United States

Department of

Agriculture

Forest Service

Pacific Northwest

Research Station

General Technical

Report

PNW-GTR-596

January 2004

Proceedings: Views From the

Ridge—Considerations for

Planning at the Landscape Scale
Compilers

Hermann Gucinski (retired) was a physical scientist, Forestry Sciences Laboratory, 3200 SW Jefferson

Way, Corvallis, OR 97331; Cynthia Miner is a general biologist and Becky Bittner is a forester, Pacific

Northwest Research Station, 333 SW First Avenue, Portland, OR 97208-3890.

Papers were presented at a conference by the authors, who are therefore responsible for the content and

accuracy. Opinions expressed may not necessarily reflect the position of the U.S. Department of

Agriculture.

The use of trade, firm, or corporation names in this publication is for the information and convenience of

the reader. Such use does not constitute an official endorsement or approval by the U.S. Department of

Agriculture of any product or service to the exclusion of others that may be suitable.

Photo credits

Top photo taken by Roger Clark, bottom left to right Kevin Burke, Roger Clark
Proceedings: Views From the Ridge—Considerations for Planning at the

Landscape Scale

Hermann Gucinski, Cynthia Miner, and Becky Bittner

Editors

Views From the Ridge—Considerations for Planning at the Landscape Scale,

Vancouver, WA, November 2-4, 1999

Sponsored by:

Pacific Northwest Research Station, USDA Forest Service

Western Forestry and Conservation Association

U.S. Department of Agriculture

Forest Service

Pacific Northwest Research Station

Portland, Oregon

General Technical Report PNW-GTR-596

January 2004
Abstract

Gucinski, Hermann; Miner, Cynthia; Bittner, Becky, eds. 2004. Proceedings: views from the ridge—

considerations for planning at the landscape scale. Gen. Tech. Rep. PNW-GTR-596. Portland, OR:

U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station. 133 p.

When resource managers, researchers, and policymakers approach landscape management, they bring

perspectives that reflect their disciplines, the decisions they make, and their objectives. In working at a

landscape level, they need to begin developing some common scales of perspective across the variety of

forest ownerships and usages. This proceedings is a compilation of 22 papers presented at a conference

that addressed divergent views on landscape management. The conference was a forum for exchanging

concepts and knowledge from research and management experiences about managing landscapes. The

program addressed the issues of managing landscapes when everyone has a different perspective;

approaching landscape management from aquatic, terrestrial, and socioeconomic viewpoints; and

characterizing landscape management.

Keywords: Landscape management, forest policy, forest management, aquatic, terrestrial,

socioeconomic.
Contents

1 Introduction

Hermann Gucinski

Conference Overview

5 From Red Queens to Mad Hatters—A Wonderland of Natural Resource Management

Lance Gunderson

11 What Is a Landscape and How Is One Studied?

Virginia H. Dale and Barry R. Noon

How Do We Determine Scale?

17 Landscapes: The Dilemma of Scale and the Role of Theory

Lee Benda and Daniel Miller

22 Scale Considerations for Linking Hillslopes to Aquatic Habitats

Robert R. Ziemer

33 Landscape Assessment in a Multiownership Province

Thomas A. Spies

38 Implications of Scale on Viability Assessments of Terrestrial Wildlife Species

Martin G. Raphael

42 Projecting Potential Landscape Dynamics: Issues and Challenges

Ronald P. Neilson

48 Scaling and Landscape Dynamics in Northern Ecosystems

Marilyn Walker

57 Landscape Perspectives

Roger N. Clark, Linda E. Kruger, Stephen F. McCool, and George H. Stankey

61 Landscape-Level Management, It’s All About Context

Bruce Shindler

62 Human Adaptation to Environmental Change: Implications at Multiple Scales

Ellen M. Donoghue, Terry L. Raettig, and Harriet H. Christensen

67 Land Use and Land Cover Dynamics: Changes in Landscapes Across Space and Time

Ralph J. Alig

Worldviews Panel

75 Private Landowner Perspective on Landscape Management

Carl F. Ehlen

78 Back to the Future: The Value of History in Understanding and Managing Dynamic

Landscapes

Penelope Morgan
Case Studies

87 Northwest Forest Plan

Nancy M. Diaz

93 Recent Changes (1930s-1990s) in Spatial Patterns of Interior Northwest Forests, USA

P.F. Hessburg, B.G. Smith, R.B. Salter, R.D. Ottmar, and E. Alvarado

Landscape Methodology

95 Analysis and Communication of Monitoring Data With Knowledge-Based Systems

Keith M. Reynolds and Gordon H. Reeves

105 Seeing the Forest and the Trees: Visualizing Stand and Landscape Conditions

Robert J. McGaughey

110 A Method to Simulate the Volume and Quality of Wood Produced Under an Ecologically

Sustainable Landscape Management Plan

Glenn Christensen, R. James Barbour, and Stuart Johnston

Transforming Information From Many Perspectives to Action on the Ground

119 A Social Science Perspective on the Importance of Scale

Linda E. Kruger

Conclusion

127 Summary Remarks on Views From the Ridge

T.F.H. Allen

130 The Future of Landscape-Level Research at the Pacific Northwest Research Station

Thomas J. Mills
1

Fred Swanson, a scientist who has devoted much

of his career to the study of the processes that

affect the character of a landscape, was asked

while leading a tour of the H.J. Andrews Experimental Forest in Oregon with the group poised

atop a commanding ridge, “Well, just what is a

good landscape?”

As a scientist committed to expanding knowledge

rather than to just citing known facts, he took this

question as a serious challenge, admitted to finding it perplexing, and used it in turn to engender

deep discussion, and some introspection, around

the campfire that evening.

Before we can use the same question as a framework for the contributions in this volume, it might

be good to ask: “What is a landscape?” and, because this is a scientific endeavor, “What is landscape ecology, and how might it contribute toward

the larger question?” For it was indeed the objective of the symposium, and the proceedings that

resulted, to take the “View From the Ridge” as a

scientific challenge, rather than a subjective one,

and to try to learn if a scientifically framed answer

can also help with the subjective part of the

needed answer.

Webster’s unabridged dictionary and the Oxford

English Dictionary have similar definitions: “a portion of land or territory, which the eye can comprehend in a single view, including all the objects so

seen” for the former, and “a view or prospect of

natural in-land scenery, such as can be taken in

at a glance from one point of view; a piece of

country scenery” for the latter. Both offer some

additional definitions: “a tract of land with its distinguishing characteristics and features, esp.

considered as a product of modifying or shaping

processes and agents (usually natural)”—“a view,

prospect of something”—“a distant prospect: a

vista,”—“a bird’s-eye view; a plan, sketch, map.”

Thus, our title, “Views From the Ridge” is appropriate, although one contributor, Bob Ziemer,

astutely notes that a “view from space” would

provide a yet larger prospect (“Vogelschau”

[bird’s-eye view] may be the most apropos German word for this), whereas “a view from the valley” would help discern the delivery of results from

upland processes when taking an aquatic or riparian perspective.

These processes, the delivery of mass and energy, among others, bring us to the scientific part

of the inquiry—the appropriate subject of “landscape ecology.” Richard T.T. Forman and Michael

Godron (1986) used this definition in their seminal

work:

Landscape ecology is the study of structure, function and change in a heterogeneous land area composed of interacting

ecosystems. It therefore focuses on:

• structure, the spatial patterns of landscape elements and ecological objects

(such as animals, biomass and mineral

nutrients);

• function, the flows of objects between

landscape elements; and

• change, alterations in the mosaic through

time.

Monica Turner (1989) defines it thus:

Landscape ecology emphasizes the interaction between spatial pattern and ecological process—that is, the causes and

consequences of spatial heterogeneity

across a range of scales. Two important

aspects of landscape ecology distinguish it

from other subdisciplines within ecology.

First, landscape ecology explicitly addresses the importance of spatial configuration for ecological processes. Not only is

landscape ecology concerned with how

much there is of a particular component

but also with how it is arranged. Second,

landscape ecology often focuses upon

spatial extents that are much larger than

those traditionally studied in ecology.

1

Physical scientist (retired) Forestry Sciences Laboratory,

3200 SW Jefferson Way, Corvallis, OR 97331.

Introduction

Hermann Gucinski1
2

The following papers show the interest focused on

the importance of spatial configuration for an ecological process and will demonstrate the astonishing variety of both viewpoints and scales used to

address problems. This shows the science to be

evolving and is a sign of the value placed on problems in this area. A brief look at the history of forestry science shows its earliest endeavors, silviculture and entomology, to be largely driven by

stand-scale processes. Problems were considered solvable at that scale. Not only that, but the

nature of the problem and suggested solutions

were seen as largely separable. You isolated each

variable, and treatments of that variable were

based on the discipline within which it fell.

Although this is oversimplified, earlier scientific

endeavors engendered the separation of the disciplines and slowed understanding of the interdependence of ecological processes. “If all you have

is a hammer, every problem will begin to resemble a nail.” This approach worked for a long

time.

Many phenomena contributed to the expanding

view of ecological processes. We recognized that

the accumulation and translocation of long-lived

pollutants required a comprehensive look at biological, hydrological, and atmospheric processes.

So did the need to develop concepts of “carrying

capacity” as the pressures of nonsustainable resource use—hastened by population growth—

brought conditions that could no longer be

described or understood at stand levels. This

development challenged resource managers to

abandon linear approaches to management—

ecological processes are cyclical in nature, and

evolutionary development has allowed highly integrated system functioning that produces no

waste. Superimposing solutions based on linear

thinking caused new problems to pop up in places

outside the scientific discipline where the original

problem first appeared. Addressing the consequences resulted in yet other problems, leading to

a vicious circle of “stimulus-response.”

That dynamic can be broken by moving up in

scale from the domain of the initial problem, seeking to understand the connections while standing

on the ridge—or, alternatively, in the valley. This

can help us regain perspective, and find pathways

to solutions. Dale and Noon tackle this by relating

the view from the ridge to a quite specific ridge,

namely Oak Ridge, site of the Oak Ridge National

Laboratory and its rich history of contributions to

landscape ecology. Today’s efforts are enhanced

by better tools and methods, as Spies notes in

his contribution, and they also require looking

beyond political boundaries such as ownerships.

McGaughey introduces us to valuable visualization tools now available to permit examination of

landscape “treatment” scenarios. Raphael argues

that being able to hold onto all scales is a necessity when considering the problem of “viability” of

a species that is threatened. Clark et al. wrestle

with the subjective components of a landscape as

they relate to the values that people assign to it.

And, as Shindler reminds us, right up to the

present, our decisions have almost always been

made at the stand level. Morgan expands our

vista to not only view a landscape in space, but

become aware of it over time such as a knowledge of history permits. Here the concept of “historical range of variation” can be a vital tool.

Benda and Miller take landscape processes under

the lens, focusing on the differences between

stochastic and deterministic processes. Confusing these can have disastrous consequences.

Neilson reminds us of the nature of “emergent

properties” when going to a larger scale, and uses

climate response as a useful integrator for these

processes.

The intent here is not to give away the principal

theses and conclusions of each contributor. Instead, I want to whet the appetite of the reader,

convey the breadth and depth that are contained

in this volume, reflect on the variability of the approaches outlined, and weigh their implications.

Finally, I hope the information given and the challenges raised will encourage the reader to rethink

the question, “What is a good landscape?” in light

of available science as it illuminates the subjective

needs we have.

Literature Cited

Forman, R.T.T.; Godron, M. 1986. Landscape

ecology. New York: John Wiley and Sons.

Turner, M.G. 1989. Landscape ecology: the effect

of pattern on process. Annual Review of Ecology and Systematics. 20: 171-191.
3
4

Conference Overview
5

Lewis Carroll (1899) created a number of memorable characters who appear and reappear

throughout the adventures of Alice in Wonderland.

A few of these characters highlight and resonate

with my sense and experience of the kinds of

issues faced by resource managers. Just as Alice

is bewildered by the complexities and uncertainties of Wonderland, managers often face similar

issues of sensemaking and coping with the inevitable surprises of complex systems of humans

and nature. In the following sections, I use these

rich characters from Wonderland as an entree

into a set of topics that will hopefully stimulate

some ideas related to the paradigms that underlie

our management of natural resources at the landscape scale, beginning with the Red Queen.

Red Queens and Other Caricatures

“Well, in our country,” said Alice, still panting a little, “you’d generally get to somewhere else—if you ran very fast for a long

time, as we’ve been doing.”

“A slow sort of country!” said the Queen.

“Now, here, you see, it takes all the running you can do, to keep in the same

place. If you want to get somewhere else,

you must run at least twice as fast as

that!”

........Lewis Carroll

The Red Queen’s action depicted in this scene is

often used as a metaphor by evolutionary biologists to describe whether species can adapt to

rapidly changing environments. I see similar “Red

Queen dilemmas” as practitioners work as fast

as they can to cope with rapidly and unpredictably

changing systems. This metaphor can be extended to include a wider set of assumptions or

myths that help to explain how nature operates.

Each of these myths has a different supposition of

how stable systems are (in the sense of responding to perturbations over time), the types of processes that support that stability domain, consequences of those assumptions, and explanations

for policy and action. At least five such caricatures

are described in the following paragraphs (modified from Holling and Gunderson 2002).

Nature Flat

Although this perception is perhaps so simplistic

as to be silly, it is included here as a starting point

from which subsequent contrasts with other views

can be made. In this view, the word “flat” is used

to describe a system in which there is little or no

stability of structure over time. The hands of

humans, given sufficient resources can change

nature, and there are no feedbacks or consequences of those actions—it is much like rolling a

ball around on a cookie sheet. The processes that

affect the state of nature are random or stochastic. In such a view of nature, policies and politics

are random as well, often described as garbage

can dynamics (March and Olsen 1989). It is a

nature that is infinitely malleable and amenable to

human domination. As such, the issues of resource use, development, or control are identified

as issues of people and resolved by activism or

community organization.

Nature Balanced

The second is a view of nature at or near an equilibrium condition, which can be static or dynamic.

Hence if nature is disturbed, it will return to an

equilibrium through (in systems terms) negative

feedback. As such, nature seems to be infinitely

forgiving. This is the view of nature that underpins

logistic growth where the issue is how to navigate

a looming and turbulent transition—demographic,

economic, social, and environmental—to a sustained plateau. This is the view of several institutions with a mandate for reforming global resource and environmental policy: the Brundtland

Commission (Brundtland and Khalid 1987), the

World Resources Institute, the International Institute of Applied Systems Analysis (Clark and Munn

1986), and the United Nations (Munasinghe and

McNeely 1995) for example, who are contributing

From Red Queens to Mad Hatters—A Wonderland of Natural

Resource Management

Lance Gunderson1

1

Associate professor and Chair, Department of Environmental

Studies, Emory University, Atlanta, GA 30322; Tel: 404-727-

2429; e-mail: lgunder@emory.edu
6

skillful scholarship and policy innovation. They are

among some of the most effective forces for

change.

