvement projects in the Grande Ronde and John Day River basins in eastern

Oregon. Portland, OR: U.S. Department of Energy, Bonneville Power Administration,

Division of Fish and Wildlife. 53 p.

Bettinger, P.; Bradshaw, G.A.; Weaver, G.W. 1996a. Effects of geographic information

system vector-raster-vector data conversion on landscape indices. Canadian Journal

of Forest Research. 26(8): 1416-1425.

Bettinger, P.; Johnson, K.; Sessions, J. 1996b. Forest planning in an Oregon case

study: defining the problem and attempting to meet goals with a spatial analysis technique. Environmental Management. 20(4): 565-577.

Betts, B.J.; Wisseman, R.W. 1995. Geographic range and habitat characteristics of the

caddisfly Cryptochia neosa. Northwest Science. 69(1): 46-51.

Bohle, T.S. 1994. Stream temperatures, riparian vegetation, and channel morphology

in the Upper Grande Ronde River watershed, Oregon. Corvallis, OR: Oregon State

University. 116 p. M.S. thesis.

Bolon, N.A. 1994. Estimates of the values of elk in the Blue Mountains of Oregon and

Washington. Gen. Tech. Rep. PNW-GTR-316. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 38 p.

Bormann, B.T.; Brookes, M.H.; Ford, E.D. [et al.]. 1994. Volume V: a framework for

sustainable-ecosystem management. Gen. Tech. Rep. PNW-GTR-331. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station.

61 p. (Everett, R.L., assessment team leader, Eastside forest ecosystem health

assessment).
194

Brady, T.J. 2001. The significance of population successional status to the evolution

of seedling morphology in Pinus contorta var. latifolia (Pinaceae). Madroño. 48(3):

138-151.

Brookshire, E.N.J. 2000. Forests to floodplain meadows: detrital dynamics on two

headwater streams. Corvallis, OR: Oregon State University. 112 p. M.S. thesis.

Bryant, L.D. 1982. Response of livestock to riparian zone exclusion. Journal of Range

Management. 35(6): 780-785.

Bryant, L.D. 1993. Quality of bluebunch wheatgrass (Agropyron spicatum) as a winter

range forage for Rocky Mountain elk (Cervus elaphus nelsoni) in the Blue Mountains

of Oregon. Corvallis, OR: Oregon State University. 147 p. Ph.D. dissertation.

Bryce, S.A.; Clarke, S.E. 1996. Landscape-level ecological regions: linking state-level

ecoregion frameworks with stream habitat classifications. Environmental Management. 20(3): 297-311 .

Bryson, D. 1993. Northeast Oregon hatchery Grande Ronde River management plan.

Portland, OR: U.S. Department of Energy, Bonneville Power Administration; final

report. [Pages unknown].

Buckhouse, J.C.; Gaither, R.E. 1982. Potential sediment production within vegetative

communities in Oregon’s Blue Mountains. Journal of Soil and Water Conservation.

37(2): 120-122.

Bull, E.L. 1980. Resource partitioning among woodpeckers in northeastern Oregon.

Moscow, ID: University of Idaho. 109 p. Ph.D. dissertation.

Bull, E.L. 1984. Bird response to beetle-killed lodgepole pine. Murrelet. 64(3): 94-96.

Bull, E.L. 1987. Ecology of the pileated woodpecker in northeastern Oregon, USA.

Journal of Wildlife Management. 51(2): 472-481.

Bull, E.L. 2000. Seasonal and sexual differences in American marten diet in northeastern Oregon. Northwest Science. 74(3): 186-191.

Bull, E.L. 2001. Survivorship of pileated woodpeckers in northeastern Oregon. Journal of

Field Ornithology. 72(1): 131-135.

Bull, E.L. [In press]. Use of nest box use by Vaux’s swifts. Journal of Field Ornithology.

Bull, E.L.; Akenson, J.J.; Henjum, M.G. 2000. Characteristics of black bear dens in

trees and logs in northeastern Oregon. Northwestern Naturalist. 81: 148-153.

Bull, E.L.; Anderson, R.G. 1978. Notes on flammulated owls in northeastern Oregon.

Murrelet. 59: 26-27.

Bull, E.L.; Aubry, K.B.; Wales, B.C. 2001a. Effects of disturbance on forest carnivores

of conservation concern in eastern Oregon and Washington. Northwest Science.

75(Spec. issue): 180-184.

Bull, E.L.; Beckwith, R.C. 1993. Diet and foraging behavior of Vaux’s swifts in northeastern Oregon. Condor. 95: 1016-1023.

Bull, E.L.; Blumton, A.K. 1997. Roosting behavior of postfledgling Vaux’s swifts in

northeastern Oregon. Journal of Field Ornithology. 8: 302-305.
195

Bull, E.L.; Blumton, A.K. 1999. Effect of fuels reduction on American martens and their

prey. Res. Pap. PNW-RP-539. Portland, OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station. 9 p.

Bull, E.L.; Carter, B.E. 1996. Tailed frogs: distribution, ecology, and association with

timber harvest in northeastern Oregon. Res. Pap. PNW-RP-497. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 11 p.

Bull, E.L.; Collins, C.T. 1993. Nesting chronology, molt, and ectoparasites of Vaux’s

swifts in northeastern Oregon. Avocetta. 17: 203-207.

Bull, E.L.; Collins, C.T. 1996. Nest site fidelity, breeding age, and adult longevity in the

Vaux’s swift. North American Bird Bander. 21: 49-51.

Bull, E.L.; Hayes, M.P. 2000. Livestock effects on reproduction of the Columbia spotted

frog. Journal of Range Management. 53(3): 291-294.

Bull, E.L.; Hayes, M.P. 2001. Post-breeding season movements of Columbia spotted

frogs (Rana luteiventris) in northeastern Oregon. Western North American Naturalist.

6: 119-121.

Bull, E.L.; Hayes, M.P. 2002. Overwintering of Columbia spotted frogs in northeastern

Oregon. Northwest Science. 76: 141-147.

Bull, E.L.; Heater, T.W. 1995. Intraspecific predation on American marten. Northwestern

Naturalist. 76: 132-134.

Bull, E.L.; Heater, T.W. 2000. Resting and denning sites of American martens in northeastern Oregon. Northwest Science. 74(3): 179-185.

Bull, E.L.; Heater, T.W. 2001. Home range and dispersal of the American marten in

northeastern Oregon. Northwestern Naturalist. 82: 7-11.

Bull, E.L.; Henjum, M.G. 1990. Ecology of the great gray owl. Gen. Tech. Rep. PNWGTR-265. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 39 p.

Bull, E.L.; Hohmann, J.E.; Henjum, M.G. 1987. Northern pygmy-owl nests in northeastern Oregon. Journal of Raptor Research. 21(2): 77-78.

Bull, E.L.; Holthausen, R.S. 1993. Habitat use and management of pileated woodpeckers in northeastern Oregon. Journal of Wildlife Management. 57: 335-345.

Bull, E.L.; Holthausen, R.S.; Beckwith, R.C. 1992a. Arthropod diet of pileated woodpeckers in northeastern Oregon. Northwestern Naturalist. 73: 42-45.

Bull, E.L.; Holthausen, R.S.; Henjum, M.G. 1992b. Roost trees used by pileated

woodpeckers in northeastern Oregon. Journal of Wildlife Management. 56: 786-793.

Bull, E.L.; Meslow, E.C. 1988. Breeding biology of the pileated woodpecker—management implications. Res. Note PNW-RN-474. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 8 p.

Bull, E.L.; Parks, C.G.; Torgersen, T.R. 1997. Trees and logs important to wildlife in

the interior Columbia basin. Gen. Tech. Rep. PNW-GTR-391. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 55 p.
196

Bull, E.L.; Shepherd, J.F. 2003. Water temperature at oviposition sites of Rana

lueteiventris in northeastern Oregon. Western North American Naturalist. 63(1):

108-113.

Bull, E.L.; Skovlin, J.M. 1982. Relationships between avifauna and streamside vegetation. Transactions of the 47th North American Wildlife and Natural Resources Conference: 496-506.

Bull, E.L.; Torgersen, T.R.; Blumton, A.K. [et al.]. 1995. Treatment of an old-growth

stand and its effects on birds, ants, and large woody debris: a case study. Gen. Tech.

Rep. PNW-GTR-353. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 12 p.

Bull, E.L.; Torgersen, T.R.; Wertz, T.L. 2001b. The importance of vegetation, insects,

and neonate ungulates in black bear diet in northeast Oregon. Northwest Science.

75: 244-253.

Bull, E.L.; Wales, B.C. 2001a. Effects of disturbance on amphibians of conservation

concern in eastern Oregon and Washington. Northwest Science. 75(Spec. issue):

174-179.

Bull, E.L.; Wales, B.C. 2001b. Effects of disturbance on birds of conservation concern

in eastern Oregon and Washington. Northwest Science. 75(Spec. issue): 166-173.

Bull, E.L.; Wright, A.L.; Henjum, M.G. 1989. Nesting and diet of long-eared owls in

conifer forests, Oregon. Condor. 91(4): 908-912.

Bull, E.L.; Wright, A.L.; Henjum, M.G. 1990. Nesting habitat of flammulated owls in

Oregon. Journal of Raptor Research. 24: 52-55.

Carlson, J.Y. 1989. Effects of forest management on fish habitat and macroinvertebrates

in northeast Oregon. Corvallis, OR: Oregon State University. 127 p. M.S. thesis.

Carmichael, R.W. 1993. Preliminary results of habitat patient-template analysis for

Grande Ronde basin stocks of spring chinook. Tech. Memorandum. La Grande, OR:

Oregon Department of Fish and Wildlife, Fish Research and Development. [Pages

unknown].