Nature Anarchic

If the previous myth is one where the system stability is defined as a ball at the bottom of a cup,

this myth is one of a ball at the top of a hill. It is

globally unstable. It is a view dominated by hyperbolic processes of growth and collapse, or where

increase is inevitably followed by decrease. It is a

view of fundamental instability where persistence

is only possible in a decentralized system with

minimal demands on nature. It is the view of

some extreme environmentalists. If the previous

view assumes that infinitely ingenious humans do

not need to learn anything different, this view assumes that humans are incapable of learning.

This is implicit in the writings of Tenner (1996),

where he argues that all technology that is unleashed will eventually “bite back.” This view presumes that small is beautiful because of the

inevitable catastrophe of any policy. It is a view

where the precautionary principle dominates

policy, and social activity is focussed on maintenance of the status quo.

Nature Resilient

The fourth view is of nested cycles organized by

fundamentally discontinuous events and processes. That is, there are periods of exponential

change, periods of growing stasis and brittleness,

periods of readjustment or collapse, and periods

of reorganization for renewal. Instabilities organize

the behaviors as much as do stabilities. This has

recently been the focus of fruitful scholarship in a

wide range of fields—ecological, social, economic, and technical. These dynamics have similarities in Harvey Brook’s view of technology

(1986), Brian Arthur’s and Kenneth Arrow’s recent

views of the economics of innovation and competition (Waldrop 1992), Mary Douglas’ (1978) and

Mike Thompson’s (1983) views of cultures, Don

Michael’s view of human psychology (1984), and

Barbara Tuchman’s (1978) and William McNeill’s

(1979) views of history. The “nature resilient” view

is a view of multiple stable states in ecosystems,

and management approaches that are adaptive.

But both of these presume a stationary landscape. In this case, our cookie sheet has been

molded and curved in three dimensions, but it is

fixed over time.

Nature Evolving

The emerging fifth view is evolutionary and adaptive. It has been given recent impetus by the paradoxes that have emerged in successfully applying

the previous more limited views. Complex systems behavior, discontinuous change, chaos and

order, self-organization, nonlinear system behavior, and adaptive evolving systems are all the

present code words characterizing the more recent activities. Such thinking is leading to integrative studies that combine insights and people from

developmental biology and genetics, evolutionary

biology, physics, economics, ecology, and computer science. It is a view of an actively shifting

landscape with self-organization (where the stability of the landscape affects behavior of the variables, and the variables, plus exogenous events,

affect the stability of the landscape). It is a view of

cross-scale interactions of processes–dubbed

panarchy in previous writings (Gunderson et. al.

1995, Holling and Gunderson 2002). It is a view

that requires a focus on active policy probes of a

shifting domain and a focus on institutional and

political flexibility for learning.

Comparing and contrasting these underlying caricatures or worldviews, provides some insight into

how we create our wonderlands in order to make

prescriptions for action. It is also useful to note

how these partial myths are adopted and reinforced and prescribed by a variety of disciplines,

as described in the next section, organized

around Mad Hatters of various disciplines.

Disciplinarily Mad Hatters

Alice had been looking over his shoulder

with some curiosity. “What a funny watch!”

she remarked. “It tells the day of the

month, and doesn’t tell what o’clock it is!”

“Why should it?” muttered the Hatter.

“Does YOUR watch tell you what year it

is?”
7

“Of course not,” Alice replied very readily,

“but that’s because it stays the same year

for such a long time together.”

“Which is just the case with MINE,” said

the Hatter.

Alice felt dreadfully puzzled. The Hatter’s

remark seemed to have no sort of meaning in it, and yet it was certainly English. ”I

don’t quite understand you,” she said, as

politely as she could.

........L. Carroll

The Mad Hatter utters seemingly nonsensical

questions and answers in his dialogues with Alice

at the tea party. He reminds me of those of us

who are technically or scholarly oriented, the educated skeptics who pay attention to different indicators, have different frames of reference and

different interpretations and understandings. As

with the Mad Hatter, in attempting to communicate our technical understanding to policymakers

or decisionmakers, more often than not, we are

politely misunderstood. And all of us are like the

Hatter in that we wear our disciplinary hats

proudly—whether as ecologist, biologist, political

scientist, economist, or any other scholarly categorization. Yet there is a growing sense that

these discipline-based organizations of inquiry

and understanding are problematic.

Management of global and regional resources is

not an ecological problem, nor an economic one,

nor a social one. It is a combination of all three.

And yet actions to integrate all three inevitably

shortchange one or more. Sustainable designs

driven by conservation interests ignore the needs

for an adaptive form of economic development

that emphasizes enterprise and flexibility. Those

driven by economic and industrial interests act as

if the uncertainty of nature can be replaced with

human engineering and management controls, or

ignored altogether. Those driven by social interests act as if community development and empowerment of individuals hold the key and there

are no limits to the imagination and initiative of

local groups. As investments fail, the policies of

government, private foundations, international

agencies, and nongovernmental organizations flip

from emphasizing one kind of myopic solution to

another. Over the last three decades, such policies have flipped from large investment schemes,

to narrow conservation ones to, at present,

equally narrow community development ones.

Each one builds their efforts on theory, although

many would deny anything but the most pragmatic

and nontheoretical foundations. The conservationists depend on theories of ecology and evolution,

the developers on variants of free market models,

the community activists on theories of community

and social organization. All these theories are

correct in the sense of being partially tested and

credible representations of one part of reality. The

problem is that they are partial. That partiality of

concepts leads to the search for theories of

change that bridge disciplines in rich ways.

One such integrated theory is Holling’s (1992)

adaptive cycle. The heuristic combines ecological

theories of succession and ecosystem development with other concepts of stability and resilience. It is a rich framework to indicate how

natural capital and connectivity of systems increase slowly over time. But those properties lead

to an increasing vulnerability and inevitable periods of destruction and reorganization. Authors

have used this framework to explain co-evolution

of resources and management through time

(Light et al. 1995), business and organizational

dynamics (Westley 1995), and political systems

(Holling and Sanderson 1996).

The above excerpt from the tea party, in which

Alice and the Mad Hatter discuss differences in

their watches, also suggests to me that one of the

key challenges that resource managers face is

overcoming obstacles of scale. Those obstacles

are both theoretical and practical. How managers

attempt to analyze and learn from their actions

are both related to issues of scale. Most models

and modes of inquiry are scale bound and dependent. Walters (1997) cites the cross-scale problem as a severe obstacle in most assessment/

modeling activities. Development of new theories

is needed to help address ecosystem and natural

resource dynamics across space and time scales.

Over the last 40 years, time and space have been

separated for analytical purposes. Most field ecologic investigations either freeze space and experiment over time or freeze time and look at

spatial patterns (witness the explosion and ubiquity of geographic information system technology

in resource management agencies). Perhaps

there are practical reasons for this pattern, but it

also can be explained in part because of underlying theoretical frameworks. There is a growing
8

sense that this separable-dimension framework

results in assessments with different outputs, suggesting the need for integration and reconciliation.

Through The Looking Glass and What

Alice Found There

For some minutes Alice stood without

speaking, looking out in all directions over

the country—and a most curious country it

was. There were a number of little brooks

running across from side to side, and the

ground between was divided up into

squares by a number of hedges, that

reached from brook to brook.

“I declare it’s marked out just like a large

chessboard!” Alice said at last. “There

ought to be some men moving about

somewhere—and so there are!” she

added in a tone of delight, and her heart

began to beat quick with excitement as

she went on. “It’s a great game of chess

that’s being played all over the world—if

this is the world at all, you know. Oh, what

fun it is!

........L. Carroll

One of the enduring and endearing aspects of the

Alice in Wonderland stories is that she faces an

uncertain world (from the nightmarish to the sublime) with hope and wonder. For some who deal

with issues of natural resource management,

there is only doubt and gloom. However, I tend to

agree with Alice, and I suggest that there is reason to hope. But that hope is founded on developing and creating new ways to think about and

manage issues of the environment.

Perhaps it is time to rethink the paradigms or

foundations of resource management institutions,

and place more emphasis on development of

sustaining foundations for dealing with complex

resource issues. Learning is a long-term proposition that requires a ballast against short-term politics and objectives. Another shift likely will require

a change in the focus of actions away from management by objectives and determination of

optimum policies toward new ways to define, understand, and manage these systems in an everchanging world. That focus should not be solely

on variables of the moment (water levels, population numbers) and their correlative rates, but

rather on more enduring system properties such

as resilience, adaptive capacity, and renewal capability. Indirectly, these system properties have

been explored in large complex ecosystems

such as the Grand Canyon (Walters 1997), the

Columbia River basin (Volkmann and McConnaha

1993), and the Everglades (Gunderson 1999). A

resilience or adaptive capacity framework involves

both the human components of the system (operations, rules, policies, and laws) and the biophysical components of the landscape and its

ecosystems. The shift of focus to a learning basis

is likely to require flexible linkages with a broader

set of actors, or network. Another way of saying

this bluntly is, until management institutions are

able and willing to embrace uncertainty and systematically learn from their actions and respond to

that learning, adaptive management will not continue in its original context, but rather be redefined

in a weak context of “flexibility in decisionmaking”

(Gunderson 1999).

But what does it take to be hopeful in a world that

is perhaps becoming much more unforgiving? As

the degree of human impact continues to increase

in scale, a key unanswered question is whether

the adaptive capacity of both ecologic and social

systems can keep pace with this expanding human footprint. Under those conditions, the prescription for facilitating constructive change

appears to be:

• Identify and reduce destructive constraints and

inhibitions on ecological change, such as perverse subsidies (e.g., sugar farming in the

Everglades).

• Protect and preserve the accumulated experience on which change will be based (such as

managers in land management agencies with

multiple decades of experience).

• Stimulate innovation in a variety of fail-safe

experiments that probe possible directions in

ways that are low in costs for people’s careers

and organizations’ budgets (such as adaptive

policies in the Grand Canyon).

• Encourage new foundations for renewal that

build and sustain the capacity of people,

economies, and nature for dealing with

change.
9

These suggestions are founded on the premise

that we must learn our way into an uncertain future. That learning should help guide deliberations

toward workable and sustainable futures. Those

deliberations will not solve all social or distributional issues, but rather might help frame ways to

work through this wonderland of resource management—we don’t have the luxury of awakening

and realizing that it may have been a dream.

Acknowledgments

This is a contribution from the Resilience Network, funded by a grant from the John D. and

Catherine T. MacArthur Foundation. Buzz Holling

continues to inspire creative and novel approaches to resource management.

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Brooks, H. 1986. The typology of surprises in

technology, institutions and development. In:

Clark, W.C.; Munn, R.E., eds. Sustainable

development of the biosphere. Cambridge,

United Kingdom: Cambridge University Press:

325-348.

Brundtland, G.H.; Khalid, M., eds. 1987. Our

common future. Oxford, United Kingdom: Oxford University Press.

Carroll, L. 1899. Through the looking glass and

what Alice found there. New York; London:

Macmillan and Co., Ltd.

Clark, W.C.; Munn, R.E., eds. 1986. Sustainable

development of the biosphere. Cambridge,

United Kingdom: Cambridge University Press.

Douglas, M. 1978. Cultural bias. Royal Anthropological Institute. [Publisher and location unknown.]

Gunderson, L. 1999. Resilience, flexibility and

adaptive management—antidotes for spurious

certitude? Conservation Ecology. 3(1): 7.

http://www.consecol.org/vol3/iss1/art7.

(10 November 2003).

Gunderson, L.; Holling, C.S.; Light, S.S., eds.

1995. Barriers and bridges for the renewal of

ecosystems and institutions. New York: Columbia University Press.

Holling, C.S. 1992. Cross-scale morphology,

geometry and dynamics of ecosystems. Ecological Monographs. 62(4): 447-502.

Holling, C.S.; Gunderson, L.H. 2002. Panarchy,

understanding transformations in systems of

humans and nature. Washington, DC: Island

Press.

Holling, C.S.; Sanderson, S. 1996. Dynamics of

(dis)harmony in ecological and social systems.

In: Hanna, S., ed. Rights to nature. Washington DC: Island Press: 57-85.

Light, S.S.; Gunderson, L.H.; Holling, C.S.

1995. The Everglades: evolution of management in a turbulent ecosystem. In: Light, S.S.;

Gunderson, L.H; Holling, C.S. eds. Barriers

and bridges to the renewal of ecosystems and

institutions. New York: Columbia University

Press: 103-168.

March, J.G.; Olsen, J.P. 1989. Rediscovering

institutions. New York: Free Press.

McNeill, W.H. 1979. The human condition: an

ecological and historical view. Princeton, NJ:

Princeton University Press.

Michael, D.N. 1984. Reason’s shadow: notes on

the psychodynamics of obstruction. Technical

Forecasting and Social Change. 26(2): 149-

153.

Munasinghe, M.; McNeely, J. 1995. Key concepts and terminology of sustainable development. In: Munasinghe, M; Shearer, W., eds.

Defining and measuring sustainability: the

biogeophysical foundations. Washington DC:

World Bank: 19-56.

Tenner, E. 1996. Why things bite back: technology and the revenge of unintended consequences. New York: Knopf.
10

Thompson, M. 1983. A cultural bias for comparison. In: Kunreuther, H.C.; Linnerooth, J. Risk

analysis and decison processes: the siting of

liquid energy facilities in four countries. Berlin:

Springer: 232-262.

Tuchman, B.W. 1978. A distant mirror. New York:

Ballantine.

Volkman, J.M.; McConnaha, W.E. 1993.

Through a glass, darkly: Columbia River

salmon, the Endangered Species Act, and

adapative management. Environmental Law.

23: 1249-1272.

Waldrop, M. 1992. Complexity: the emerging

science at the edge of order and chaos. New

York: Simon and Schuster.

Walters, C. 1997. Challenges in adaptive management of riparian and coastal ecosystems.

Conservation Ecology [online]. 1(2): 1. http://

www.consecol.org/vol1/iss2/art1.

(10 November 2003).

Westley, F. 1995. Governing design. In: Light,

S.S.; Gunderson, L.H.; Holling, C.S., eds.

Barriers and bridges to the renewal of ecosystems and institutions. New York: Columbia

University Press: 391-427.
11

Introduction

Because this workshop is entitled “Views From

the Ridge,” I interpret my task in reviewing contributions to resource management from landscape

ecology to be to provide you with the view from

Oak Ridge. The Environmental Sciences Division

at Oak Ridge National Laboratory (ORNL) was

formed in 1955 as a response to the concern of

how radiation was affecting the environment. The

Division’s objectives rapidly expanded to include

analysis of environmental effects of all aspects of

energy use. This topic clearly encompasses all

aspects of environmental sciences, and now our

Division houses 96 scientists with degrees from

18 fields of study.

The history of advancements in environmental

sciences at ORNL parallels developments in land

management and ultimately leads to a landscape

perspective. Therefore, I thought it would be useful to highlight those scientific achievements as a

precursor to discussing landscapes. Over the

years, ORNL scientists have participated in the

development of key research areas that formed

the basis for landscape ecology (Hagen 1992).

Supported by the International Biological Program, the field of systems ecology was created.

Systems ecology views ecological interactions

from a holistic perspective and seeks to quantify

interactions of varied components. Global change

research was initiated shortly after views of the

Earth from space led to a realization that the ecological system was global. But this view was

tainted with clouds of pollution. Recognition that

human impacts occur on a global as well as local

scale led to remediation science as a way to use

the scientific process to learn about ways to remedy pollution problems. Yet this application of

ecological science to real-world problems was

difficult because of the intricacies of ecological

systems. To deal with this complexity, first hierarchy theory (O’Neill et al. 1986) and then risk

analysis (Bartell et al. 1994, Suter 1992) arose.

However, neither of these advances recognized

the spatial relationships inherent to ecological

interactions. Landscape ecology has recently

come to be a new field of study that explicitly focuses on spatial interactions (Turner 1989, Turner

and Gardner 1991).

Need for a Landscape Perspective

From an ecological viewpoint, a landscape is a

spatial extent over which ecological processes

take place (King 1997). More simply, it refers to a

spatially heterogenous area that has a similar

geomorphology and disturbance regime (Turner

and Gardner 1991).

A landscape perspective is needed to address

today’s land management problems for several

reasons. It is now recognized that the spatial

scale of environmental problems is large and that

all ecological processes (and management actions) occur in a spatial context and are constrained by spatial location. As an example,

Fraser fir (Abies fraseri (Pursh) Poir.) are dying in

the southern Appalachians as a result of herbivory

and population dynamics of the introduced woolly

adelgid (Adelges piceae Ratzeburg), but the insects’ distribution, and thus fir mortality, is influenced by the topographic conditions that restrict

the fir to the highest peaks (Dale et al. 1991).

Furthermore, ecological systems can be viewed

as spatially and temporally hierarchical. That is,

processes observed at one level of organization

arise from lower level behaviors and are constrained by higher level processes. Therefore,

solutions for contemporary environmental problems need to be provided within a spatial context.

For example, natural areas that provide essential

ecological services are limited in extent, and their

contributions must be interpreted within the landscape matrix in which they reside and with the

understanding that environmental conditions may

change over space as well as time (as with global

warming). Thus spatially optimal solutions to land

management options should be considered.

What Is a Landscape and How Is One Studied?

Virginia H. Dale1 and Barry R. Noon2

1 Corporate fellow, Environmental Sciences Division, Oak

Ridge National Laboratory, Oak Ridge, TN 37831-6036; Tel:

865-576-8043; e-mail: dalevh@ornl.gov

2 Department of Fishery and Wildlife Biology, Colorado State

University, Fort Collins, CO 80523-1474; Tel: 970-491-7905;

e-mail: brnoon@cnr.colostate.edu
12

A Landscape Approach to Land

Management

The defining attributes of an ecological landscape

are structure, composition, function, and change

(fig. 1). Structure deals with the physical relationships of landscape elements to each other: their

shape, patchiness, juxtaposition, etc. Composition

refers to the variety of elements that make up a

landscape (e.g., cover types, land forms, etc.).

Function indicates the ecological processes that

occur on the landscape (e.g., persistence of

patches, rates of nutrients and energy flow, erosion, etc.). These attributes lead to the key focus

of landscape ecology: estimating the reciprocal

relationships between landscape structure, function, and composition and how they might change

over time.

Linking landscape ecology to application takes

several steps. First, analyses must move beyond

a description of the attributes of structure, function, and composition to analyze interactions

among these attributes. Second, structure, function, and composition should be considered at

multiple spatial scales (see fig. 1). For example, it

is critical to know how structure, function, and

composition of the landscape are reflected in

population or ecosystem features. Finally, knowledge of temporal dynamics of landscape change

is essential. Natural disturbance regimes can be

characterized by their frequency, spatial extent,

intensity, and duration. System resilience has

evolved in the context of these disturbances, and

thus it is important to compare human-caused

disturbance regimes to natural disturbance regimes to determine if human impacts lie within the

bounds of system resilience. The concept of historical range of variability has value as a benchmark for human-induced changes. It is important

to understand reciprocal relationships between

disturbance and landscape pattern (e.g., disturbances both respond to and create landscape

pattern).

Key goals of responsible land management are to

provide for societal needs without usurping the

resources of future human generations and to

maintain ecological integrity and thus sustainable

ecological systems. The concept of ecological

integrity refers to system wholeness, including the

presence of appropriate species, populations, and

communities as well as the occurrence of processes at appropriate scales (Angermeier and Karr

1994, Karr 1991). To maintain integrity, it is necessary to perpetuate the “characteristic” structure,

composition, and processes of ecological systems, preserve those key elements of landscape

geometry that facilitate essential processes, retain

the productive capabilities of the land, and maintain the evolutionary capabilities of ecological

systems. Often resource extraction or use compromises these features of integrity, and thus

management actions seek ways to reinstate these

features across the landscape.

The Land Use Committee of the Ecological Society of America recommends several guidelines to

assist managers in decisions about the use of

land (Dale et al. 2000). The guidelines are presented in full awareness that all of these rules of

thumb cannot be implemented in every (or even

most) situations. These guidelines suggest that,

when possible, land managers should:

• Examine impacts of local decisions in a regional context.

• Plan for long-term change and unexpected

events.

• Preserve rare landscape elements and associated species.

• Avoid land uses that deplete natural resources.

• Retain large contiguous or connected areas

that contain critical habitats.

• Minimize the introduction and spread of nonnative species.

• Avoid or compensate for the effects of development on ecological processes.

• Implement land use and management practices that are compatible with the natural potential of the area.

These guidelines are based on ecological principles such as the idea that the size, shape, and

spatial relationships of habitat patches on the

landscape affect the structure and function of

ecosystems (Dale et al. 2000). This landscape

principle has several corollaries:
13

• Landscape elements vary in spatial distribution and quality in time and space.

• The structure and attributes of landscape elements and patches affect movement (flows of

matter and energy), which in turn affects spatial distributions.

• The nature of boundaries between patches

and matrix elements controls horizontal flows

across landscapes.

• The spatial context (neighborhood) of a patch

affects its properties and dynamics.

Several new insights to management arise from a

landscape perspective. The concept of ecological

integrity needs further interpretation within the

landscape perspective so that it becomes measurable and thus a practical management tool at all

scales. Methods are needed to reliably estimate

an expected range of natural variation for specific

ecological systems (see Parsons et al. 1999).

Improved procedures are needed for selecting

ecological indicators to assess the status and

trend of ecological systems (allowing interpretation of indicators for large spatial and temporal

scales).

Acknowledgments

Comments on the abstract by Tony King and

two anonymous reviews are greatly appreciated.

Some of the ideas reported here were developed

on a project funded by the Conservation Program

of the Strategic Environmental Research and

Development Program through the U.S. Department of Defense Military Interagency Purchase

Requisition No. 74RDV53549127 and the Office

of Biological and Environmental Research, U.S.

Department of Energy (DOE). Oak Ridge National

Laboratory is managed by Lockheed Martin Energy Research Corporation for DOE under contract DE-AC05-96OR22464.

Figure 1—The structural, compositional, and functional components of ecological systems as viewed at various levels of

ecological organization: the landscape, ecosystem, and population (from Dale and Beyeler 2001).
14

Literature Cited

Angermeier, P.L.; Karr, J.R. 1994. Biological

integrity versus biological diversity as policy

directives: protecting biotic resources.

BioScience. 44: 690-697.

Bartell, S.M.; Gardner, R.H.; O’Neill, R.V. 1994.

Forecasting toxicological risk in aquatic ecosystems. New York: Columbia University

Press.

Dale, V.H.; Beyeler, S.C. 2001. Challenges in the

development and use of ecological indicators.

Ecological Indicators. 1: 3-10.

Dale, V.H.; Brown, S.; Haeuber, R.A. [et al.].

2000. Ecological principles and guidelines for

managing the use of land. Ecological Applications. 10: 639-670.

Dale, V.H.; Gardner, R.H.; DeAngelis, D.L. [et

al.]. 1991. Elevation-mediated effects of balsam woolly adelgid on southern Appalachian

spruce-fir forests. Canadian Journal of Forest

Research. 21: 1639-1648.

Hagen, J.B. 1992. An entangled bank: the origins

of ecosystems ecology. New Brunswick, NJ:

Rutgers University Press.

Karr, J.R. 1991. Biological integrity: a longneglected aspect of water resource management. Ecological Applications. 1: 66-84.

King, A.W. 1997. Hierarchy theory: a guide to

system structure for wildlife biologists. In:

Bissonette, J.A., ed. Wildlife and landscape

ecology. New York: Springer-Verlag: 185-212.

O’Neill, R.V.; DeAngelis, D.L.; Waide, J.B.;

Allen, T.F.H. 1986. A hierarchical concept of

ecosystems. Princeton, NJ: Princeton University Press. 254 p.

Parsons, D.J.; Swetnam, T.W.; Christensen,

N.L. 1999. Uses and limitations of historical

variability concepts in managing ecosystems.

Ecological Applications. 9: 1177-1178.

Suter, G.W., II. 1992. Ecological risk assessment.

Chelsea, MI: Lewis Publishers.

Turner, M.G. 1989. Landscape ecology: the effect

of pattern on process. Annual Review of Ecology and Systematics. 20: 171-197.

Turner, M.G.; Gardner, R.H., eds. 1991. Quantitative methods in landscape ecology: the

analysis and interpretation of landscape heterogeneity. New York: Springer-Verlag. 536 p.
15
16

How Do We Determine Scale?
17

Introduction: The Dilemma of Scale

Landscapes fall into a class of objects that fit the

adage: “you know it when you see it, but it’s hard

to define.” As one looks from a ridge into a forested valley, words such as ecosystems, interactions, disturbance, and connectivity come readily

to mind. But, it has proven to be another matter

entirely to scientifically define a landscape as a

whole system of interacting parts that can be

readily integrated into management of natural

resources, environmental assessments, watershed restoration, and regulation. This is the dilemma of scale. Landscapes comprise thousands

of components and processes that are difficult to

characterize at any one time. Furthermore, interactions among landscape components occur over

decades to centuries, making it difficult to analyze

them over the short duration of research studies.

The study of landscapes, therefore, poses a complicated problem.

Major components of riverine habitats depend on

the supply, routing, and storage of inorganic and

organic materials that originate from terrestrial

sources. A stochastic climate exerts a degree of

randomness in the supply of sediment and organic debris to channel networks over 10 to 100

years; topography and channel-network geometry

impose a spatially determined organization in the

routing and storage of those materials. Hence,

aquatic and riparian habitats have both stochastic and deterministic origins. Studies that have

incorporated stochastic effects have been referred to as disturbance ecology (Pickett and

White 1985), temporal hierarchies (Frissel et al.

1986), pulses (Junk et al. 1989), and landscape

dynamics (Benda et al. 1998). Studies focusing

on deterministic aspects are described in terms

of continuums (Vannote et al. 1980), spatial hierarchies (Frissel et al. 1986), ecotones (Naiman et

al. 1988), and classification systems (Montgomery

and Buffington 1997, Rosgen 1995). Despite a

sustained interest in ecological processes over

a range of scales (Naiman and Bilby 1998,

Swanson et al. 1988), it has proven difficult to

develop general principles on how stochastic and

deterministic landscape factors, in combination,

govern habitat development. One example of this

limitation is the continuing inability to define natural disturbance regimes, including the range of

variability in aquatic and riparian environments

(Benda et al. 1998, Naiman et al. 1995). In practice, this has often led to a preference for single

environmental states and single-value regulatory

thresholds by many scientists, managers, and

regulators.

The lack of quantitative and predictive theory on

landscape-scale processes has created a dependence on case studies that often have focused on

unique and detailed aspects of landscapes, and

on classification systems that emphasized spatial

determinism (i.e., stochastic effects ignored).

Moreover, theory absence discourages hypothesis testing and commensurable research efforts

(similar things measured in similar ways). These

problems in combination increase the perceived

difficulty of landscape-scale and environmental

problems. In sum, the lack of theory hinders the

scientific analysis of landscapes and therefore

management planning at the landscape scale.

Role of Theory in the Study of

Landscapes

“Theory” refers to an explicit set of rules and parameters that are used to describe observed phenomena in a quantitative manner and that accord

with the empirical record (Gell-Mann 1994, Popper 1972). Theories should make testable predictions and hence be in a continual state of evaluation, rejection, and modification (Popper 1972). In

the study of landscapes, theories are generally

applied at small spatial and temporal scales (i.e.,

slope stability and sediment transport theories).

The term “concept” in the aquatic sciences generally refers to new and innovative ideas, and it is

that class of knowledge where the greatest strides

have been made in articulating the multivariate

attributes of landscapes. Concepts, however, do

not make testable predictions in the same way

Landscapes: The Dilemma of Scale and the Role of Theory

Lee Benda and Daniel Miller1

1 Earth Systems Institute, 1314 NE 43rd St., Suite 206-207,

Seattle, WA 98105-5832; Tel: 425-787-1960/206-633-1792;

e-mail: leebenda@aol.com/dan@ohana.org
18

theories do because they contain components

that are not fully or explicitly defined. Concepts

may play a key role in the development of a discipline because they act as verbal precursors to the

development of quantifiable and testable theories

(Haines-Young and Petch 1986). A third class of

knowledge, “classification systems,” provides an

organizing framework for grouping items into similar categories. Classification is a powerful technique for developing a common vocabulary and

for arraying physical and biological properties of

certain watershed elements. Typically, classification is a precursor to development of theories and

laws (Hempel 1966).

Developing theoretical understanding pertinent to

large scales is a critical step in the coordinated

and organized study of landscapes. First, landscape-scale theory would encourage the measurements of landscape attributes in similar ways,

thereby contributing to a regional pursuit of general principles, similar to theories at smaller

scales. This would tend to counter the notion that

every place is unique and has to be studied

uniquely on its own merits. Second, because landscape study is fundamentally interdisciplinary,

theory would encourage and guide how different

scientific disciplines would need to converge or

merge in studies of various phenomena. Third,

theory makes it easier and more defensible to

extrapolate findings from one landscape to another, thereby obviating the need for re-creating

the wheel at every location. Fourth, theory allows

“bridges” to be built among incomplete data (either temporally or spatially), a strategy that could

be cast in terms of “hypotheses,” but that would

allow for more comprehensive understanding.