Carmichael, R.W.; Boyce, R.R. 1986. U.S. v. Oregon, Grande Ronde River spring

chinook production report. In: U.S. v. Oregon Subbasin Production Reports. Portland,

OR: Oregon Department of Fish and Wildlife. [Irregular pagination].

Case, R.L. 1995. The ecology of riparian ecosystems of northeast Oregon: a shrub recovery at Meadow Creek and the structure and biomass of headwater Upper Grande

Ronde ecosystems. Corvallis, OR: Oregon State University. 137 p. M.S. thesis.

Chen, Y.D. 1996. Hydrologic and water quality modeling for aquatic ecosystem protection and restoration in forest watersheds: a case study of stream temperature in the

Upper Grande Ronde River, Oregon. Athens, GA: University of Georgia. 268 p. Ph.D.

dissertation.

Chen, Y.D.; Carsel, R.F.; McCutcheon, S.C. [et al.]. 1998a. Stream temperature simulation of forested riparian areas: I. Watershed-scale model development. Journal of

Environmental Engineering. 124(4): 304-315.
197

Chen, Y.D.; McCutcheon, S.C.; Norton, D.J. [et al.]. 1998b. Stream temperature

simulation of forested riparian areas: II. Model application. Journal of Environmental

Engineering. 124(4): 316-328.

Clark, P.E. 1996. Use of livestock to improve the quality of elk winter range forage

in northeastern Oregon. Corvallis, OR: Oregon State University. 179 p. Ph.D.

dissertation.

Clarke, S.E.; Bryce, S.A., eds. 1997. Hierarchical subdivisions of the Columbia Plateau

and Blue Mountains ecoregions, Oregon, and Washington. Gen. Tech. Rep. PNWGTR-395. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 114 p.

Clarke, S.E.; Garner, M.W.; McIntosh, B.A. [et al.]. 1997. Landscape-level ecoregions

for seven contiguous watersheds, northeast Oregon and southeast Washington. In:

Clarke, S.E.; Bryce, S.A., eds. Hierarchical subdivisions of the Columbia Plateau and

Blue Mountains ecoregions, Oregon and Washington. Gen. Tech. Rep. PNW-GTR395. Portland, OR: [U.S. Department of Agriculture], Forest Service, Pacific Northwest

Research Station: 53-113.

Clausnitzer, R.R. 1979. Annual understory production as a function of overstory structure and successional status in the Abies grandis/Pachistima myrsinites habitat type

in the Blue Mountains of southeastern Washington and northeastern Oregon. Pullman, WA: Washington State University. 58 p. M.S. thesis.

Clausnitzer, R.R. 1993. The grand fir series of northeastern Oregon and southeastern

Washington [microform]: successional stages and management guide. R6-ECO-TP

050-93. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region, Wallowa-Whitman National Forest. 193 p.

Clifton, C.F.; Harris, R.M.; Fitzgerald, J.K. 1999. Flood effects and watershed response in the northern Blue Mountains, Oregon and Washington. In: Olsen, D.S.;

Potyondy, J.P., eds. Wildland hydrology proceedings. Herdon, VA: American Water

Resources Association: 175-182.

Cochran, P.H.; Barrett, J.W. 1993. Long-term response of planted ponderosa pine

to thinning in Oregon’s Blue Mountains. Western Journal of Applied Forestry. 8(4):

126-132.

Cochran, P.H.; Barrett, J.W. 1995. Growth and mortality of ponderosa pine poles

thinned to various densities in the Blue Mountains of Oregon. Res. Pap. PNW-RP483. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 27 p.

Cochran, P.H.; Dahms, W.G. [1998]. Lodgepole pine development after early spacing

in the Blue Mountains of Oregon. Res. Pap. PNW-RP-503. [Portland, OR]: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 24 p.

Cochran, P.H.; Seidel, K.W. 1995. Growth of western larch under controlled levels of

stocking. In: Schmidt, W.C.; McDonald, K.J., comps. Ecology and management of

Larix forests: a look ahead. Proceedings of an international symposium. Gen. Tech.

Rep. INT-319. [Ogden, UT]: U.S. Department of Agriculture, Forest Service, Intermountain Research Station: 285-292.
198

Cook, J.G.; Irwin, L.L.; Bryant, L.D. [et al.]. 1999. Relations of forest cover and condition of elk: a test of the thermal cover hypothesis in summer and winter. Wildlife

Monographs 141: 1-61.

Cook, J.G.; Riggs, R.A.; Tiedemann, A.R.; Irwin, L.L.; Bryant, L.D. 1996. Ungulate

relationships on rangelands. In: Edge, W.D.; Olsen-Edge, S.L., eds. Proceedings of

a symposium on sustaining rangeland ecosystems. [Corvallis, OR]: Oregon State

University Extension Service: 155-159.

Cordova, J.J. 1995. Streamside forests, channel constraint, large woody debris characteristics, and pool morphology in low order streams, Blue Mountains, Oregon.

Corvallis, OR: Oregon State University. 143 p. M.S. thesis.

Corrarino, C.A.; Brusven, M.A. 1983. The effects of reduced stream discharge on insect drift and stranding of insects. Freshwater Invertebrate Biology. 2(2): 88-98.

Coulter, E.D. 1999. Hungry Bob harvest production study: mechanical thinning for fuel

reduction in the Blue Mountains of northeast Oregon. Corvallis, OR: Oregon State

University. 96 p. M.S. thesis.

Crowe, E.A.; Clausnitzer, R.R. 1997. Mid-montane wetland plant associations of the

Malheur, Umatilla, and Wallowa-Whitman National Forests. Tech. Pap. R6-NR-ECOLTP-22-97. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region. 299 p.

Davis, L.S.; Ruth, L.W.; Teeguarden, D. [et al.]. 1991. Ballot box forestry. Journal of

Forestry. 89(12): 10-18.

Delucchi, P.B. 1976. Effects of Douglas-fir tussock moth infestation on outdoor recreationists in the Blue Mountains, Oregon. Corvallis, OR: Oregon State University. 124 p.

M.S. thesis.

Diaz-Avalos, C. 1998. Space-time analysis of forest fires. Seattle, WA: University of

Washington. 120 p. Ph.D. dissertation.

Diaz-Avalos, C.; Peterson, D.L.; Alvarado, E. [et al.]. 2001. Space-time modelling of

lightning-caused ignitions in the Blue Mountains, Oregon. Canadian Journal of Forest

Research. 31(9): 1579-1593.

Diebel, K. 1997. Grande Ronde Basin Water Quality Monitoring: plans for six key

subwatersheds. [La Grande, OR]. Unpublished document. On file with: Grande Ronde

Model Watershed, 10901 Island Ave, La Grande, OR. Prepared for Union Soil and

Water Conservation District, Wallowa Soil and Water Conservation District, and

Grande Ronde Model Watershed Program. [Irregular pagination].

Downing, K.B.; Delucchi, P.B.; Williams, W.R. 1977. Impact of the Douglas-fir tussock moth on forest recreation in the Blue Mountains. Res. Pap. PNW-RP-224. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest

and Range Experiment Station. 14 p.

Duncan, A. 1998. History, science, the law, and watershed recovery in the Grande

Ronde: a case study. ORESU-G-97-001. Corvallis, OR: Oregon Sea Grant. 82 p.

Dwire, K.A. 2001. Relations among hydrology, soils, and vegetation in riparian meadows: influence on organic matter distribution and storage. Corvallis, OR: Oregon State

University. 168 p. Ph.D. dissertation.
199

Ebersole, J.L. 1994. Stream habitat classification and restoration in the Blue Mountains

of northeast Oregon. Corvallis, OR: Oregon State University. 59 p. M.S. thesis.

Ebersole, J.L.; Liss, W.J.; Frissell, C.A. 2002. Heterogeneous thermal habitat for a

stream fish assemblage. Ecological Society of America Annual Meeting Abstracts.

87: 120.

Ebert, K.M. 1987. The effects of wilderness recreation on avian species richness and

distribution in the Eagle Cap Wilderness Area. Pullman, WA: Washington State University. 52 p. M.S. thesis.

Edgerton, P.J.; Smith, J.G. 1971. Seasonal forage use by deer and elk on the Starkey

Experimental Forest and Range, Oregon. Res. Pap. PNW-112. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Forest and Range

Experiment Station. 12 p.

Evans, J.W. 1991. Powerful rockey: the Blue Mountains and the Oregon Trail, 1811-

1883. La Grande, OR: Eastern Oregon State College and Pika Press. 374 p.

Everett, R.L., comp. 1994. Volume IV: restoration of stressed sites and processes.

Gen. Tech. Rep. PNW-GTR-330. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 123 p. (Everett, R.L., assessment

team leader, Eastside forest ecosystem health assessment; volume IV).

Everett, R.; Hessburg, P.; Jensen, M.; Bormann, B. 1994. Volume I: executive summary. Gen. Tech. Rep. PNW-GTR-317. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station. 61 p. (Everett, R.L., assessment

team leader, Eastside forest ecosystem health assessment).

Ferguson, B.A. 1994. Fungal root pathogen interactions in a mixed conifer forest in the

Blue Mountains of northeastern Oregon. Corvallis, OR: Oregon State University. 128 p.

M.S. thesis.

Ferguson, S. 2001. Climatic variability in eastern Oregon and Washington. Northwest

Science. 75(Spec. issue): 62-69.

Filip, G.M.; Bryant, L.D.; Parks, C.A. 1989a. Mass movement of river ice causes

severe tree wounds along the Grande Ronde River in northeastern Oregon. Northwest

Science. 63(5): 211-213.