This would make explicit the gaps in data and

understanding and would aid in targeting future

research priorities. Fifth, general theoretical principles would create a hierarchy of scientific understanding in which case studies of processes or

conditions obtained over small spatial and temporal scales would be evaluated in the context of the

larger scales that characterize landscapes. These

advantages would apply to research in the vegetative, geomorphic, hydrologic, and biotic sciences; in natural resource management; and in

restoration and conservation biology.

The Study of Large Numbers of

Interacting Landscape Processes

Clues for developing inductive or deductive theories at large scales pertinent to landscapes are

found in the scientific disciplines that have already

tackled problems involving large numbers of deterministic and stochastic elements. One successful strategy has been to represent the interactions of many small-scale processes by larger

scale parameters. For example, application of

analytical mechanics to the problem of landslide

prediction views soil as a “continuum,” even

though soil is composed of many individual

grains. For soil, continuum mechanics represents

the multitude of millimeter-scale grain-to-grain

interactions by meter-scale parameters such as

soil cohesion, bulk density, and soil friction angle.

(A similar approach has been applied to problems

involving turbulent fluid flow [e.g., fluid mechanics]). Analytical mechanics is most effective when

dealing with problems at relatively small spatial

and temporal scales, and it runs into difficulty

when applied at larger scales. For landsliding, the

use of a one-dimensional, infinite-slope model is

an example of simplifying the interactions of multiple three-dimensional unit volumes of soil involved with failures.

Statistical mechanics provides another technique for predicting the behavior of exceedingly

large numbers of randomly behaving elements. A

purely statistical approach can describe the behavior of gases that contain vast numbers of randomly colliding molecules (James Clark Maxwell

[1831-1879] and Ludwig Boltzmann [1844-1906]).

To calculate the macroenergy state of a gas in

response to applied temperature and pressure,

molecules are parameterized by probability distributions of energy states. As pointed out by Dooge

(1986), however, there are large differences between the statistical mechanical approach that

depends on concepts of energy equilibrium and

average conditions, and the nonequilibrium and

transient conditions manifest in hydrologic and

geomorphic processes that are of interest to scientists and resource managers.
19

In the context of these methods, landscapes contain too many components to be treated strictly

deterministically and too few components to be

treated purely statistically. Environmental systems

that fall between the end members of determinism and stochastism but that exhibit both characteristics have been referred to as “intermediate

number systems,” or systems of “organized complexity” (Weinberg 1975). This characterization

also has been extended to ecological and geomorphological systems (Allen and Starr 1982,

Graf 1988). To deal with systems of organized

complexity, “systems theory” has been developed

(Von Bertalanffy 1968). Application of systems

theory typically relies on building comprehensive

mathematical models that are used to scale up

analytical descriptions of processes at small

scales to predict the macrobehavior of a system

of such processes over larger space and time

scales. This so-called “upwards approach” has

been applied to the study of certain hydrological

problems (Rodriguez-Iturbe and Valdes 1979,

Roth et al. 1989, Smith and Bretherton 1972).

Pursuit of General Landscape Theory

The concept of “organized complexity” is proposed as a framework for unifying random and

organized attributes of landscapes that govern the

flux, storage, and routing of mass between and

within terrestrial and aquatic systems. Randomness refers to behavior that is not predictable in

detail (such as climate), but that can be described

in probabilistic terms. Organization refers to spatial regularities or patterns in a landscape and can

include laws of stream ordering and bifurcation

(Horton 1945, Strahler 1952), and systematic

variations in network geometry, such as decreasing channel gradient and increasing channel width

with increasing drainage area (Leopold et al.

1964).

Pursuit of landscape theory requires landscapescale parameters. These include temporal distributions of the frequency-magnitude characteristics of climatic, hydrologic, and geomorphic

events, and spatial distributions that characterize

the attributes of large numbers of landscape elements (Benda et al. 1998). A general landscape

theory is proposed that predicts how mixtures of

climate, topography, lithology, and vegetation impose overarching constraints on the probability

distributions and spatial patterns of sediment and

wood flux to streams. Included is how temporal

distributions of material fluxes evolve along a

channel network owing to asynchronous material

supply, network geometry, attrition, spatial scale

(drainage area), and transport and storage regimes. The derived long-term probability distributions of material flux and storage indicate the

stochastic and deterministic origins of aquatic and

riparian landforms. Probability distributions also

define the space-time structure of variability or the

natural disturbance regime.

The general theory is a work in progress, and

hence there is need for testing and refining general principles pertaining to climatic and vegetation disturbances, erosion regimes, sediment

routing, and wood recruitment. In addition, new

theoretical principles covering riparian vegetation

and the formation of aquatic and valley floor habitats are needed. Many of the overarching interactions between stochastic and deterministic

landscape factors can be sketched on the back of

a napkin. Simulation modeling and field studies

are needed to make more quantitative and landscape-specific predictions (Benda and Dunne

1997a, 1997b; Benda and Sias 1998). Refer to

General Landscape Theory of Organized Complexity (Benda et al. 1999) for a more thorough

discussion.

Potential Applications of Landscape

Theories:

1. Guide field studies of landscape-scale processes.

2. Provide context for studies conducted at

small spatial and temporal scales.

3. Define natural disturbance regimes through

probability and frequency distributions.

4. Evaluate environmental change through shifts

in distribution form (in time or space).

5. Promote risk assessments that use a probabilistic approach.

6. Base environmental analyses, resource management planning, environmental regulation,

watershed restoration, and conservation biology on a theoretical foundation.
20

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Allen, T.F.H.; Starr, T.B. 1982. Hierarchy: perspectives for ecological complexity. Chicago,

IL: University of Chicago Press. 310 p.

Benda, L.; Dunne, T. 1997a. Stochastic forcing of

sediment routing and storage in channel networks. Water Resources Research. 33(12):

2865-2880.

Benda, L.; Dunne, T. 1997b. Stochastic forcing

of sediment supply to the channel network

from landsliding and debris flow. Water Resources Research. 33(12): 2849-2863.

Benda, L.; Miller, D.; Dunne, T. [et al.]. 1998.

Dynamic landscape systems. In: Naiman, R.;

Bilby, R., eds. River ecology and management:

lessons from the Pacific Coastal Ecoregion.

Washington, DC: Springer-Verlag: 261-288.

Chapter 12.

Benda, L.; Miller, D.; Sias, J. [et al.]. 1999.

General landscape theory of organized complexity. Seattle, WA: Earth Systems Institute.

Benda, L.; Sias, J. 1998. Wood budgeting: landscape controls on wood abundance in

streams. Seattle, WA: Earth Systems Institute.

70 p.

Dooge, J.C. 1986. Looking for hydrologic laws.

Water Resources Research. 22: 465-585.

Frissell, C.A.; Liss, W.J.; Warren, C.E.; Hurley,

M.D. 1986. A hierarchical framework for

stream habitat classification: viewing streams

in a watershed context. Environmental Management. 10(2): 199-214.

Gell-Man, M. 1994. The quark and the jaguar:

adventures in the simple and complex. New

York: W.H. Freeman and Company. 329 p.

Graf, W.L. 1988. Fluvial processes in dryland

rivers. Berlin, West Germany: Springer. 346 p.

Haines-Young, R.; Petch, J. 1986. Physical geography: its nature and methods. London,

England: Harper and Row. 230 p.

Hempel, C.G. 1966. Philosophy of natural science. Upper Saddle River, NJ: Prentice Hall.

Horton, R.E. 1945. Erosional development of

streams and their drainage basins: hydrophysical approach to quantitative morphology.

Bulletin of the Geological Society of America.

56: 275-370.

Junk, W.J.; Bayley, P.B.; Sparks, R.E. 1989. The

flood-pulse concept in river-floodplain systems.

Canadian Special Publication of Fisheries and

Aquatic Sciences. 106: 110-127.

Leopold, L.B.; Wolman, M.G.; Miller, J.P. 1964.

Fluvial processes in geomorphology. San Francisco: Freeman. 522 p.

Montgomery, D.R.; Buffington, J.M. 1997.

Channel reach morphology in mountain drainage basins. Geological Society of America

Bulletin. 109: 595-611.

Naiman, R.J.; Bilby R.E., eds. 1998. River ecology and management: lessons from the Pacific

Coastal Ecoregion. New York: Springer-Verlag.

Naiman, R.J.; DeCamps, H.; Pastor, J.;

Johnston, C.A. 1988. The potential importance of boundaries to fluvial ecosystems.

Journal of the North American Benthological

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Naiman, R.J.; Magnuson, J.J.; McKnight, D.M.

1995. The freshwater imperative: a research

agenda. Washington, DC: Island Press. 165 p.

Pickett, S.T.A.; White, P.S., eds. 1985. The ecology of natural disturbance and patch dynamics. New York: Academic Press.

Popper, K.R. 1972. The logic of scientific discovery. 6th ed., rev. London, England: Hutchinson.

Rodriguez-Iturbe, I.; Valdes, J.B. 1979. The

geomorphic structure of hydrologic response.

Water Resources Research. 15(6): 1409–

1420.

Rosgen, D.L. 1995. A stream classification system. In: Johnson, R.R.; Zeibell, C.D.; Patton,

D.R. [et al.], eds. Riparian ecosystems and

their management: reconciling conflicting uses.

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Station: 91-95.
21

Roth, G.; Siccardi, F.; Rosso, R. 1989. Hydrodynamic description of the erosional development of drainage patterns. Water Resources

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the conservation of mass in drainage basin

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Woodmansee, R.G. 1988. Landform effects

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Vannote, R.L.; Minshall, G.W.; Cummins, K.W.

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22

The title of this conference, “Views From the

Ridge,” suggests a particular scalar view of issues. From the ridge, one obtains a somewhat

broad but restricted view of the landscape. Certainly, “Views From Space” would provide a larger

spatial overview in which landscape pattern becomes a dominant theme. For an aquatic or riparian theme, “Views From the Valley” would suggest

looking upward to the hillslope and ridges, in contrast to looking down from the ridge. Issues concerning appropriate scale have been prevalent in

most of the recent landscape assessments, including the Northwest Forest Plan (FEMAT 1993),

the PACFISH (1994) strategy, and, most recently,

the Forest Service Roads Analysis (USDA Forest

Service 1999) procedure. In all of these efforts,

three struggles were common: (1) issue identification and integration of information across multiple

disciplines, (2) appropriate spatial scales, and (3)

appropriate temporal scales.

Issue Identification and Integration of

Information Across Multiple

Disciplines

Several decades ago, some of us thought that it

would be a good idea to get a bunch of fishery

researchers and watershed researchers together

for a joint meeting. The joint meeting lasted about

4 hours until someone voiced the opinion that we

had nothing in common to speak about and the

meeting broke up into two different rooms: one

room for the biologists and another for the physical scientists. Since that time, interdisciplinary

work has improved. At least now we occasionally

can identify common issues. But still, people continue to struggle with understanding the crosscutting complexity within a common issue. For

example, foresters tend to identify forestry issues

as centered around trees; hydrologists see forestry issues as related to water quality or quantity;

biologists see the same forestry issues as revolving around birds, salamanders, or fish. Seldom

are we successful in dealing with the full complexity of the issue across disciplines. Traditional ways

of looking at problems are either from the top

down, or from the bottom up.

Top Down

The top-down approach (fig. 1) starts with some

land use activity, such as logging, grazing, or urbanization. The next step is to identify the onsite

changes produced by that activity; that is, how

does that land use activity modify the site—soil,

vegetation, terrain, slope, and so forth. Then, how

are these onsite changes translated into altered

watershed products? Primary products of altered

watersheds are water, sediment, organics, chemicals, and heat. And finally, how are these products

transported away from the site of disturbance to

cause some offsite impact? For example, suppose there are logging and associated roads in a

particular watershed. These activities compact the

soil, modify the vegetation, and alter the topography by making the slope steeper at road cuts and

fills. These physical changes can modify runoff

timing and volume, wood input to streams, surface erosion, and landslides. The result can produce changes in peak flow, base flow, water

temperature, channel condition, and sediment.

Society is more concerned about the consequences of these changes offsite: increased

flooding, increased sedimentation, fewer salmon,

and so forth. By looking at the full set of potential

influences of a land-disturbing activity, a broader

range of potential concerns can be identified than

if we simply focused on our favorite impact.

Bottom Up

Another equally useful approach (fig. 2), which is

a common engineering exercise, is to identify

some offsite impact and trace the way back up to

find the activity that caused that offsite impact. For

example, if a bridge was washed out, there could

be many potential reasons including increased

peak flow, channel erosion, water diversion, battering by debris, and so forth. Identification of the

correct process and successive linkages is important in order to be successful in preventing future

failures or to identify the guilty party.

Scale Considerations for Linking Hillslopes to Aquatic Habitats

Robert R. Ziemer1

1 Chief research hydrologist, U.S. Department of Agriculture,

Forest Service, Pacific Southwest Research Station, 1700

Bayview Dr., Arcata, CA 95521; Tel: 707-825-2936; e-mail:

rziemer@fs.fed.us
23

Figure 1—The top-down approach

starts with a land-disturbing activity,

then describes the onsite changes,

the subsequent effects of these

changes, and finally the consequences (from Ziemer and Reid

1997).

Figure 2—The bottom-up approach starts with an identified consequence (bridge washed out),

then describes the important conditions and linkages that could have produced the problem,

then the processes that caused the conditions, and finally links to the land-disturbing activities

(from Ziemer and Reid 1997).
24

To be most successful, we should analyze the

issues simultaneously from the top down and

bottom up by linking the land use activity to potential offsite impacts, and also by linking identified

offsite impacts to potential land use activities

(fig. 3).

Putting It Together

As an example, let us take “disappearing salmon”

as an issue for consideration (fig. 4). If we were to

simply focus on the number of salmon at a particular point as the appropriate metric of success,

we may develop some programs of salmon restoration that are rather silly when the problem is

considered within its broader context. For example, we might try to restore habitat above a

dam or a culvert where the fish are unable to

reach. Or, perhaps the reason the fish numbers

are low is because they were caught downstream.

By producing diagrams similar to figure 4, we can

begin to visualize and understand the complexity

and interactions within the issue of concern. The

process of developing the diagram is more important that the final diagram itself. In building the

diagram, individuals with different backgrounds

and focus can identify where their knowledge contributes to the solution of a single issue. In figure

4, there are three major components potentially

affecting salmon: land use, human predation,

and ocean conditions. The land use and terrestrial

conditions include the traditional issues and linkages: logging, grazing, agriculture, urbanization,

dams, and so forth, with their associated effects.

The human predation component addresses

sport, commercial, and subsistence fishing. The

ocean conditions influence a major portion of the

salmon’s life cycle.

The traditional view of the problem (fig. 5) is to

ignore all of this complexity and other influences

and focus on the parts that we particularly care

about. We select a land use of interest and evaluate the linkages and pathways between that land

use (logging) and the target concern (disappearing salmon). Commonly, we further narrow the

scope to a specific component, for example, to

woody debris. We want to demonstrate that a

change in woody debris has some effect on disappearing salmon. So this becomes our top-down

approach. We only think about how woody debris

is affecting the salmon and we ignore all of the

other influences.

It is common to find that an agency only considers

those components for which they are directly responsible and ignores the potential effects of

other land uses. For example, a forestry agency

becomes only concerned with the effects of forest

land management on salmon, while the influence

Figure 3—The top-down and bottom-up

approaches can be merged into a singleanalysis approach by linking the land use

activity to potential offsite impacts, and

also by linking identified offsite impacts to

potential land-use activities.
25

Figure 4—A generalized diagram of some possible important interactions affecting “disappearing salmon” (from

Ziemer and Reid 1997).

Figure 5—Example of a typical shortcut that ignores many of the important components in the generalized

diagram to link a particular component to “disappearing salmon” (from Ziemer and Reid 1997).
26

of agriculture, urbanization, dams, fishing, and so

forth are ignored because the forestry agency is

only authorized to regulate logging or manage

timberland. This focus is appropriate at a later

time when the agency decides upon a program of

action. Unfortunately, such a myopic view often

misses the context of the agency’s program within

the larger issue and can lead to uneven regulation

or to ineffective management actions.

The end point of problem simplification is to select

some index that directly links the activity to the

target issue without regard to other influences

(fig. 6). For example, a group working to restore

salmon runs in the South Fork Trinity River in

northwestern California assumed that their favorite variable, changes in the volume of large pools

in the mainstem river, was related to the number

of returning salmon. The group decided to measure annual changes in the volume of these large

pools and then to correlate these annual pool

volume changes to logging and road building,

which were assumed to produce decreased pool

volume, and to the amount of future watershed

rehabilitation, which was assumed to result in

increased pool volume. In other words, pool volume was the index that was to tie changes in land

use to fish. None of the other components or influences upon fish numbers were to be evaluated or

considered. The problem was that the group had

no information about what was happening to fish

downstream and no independent indication that

there was any relation between fish numbers and

pool volume, let alone between land use and pool

volume.

Spatial Scale

Individuals who design projects, such as timber

sales, roads, grazing permits, recreation facilities,

and so forth, are quite accustomed to and comfortable in dealing with the project or subwatershed scale (fig. 7) that ranges from 10 to a few

thousand acres. Project designers are less accustomed to evaluating the context of that project

within larger scales. The appropriate size of that

larger scale depends strongly on the issue being

considered. If, for example, there is a concern

about the effect of a project on the drinking water

supply for a small community, evaluating the

subwatershed directly above the water supply

intake is the appropriate geography and scale.

Areas beyond that direct influence are not relevant to the problem. If, however, we are dealing

with the effect of a project on anadromous fish,

then we are dealing with a much different geographical and spatial arena. For each of the boxes

and linkages in the disappearing salmon diagram

(fig. 4), there are sets of scales that are appropriate to that box. For the fish population, the scales

range from the individual stream reach to the

Pacific Northwest, including the ocean. Salmon

stocks from the Columbia River may compete in

the ocean for food and resources with salmon

from northwestern California. Anything that

changes the competitive advantage of one stock

is important to consider. Further, there may be

migratory wandering of fish from one river system

to another. A depleted stock from one river may

result in success of stocks from another river

because of reduced competition, or vice versa. It

is important to recognize such external forces that

are operating at the large scale outside of the immediate frame of reference. Similarly, within a

given river system, it is not possible to evaluate

the value of improving fish habitat quality at the

small watershed scale without some understanding of how habitat along the migratory route influences the population. In the extreme example,

improving salmon habitat above a migration barrier will have no effect, because the fish will never

be able to use that habitat.

The appropriate scale or geography depends on

the issue to be addressed. Some issues remain

fixed in one location (trees, soil fertility), whereas

others are mobile (animals, water, sediment).

Products associated with aquatic issues (water,

heat, chemicals, wood, sediment) tend to move

downslope or downstream and are constrained

within defined topographic boundaries. Fish

move upstream and downstream, so for them,

watershed boundaries are useful geographic

limits. Terrestrial animals (deer, birds) are not

constrained by watershed boundaries, and the

watershed concept is not particularly useful. For

these animals, movement range is a more useful

scale than topographic boundaries.
27

Figure 6—Occasionally, an index is used to link a land-disturbing activity to the target, ignoring all of the complexity and interactions that may also influence the target (from Ziemer and Reid 1997). (ECA = equivalent clearcut area, TMDL = total maximum daily load.)

Figure 7—A hierarchy of spatial scales.

Vegetation 

change 

High water 

velocities 

Disappearing 

Salmon

Fishing 

Habitat 

change 

More predation 

Altered riparian 

vegetation 

Less woody 

debris 

Shallow 

water 

Altered circulation 

and temperature 

Industrialization 

Subsistence 

Sport 

Commercial 

Ocean Freshwater 

and estuary

Migration 

blockage 

High water 

temperature 

Altered spawning 

gravels 

Dams

Logging, grazing, 

urbanization, etc.

Aggradation 

More erosion 

Higher 

peak 

flows 

ECA, 

TMDL, 

etc.

The Index Approach
28

A survey of any geographic area will result in a

high variance for most parameters. For example,

consider a hypothetical survey of 30 streams to

evaluate the risk of mortality of some species of

fish (fig. 8). Some streams have good habitat and

a low risk of mortality resulting from some action,

whereas others will have a high risk. The level of

“acceptable” risk has two components, biological

and social. If the species is abundant, it may be

biologically and socially acceptable to adopt a

level of regulation that would overprotect some

streams and underprotect others. As the species

becomes rarer, a higher level of regulation may be

appropriate, depending on the consequences of

making a judgment error. The problem with regulations that produce or require a generic “designer

stream” is that stream systems are dynamic and

may require a wide range of evolving habitat conditions to be productive. The stream systems

described by Reeves (this volume) require a substantial amount of perturbation and resulting productivity changes over time. Designing for the

perceived “ideal” condition in all places all of the

time may lead to a poor stream condition in the

future. Further, a poor condition today may contain exactly the components needed for the best

habitat in the future.

Temporal Scale

It is well known that “significant” hydrologic or

meteorologic events occur rarely, and the temporal distribution of these events is not uniform. This

presents a problem because most monitoring

activities represent only a short snapshot of the

temporal distribution of events. If the long-term

distribution was uniform and well behaved, the

snapshot may be an adequate representation of

the expected population of future events. However, if the events are not uniformly distributed

(fig. 9), then any short period of monitoring can

produce flawed information. For example, assume habitat conditions are monitored on a

stream continuously for 75 years, considered by

most to be an exceedingly long record. If the

monitoring period ran from year 1 to 75 (fig. 9),

the conditions represented would be greatly different than if the period was from year 75 to 150.

More realistically, most monitoring activities are

much shorter than 75 years, often 10 or fewer

years. Any 10-year period in figure 9 could find

conditions ranging from no severe storms to multiple storms. In other words, the temporal scale

needed to adequately represent the significant

geomorphic or ecologic drivers is often orders of

magnitude longer than our monitoring database.

How does this relate to the level of regulation and

risk of mortality? Suppose that the average of the

streams depicted in figure 8 had a monitoring

record of 30 years (fig. 10). The maximum risk

of mortality, and perhaps the appropriate level

of regulation, could differ substantially based on

which period is monitored: for example, years

1 through 10, years 11 through 20, or the entire

30-year record.

What is the appropriate time scale to consider?

The answer depends strongly upon the issue.

Different folks or the same folks considering

different issues look at the problem differently

(table 1). For those in the corporate world of profits and losses, a quarter (of a year) is an important scale. Corporate well-being 150 years from

now is often not an important consideration to the

board of directors. Politicians like to see programs

that they sponsor put into effect and have some

result during their time in office. For politicians,

the election cycle (2, 4, or 6 years) is an important

time scale. The length of a human life is an important time scale for people, and sometimes planning includes several generations, that is,

planning cycles ranging from 10 to perhaps 100

years. For most people, something that happened

20 years ago was a long time in the past. With

some exceptions, such as planning for infrequent

but catastrophic events such as earthquakes and

floods, something that happens once every 20

years or so is beyond the immediate concern of

most people. However, a 20-year time scale is

extremely long for an insect species having several life cycles per year, or extremely short for a

redwood or bristlecone pine having a life cycle of

1,000 years or longer. An individual storm becomes very important for the domestic water user

who turns on the water tap and finds the water to

be turbid. Geomorphic events that shape the

stream channel may occur only once a decade,

century, or millennium.
29

Figure 8—Hypothetical survey of streams for risk of fish mortality and the level of regulation needed to protect fish

at two levels of abundance (from Ziemer 1994).

Figure 9—Distribution and magnitude of severe storms during a single 300-year simulation (from

Ziemer 1991).

Endangered 

species 

Underprotected 

Overprotected 

Abundant

species

Stream identifier 

Risk of mortality 

Levels of regulation 
30

Table 1—Appropriate time scales

Entity Period Years

Corporations Quarterly profits and losses 0.25

Politicians Election cycles 2, 4, or 6

Humans Memory of significant events 1 to 20

Humans Lifespan 50 to 100

Insects Life cycle 0.2 to 1

Anadromous fish Life cycle 2 to 4

Humans Life cycle 50 to 100

Trees Life cycle 100 to 1,500

Domestic water user Individual storm 0.1 to 5

Channel adjustments Large storm 1 to 1,000

Figure 10—Hypothetical risk of fish mortality based on monitoring streams for different periods of

time and the effect of cycles or unusual events on the perceived level of regulation needed to

protect fish (from Ziemer 1994).
31

Finally, how one views the world depends strongly

on conceptual models about how things operate.

For example, our belief about how the level of

watershed disturbance is related to salmon habitat (fig. 11) has a strong influence on land management and restoration strategies. The initial

assumption for both curves a and b is that the

best habitat represents that area having the least

watershed disturbance. In one model (fig. 11,

curve a), a watershed can be increasingly disturbed with little effect on habitat quality until a

threshold is reached, beyond which there is a

precipitous decline in habitat quality. The management objective would be to allow disturbance activities to continue until just before the point is

reached where habitat quality begins to drop rapidly. Conversely, curve a suggests that a severely

degraded habitat can be restored with a small

reduction in the amount of watershed disturbance.

The second model (fig. 11, curve b) suggests that

a small amount of disturbance in watersheds having the best habitat can result in a rapid decline in

habitat quality. Once the habitat quality is low,

additional disturbance has little incremental effect

on habitat quality. Conversely, curve b suggests

that recovery of habitat quality in heavily disturbed

watersheds will require a huge effort before any

improvement will result. Many past land management plans followed assumptions of curve a. The

Northwest Forest Plan (FEMAT 1993) aquatic

conservation strategy follows the assumptions of

curve b, that is, to identify and protect those watersheds that have the best remaining habitat (key

watersheds), and to concentrate continued harvesting in those areas having the poorest habitat

(matrix). It is important to determine which of

these models best represents the relationship

between watershed disturbance and habitat

quality.

Figure 11—Two conceptual models of the relation between watershed disturbance and salmonid habitat:

(a) habitat quality is not degraded until substantial watershed disturbance is reached; (b) habitat quality is

degraded most quickly during initial stages of watershed disturbance (from Ziemer 1997).
32

Conclusion

Management and policy strategies to sustain a

resource depend on physical and biological hypotheses that often are untested. The success or

failure of a particular strategy will depend strongly

on how the resource actually responds once that

strategy is applied. Understanding the response

of the resource, in turn, will depend critically on

viewing that resource from the appropriate scale

in time and space.

Literature Cited

Forest Ecosystem Management Assessment

Team [FEMAT]. 1993. Forest ecosystem management: an ecological, economic, and social

assessment. Portland, OR: U.S. Department

of Agriculture; U.S. Department of the Interior

[et al.].

PACFISH. 1994. Environmental assessment for

the implementation of interim strategies for

managing anadromous fish-producing watersheds in eastern Oregon and Washington,

Idaho, and portions of California. Washington,

DC: U.S. Department of Agriculture, Forest

Service; U.S. Department of the Interior,

Bureau of Land Management. 68 p. + attachments.

U.S. Department of Agriculture, Forest Service. 1999. Roads analysis: informing decisions about managing the national forest

transportation system. Misc. Rep. FS-643.

Washington, DC. 222 p.

Ziemer, R.R. 1991. An approach to evaluating the

long-term effects of land use on landslides,

erosion, and stream channels. In: Proceedings, Japan-U.S. workshop on snow avalanche, landslide, debris flow prediction and

control. Tsukuba, Japan: Organizing Committee of the Japan-U.S. Workshop on snow avalanche, landslide, debris flow prediction and

control: 533-542.

Ziemer, R.R. 1994. Cumulative effects assessment impact thresholds: myths and realities.

In: Kennedy, A.J., ed. Cumulative effects assessments in Canada: from concept to practice. Edmonton, AB: Alberta Association of Professional Biologists: 319-326.

Ziemer, R.R. 1997. Temporal and spatial scales.

In: Williams, J.E.; Wood, C.A.; Dombeck. M.P.,

eds. Watershed restoration: principles and

practices. Bethesda, MD: American Fisheries

Society: 80-95. Chapter 6.

Ziemer, R.R.; Reid, L.M. 1997. What have we

learned, and what is new in watershed science? In: Sommarstrom, S., ed. What is watershed stability? Proceedings, sixth biennial

watershed management conference. Report

No. 92. Davis, CA: University of California,

Water Resources Center: 43-56.
33

Controversies about forest sustainability, advances in the sciences of landscape ecology and

ecosystem management, and new tools such as

geographic information systems (GIS) and remote

sensing have led natural resource policymakers,

planners, and managers from the stand, to the

landscape, and to regional scales. As scientists

and managers have expanded to these broader

scales, they have typically encountered multiownership landscapes. The management and

scientific challenges posed by multiownership

landscapes are especially complex. Species and

ecosystems do not recognize legal boundaries

between ownerships, and the landscape dynamics of individual ownerships are controlled by a

complex of economic, social, political, and biophysical forces. The aggregate ecological conditions of landscapes are controlled by the spatial

pattern and dynamics of individual owners and

ecological interactions among those ownerships.