Filip, G.M.; Christiansen, E.; Parks, C.A. 1989b. Secondary resin production increases with vigor of Abies grandis inoculated with Trichosporium symbioticum in

northeastern Oregon. Res. Note PNW-RN-489. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 11 p.

Filip, G.M.; Colbert, J.J.; Parks, C.A. [et al.]. 1989c. Effects of thinning on volume

growth of western larch infected with dwarf mistletoe in northeastern Oregon. Western

Journal of Applied Forestry. 4(4): 143-144.

Filip, G.M.; Parks, C.A. 1987. Simultaneous infestation by dwarf mistletoe and western

spruce budworm decreases growth of Douglas-fir in the Blue Mountains of Oregon.

Forest Science. 33(3): 767-773.

Filip, G.M.; Parks, C.A. 1991. First report of stem cankers caused by Cytospora species on Alnus incana in Oregon. Plant Disease. 75(12): 1286.
200

Filip, G.M.; Parks, C.A.; Seidel, K.W. [et al.]. 1987. Incidence of decay fungi in

stumps of two thinned western larch stands in northeastern Oregon. Res. Note PNWRN-468. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 5 p.

Filip, G.M.; Parks, C.A.; Starr, G.L. 1992. Incidence of wound-associated infection by

Cytospora sp. in mountain alder, red-osier dogwood, and black hawthorn in Oregon.

Northwest Science. 66(3): 194-198.

Filip, G.M.; Torgersen, T.R.; Parks, C.A. [et al.]. 1996. Insect and disease factors in

the Blue Mountains. In: Jaindl, R.G.; Quigley, T.M., eds. Search for a solution: sustaining the land, people, and economy of the Blue Mountains. Washington, DC:

American Forests: 169-202.

Filip, G.M.; Yang-Erve, L. 1997. Effects of prescribed burning on the viability of

Armillaria ostoyae in mixed-conifer forest soils in the Blue Mountains of Oregon.

Northwest Science. 71(2): 137-144.

Fowler, W.B.; Helvey, J.D.; Johnson, C. 1979. Baseline climatic and hydrologic relationships for the High Ridge evaluation area in the Blue Mountains of Oregon. Gen.

Tech. Rep. PNW-GTR-91. Portland, OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Forest and Range Experiment Station. 17 p.

Franklin, J.F.; Dyrness, C.T. 1973. Natural vegetation in Oregon and Washington. Gen.

Tech. Rep. PNW-8. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Forest and Range Experiment Station. 417 p.

Ganskopp, D.C. 1978. Plant communities and habitat types of the Meadow Creek experimental watershed. Corvallis, OR: Oregon State University. 162 p. M.S. thesis.

Gast, W.R., Jr.; Scott, D.W.; Schmitt, D. [et al.]. 1991. Blue Mountains forest health

report: new perspectives in forest health. [Portland, OR]: U.S. Department of Agriculture, Forest Service, Malheur, Umatilla, and Wallowa-Whitman National Forests.

[Irregular pagination].

Gebauer, C.E. 1998 . Forest grazing and site quality: influences of cattle, big game and

tree species on soil nutrients, soil compaction and vegetation of a seral forest in

northeastern Oregon. Pullman, WA: Washington State University. 109 p. M.S. thesis.

Geist, J.M. 1977. Nitrogen response relationships of some volcanic ash soils. Soil Science Society of America. 41(5): 996-1000.

Geist, J.M.; Hazard, J.W.; Seidel, K.W. 1989. Assessing physical conditions of some

Pacific Northwest volcanic ash soils after forest harvest. Soil Science Society of

America. 53(3): 946-950.

Geist, J.M.; Strickler, G.S. 1978. Physical and chemical properties of some Blue Mountain soils in eastern Oregon. Res. Pap. PNW-236. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station.

19 p.

Gildemeister, J. 1998. Watershed history: Middle and Upper Grande Ronde River

subbasins. La Grande, OR: [Publisher unknown]. [Irregular pagination].
201

Gill, R.E. 1994. Sediment delivery to headwater stream channels following road construction and timber harvest in the Blue Mountains, Oregon. Corvallis, OR: Oregon

State University. 59 p. M.S. thesis.

Gillen, R.L.; Krueger, W.C.; Miller, R.F. 1985. Cattle use of riparian meadows in

the Blue Mountains of northeastern Oregon. Journal of Range Management. 38(3):

205-209.

Goggans, R. 1985. Habitat use by flammulated owls in northeastern Oregon. Corvallis,

OR: Oregon State University. 54 p. M.S. thesis.

Grimble, D.G.; Beckwith, R.C. 1992-1994. A survey of the Lepidoptera fauna from the

Blue Mountains of eastern Oregon. Journal of Research on the Lepidoptera. 31(1-2):

83-102.

Grimble, D.G.; Beckwith, R.C.; Hammond, P.C. 1993. New Lepidoptera records for

the Blue Mountains of eastern Oregon. Res. Pap. PNW-RP-469. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 6 p.

Hall, F.C. 1973. Plant communities of the Blue Mountains in eastern Oregon and southeastern Washington. R-6 Area Guide. [Portland, OR]: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Region. 62 p.

Hall, F.C. 1974. Key to environmental indicator plants of the Blue Mountains in eastern

Oregon and southeastern Washington. R6 Area Guide 3-2. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region. 51 p.

Hall, F.C. 1976. Fire and vegetation in the Blue Mountains—implications for land managers. In: Komareck, E.V., ed. Tall Timbers Research Station. Proceedings of the 15th

annual Tall Timbers fire ecology conference. Tallahassee, FL: Tall Timbers Research

Station: 155-170.

Hall, F.C. 1977. Ecology of natural underburning in the Blue Mountains of Oregon. R6-

Ecol. 79-001. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Region. 11 p.

Hall, F.C. 1980. Fire history—Blue Mountains, Oregon. In: Stokes, M.A.; Dietrich, J.H.,

eds. Proceedings of fire history workshop. Fort Collins, CO: U.S. Department of

Agriculture, Forest Service, Rocky Mountain Forest and Range Experiment Station:

75-81.

Hall, T.; Bigler-Cole, H. 2001. Sociocultural factors and forest health management.

Northwest Science. 75(Spec. issue): 208-233.

Harrod, R.J. 2001. The effect of invasive and noxious plants on land management in

eastern Oregon and Washington. Northwest Science. 75(Spec. issue): 85-90.

Harvey, A.E.; Geist, J.M.; McDonald, G.I. [et al.]. 1994. Biota and abiotic processes

in eastside ecosystems: the effects of management on soil properties, processes,

and productivity. Gen. Tech. Rep. PNW-GTR-323. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 71 p. (Everett, R.L.,

assessment team leader, Eastside forest ecosystem health assessment; Hessburg,

P.F., science team leader and tech. ed., Volume III: assessment).
202

Hayes, J.L.; Daterman, G.E. 2001. Bark beetles in eastern Oregon and Washington.

Northwest Science. 75(Spec. issue): 21-30.

Hayes, J.L.; Ragenovich, I. 2001. Non-native invasive forest insects of eastern Oregon

and Washington. Northwest Science. 75(Spec. issue): 77-84.

Haynes, R.; Fight, R.; Lowell, E. [et al.]. 2001. Economic aspects of thinning and

harvest for forest health improvement in eastern Oregon and Washington. Northwest

Science. 75(Spec. issue): 199-207.

Helvey, J.D.; Tiedemann, A.R. 1978. Effects of defoliation by Douglas-fir tussock moth

on timing and quantity of streamflow. Res. Note PNW-326. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment

Station. 13 p.

Hemstrom, M. 2001. Vegetative patterns, disturbances, and forest health in eastern

Oregon. Northwest Science. 75(Spec. issue): 91-109.

Hemstrom, M.; Smith, T.; Evans, T. [et al.]. 2002. Midscale analysis of streamside

characteristics in the Upper Grande Ronde subbasin, northeastern Oregon. Res. Note

PNW-RN-534. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 16 p.

Hermens, R.A.; Turner, J.E. 1985. La Grande, 1885-1985. La Grande, OR: Grande

Ronde Publishing Co. 156 p.

Hessburg, P.F.; Mitchell, G.R.; Filip, G.M. 1994. Historical and current roles of insects

and pathogens in eastern Oregon and Washington forested landscapes. Gen. Tech.

Rep. PNW-GTR-327. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 72 p. (Everett, R.L., assessment team leader,

Eastside forest ecosystem health assessment; Hessburg, P.F., science team leader

and tech. ed., Volume III: assessment).

Heyerdahl, E.K. 1997. Spatial and temporal variation in historical fire regimes of the

Blue Mountains, Oregon and Washington: the influence of climate. Seattle, WA:

University of Washington. 224 p. Ph.D. dissertation.

Heyerdahl, E.K.; Agee, J.K.; Brubaker, L.B. 1996. Historical size and seasonality of

low severity fires in the Blue Mountains, Oregon, from tree rings. Bulletin of the Ecological Society of America. 77(3 Suppl. Part 2): 195.

Heyerdahl, E.K.; Brubaker, L.B.; Agee, J.K. 2001. Spatial controls of historical fire

regimes: a multiscale example from the interior West, USA. Ecology. 82(3): 660-678.

Higgins, D.A.; Maloney, S.B.; Tiedemann, A.R. [et al.]. 1988. Calibration of waterbalance model for small watersheds in eastern Oregon. Water Resources Bulletin.

24(2): 347-360 .

Higgins, D.A.; Tiedemann, A.R.; Quigley, T.M. [et al.]. 1989. Streamflow characteristics of small watersheds in the Blue Mountains of Oregon. Water Resources Bulletin.