The dominant disturbance regimes in many landscapes are now directly or indirectly controlled by

human activities. Consequently, to understand

and predict these anthropogenic disturbances, we

must also understand their linkages to economics,

policy, and sociology. Solutions to problems of

conservation policy and practices for multiownership landscapes do not lie in isolated owner-byowner planning and management. Broader scale

approaches are needed. Work in multiownership

landscapes also reveals the need for increased

integration among ecological and social sciences.

The challenges to conducting integrated regional

assessments are numerous and frequently not

appreciated by scientists who typically have little

experience in these types of efforts.

A group of Pacific Northwest Research Station

and university scientists is currently involved in

a research program that is designed to test and

evaluate multiownership issues at province

scales. The Coastal Landscape Analysis and

Modeling Study (CLAMS) is a large interdisciplinary effort designed to evaluate aggregate effects of different forest policies on the ecological

and socioeconomic conditions of the Coast

Range province as a whole (Spies et al. 2002;

www.fsl.orst.edu/clams). Here, I briefly describe

our general approach and present an example of

a simulation of changing forest landscape conditions over time. I discuss the potential ecological

consequences of the mosaic of different ownership policies and conclude by identifying some of

the challenges associated with building integrated

regional models.

The goal of CLAMS is to develop and evaluate

concepts and tools to help understand patterns

and dynamics of ecosystems at province scales

and to analyze the aggregate ecological and socioeconomic consequences of forest policies for

different owners. Our approach is based on the

assumption that by knowing landscape structure

and dynamics of vegetation we can project consequences of different forest policies for biological

and social responses. The major steps in our

approach are:

1. Build high-resolution spatial models (grain

size of 0.1 to 10 ha) of current biophysical

conditions (e.g., vegetation, ownership patterns, topography, streams) across all owners

by using Landsat satellite imagery, forest inventory plots, and GIS layers.

2. Conduct surveys and interviews of forest

landowners to determine their expected management intentions (e.g., rotation ages, thinning regimes, riparian management intensity)

under current policies and to develop spatial

land use change models based on retrospective studies.

3. Project expected successional changes in

forest structure and composition under different management regimes by using stand

dynamics models.

4. Build a landscape change simulation system

based on forest management intentions and

forest stand models to project potential landscape structure for 100 to 200 years.

Landscape Assessment in a Multiownership Province

Thomas A. Spies1

1 Research ecologist, U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 3200 SW Jefferson Way, Corvallis, OR

97331; Tel: 541-750-7354; e-mail: tspies@fs.fed.us
34

5. Develop biophysical response models for

habitat quality for selected terrestrial and

aquatic vertebrate species, viability of selected vertebrates species, coarse-filter

measures of community and landscape conditions, historical range of natural variation of

forest successional stages, and landslide and

debris flow potential.

6. Develop socioeconomic response models for

measures of employment and income by economic sector, timber value and production,

recreational opportunities, and contingent

value of biological diversity to the public.

7. Estimate potential ecological and socioeconomic consequences of current forest policies

by using the landscape simulator and various

response models.

8. Evaluate, test, and revise overall simulator

system and submodels.

9. Provide policymakers, landowners, and the

public with results of spatial projections of

consequences and interact with those groups

of people to help inform debate and facilitate

collaborative learning.

At this point in the project we are simulating only

forest management-related disturbances (e.g.,

clearcutting, partial cutting, thinning) and landslide

and debris flow disturbances. We focus on these

because they are among the most frequent in the

region, potentially have large impact on measures

of biological diversity, and are of great interest in

current policy debates. We are not simulating

stochastic disturbances such as wildfire, wind,

insects, and disease. Studies in the region indicate that wildfire occurs infrequently (150 to 400

years) and its spatial pattern is only weakly controlled by topography, especially for large fire

events (Impara 1997). Smaller wind and pathogen

disturbances are quite frequent, but they are difficult to predict and typically occur at patch sizes

below our level of spatial resolution for this provincial study. Climate change is another process that

we do have in the current model. These other

ecological processes could be incorporated into

future modeling efforts, either directly in the simulation model or as scenarios (e.g., effects of a

large fire) for comparative analysis. These processes could have profound implications to management. For example, a large, rare fire event

could influence ecological and socioeconomic

systems for decades and centuries. Relatively

fine-scale processes such as disease or landslides could affect biophysical potential across

large areas. We do not mean to imply that these

other processes are not important but our initial

interest is in isolating the effects of management

actions. The model should be viewed not as a

predictive tool but rather as a computer-based

experiment to provide insights into the relative

effects of different forest policies.

We developed a prototype of our landscape

simulator for the Coast Range province and ran

it for a 100-year scenario under current policies

(fig. 1). Patterns of current forest condition are

nonuniformly distributed across ownerships. Current vegetation patterns in the province are characterized by a predominance of early and midsized conifer forests. Forests dominated by trees

of the largest size classes (large and very large

conifers) are rare and restricted primarily to public

lands. Broadleaf forests are less common than

coniferous forests and tend to be concentrated in

riparian areas. Old-growth forest condition (approximately equivalent to the very large conifer

class) is currently a small percentage of the total

area, and what is remaining is concentrated on

Bureau of Land Management (BLM) and Forest

Service lands in the southwestern portion of the

province. Little old growth occurs on private land,

but some small remnant patches do occur and

form the basis of Habitat Conservation Plans for

the northern spotted owl (Strix occidentalis

caurina). Conversely, open (pasturelands, meadows, agricultural lands, and recent clearcuts) and

early-successional stages of forest (typically forests less than 15 to 20 years old) occupy almost

40 percent of the province and are concentrated

on private lands.

By 50 years into the simulation of future conditions, the pattern of vegetation classes has

changed dramatically. Amounts of large-diameter

classes have increased, especially on federal

lands, and the spatial pattern of vegetation has

begun to resemble the underlying ownership pattern. Young plantations (10 to 30 years old) on

federal lands have matured and are beginning to

blend into the matrix of large conifer size classes.

On private lands, intensive forest management
35

(40- to 50-year rotations) keep these landscapes

cycling between early successional stages and

harvest-age timber plantations. By 100 years, the

contrasting patterns of vegetation across ownerships are even stronger.

Although total amounts of late-successional forest

have increased dramatically in the Coast Range

in this simulation, the spatial pattern of these forests creates considerable potential edge effects

and spatial pattern interactions, especially on BLM

checkerboard lands. The simulations suggest that

large watersheds of the Coast Range will develop

into a mosaic of very different landscape types

based on the amount and spatial pattern of forest

conditions. These landscapes range from watersheds dominated by late-succesional forest to

watersheds dominated by early-successional

and mature-forest plantations. Between these

extremes is a wide range of mixtures of successional dominance and dispersed or blocked spatial patterns. Consequently, we hypothesize that

a new landscape pattern is emerging in this province in which ownership patterns, management

strategies, and boundaries will control patterns of

biophysical processes more than in the past. The

ecological and socioeconomic consequences of

changing diversity and spatial pattern are the primary focus of our ongoing research efforts.

To summarize, we have learned that recently enacted forest policies in the Oregon Coast Range

have the potential to create novel landscape patterns of vegetation. We hypothesize that in this

dynamic landscape, the combination of complex

ownership patterns, contrasting management

regimes, and ecological processes create the

spatial interactions that could not be predicted

based on information from individual ownerships

Figure 1—Current conditions (as of 1995) and simulated changes in forest types of the Coast Range at 50 and 100 years into

the future under current policies.
36

in isolation from each other. Although simple

analysis of ownership patterns indicates a strong

potential for aggregate effects in this province,

more detailed analyses are needed to test the

degree and distribution of these effects. The spatial interactions that we expect to have the greatest impact on the ecological systems of this

province are the following:

• Imbalances and gaps in seral stage distributions across environmental strata, including

subecoregions, watersheds, and topographic

positions.

• Gaps in distribution of habitat of relatively

wide-ranging species (such as the northern

spotted owl or salmonids) whose movement

patterns are at similar scales to ownership

tracts and management allocations within

ownerships.

• Decline in aquatic habitat quality in stream

reaches and watersheds as amounts of large

wood are lost because of forest and agricultural management practices along streams

and upslope in landslide and debris flow

areas that are sources of large wood for

many streams.

The building of integrated regional models to assess forest policies is a relatively new endeavor,

and many scientists have little experience with

this type of integrated research, which also may

be conducted in an unfamiliar policy and public

environment. We have learned much about the

process of building integrated regional models to

assess ecological and socioeconomic effects. Our

lessons learned include:

• The importance of problem definition and

the conceptual model. Without adequate

problem definition and conceptual framework,

the process can degenerate into separate

studies that may not meet project goals.

• The importance of involving policymakers

and identifying policy questions. Without

incorporating policymakers and specific policy

questions at the beginning, the potential relevance of the project will be diminished.

• The difficulty of developing spatial information about landscapes and regions. Spatial information about provinces and regions is

inadequate and will always be flawed. The

challenge is to determine when data quality is

good enough to provide a first approximation

at large scales.

• The value of landscape projections. Spatial

projections of possible future landscapes are

a powerful way to engage policymakers and

stakeholders in joint learning efforts.

• The challenge of measuring ecological

effects. We lack quantitative measures of

ecological response. The challenge is to blend

empirical, modeling, and expert judgment

approaches to provide working hypotheses for

use in model projections and to direct future

research.

• The challenge and importance of scale.

The spatial and temporal scales of ecological,

policy, and socioeconomic processes and

measures are typically not the same. Continuous attention to scale is needed to ensure that

linkages can be made among components.

• The diversity of ways that integration either happens or not. Integration across disciplines is central to the effort. Although not all

scientists in the team have the time and interest to attend to integration of the project as a

whole, one or a few leaders must pay close

attention to this process.

• The challenge of conducting science in

public policy and private landowner environment. Applying landscape ecology to large

multiownership areas cannot be done entirely

within the walls of a research institution. Scientists must interact with policymakers and

stakeholders in new and sometimes uncomfortable ways. These interactions can be time

consuming and disruptive to the “normal” process of research. Without them, however, the

relevance of the effort can be seriously jeopardized.
37

These lessons on the process are important for

scientists, policymakers, funding agencies, and

management agencies. These types of efforts

require, above all, patience, leadership, long-term

funding, and flexibility to deal with different perspectives and changing goals.

Beyond these challenges and the lessons from

the research process, we expect this effort to

make significant contributions to policymaking

and the science of landscape assessments. We

expect that the detailed ecological and spatial

structure of the model will help us understand the

relative importance of fine-scale management

decisions at broad scales and the importance of

broad-scale policy decisions at fine scales. We

expect to determine the locations in a region

that can provide the greatest contribution to

biodiversity goals. We expect to learn if a different

mix of policies could provide greater overall ecological and socioeconomic values than the current

policies. Finally, we expect to discover how much

fine-scale information is needed to answer our

questions and understand the dynamics of landscapes and ecosystems at broad spatial scales.

Literature Cited

Impara, P.C. 1997. Spatial and temporal patterns

of fire in the forests of the central Oregon

Coast Range. Corvallis, OR: Oregon State

University. 354 p. Ph.D. dissertation.

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. Cambridge, MA: Cambridge University Press: 179-277.
38

Introduction

A prudent manager desiring to meet objectives of

ecological sustainability and society’s economic

needs and social desires must consider a variety

of scales, both temporal and spatial. This is perhaps an obvious point, but the techniques and

operational requirements to manage at multiple

scales are not always so obvious. Large-scale

assessments and conservation strategies, such

as the Northwest Forest Plan and the ongoing

Interior Columbia Basin Ecosystem Management

Project, illustrate the challenges and frustrations

of managing at multiple scales. In particular,

meeting the legal requirements for species viability, as embodied in the Endangered Species Act

and the National Forest Management Act, has

forced a clear and explicit recognition of the need

for a broader view and has crystalized the difficulties managers face. In this paper, I introduce

some of these challenges and describe recent

attempts to meet them.

The viability requirement of the National Forest

Management Act illustrates the many facets of

species conservation. Viability is defined in the

current regulations (36 CFR 219.19) as:

...a viable population shall be regarded as one

which has the estimated numbers and distribution of reproductive individuals to insure its

continued existence in the planning area. In

order to insure that viable populations will be

maintained, habitat must be provided to support, at least, a minimum number of reproductive individuals and that habitat must be well

distributed so that those individuals can interact with others in the planning area.

Key points in this definition include considerations of numbers, distribution, interactions

(i.e., among individuals within populations), habitat, and boundary (i.e., planning area). New draft

regulations, as proposed following the report of

the Committee of Scientists (Federal Register

2000 65: 67514-67581), define species viability

as:

A species consisting of self-sustaining and

interacting populations that are well distributed

through the species’ range. Self-sustaining

populations are those that are sufficiently

abundant and have sufficient diversity to display the array of life history strategies and

forms to provide for their long-term persistence and adaptability over time.

New considerations introduced in these regulations include adaptability (a concept that includes

genetic diversity), and time.

All Scales Count

To evaluate whether management will contribute

to or detract from species viability, one must consider a variety of scales, both spatial and temporal. The reason for this is simple: animals respond to their environment at a variety of scales.

For example, consider the marbled murrelet

(Brachyrhamphus marmoratus). This bird nests

on large-diameter branches of large-diameter

coniferous trees, usually within patches of older

forest. At the microsite level, a tree must have a

sufficiently large limb to support the bird’s nest. At

a slightly larger scale, the important elements are

the nest tree itself and the structure of the canopy

surrounding that tree. A nesting murrelet feeds in

coastal waters and makes daily trips to the nest to

care for its young. The canopy must allow space

for a flight path into the nest. At the same time,

cover must be sufficient to protect the nest from

potential predators. Therefore, the structure of the

nest stand is also important as the size and shape

of that stand may influence the abundance of

predators and the susceptibility of the nest to predation. Over a broader scale, one must consider

Implications of Scale on Viability Assessments of Terrestrial

Wildlife Species

Martin G. Raphael1

1 Research wildlife biologist, U.S.Department of Agriculture

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 3625 93rd Ave. SW, Olympia, WA

98512-9193; Tel: 360-753-7662; e-mail: mraphael@fs.fed.us
39

the total extent of suitable nesting habitat, as this

determines the size of the murrelet population and

its overall distribution over a landscape.

As illustrated in this example, several levels of

habitat selection exist. The smallest scale is

where individual animals obtain resources at

any point in time. It is where a nest is located or

where a prey item is captured–a specific microsite

or habitat element. An intermediate scale is an

animal’s home range, the geographic area an

animal traverses to obtain resources during a

specified period. A description of habitat conditions within a home range might include the extent of various cover types, their arrangement

and pattern, and the composition of each of the

types of cover. A larger scale encompasses the

set of conditions that support a population of animals over time. The size of the area to consider

is determined by the extent of the population or

may be an arbitrary definition covering a specified

number of individuals from within a larger population. At an even broader scale, patterns of biodiversity might be described. This scale covers

the geographic area needed to support a community of species, each of which is represented

by populations. In this case, the area is large

enough to contain a variety of cover types and

structures, each of sufficient extent to support

these populations.

Research on habitat relationships of the northern

spotted owl (Strix occidentalis caurina) can be

used to illustrate the importance of consideration

of many scales. As evidenced in figure 1, spotted

owls choose nest sites in concentrated patches of

nesting habitat. This is suggested by the greater

difference between nest sites and random sites at

the smallest circle size. As circles around nests

grow larger, the differences between amounts of

habitat in nest sites and random sites grow

smaller. At very large sizes, both nesting circles

and random circles would reflect average conditions in the broader landscape. This example

shows that smaller scales reveal important biological relationships. In turn, larger scales are

necessary to describe population phenomena, so

both scales are important in assessing habitat

conditions.

Another important scale consideration is the effect

of study area boundary on measures of landscape

pattern. Using the example in figure 1, note that

the smallest circular area contains only one patch

of habitat and that the boundary defined by the

circle cuts off part of that patch. A measure of

patch size is biased because the circle is too

small to contain the whole patch. Similarly, measures of edge can be biased because artificial

edges are created around the boundary of the

study area. This suggests that calculation of

measures of landscape pattern should be done

on a landscape that is much larger than the average patch size in that landscape, perhaps on the

order of 10 to 50 times as large as the average

patch size.

Figure 1—Amount of spotted owl nesting habitat in circular areas of varying size. The figure on the left is a

comparison of mean (+ standard error) percentage of habitat in a sample of 89 nest sites and 100 randomly

located sites, Coast Range, Oregon. The figure on the right is a sample of one site showing habitat (dark) and

a nested set of circular areas.

Circular Area (ha)

0 200 400 600 800 1000 1200

Percent Habitat

10

15

20

25

30

35

40

45

50

Owl Sites

Random Sites

Circular area (hectares) 

Owl sites 

Random sites

Habitat (percentage of area) 

0 200 400 600 800 1,000 1,200
40

The temporal dimension is also important. Species viability cannot be assessed at a single point

in time. At any particular time, a species (or population) exists or it does not. Land managers are

generally more interested in the future. A typical

question is, If I manage the land in some manner,

is it likely the species will persist into the future?

Time can be assessed relative to generation time

of the species in question. Short-lived species

(e.g., most insects or annual plants) experience

many generations over a decade; longer lived

species may take a century or more for multiple

generations to pass. Viability assessments of

vertebrates are often considered over hundreds

of years.

Species Viability in the Interior

Columbia River Basin

The interior Columbia River basin presents another good illustration of the importance of scale

in evaluating viability of terrestrial wildlife (fig. 2).

In this case, we2 assessed habitat conditions for

a set of individual species at two geographic

scales, the subwatershed and the entire basin.

At the subwatershed scale, we estimated the total

extent of primary habitat within each of about

7,000 subwatersheds that make up the basin.

Quality of habitat was adjusted by using models

that accounted for more specific habitat elements

that might affect populations in that watershed.

2 Raphael, M.G.; Wisdom, M.J.; Rowland, M.M. [et al.]. 2001.

Status and trend of habitats of terrestrial vertebrates in relation to land management in the interior Columbia River basin.

In: Forest ecology and management. Elsevier Science B.V.

153(1-3): 63-87.

Figure 2—Trend in habitat of the pygmy nuthatch from historical to current to hypothetical future in the interior

Columbia River basin.
41

We then displayed the geographic distribution of

habitat quality over a species’ range at three periods in time (fig. 2): historically (circa 100 years

ago), currently (average conditions over the past

decade), and future (100 years into the future

under a supplemental draft environmental impact

statement alternative). We used three general

indices to evaluate, at the broad scale, condition

of habitat as it might influence species viability at

each period. We summarized the total amount

of habitat (actually a weighted average of habitat

quality relative to historical conditions), percentage of historical range that is occupied (extent),

and connectivity of habitat. By using Bayesian

methods and conditional probability tables, these

three indices were combined (see footnote 2 for

detailed methods) to summarize the likelihood of

conditions that would support the species at each

time.

As shown in this example, trend in any one

subwatershed is not particularly informative in

evaluating viability. It is necessary to take a much

broader view encompassing the species range to

gain such insight. But conditions within each

subwatershed are critical for building an aggregate picture of habitat suitability for a given species over an extensive landscape.

Conclusion

Scale is a vitally important consideration in assessing species viability. No one scale is sufficient. We need to consider all scales, from local

to regional, and each is important in answering

different questions.
42

Natural resource science and management seem

to have entered the “age of the landscape.” Historically, resources have been studied and managed from a stand, or site, perspective and have

generally been approached as single-issue problems. Forests, water, fish, and biodiversity were

treated largely as separate topics. The recent shift

to a landscape perspective is an explicit recognition that the world is far more complex than can

be comprehended from strictly site-based, singleissue studies. Thus, scientists and managers are

challenged to address resource issues at multiple

scales: site, landscape, regional, national, international, and integrated across multiple resources.

Examples of the latter include vegetation and

wildlife habitat interactions; upland vegetation

dynamics affecting water quantity and quality;

climate, vegetation, pest, disease, and fire interactions; ecosystem productivity and biodiversity;

and many others. Natural resource management

has become so pervasive that it is comparable in

scale to most large-scale natural patterns of resource structure and function.

My intent in this discussion is to point out some of

the prevailing issues and challenges facing resource managers and scientists alike in predicting

or “forecasting” possible trajectories of such complex landscapes. Under the assumption that the

climate and land use patterns of the future will be

different from the past, I presume that a processbased modeling approach is required, that is, an

approach that is robust to changing environmental

conditions and that can comfortably incorporate

increasing levels of complexity. The discussion

reflects my personal views and is not intended to

be a complete review of the issues and technologies available.

Natural resource issues occur across a range of

spatial and temporal scales. Most processes are

small scale, for example leaf physiology or water

infiltration. Others are intermediate, or landscape

scale, such as metapopulation dynamics or seed

dispersal. Few processes are truly large scale.

Most large-scale patterns are recognized as

“emergent properties,” that is, they arise from

small-scale processes and interactions yet reveal

coherent large-scale patterns. The distributions of

species and ecological zones and the regional

patterns of species diversity are examples of

emergent properties. Such large-scale emergent

properties often are correlated with large-scale

climate patterns. However, the regional climate

patterns are themselves emergent properties of

the small-scale fluid dynamics of the atmosphere,

playing out on a rotating sphere and interacting

with oceans, continents, mountains, and other

surface features, including vegetation.

Correlations between large-scale resource patterns and climate are useful in calling attention to

the relationship and point to likely causation. If we

could view the climate as a very slowly changing

phenomenon, for example, glacial-interglacial

cycles, then we could largely ignore mechanisms

of interaction between resources and climate and

simply focus on the resource processes. However, we now know that the world is heating up

and that perhaps half of the current rate of heating

is human caused (Trenberth 2001). We cannot

say with certainty what the future climate holds,

only that we cannot assume the status quo. Thus,

we must strive to understand and predict resource

interactions and future trajectories from first principles, which take us to the small scale of dynamic processes. Yet, we must acquire predictive

capabilities of future resource trajectories over

large spatial extents. It is ultimately the regional

emergent properties of resources for which we

must manage. The challenge of the day, therefore, is to develop predictive capability over very

large spatial extents from small-scale processes.

Projecting Potential Landscape Dynamics:

Issues and Challenges

Ronald P. Neilson1

1 Bioclimatologist, U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 3200 SW Jefferson Way, Corvallis, OR

97331; Tel: 541-750-7303; e-mail: rneilson@fs.fed.us
43

A Framework for Science and

Management

Scientists appear to be converging on a threescale structure for developing model-based predictive capabilities of resource trajectories and

multiresource interactions. These are the site, or

stand scale, spanning a few tens of meters; the

landscape scale, spanning a few to tens of kilometers; and the regional or continental scale,

spanning hundreds to thousands of kilometers.

Approaches to these three scales are either top

down (empirically based) or bottom up (process

based), being distinguished primarily by the resolution of the simulation grid. Stands may be considered as spatially homogeneous at a scale to

about 10 meters and may be treated as point

simulations, e.g., traditional stand or “gap” models

(Shugart and Smith 1996). Stands are also often

simulated as spatially explicit with a grid resolution

of perhaps 1 meter, but this is less common

(Miller and Urban 1999, Peters 2000). Each grid

cell contains a full model simulation and may or

may not include cell-to-cell interactions. The spatially explicit approach is bottom up; the spatially

aggregated approach is top down. The stand or

point model can be placed on a grid for spatially

explicit simulations of heterogeneous landscapes

with a grid resolution of perhaps tens of meters.

Regional-scale models are of necessity coarse

grid, ranging in grid resolution from about 1 km up

to about 50 km or more. Clearly, even the highest

resolution regional model must absorb considerable spatial heterogeneity within each grid cell.

Independent models have been developed at all

of these scales; however, there is little coherency

among those differently scaled models. For example, traditional “gap” models, which simulate

succession in a small opening, such as a singletree blowdown, use empirical curves based on

degree-day sums (temperature sums over time)

(Botkin et al. 1972), whereas other models might

use elaborate physiologically based processes for

the same purpose (Running and Hunt 1994). In

the extreme, such models can produce opposite

responses to external forcing, such as climate

change, even though both may be equally well

calibrated to current conditions (Loehle and

LeBlanc 1996).

One approach to building a verifiably accurate

regional-scale model is to take advantage of the

top-down and bottom-up approaches across all

scales while relying on a core modeling paradigm

that carries through all scales. Thus, the core to

all of the scales is the site-based model, which

must incorporate such things as leaf physiology;

competition among life forms for light, water, and

nutrients; soil hydrology; and other processes.

At each unique scale, scale-specific phenomena

likely must be included, but the approach may

vary depending on whether it is top down or

bottom up. Many forest simulation and management models do not require the physiological,

biogeochemical, and hydrological processes

(Crookston and Stage 1999). These are empirically based models that cannot accept a changing climate as input. I thus restrict my comments

to the process-based approach to ecosystem

modeling.

The unique aspect of global ecosystem modeling

in comparison to more traditional ecological modeling is that the primary points of interest are the

emergent, large-scale spatial patterns and their

dynamics. Large-scale biogeographic modeling

can be simulated from small-scale processes

(leaf to landscape), but calibrated to large-scale

biogeographic and hydrologic patterns (Neilson

1995). The challenge is to find the simplest model

structure that is sufficient to capture the necessary processes at all the appropriate scales. One

may find that a particular mathematical representation of a process works fine in most locations,

but needs to be recalibrated at each. Presumably,

however, if one is appropriately representing the

processes, a single calibration will suffice in all

locations. For example, I used large-scale biogeographic and hydrologic patterns as simultaneous

constraints to help determine both model structure and calibration (Neilson 1995).

In constructing the Mapped Atmosphere-PlantSoil System (MAPSS) vegetation distribution

model, I coupled the simulation of leaf area index

(LAI, the area of leaves per unit area of ground) to

the simulation of site hydrology (Neilson 1995).

The LAI was used, in part, to define boundaries or

ecotones between different vegetation types, such

as that between forest and savanna, thus providing the biogeographic constraint at the regional

and continental scales. The simulation of LAI was

dependent upon the accurate simulation of seasonal soil moisture and its distribution through the

soil profile, as transpiration is a function of leaf

area, stomatal conductance, and vertical root

distribution. The hydrologic module was calibrated
44

against locally observed runoff in contrasting regions across the United States and was initially

structured quite simply. However, the simple

structure required unique calibrations for each

region of the country. I incrementally increased

the complexity of the hydrology model until I found

the minimum complexity that would accurately

simulate runoff in all the diverse regions of the

country with a single calibration, and which also

accurately simulated the LAI to provide proper

mapping of vegetation boundaries. Thus, the

model was simultaneously constrained by both

vegetation and hydrologic patterns at the large

scale of emergent properties, but was based on

the simulation of small-scale processes.

A robust framework of science can be constructed

by combining the top-down and bottom-up approaches. Each spatial scale can be represented

from both perspectives. At the top of the hierarchy, grid cells are sufficiently coarse to simulate

wall-to-wall coverage but with uncertainties owing

to subcell heterogeneity, because each grid cell is

usually treated as being spatially homogeneous.

Higher resolution grids can be used; however, the

finer scales would only be feasible over smaller

spatial extents, that is within a sampling framework over specific watersheds with subplots and

so on. Each scale can inform the other; process

constraints can be imposed through all levels

from a common small-scale theory, and largescale constraints, such as biogeographic patterns,

can be imposed from above. Thus, each level has

the ability to peer up or down one level, and the

structure can be moved up and down levels for as

many levels as are of interest. Yet, the core processes are applied at all spatial scales, thus ensuring that the patterns and sensitivities of the

applications at different scales will be fully internally consistent.

Historical management practices can be similarly

approached, spatially explicit at a scale of focus,

statistical below, and deterministic above. For

example, at the national scale, targets might be

set for harvest or fuel reduction practices, but

their locations are not determined. These targets

might be further dissected to specific regions,

providing a spatially determined component, but

within each domain, the cutting or thinning represents a statistical target and is not spatially determined. This process can continue iteratively, until

final operations are spatially determined at the

finest scale of interest. This is the inverse of the

natural landscape, where the large-scale patterns

are emergent from below and constrained from

above. Management emerges from the top and is

implemented below. However, top-down management also clearly is constrained by the bottom-up

spatial resource availability and condition. Nestedscale management modeling can be vertically

integrated with the nested-scale ecological modeling. Some of the issues and challenges in constructing the ecological side of this dual hierarchy

are addressed below.

Subcell Heterogeneity: Representing

the Landscape in Coarse Grids

Much of the challenge of large-scale resource

management revolves around the opposing concepts of spatial heterogeneity and homogeneity.

For example, as one moves from wet to dry along

an aridity gradient, the density of a forest will thin

to a point where a grassy understory just begins

to be supportable because of enhanced understory light. This is an unstable threshold condition

because new processes suddenly enter the system forcing it away from the point of transition as

follows. Introduction of an understory entrains

positive feedbacks through competition for water,

which further thins the canopy overstory. Additional feedbacks through fire can thin the overstory even more, allowing yet more grass and

more fire until equilibrium is reached. Thus, the

system undergoes a transition from a spatially

homogeneous entity to a heterogeneous one.

Along this hypothetical aridity gradient, with no

topographic complexity, there is an endogenous

shift from a homogeneous system (forest) at the

wet end to a heterogeneous system (savanna)

with increasing aridity and back to a homogeneous system (grassland) with further increases

in aridity. The system has also gone through scale

transitions, from coarse-scale forest, to fine-scale

tree-grass patches, to coarse-scale grassland.