25(6): 1131-1149.

Hines, C.; Bradshaw, G.A. 1997. Landscape analysis of black cottonwood community

dynamics, Grande Ronde River, Oregon, USA: assessing restoration potential and

long-term viability. Bulletin of the Ecological Society of America. 78(4 Suppl): 109.
203

Hines, C.A. 1998. Evaluating the restoration potential of potential black cottonwood

(Populus trichocarpa) from multiple scales of observation, Grande Ronde River basin,

Oregon, USA. Corvallis, OR: Oregon State University. 149 p. M.S. thesis.

Hitchcock, M.; Ager, A. 1992. Microcomputer software for calculating an elk habitat

effectiveness index on Blue Mountain winter range. Gen. Tech. Rep. PNW-GTR-301.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 13 p.

Holechek, J.; Vavra, M.; Skovlin, J. [et al.]. 1982a. Cattle diets in the Blue Mountains

of Oregon, USA 1. Forests. Journal of Range Management. 35(2): 239-242.

Holechek, J.; Vavra, M.; Skovlin, J. [et al.]. 1982b. Cattle diets in the Blue Mountains

of Oregon, USA 2. Grasslands. Journal of Range Management. 35(1): 109-112.

Holechek, J.L.; Berry, T.J.; Vavra, M. 1987. Grazing system influences on cattle performance on mountain range. Journal of Range Management. 40(1): 55-59.

Holechek, J.L.; Vavra, M. 1983. Fistula sample numbers required to determine cattle

diets on forest and grassland ranges. Journal of Range Management. 36(3): 323-326.

Holechek, J.L.; Vavra, M.; Skovlin, J. 1980. Performance, diet and intake of yearling

heifers under rest-rotation and season-long grazing systems. In: Society for Range

Management 33rd annual meeting. [Place of publication unknown]: Society for Range

Management: [Pages unknown].

Holechek, J.L.; Vavra, M.; Skovlin, J. 1981. Diet quality and performance of cattle on

forest and grassland range. Journal of Animal Science. 53(2): 291-298.

Holechek, J.L.; Vavra, M.; Skovlin, J. 1983. Cattle diets and daily gains on a mountain riparian meadow in northeastern Oregon, USA. Journal of Range Management.

35(6): 745-757.

Howell, P.J. 2001. Effects of disturbance and management of forest health on fish and

fish habitat in eastern Oregon and Washington. Northwest Science. 75(Spec. issue):

157-165.

Huff, M.H.; Ottmar, R.D.; Alvarado, E. [et al.]. 1995. Historical and current landscapes

in eastern Oregon and Washington. Part II: Linking vegetation characteristics to potential fire behavior and related smoke production. Gen. Tech. Rep. PNW-GTR-355.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 43 p.

Huntington, C.W. 1994. Stream and riparian conditions in the Grande Ronde basin

1993. Canby, OR: Clearwater Biostudies, Inc. [Pages unknown]. Unpublished document. On file with: Grande Ronde Model Watershed, 10901 Island Ave., La Grande,

OR 97850.

Ince, P.J. 1982. Economic perspective on harvesting and physical constraints on utilizing small, dead lodgepole pine. Forest Products Journal. 32(11/12): 61-66.

Irwin, L.L.; Cook, J.G.; Riggs, R.A.; Skovlin, J.M. 1994. Effects of long-term grazing

by big game and livestock in the Blue Mountains forest ecosystems. Gen. Tech. Rep.

PNW-GTR-325. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 49 p. (Everett, R.L., assessment team leader, Eastside

forest ecosystem health assessment; Hessburg, P.F., science team leader and tech.

ed., Volume III: assessment).
204

Jaindl, R.G.; Quigley, T.M., eds. 1996. Search for a solution: sustaining land, people,

and the economy of the Blue Mountains. Washington, DC: American Forests. 316 p.

James, G. 1984. Grande Ronde River basin—recommended salmon and steelhead habitat improvement measures. Working Rep. [Place of publication unknown]: Confederated Tribes of the Umatilla Indian Reservation. 58 p. [plus appendices].

Jensen, M.E.; Bourgeron, P.S., tech. eds. 1994. Volume II: Ecosystem management:

principles and applications. Gen. Tech. Rep. PNW-GTR-318. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station.

376 p. (Everett, R.L., assessment team leader, Eastside forest ecosystem health

assessment).

Johnson, C.G., Jr. 1981. An interpretation of synecologic relationships in the Billy

Meadows Area of the Wallowa-Whitman National Forest. Corvallis, OR: Oregon State

University. 342 p. Ph.D. dissertation.

Johnson, C.G., Jr. 1994. Forest health in the Blue Mountains: a plant ecologist’s perspective on ecosystem processes and biological diversity. Gen. Tech. Rep. PNWGTR-339. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 23 p.

Johnson, C.G., Jr. [1998]. Vegetation response after wildfires in national forests of

northeastern Oregon. Tech. Pap. R6-NR-ECOL-TP-06-98. [Portland, OR]: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region. 157 p.

Johnson, C.G. Jr.; Clausnitzer, R.R. 1992. Plant associations of the Blue and Ochoco

Mountains. Tech. Pap. R6-ERW-TP-036-92. [Portland, OR]: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region, Wallowa-Whitman National Forest.

164 p.

Johnson, C.G. Jr.; Clausnitzer, R.R.; Mehringer, P.J.; Oliver, C.D. 1994. Biota and

abiotic processes of eastside ecosystems: the effects of management on plant and

community ecology, and on stand and landscape vegetation dynamics. Gen. Tech.

Rep. PNW-GTR-322. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 66 p. (Everett, R.L., assessment team leader,

Eastside forest ecosystem health assessment; Hessburg, P.F., science team leader

and tech. ed., Volume III: assessment).

Johnson, L.C. [1997]. A brief history of Union County, Oregon. La Grande, OR: Grande

Ronde Publishing Company. 76 p.

Keefe, M.; Anderson, D.J.; Carmichael, R.W. [et al.]. 1995. Early life history study

of Grande Ronde River basin chinook salmon: annual progress report. Portland, OR:

U.S. Department of Energy, Bonneville Power Administration. [Pages unknown].

Keefe, M.L.; Carmichael, R.W.; Jonasson, B.C. [et al.]. 1994. Fish research project

Oregon: investigations into the life history of spring chinook salmon in the Grande

Ronde River basin. La Grande, OR: Oregon Department of Fish and Wildlife. Annual

report prepared for U.S. Department of Energy, Bonneville Power Administration, Environment, Fish and Wildlife; project number 92-026-01; contract 94BI33299. [Pages

unknown]. On file with: Grande Ronde Model Watershed, 10901 Island

Avenue, La Grande, OR 97850.
205

Keith, T. 1991. Restoring forest health in the Blue Mountains: a strategy and action plan

for state and private lands. Salem, OR: Oregon Department of Forestry, Public Affairs

Office. 7 p.

Kemp, W.P.; Dennis, B.; Beckwith, R.C. 1986. Stochastic phenology model for the

western spruce budworm (Lepidoptera, Tortiricidae). Environmental Entomology.

15(3): 547-554.

Klock, G.O.; Lopushinsky, W. 1980. Soil water trends after clearcutting in the Blue

Mountains of Oregon. Res. Note PNW-RN-361. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station.

8 p.

Knight, R.W. 1977. Streamside erosional response to animal grazing practices on

Meadow Creek in northeastern Oregon. Corvallis, OR: Oregon State University. 68 p.

M.S. thesis.

Korfhage, R.C.; Nelson, J.R.; Skovlin, J.M. 1980. Summer diets of Rocky Mountain

elk in northeastern Oregon. Journal of Wildlife Management. 44(3): 746-750.

Kreger, A.E.; Roschke, D.J. 1991. Wallowa-Whitman National Forest soils database.

Soil Survey Horizons. 32(4): 91-96.

LaBonte, J.R.; Scott, D.W.; McIver, J.D. [et al.]. 2001. Threatened, endangered, and

sensitive insects in eastern Oregon and Washington forests and adjacent lands.

Northwest Science. 75(Spec. issue): 185-198.

Langston, N. 1994. The general riot of the forest: landscape in the Blue Mountains.

Seattle, WA: University of Washington. 324 p. Ph.D. dissertation.

Langston, N. 1995. Forest dreams, forest nightmares: the paradox of old growth in the

inland West. Seattle, WA: University of Washington Press. 368 p.

Langston, N. 2000. When sound science is not enough: regulating the Blues. Journal

of Forestry. 98(11): 31-35.

Leckenby, D.A. 1984. Elk use and availability of cover and forage habitat components in

the Blue Mountains, northeast Oregon, 1976-1982. Wildlife Res. Rep. 14. Portland,

OR: Oregon Department of Fish and Wildlife, Research and Development. 40 p.

Lehmkuhl, J.F.; Hessburg, P.F.; Everett, R.L. [et al.]. 1994. Historical and current

forest landscapes of eastern Oregon and Washington. Part I: Vegetation pattern and

insect and disease hazards. Gen. Tech. Rep. PNW-GTR-328. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 88 p.

(Everett, R.L., assessment team leader, Eastside forest ecosystem health assessment; Hessburg, P.F., science team leader and tech. ed., Volume III: assessment).

Lennette, A.P. 1999. Twenty-five year response of Larix occidentalis stem forms to

five stand density regimes in the Blue Mountains of eastern Oregon. Corvallis, OR:

Oregon State University. 59 p. M.S. thesis.

Lundquist, J.E.; Beatty, J.S. 1999. A conceptual model for defining and assessing condition of forest stands. Environmental Management. 23(4): 519-525.
206

Lundquist, J.E.; Beatty, J.S. 2002. A method for characterizing and mimicking forest

canopy gaps caused by different disturbances. Forest Science. 48(3): 582-594.

Lundquist, J.E.; King, R.M.; Beatty, J.S. 1996. Assessing the relative influence of disease in forest ecosystems in the Blue Mountains. Phytopathology. 86(11 Supplement): S38.

Lytjen, D.J. 1998. Ecology of woody riparian vegetation in tributaries of the Upper

Grande Ronde River basin, Oregon. Corvallis, OR: Oregon State University. 76 p.

M.S. thesis.

Maloney, S.B.; Tiedemann, A.R.; Higgins, D.A. [et al.]. 1999. Influence of stream

characteristics and grazing intensity on stream temperatures in eastern Oregon.

Gen. Tech. Rep. PNW-GTR-459. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station. 19 p.

Mannan, R.W. 1982. Bird populations and vegetation characteristics in managed and

old-growth forests, northeastern Oregon. Corvallis, OR: Oregon State University. 67 p.

Ph.D dissertation.

Marcot, B.G.; Wisdom, M.J.; Li, H.W.; Castillo, G.C. 1994. Managing for featured,

threatened, endangered, and sensitive species and unique habitats for ecosystem

sustainability. Gen. Tech. Rep. PNW-GTR-329. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 39 p. (Everett, R.L.,

assessment team leader, Eastside forest ecosystem health assessment; Hessburg,

P.F., science team leader and tech. ed., Volume III: assessment).

Maruka, K.R. 1994. Fire history of Pseudotsuga menziesii and Abies grandis stands in

the Blue Mountains of Oregon and Washington. Seattle, WA: University of Washington. 73 p. M.S. thesis.

Mason, R.R. 1996. Dynamic behavior of Douglas-fir tussock moth populations in the

Pacific Northwest. Forest Science. 42(2): 182-191.

Mason, R.R.; Paul, H.G. 1988. Predation on larvae of Douglas-fir tussock moth, Orgyia

pseudotsugata (Lepidoptera: Lymantriidae), by Metaphidippus aeneolus (Araneae:

Salticidae). Pan-Pacific Entomologist. 64(3): 258-260.

Mason, R.R.; Paul, H.G. 1996. Case history of population change in a Bacillus

thuringiensis-treated vs. an untreated outbreak of the western spruce budworm. Res.

Note PNW-RN-521. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 11 p.

Mason, R.R.; Wickman, B.E. [1988]. The Douglas-fir tussock moth in the interior

Pacific Northwest. In: Berryman, A.A., ed. Dynamics of forest insect populations:

patterns, causes, implications. New York: Plenum Press: 179-209.

McCluskey, D.C. 1976. DDT and reproductive success of bluebirds and house wrens in

northeastern Oregon. Corvallis, OR: Oregon State University. 44 p. M.S. thesis.

McHugh, P. 2003. A model-based approach to assessing the potential response of

chinook salmon to habitat improvements. Logan, UT: Utah State University. 183 p.

M.S. thesis.
207

McInnis, M.L.; Quigley, T.M.; Vavra, M. [et al.]. 1990. Predicting beef cattle stocking

rates and live weight gains on eastern Oregon rangelands: description of a model.

Simulation: 137-145.

McIntosh, B.A. 1992. Historical changes in anadromous fish habitats in the Upper

Grande Ronde River, Oregon. Corvallis, OR: Oregon State University. 88 p. M.S.

thesis.

McIntosh, B.A. 1995. Historical changes in stream habitats in the Columbia River basin.

Corvallis, OR: Oregon State University. 175 p. Ph.D. dissertation.

McIntosh, B.A.; Price, D.M.; Torgersen, C.E. [et al.]. 1995. Distribution, habitat utilization, movement patterns, and the use of thermal refugia by spring chinook in

the Grande Ronde, Imnaha, and John Day basins. Progress Rep. Project 93-700.

Portland, OR: U.S. Department of Energy, Bonneville Power Administration. 16 p.

McIntosh, B.A.; Sedell, J.R.; Smith, J.E. [et al.]. 1994a. Historical changes in fish

habitat for select river basins of eastern Oregon and Washington. Northwest Science.

68(Spec. issue): 36-53.

McIntosh, B.A.; Sedell, J.R.; Smith, J.E. [et al.]. 1994b. Management history of eastside ecosystems: changes in fish habitat over 50 years, 1935 to 1992. Gen. Tech.

Rep. PNW-GTR-321. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 55 p. (Everett, R.L., assessment team leader,

Eastside forest ecosystem health assessment; Hessburg, P.F., science team leader

and tech. ed., Volume III: assessment).

McIver, J.D.; Starr, L. 2000. Environmental effects of postfire logging: literature review

and annotated bibliography. Gen. Tech. Rep. PNW-GTR-486. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 72 p.

McIver, J.D.; Starr, L. 2001. A literature review on the environmental effects of postfire

logging. Western Journal of Applied Forestry. 16(4): 159-168.

McIver, J.D.; Torgersen, T.R.; Cimon, N.J. 1997. A supercolony of the thatch ant

Formica obscuripes Forel (Hymenoptera: Formicidae) from the Blue Mountains of

Oregon. Northwest Science. 71(7): 18-29.

McLemore, C.E.; Meehan, W.R. 1988. Invertebrates of Meadow Creek, Union County,

Oregon, and their use as food by trout. Res. Pap. PNW-RP-394. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 13 p.

Meays, C.L. 2000. Elevation, thermal environment, and stream temperatures on headwater streams in northeastern Oregon. Corvallis, OR: Oregon State University. 140 p.

M.S. thesis.

Mobrand, L.; Lestell, L.; Gilbertson, L. [et al.]. 1995. Grande Ronde model watershed

ecosystem diagnosis and treatment: template for planning status report for Grande

Ronde Model Watershed project and progress report on the application of an ecosystem analysis method to the Grande Ronde watershed using spring chinook salmon

as a diagnostic species. Portland, OR: U.S. Department of Energy, Bonneville Power

Administration; final report; project 94-030. [Pages unknown]. On file with: Grande

Ronde Model Watershed, 10901 Island Avenue, La Grande, OR 97850.
208

Moffat, R.; Wellman R.; Gordon, J. 1990. Statistical summaries of streamflow data

in Oregon: monthly and annual streamflow, and flow-duration curves; open-file report

90-118. Portland, OR: U.S. Department of the Interior, Geological Survey. [Pages

unknown]. Vol. 1.

Mohr, F.; Both, B. 1996. Confinement—a suppression response for the future? Fire

Management Notes. 56(2): 17-22.

Moore, K.R.; Henny, C.J. 1984. Age-specific productivity and nest characteristics of

Coopers hawks. Northwest Science. 58(4): 290-299.

Moser, B.W.; Witmer, G.W. 2000. The effects of elk and cattle foraging on the vegetation, birds, and small mammals of the Bridge Creek Wildlife Area, Oregon. International Biodeterioration and Biodegradation. 45(3-4): 151-157.

Murphy, C.F.; Croft, B.A. 1990. Forest ant composition and foraging following aerial

spraying of carbaryl to suppress western spruce budworm. Canadian Entomologist.

122(7-8): 595-606.

Mutch, R.W.; Arno, S.F.; Brown, J.K. [et al.]. 1993. Forest health in the Blue Mountains: a management strategy for fire-adapted ecosystems. Gen. Tech. Rep. PNWGTR-310. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 14 p.

Neitzel, D.A.; Frest, T.J. 1992. Survey of Columbia River basin streams for Columbia

pebblesnail (Fluminicola columbiana) and shortface lanx (Fisherola nuttalli). Tech.

Rep. PNL-8229. Richland, WA: Battelle Pacific Northwest Labs. 83 p.

Noll, W.; Williams, S.; Boyce, R. 1987. Grande Ronde River basin fish habitat improvement implementation plan. Portland, OR: Oregon Department of Fish and Wildlife. [Pages unknown].

Northwest Power Planning Council. 1990. Grande Ronde River subbasin salmon

and steelhead production plan. Columbia basin system planning. Portland, OR:

Northwest Power Planning Council, and the agencies and Indian tribes of the Columbia Basin Fish and Wildlife Authority. [Pages unknown].

Nowak, M.C. 1999. Predation rates and foraging ecology of adult female mountain

lions in northeastern Oregon. Pullman, WA: Washington State University. 75 p.

M.S. thesis.

Noyes, J.H.; Johnson, B.K.; Bryant, L.D. [et al.]. 1996. Effects of bull age on conception dates and pregnancy rates of cow elk. The Journal of Wildlife Management.

60(3): 508-517 .

Oester, P.T.; Emmingham, W.; Larson, P. [et al.]. 1995. Performance of ponderosa

pine seedlings under four herbicide regimes in northeast Oregon. New Forests.

10(2): 123-131.

Oliver, C.D.; Irwin, L.L.; Knapp, W.H. 1994. Eastside forest management practices:

historical overview, extent of their applications, and their effects on sustainability of

ecosystems. Gen. Tech. Rep. PNW-GTR-324. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 73 p. (Everett, R.L.,

assessment team leader, Eastside forest ecosystem health assessment; Hessburg,

P.F., science team leader and tech. ed., Volume III: assessment).
209

Olson, D.L. 2000. Fire in riparian zones: a comparison of historical fire occurrence

in riparian and upslope forests in the Blue Mountains and southern Cascades of

Oregon. Seattle, WA: University of Washington. 274 p. M.S. thesis.

Oregon Department of Fish and Wildlife. [1988]. Summer steelhead creel surveys in

the Grande Ronde, Wallowa, and Imnaha Rivers for the 1987-88 run year; progress

report. Portland, OR: Oregon Department of Fish and Wildlife, Fish Division. [Pages

unknown].

Oregon Department of Fish and Wildlife. [1990]. Grande Ronde River subbasin:

salmon and steelhead production plan. [Portland, OR]. 163 p.

Oregon Department of Fish and Wildlife. [1993-1996]. Residual hatchery steelhead:

characteristics and potential interactions with spring chinook salmon in northeast

Oregon; progress report. Portland, OR: [Pages unknown].

Oregon Department of Fish and Wildlife. [1994]. Smolt migration characteristics and

mainstem Snake and Columbia River detection rates of Grande Ronde and Imnaha

River naturally produced spring chinook salmon; progress report. Portland, OR:

[Pages unknown].

Oregon Department of Fish and Wildlife. [1999]. Summer steelhead creel surveys in

the Grande Ronde, Wallowa, and Imnaha Rivers for the 1998-99 run year; progress

report. Portland, OR: Oregon Department of Fish and Wildlife, Fish Division. [Pages

unknown].

Oregon Department of Transportation. 1984. Grande Ronde and Wallowa River scenic waterway study, Union and Wallowa Counties. [Place of publication unknown]:

State Parks and Recreation Division, Scenic Waterways Program. [Pages unknown].

Otting, N.J. 1998. Ecological characteristics of montane floodplain plant communities in

the Upper Grande Ronde basin, Oregon. Corvallis, OR: Oregon State University. 71 p.

M.S. thesis.

Ottmar, R.D.; Sandberg, D.V. 2001. Wildland fire in eastern Oregon and Washington.

Northwest Science. 75(Spec. issue): 46-54.

Parker, S.J.; Keefe, M.; Carmichael, R.W. [1995]. Natural escapement monitoring

of spring chinook salmon in the Imnaha and Grande Ronde River basins; progress

report. Portland, OR: Oregon Department of Fish and Wildlife. 15 p.

Parks, C.A.; Hoffman, J.T. 1991. Control of western dwarf mistletoe with the plantgrowth regulator ethephon. Res. Note PNW-RN-506. Portland, OR: U.S. Department

of Agriculture, Forest Service, Pacific Northwest Research Station. 4 p.

Parks, C.G.; Bednar, L.; Tiedemann, A.R. 1998. Browsing ungulates—an important

consideration in dieback and mortality of Pacific yew (Taxus brevifolia) in a northeastern Oregon stand. Northwest Science. 72(3): 190-197.
210

Parks, C.G.; Bull, E.L. 1997. American marten use of rust and dwarf mistletoe brooms

in northeastern Oregon. Western Journal of Applied Forestry. 12: 131-133.

Parks, C.G.; Bull, E.L.; Tinnin, R.O. [et al.]. 1999. Wildlife use of dwarf mistletoe

brooms in Douglas-fir in northeastern Oregon. Western Journal of Applied Forestry.

14(2): 100-105.

Parks, C.G.; Flanagan, P.T. 2001. Dwarf mistletoes, rust disease, and stem decays

in eastern Oregon and Washington. Northwest Science. 75(Spec. issue): 31-37.

Parks, C.G.; Schmitt, C.L. 1997. Wild edible mushrooms in the Blue Mountains:

resource and issues. Gen. Tech. Rep. PNW-GTR-393. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 22 p.

Parry, D.L.; Filip, G.M.; Willits, S.A. [et al.]. 1996. Lumber recovery and deterioration

of beetle-killed Douglas-fir and grand fir in the Blue Mountains of eastern Oregon.

Gen. Tech. Rep. PNW-GTR-376. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station. 24 p.

Pelren, E.C. 1996. Blue grouse winter ecology in northeastern Oregon. Corvallis, OR:

Oregon State University. 67 p. Ph.D. dissertation.

Pelren, E.C.; Crawford, J.A. 1999. Blue grouse nesting parameters and habitat associations in northeastern Oregon. Great Basin Naturalist. 59(4): 368-373.

Petersen, G.J.; Mohr, F.R. 1984. Underburning on white fir sites to induce natural

regeneration and sanitation. Fire Management Notes. 45(2): 17-20.

Peterson, W.C.; Hibbs, D.E. 1989. Adjusting stand density management guides for

sites with low stocking potential. Western Journal of Applied Forestry. 4(2): 62-65.

Porath, M.L.; Momont, P.A.; DelCurto, T. [et al.]. 2002. Offstream water and trace

mineral salt as management strategies for improved cattle distribution. Journal of

Animal Science. 80(2): 346-356.

Powell, D.C. 1994. Effects of the 1980s western spruce budworm outbreak on the

Malheur National Forest in northeastern Oregon. Tech. Pap. R6-FI&D-TP-12-94. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Region,

Forest Insects and Diseases Group. 176 p.

Powell, D.C. 1999. Historical references about vegetation conditions: a bibliography

with abstracts. Tech. Pap. F14-SO-TP-05-99. [Place of publication unknown]: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Region. 310 p.

Price, D.M. 1998. Multiscale habitat electivity and movement patterns by adult spring

chinook salmon in seven river basins of northeast Oregon. Corvallis, OR: Oregon State

University. 77 p. M.S. thesis.

Quigley, T.M. 1992. Forest health in the Blue Mountains: social and economic perspectives: science perspectives. Gen. Tech. Rep. PNW-GTR-296. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 9 p.
211

Quigley, T.M.; Hayes, J.L.; Starr, G.L. [et al.]. 2001. Improving forest health and productivity in eastern Oregon and Washington. Northwest Science. 75(Spec. issue):

234-251.

Quigley, T.M.; Tanaka, J.A.; Sanderson, H.R. [et al.]. 1991. Economically optimal

private land grazing strategies for the Blue Mountains of eastern Oregon. Journal of

Range Management. 44(1): 38-42.

Reed, M.A. 1998. On-site public evaluations on the use of prescribed fire and mechanical thinning. Corvallis, OR: Oregon State University. 102 p. M.S. thesis.

Riegel, G.M. 1989. Understory competition for resources in Pinus ponderosa forests

of northeastern Oregon. Corvallis, OR: Oregon State University. 189 p. Ph.D.

dissertation.

Rieman, B.; Peterson, J.T.; Clayton, J. [et al.]. 2001. Evaluations of potential effects

of federal land management alternatives on trends of salmonids and their habitats in

the interior Columbia River basin. Forest Ecology and Management. 153: 43-62.

Riggs, R.A.; Tiedemann, A.R.; Cook, J.G. [et al.]. 2000. Modification of mixed-conifer

forests by ruminant herbivores in the Blue Mountains ecological provinces. Res. Pap.

PNW-RP-527. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 77 p.

Roath, L.R.; Krueger, W.C. 1982. Cattle grazing and behavior on a forested range.

Journal of Range Management. 33(3): 332-338.

Robbins, W.G.; Wolf, D.W. 1994. Landscape and the intermontane Northwest: an

environment history. Gen. Tech. Rep. PNW-GTR-319. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 32 p.

(Everett, R.L., assessment team leader, Eastside forest ecosystem health assessment; Hessburg, P.F., science team leader and tech. ed., Volume III: assessment).

Robichaud, P.R.; Brown, R.E. 1999. What happened after the smoke cleared: onsite

erosion rates after a wildfire in eastern Oregon. Wildland Hydrology Proceedings:

419-426.

Roush, C.F. 1978. Nesting biologies and seasonal occurrence of yellowjackets in northeastern Oregon forests (Hymenoptera: Vespidae). Pullman, WA: Washington State

University. 80 p. M.S. thesis.

Ryan, R.B. 1983. Population density and dynamics of the larch casebearer (Lepidoptera: Coleophoridae) in the Blue Mountains of Oregon and Washington before the

build-up of exotic parasites. Canadian Entomologist. 115(19): 1095-1102.

Ryan, R.B. 1985. Relationship between parasitism of larch casebearer (Lepidoptera:

Coleophoridae) and dead hosts in the Blue Mountains, 1973-1983. Canadian

Entomologist. 117(8): 935-939.

Ryan, R.B. 1997. Before and after evaluation of biological control of the larch casebearer

(Lepidoptera: Coleophoridae) in the Blue Mountains of Oregon and Washington 1972-

1995. Environmental Entomology. 26(3): 703-715.

Sallabanks, R.; Riggs, R.A.; Cobb, L.E. 2002. Bird use of forest structural classes in

grand fir forests of the Blue Mountains, Oregon. Forest Science. 48(2): 311-321.
212

Sanderson, H.R.; Quigley, T.M.; Spink, L.R. 1988. Defining, implementing and evaluating grazing management strategies. Journal of Soil and Water Conservation. 43(4):

345-348.

Seidel, K.W. 1982. Growth and yield of western larch: 15-year results of a levels-ofgrowing-stock study Larix occidentalis, Wallowa-Whitman National Forest, northeastern Oregon. Res. Note PNW-398. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Forest and Range Experiment Station. 14 p.

Seidel, K.W.; Head, S.C. 1983. Regeneration in mixed-conifer partial cuttings in the

Blue Mountains of Oregon and Washington. Res. Pap. PNW-310. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range

Experiment Station. 14 p.

Sheehy, D.P. 1987. Grazing relationships of elk, deer, and cattle on seasonal rangelands in northeastern Oregon. Corvallis, OR: Oregon State University. 269 p. Ph.D.

dissertation.

Sheehy, D.P.; Slater, R. 1998. Improvement of elk habitat in the North Grande Ronde

Valley. Annual Report. [Place of publication unknown]: Eastern Oregon Agricultural

Research Center. 125 p.

Shindler, B.A.; Brunson, M.; Stankey, G.H. 2002. Social acceptability of forest conditions and management practices: a problem analysis. Gen. Tech. Rep. PNW-GTR537. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 68 p.

Shindler, B.A.; Reed, M. 1996. Forest management in the Blue Mountains: public perspectives on prescribed fire and mechanical thinning. Corvallis, OR: Oregon State

University, Department of Forest Resources. 57 p.

Shirley, D.M.; Erickson, V. 2001. Aspen restoration in the Blue Mountains of northeast

Oregon. In: Shepperd, W.D.; Binkley, D.; Bartos, D.L. [et al.], eds. Sustaining aspen

in Western landscapes: symposium proceedings. Fort Collins, CO: U.S. Department

of Agriculture, Forest Service, Rocky Mountain Research Station: 101-115.

Skovlin, J.M. 1967. Fluctuation in forage quality on summer range in the Blue Mountains. Res. Pap. PNW-44. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range Experiment Station. 20 p.

Skovlin, J.M. 1996. Interpreting landscape changes in the Blue Mountains of western

North America through repeat photography. In: West, N.E., ed. Rangelands in a sustainable biosphere. Proceedings of the 5th international rangeland congress. Denver,

CO: Society for Range Management: 521-522.

Skovlin, J.M.; Bryant, L.D.; Edgerton, P.J. 1989. Timber harvest affects elk distribution in the Blue Mountains of Oregon. Res. Pap. PNW-RP-415. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 10 p.

Skovlin, J.M.; Harris, R.W.; Strickler, G.S. [et al.]. 1976. Effects of cattle grazing

methods on the ponderosa pine-bunchgrass range in the Pacific Northwest. Tech.

Bull. 1531. [Place of publication unknown]: U.S. Department of Agriculture, Forest

Service. 40 p.
213

Skovlin, J.M.; Thomas, J.W. 1995. Interpreting long-term trends in Blue Mountain ecosystems from repeat photography. Gen. Tech. Rep. PNW-GTR-315. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station.

102 p.

Skovlin, J.M.; Vavra, M. 1979. Winter diets of elk and deer in the Blue Mountains,

Oregon. Res. Pap. PNW-260. Portland, OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Forest and Range Experiment Station. 21 p.

Smergut, T.A. 1991. Cardaria draba (L.) in the sagebrush ecosystem of northeastern

Oregon. Corvallis, OR: Oregon State University. 42 p. M.S. thesis.

Smith, A.K. 1975a. Fish and wildlife resources of the Grande Ronde basin, Oregon,

and their water requirements; federal aid to fish restoration project completion report.

Portland, OR: Oregon Department of Fish and Wildlife. 51 p.

Smith, G.W. 1975b. An ecological study of the porcupine (Erethizon dorsatum) in the

Umatilla National Forest, northeastern Oregon. Pullman, WA: Washington State

University. 101 p. M.A. thesis.

Smith, G.W. 1982. Habitat use by porcupines in a ponderosa pine/Douglas-fir forest in

northeastern Oregon. Northwest Science. 56(3): 236-240.

Sneva, F.A.; Hyder, D.N. 1962. Forecasting range herbage production in eastern

Oregon. Station Bull. 588. Portland, OR: Oregon State University, Agricultural Experiment Station. 11 p.

Snyder, J.W. 2001. Restoration of Columbian sharp-tailed grouse into northeastern Oregon. Corvallis, OR: Oregon State University. 131 p. Ph.D. dissertation.

Starr, L.; Hayes, J.L.; Quigley, T.M. [et al.]. 2001. A framework for addressing forest

health and productivity in eastern Oregon and Washington. Northwest Science.

75(Spec. issue): 1-10.

Starr, L.; Quigley, T.M., eds. 1992. Forest health in the Blue Mountains public forums,

April-June 1991. B 62/2. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Blue Mountains Natural Resources Institute.

84 p.

Steel, E.A. 1999. In-stream factors affecting juvenile chinook salmon migration. Seattle,

WA: University of Washington. 111 p. Ph.D. dissertation.

Svejcar, T.; Vavra, M. 1985a. Seasonal forage production and quality on four native and

improved plant communities in eastern Oregon. Tech. Bull. 149. Corvallis, OR: Oregon

State University, Agricultural Experiment Station. 24 p.

Svejcar, T.; Vavra, M. 1985b. The influence of several range improvements on estimated carrying capacity and potential beef production. Journal of Range Management. 38(5): 395-399.

Swetnam, T.W.; Wickman, B.E.; Paul, H.G. [et al.]. 1995. Historical patterns of western spruce budworm and Douglas-fir tussock moth outbreaks in the northern Blue

Mountains, Oregon since A.D. 1700. Res. Pap. PNW-RP-484. Portland, OR: U.S.

Department of Agriculture, Forest Service, Pacific Northwest Research Station. 27 p.
214

Tanaka, J.A.; Starr, L.; Quigley, T.M. 1995. Strategies and recommendations for addressing forest health issues in the Blue Mountains of Oregon and Washington. Gen.

Tech. Rep. PNW-GTR-350. Portland, OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station. 18 p.

Thies, W.G. 2001. Root diseases in eastern Oregon and Washington. Northwest Science. 75(Spec. issue): 38-45.

Thies, W.; Niwa, C. 2001. Interaction of various ecosystem components with prescribed

fires in ponderosa pine stands in the southern Blue Mountains. Phytopathology. 91(6

Supplement): S155-S156.

Thomas, J.W., tech. ed. 1979. Wildlife habitats in managed forests: the Blue Mountains of Oregon and Washington. Handb. 553. Washington, DC: Wildlife Management

Institute and U.S. Department of Agriculture, Forest Service. 512 p.

Thomas, J.W.; Leckenby, D.A.; Erickson, L.J. [et al.]. 1986. Wildlife habitat by design: national forests in the Blue Mountains of Oregon and Washington. In: Wildlife

Management Institute, ed. Transactions of the 51st North American Wildlife and Natural Resources Conference. Washington, DC: Wildlife Management Institute: 203-214.

Thomas, J.W.; Miller, R.J.; Black, H. [et al.]. 1976. Guidelines for maintaining and

enhancing wildlife habitat in forest management in the Blue Mountains of Oregon

and Washington. In: Proceedings: Transactions of the 41st North American wildlife

and natural resources conference. Washington, DC: Wildlife Management Institute:

452-476.

Tiedemann, A.R.; Klemmedson, J.O.; Bull, E.L. 2000. Solution of forest health problems with prescribed fire: Are forest productivity and wildlife at risk? Forest Ecology

and Management. 127(1-3): 1-18.

Tiedemann, A.R.; Quigley, T.M.; Anderson, T.D. 1988. Effects of timber harvest on

stream chemistry and dissolved nutrient losses in northeast Oregon. Forest Science.

34(2): 344-358.

Torgersen, C.E.; Price, D.M.; Li, H.W. [et al.]. 1999. Multiscale thermal refugia and

stream habitat associates of chinook salmon in northeastern Oregon. Ecological

Applications. 9(1): 301-319.

Torgersen, T.R. 2001. Defoliators in eastern Oregon and Washington. Northwest

Science. 75(Spec. issue): 11-20.

Torgersen, T.R.; Bull, E.L. 1995. Down logs as habitat for forest dwelling ants—the

primary prey of pileated woodpeckers in northeastern Oregon. Northwest Science.

69 (4): 294-303.

Trauba, W.C. 1975. Petrography of pre-tertiary rocks of the Blue Mountains, Umatilla

County, northeast Oregon. Corvallis, OR: Oregon State University. 171 p. M.S. thesis.

U.S. Army Corps of Engineers. 1999. Grande Ronde River stream restoration,

La Grande, Oregon: Grande Ronde Section 1135. Ecosystem restoration report

and environmental assessment. La Grande, OR. [Pages unknown].
215

U.S. Department of Agriculture, Forest Service. 1992a. Monitoring strategy plan,

appendix N- biological assessment. La Grande, OR: Wallowa-Whitman National

Forest, La Grande Ranger District. [Pages unknown].

U.S. Department of Agriculture, Forest Service. 1992b. Upper Grande Ronde River

anadromous fish habitat restoration and monitoring plan. Baker, OR: WallowaWhitman National Forest. [Pages unknown].

U.S. Department of Agriculture, Forest Service. 1994a. Biological assessment:

Upper Grande Ronde River (section 7). [Place of publication unknown]: WallowaWhitman National Forest, La Grande Ranger District; Umatilla National Forest, North

Fork John Day Ranger District; final report. [Irregular pagination].

U.S. Department of Agriculture, Forest Service. 1994b. Upper Grande Ronde watershed analysis report. La Grande, OR: Wallowa-Whitman National Forest. [Irregular

pagination].

U.S. Department of Agriculture, Forest Service. 1994c. Upper Grande Ronde conservation strategy for endangered Snake River spring/summer chinook salmon.

La Grande, OR: Wallowa-Whitman National Forest, La Grande Ranger District.

[Irregular pagination].

U.S. Department of Agriculture, Forest Service. 1998. Beaver Creek watershed

analysis. La Grande, OR: Wallowa-Whitman National Forest. [Irregular pagination].

U.S. Department of Agriculture, Forest Service. 2002. Meadow Creek watershed

analysis. La Grande, OR: Wallowa-Whitman National Forest, La Grande Ranger

District. [Irregular pagination].

U.S. Department of Agriculture, Natural Resources Conservation Service; U.S.

Department of Agriculture, Forest Service. 1996. Grande Ronde cooperative

river basin study for Union County. [La Grande, OR]. [Pages unknown]. Unpublished

report. On file with: Grande Ronde Model Watershed, 10901 Island City Ave.,

La Grande, OR 97850.

U.S. Department of Agriculture, Soil Conservation Service; Oregon State University Agricultural Experiment Station. 1985. Soil survey of Union County area,

Oregon. Washington, DC. 194 p.

U.S. Department of Energy, Bonneville Power Administration. 1997. Fish research

project—Oregon investigations into the early life history of naturally produced spring

chinook salmon in the Grande Ronde River basin: Bonneville Power Administration

annual report 1996. [Place of publication unknown]: [Pages unknown].

U.S. Department of the Interior, Bureau of Land Management, Baker Resource

Area Office. 1993. Wallowa and Grande Ronde Rivers: final management plan/environmental assessment. Washington, DC. [196 p.].

U.S. Department of the Interior, Bureau of Land Management; U.S. Department

of Agriculture, Forest Service. 1990. Resource assessment: Grande Ronde River,

National Wild and Scenic River. [Baker, OR]: BLM, Vale District and WallowaWhitman National Forest. 47 p.
216

U.S. Department of the Interior, Bureau of Reclamation. 1982. Baker project:

Oregon, Baker and Union Counties. [Washington, DC]: [The Pacific Northwest

Region]. 6 p.

U.S. Department of the Interior, Geological Survey. 1989. Water resources data,

Oregon, water year 1988. Vol. 1. Eastern Oregon. [Place of publication unknown].

[Pages unknown].

U.S. Department of the Interior, Geological Survey. 1996. Geology of the Blue

Mountains region of Oregon, Idaho, and Washington: petrology and tectonic evolution

of pre-tertiary rocks of the Blue Mountains Region. [Place of publication unknown].

[Pages unknown].

Union Soil and Water Conservation District. 1995. Grande Ronde River basin study:

abstracts. La Grande, OR. [Pages unknown].

Union Soil and Water Conservation District. 1999. Upper Grande Ronde River

subbasin local agricultural water quality advisory committee—Upper Grande Ronde

River subbasin agricultural water quality management area plan. La Grande, OR.

[Pages unknown].

Van Cleve, R.; Ting, R. 1960. The condition of salmon stocks in the John Day,

Umatilla, Walla Walla, Grande Ronde and Imnaha Rivers as reported by various

fisheries agencies. Seattle, WA: University of Washington. 83 p.

Vavra, M.; Phillips, R.L. 1979. Diet quality and cattle performance on forested rangeland in northeastern Oregon. Proceedings, Western Section, American Society of

Animal Science. 30: 170-173.

Vavra, M.; Phillips, R.L. 1980. Drought effects on cattle performance, diet quality

and intake. Proceedings,Western Section, American Society of Animal Science.

31: 157-160 .

Wales, B.C. 2001. The management of insects, diseases, fire, and grazing and

implications for terrestrial vertebrates using riparian habitats in eastern Oregon

and Washington. Northwest Science. 75(Spec. issue): 119-127.

Walters, T.R.; Carmicheal, R.W.; Keefe, M. 1994. Smolt migration characteristics

and mainstem Snake and Columbia River detection rates of PIT-tagged Grande Ronde

and Imnaha River naturally produced spring chinook salmon: annual progress report.

Portland, OR: Oregon Department of Fish and Wildlife. [Pages unknown].

Watershed Sciences, LLC. 2000. Remote sensing survey of the Grande Ronde River

basin, thermal infrared and color videography; final report prepared for Oregon Department of Environmental Quality. Corvallis, OR. 49 p.

Wellman, R.E.; Gordon, J.M.; Moffat, R.L. 1993. Statistical summaries of streamflow

data in Oregon: Vol. 2—Annual low and high flow, and instantaneous peak flow. Open

File Report 93-63. Portland, OR: U.S. Department of the Interior, Geological Survey.

[Pages unknown].

Wells, G.R. 1975. A sensitivity analysis of simulated river basin planning for capital

budgeting decsions. Computer Operations and Research. 2(1): 49-54.
217

White, R.G.; Milligan, J.H.; Bingham, A.E. [et al.]. 1981. Effects of reduced stream

discharge on fish and aquatic macroinvertebrate populations. OWRT B-045-IDA(1)

14-34-0001-8080. Springfield, VA: National Technical Information Service. 283 p.

Whitney, L. 1999. Grande Ronde Section 319 national monitoring program project, temperature monitoring summary report, 1993-1998. Portland, OR: Oregon Department of

Environmental Quality. [Pages unknown].

Wickman, B.E. 1976 . Douglas-fir tussock moth egg hatch and larval development in

relation to phenology of grand fir and Douglas-fir in northeastern Oregon. Res. Pap.

PNW-206. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Forest and Range Experiment Station. 13 p.

Wickman, B.E. 1978. Tree mortality and top kill related to defoliation by the Douglas-fir

tussock moth in the Blue Mountains outbreak. Res. Pap. PNW-233. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Forest and Range

Experiment Station. 47 p.

Wickman, B.E. 1986. Radial growth of grand fir and Douglas-fir 10 years after defoliation

by the Douglas-fir tussock moth in the Blue Mountain outbreak. Res. Pap. PNW-367.

Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 11 p.

Wickman, B.E. 1988. Seasonal variation of degree-day accumulation in relation to

phenology of western spruce budworm, Douglas-fir tussock moth, and host trees in

northeastern Oregon. Res. Note PNW-RN-482. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research Station. 11 p.

Wickman, B.E. 1992. Forest health in the Blue Mountains: the influence of insects and

diseases. Forest health in the Blue Mountains: science perspectives. Gen. Tech.

Rep. PNW-GTR-295. Portland, OR: U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 15 p. (Quigley, T.M., ed.; Forest health in the

Blue Mountains: the influence of insects and disease).

Wickman, B.E.; Henshaw, D.L.; Gollob, S.K. 1980. Radial growth in grand fir and

Douglas-fir related to defoliation by the Douglas-fir tussock moth in the Blue Mountains outbreak. Res. Pap. PNW-269. Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Forest and Range Experiment Station. 23 p.

Widner, G.L. 1991. Summer low flow characteristics of forest streams in northeast

Oregon. Corvallis, OR: Oregon State University. 93 p. M.S. thesis.

Williams, J.D. 1988. Overland flow and sediment production potentials in logged and

nonlogged sites of a ponderosa pine forest in northeastern Oregon. Corvallis, OR:

Oregon State University. 108 p. M.S. thesis.

Williams, M. 2000. Putting ‘flesh on the carbon-based bones’ of forest history. In:

Agnoletti, M.; Anderson, S., eds. Methods and approaches in forest history.

Wallingford, United Kingdom: CABI Publishing: 35-46.

Williams, W.R. 1976. The economic impact of Douglas-fir tussock moth on private

recreation businesses in northeastern Oregon. Corvallis, OR: Oregon State University.

73 p. M.S. thesis.
218

Williamson, N.M. 1999. Crown fuel characteristics, stand structure, and fire hazard

in riparian forests of the Blue Mountains, Oregon. Seattle, WA: University of

Washington. 98 p. M.S. thesis.

Wilson, D.; Maguire, D.; Ager, A. 2001. Effects of forest planning regulations on

potential small diameter timber harvest from overstocked stands on the Umatillla

National Forest. Misc. Rep. Pendleton, OR: U.S. Department of Agriculture, Forest

Service, Umatilla National Forest. [Pages unknown].

Wissmar, R.C.; Smith, J.E.; McIntosh, B.A. [et al.]. 1994a. A history of resource use

and disturbance in riverine basins of eastern Oregon and Washington (early 1800s1900s). Northwest Science. 68(Spec. issue): 1-35.

Wissmar, R.C.; Smith, J.E.; McIntosh, B.A. [et al.]. 1994b. Ecological health of river

basins in forested regions of eastern Washington and Oregon. Gen. Tech. Rep. PNWGTR-326. [Portland, OR]: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 65 p. (Everett, R.L., assessment team leader, Eastside

forest ecosystem health assessment; Hessburg, P.F., science team leader and tech.

ed., Volume III: assessment).

Womack, B. 1982. Prehistoric settlement patterns in the Crow and Elk Creek drainages

Wallowa-Whitman National Forest, northeastern Oregon, USA. Northwest Anthropological Research Notes. 15(2): 220.

Wondzell, S. 2001. The influence of forest health and protection treatments on erosion

and stream sedimentation in forested watersheds of eastern Oregon and Washington.

Northwest Science. 75(Spec. issue): 128-140.

Wood, B.W. 1971. Response of Canada milkvetch (Astragalus canadensis var. mortonii

(Nutt.) Wats.) to range and forest improvement practices in northeastern Oregon.

Corvallis, OR: Oregon State University. 166 p. Ph.D. dissertation.

Youngblood, A. 2000. Damage to residual trees and advance regeneration from

skyline and forwarder yarding in mixed-conifer stands of northeastern Oregon. Western Journal of Applied Forestry. 15(2): 101-107.

Youngblood, A. 2001. Old-growth forest structure in eastern Oregon and Washington.

Northwest Science. 75(Spec. issue): 110-118.

Youngblood, A.; Wickman, B.E. 2002. The role of disturbance in creating dead wood:

insect defoliation and tree mortality in northeastern Oregon. In: Laudenslayer, W.F.,

Jr.; Shea, P.J.; Valentine, B.E. [et al.], tech. coords. Proceedings of the symposium

on the ecology and management of dead wood in Western forests. Gen. Tech. Rep.

PSW-GTR-181. Albany, CA: U.S. Department of Agriculture, Forest Service, Pacific

Southwest Research Station: 155-168.

Zack, R.S.; Davis, E.J.; Raffa, K. 1979. A new host record and notes on Nosodendron

californicum Horn (Coleoptera: Nosodendridae). Coleopterists Bulletin. 33(1): 74.
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