Transitions between these physiognomic shifts in

heterogeneity are generally termed ecotones and

occur at the point of finest scale interfingering

pattern between the adjacent homogeneous

types.

If we interject topographic complexity to the above

moisture gradient, the spatial disposition of ecotones both horizontally and with elevation can

become quite complex along both elevational and
45

horizontal temperature and moisture gradients. A

transect along the west slope of the Rocky Mountains from southern Idaho to the Mexico border

illustrates the complex shifts in elevational ecotones along latitudinal temperature and moisture

gradients (Neilson 2003). Winter precipitation

decreases from north to south, but summer precipitation increases from north to south in the form

of the Arizona monsoon. In combination, the winter temperature and summer moisture gradients

create a latitudinal “wedge” of ecotones, upper

elevational ecotones increasing with decreasing

latitude and lower elevational ecotones decreasing with decreasing latitude. In the southern part

of the transect, the wide elevational separation of

ecotones creates the classic ecosystem zonation

patterns described by Whittaker and Niering

(1965) on the Santa Catalina Mountains, Arizona,

and earlier by Merriam (1890) on the San Francisco Mountains, Arizona. At the northern part of

the transect, however, the elevational ecotones

converge, creating a tremendous amount of spatial diversity across microhabitats within comparatively small landscapes. The result is a spatial

pattern of complexity through the region that contains both vertical and horizontal gradients of diversity. Peet (1978) described a similar gradient

along the east slope of the Rocky Mountains.

It is well recognized that diversity tends to increase at ecotones as the dominant organisms

from neighboring domains intermingle into complex combinations (Hansen et al. 1992). Trees

and grass, for example, interdigitate at the prairieforest ecotone, enhancing diversity. The same

type of interdigitation and spatial diversity gradients occur at elevational ecotones at the southern

end of the Rocky Mountain transect, for example

in the Santa Catalina Mountains. At the northern

end of the transect, however, with the spatial convergence of ecotones, the different vegetation

zones sort out on unique topographic slopes, aspects, and soils, compressing the interdigitation of

vegetation from the macroscale to the microscale

and creating a wholly new elevational zonation

pattern.

Thus, attempts to understand the patterns of alpha, beta, and gamma diversity (local, gradient,

and regional) at, for example, only one end of the

Rocky Mountain transect, would be only partially

revealing and would provide little general understanding of the landscape patterns. The empirical

analysis that led to the description of this wedge

of ecotones was based on a set of nested-scale

experimental seedling transplants along environmental gradients at scales of meters (shrub to

intershrub), tens of meters (landscape unique

geomorphic positions), hundreds of meters (elevation), and hundreds of kilometers (regional)

(Neilson and Wullstein 1983). Yet, simulations at

the relatively coarse scale of 10-km resolution

(Neilson 1995) were able to elicit the same regional gradients in ecotones, providing inferences

to spatial patterns and processes at much smaller

than grid-cell resolution.

Such convergence of ecotones may tend to occur

where steep airmass gradients converge. I propose that these “nodes” of airmass convergence

drive a rescaling of ecological gradients, which is

most apparent at the landscape scale. At a distance from these nodes, homogeneous vegetation occurs in large patches, but near the nodes,

smaller patches of vegetation intermix on microsites dictated by topography and soil (Neilson et

al. 1992). But, perhaps most interesting, is the

possibility of inferring landscape-scale patterns

from the coarse-scale patterns simulated by the

models. Such top-down inference of landscapescale pattern must, of course, be validated with

direct simulation of spatially explicit landscape

patterns across regional gradients.

Much of the art in landscape simulation arises

in the challenge to validate innovative top-down

modeling techniques with direct, bottom-up simulations and ground- or satellite-based data. The

question becomes one of how to represent and

simulate subcell patterns and dynamics accurately, but without having to do the direct simulation at all locations. A topographically induced

mosaic of forests and grasslands would appear

as a savanna in a large grid cell. The savanna

may provide sufficient accuracy for some issues,

but for others, it clearly will not. The spatial heterogeneity can be handled through explicit bottom-up simulation of the complex terrain, or as

unique simulations of each patch type as an

aggregated homogeneous entity. There are also

innovative ways to explicitly recognize heterogeneity in the aboveground components at the landscape scale, while preserving a more homogeneous belowground competitive environment.
46

Fires and other disturbances in the landscape

produce significant problems for large-scale simulations with coarse grids. Fires create a mosaic of

uneven-aged patches, with new patches being

created as often as each year in some cases.

There are numerous differences in the vegetation

of an area 1 year after fire and 15 years after fire.

In contrast, the differences in vegetation 100

years and 115 years after fire are minimal if the

climate and substrate are the same. Thus, one

approach is to allow creation of new patches each

year and track them individually, but as they become increasingly similar with age, merge them

back together. Initially in the course of model development, these patches, in an otherwise homogeneous grid cell, might be noninteracting and

only be represented uniquely by their areas and

ages. In grid cells with complex terrain, these

patches could be maintained on unique soils and

with unique climates, but again nonspatially. Eventually, some level of interaction among patches

could be implemented, but still without spatially

explicit representation within the cell. Spatially

explicit simulations on fine-scale grids, coupled

with ground and satellite data would assist in the

validation of these top-down approaches.

Topographically induced spatial heterogeneity

presents additional difficulties when integrating

across resources, such as between vegetation

and hydrologic processes. Hydrologic processes

are strongly coupled to vegetation processes and

span scales from local infiltration processes to

regional river routing, yet most of the physics occurs at very fine scales. A bottom-up modeling

approach will couple the vegetation and hydrologic point-scale processes and also account for

the horizontal flows of surface and subsurface

water. Thus, accurate representation of riparian

zones and stream hydrology is possible. Representation of these interactions in coarse grids also

may be possible along the lines described above,

but would require direct linkage of subgrid patch

types for routing of water between upland and

lowland parcels.

Conclusions

Current modeling approaches for natural resource

management often are organized around three

different scales: patch, landscape, and regional to

global. Most large-scale modelers are attempting

to incorporate the important processes that occur

at all three scales: patch (competition, gas exchange); landscape (fire, dynamic heterogeneity);

and global (emergent, spatial pattern). It will be

very important for practitioners working within any

one of these three modeling communities to coordinate closely with those working at the other

scales. Patch models built around one type of

ecosystem or in one region may not be well structured for working in other systems or regions.

Consistency of process should be maintained

across scales. If models are to be nested or

linked across scales, then their processes should

be based upon the same theoretical underpinnings, or they may not translate well across

scales. An area of research that I believe may

have some potential, but that remains largely

untapped, is the possibility of downscaling from

regional to landscape patterns by using coarsescale information, as in the relation between spatial ecotone convergence and landscape diversity

patterns.

The key points of this discussion serve to emphasize the importance of accurate simulation of ecosystem constraints at all relevant scales. Under a

rapidly changing climate and with changing physiology under elevated CO2

, constraints normally

assumed to be stationary must now be assumed

to be dynamic and must be explicitly simulated.

Heterogeneous landscapes are among the most

complex, yet globally among the most common

types of ecosystems. Accurate simulation of landscape patterns and processes under global

change requires attention to organism-level and

lower processes within the constraints of biomelevel dynamic biogeography. A carefully crafted,

hierarchical framework with dual-scale representation at each level can provide the structure for

integration among natural resources and between

management and natural processes in a rapidly

changing environment.

English Equivalents

1 meter (m) = 3.28 feet

1 kilometer (km) = 0.62 miles
47

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of a forest ecosystem process model for other

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global-scale models. In: Ehleringer, J.R.; Field,

C., eds. Scaling processes between leaf and

landscape levels. San Diego: Academic Press:

141-158.

Shugart, H.H.; Smith, T.M. 1996. A review of

forest patch models and their application to

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131-153.

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46: 429-452.
48

This manuscript overviews issues of scale in relation to the core research of the USDA Forest Service, Pacific Northwest Research Station (PNW)

Boreal Ecology Cooperative Research Unit located in Fairbanks, Alaska. The unit’s main research focus is the long-term ecology of boreal

forests in Alaska’s interior region. Other ongoing

and related projects focus on pattern and change

in tundra and on effects of silvicultural practices

on white spruce (Picea glauca (Moench) Voss;

the major economically important tree species)

regrowth following various cutting and clearing

treatments. Alaska’s interior region and North

Slope have experienced a warming trend over

the past two decades that has been unprecedented in the last century (Barber et al. 1998,

Hammond and Yarie 1996, Juday et al. 1998,

Serreze et al. 2000). Understanding how key patterns and processes scale in time and space is

absolutely critical to understanding how this system may respond to changing temperatures.

An alternative title for this paper, “Boreal forest–

Tundra with trees?”, makes reference to the similarities between tundra vegetation and taiga forest

understory. The understory vegetation in flat,

low-lying areas in northern boreal forests is remarkably similar in both composition and structure to tussock tundra vegetation (Jorgenson et al.

1999, 2001; Walker et al. 1994). This type is

codominated by sedges (Eriophorum vaginatum

L., Carex lugens Holm) and shrubs (Betula nana

L. or B. glandulosa Michx., Ledum palustre L. ssp.

decumbens (Ait.) Hulten or L. groenlandicum

Oeder, Salix L. spp.) and underlain by complete

coverage of mosses and lichens (Sphagnum L.

spp., Hylocomium splendens (Hedw.) Schimp.

in B.S.G., Pleurozium schreberi (Brid.) Mitt.). In

the taiga, black spruce (Picea mariana (P. Mill.)

B.S.P.) is also present in open, sparse stands.

There is a gradient between full-scale wetlands

with few trees to fully closed forests without

permafrost.

The need to explicitly recognize and account for

scale in ecosystem studies has become increasingly appreciated in the past two decades. Studies

that examine pattern or process in space must

consider explicitly the sources of variation that are

either secondary or primary to the research. This

is not a new idea; it is the foundation of biogeography and classical plant ecology, both of which

look at patterns of organisms in space and attempt to determine the causal mechanisms behind those patterns. What has become increasingly recognized is how closely together temporal

and spatial patterns are tied in most systems, and

also how traditional ecological hierarchies do not

map directly to more fundamental hierarchies

(Allen and Hoekstra 1992, Allen and Starr 1982,

O’Neill et al. 1986). Because all landscapes have

some degree of dynamism, the spatial patterns at

any point in time are the result of multiple processes operating at multiple time scales (Delcourt

et al. 1983). The National Science Foundation’s

(NSF) Long-Term Ecological Research (LTER)

Program addresses the problem of temporal

scales directly by focusing research resources at

selected sites over periods sufficient for explicit

study of decadal-scale pattern (Franklin 1987).

The Bonanza Creek and Caribou-Poker Creeks

LTER site in the Fairbanks region is one of six

LTER sites nationally that are cofunded by NSF

and USDA, and is one of two such sites within

PNW.

Northern ecosystems represent opportunities

to examine natural processes at their limits. By

focusing at these limits, we can better understand

these processes and their roles in complex situations where many factors are operating simultaneously. What is most distinctive about these

systems as a whole is that a single factor, temperature, controls essentially all other processes

(Chernov and Matveyeva 1997). Therefore

changes in this single factor will affect almost all

Scaling and Landscape Dynamics in Northern

Ecosystems

Marilyn Walker1

1 Unit leader, U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station, Boreal Ecology

Cooperative Research Unit, P.O. Box 756780, University of

Alaska Fairbanks, Fairbanks, AK 99775-6780; Tel: 907-474-

2424; e-mail: mdwalker@fs.fed.us
49

processes and patterns. I examine the interactions between climate, species abundance and

distribution, and disturbance regimes along a

gradient from the northern limit of plant growth to

the most northern forests (fig. 1). This gradient

covers key thresholds of biodiversity, including the

first introduction of woody-dominated ecosystems

in the low arctic to the first dominance of trees in

the northern boreal forests. The introduction of

new functional types into the system, first shrubs

and then trees, has dramatic impacts on temporal

and spatial patterns, and on how disturbance and

vegetation interact.

Vegetation zonation within the arctic regions has

been described by many authors, and various

approaches have been used to describe these

geobotanical zones (Walker 2000). Although

slightly different criteria can be used resulting in

different outcomes, within Alaska it is useful to

recognize three broad zones defined by summer

temperature and dominant plant structural types.

Table 1 lists characteristics of the three major

arctic zones along with transitional and fully boreal

zones. There are multiple processes and characteristics associated and interacting with these

structures. Species richness is very tightly correlated with temperature at multiple scales in these

systems (Chapin and Danell 2001, Walker 1995,

Walker et al. 2001). The decrease in species richness from south to north is mainly due to loss of

species rather than turnover in species, so that

the most northerly floras represent depauperate

versions of the southern ones (that is not wholly

true, but it is a reasonable representation). Therefore, the latitudinal similarities among the vegetation and flora increase from south to north,

because there is a smaller pool of species available. Until treeline is encountered, the dominant

species are the same or closely related throughout the zone; however, the species representing

the northern treeline vary throughout the region

(Alexandrova 1980).

Because this is such a major gradient in both

climate and structure, many other variables are

simultaneously changing and correlated along the

gradient including available moisture, energy balance and radiative transfer, distribution and depth

of permafrost (permanently frozen ground), biomass and production, and others. Changes in

vegetation structure and composition along this

gradient do not follow a classic life-zone pattern

of movement up and down an altitudinal gradient.

Instead, trees and shrubs first come into the landscape at midslope positions (fig. 2) (Van Cleve

and Viereck 1981). The presence of shallow

permafrost results in a sealed hydrologic system

and drainage conditions unsuitable for tree growth

at lower slope positions. The exception is black

spruce, Picea mariana, which grows in open

stands in permafrosted lowlands or on north-facing slopes.

The introduction of trees into the landscape has

an overridingly important influence on the spatial

and temporal domains of the systems (fig. 3). The

main differences between the two systems are:

1. Insects and herbivores have a more consistent and extensive role in the boreal system.

2. The roles of fire and flooding are out of scale

relative to other disturbances in the boreal

system, with fire being the more significant.

3. The formation and melting of ice wedges is

a significant disturbance in the Arctic,

whereas in the current boreal climate, the

main effect is surface melting of permafrost

(thermokarst), with less recovery. Ice wedge

formation is on a scale small enough to be

considered insignificant as a landscapeforming process.

4. The current timber harvest regime is quite

small relative to other stand-replacing disturbances. However, new technologies and

economies in fiber harvest may result in a

very different regime in the near future.

5. Patterns of eolian loess distribution in the

systems differ because of an interaction with

topography, vegetation, and wind regime.

Arctic rivers follow broad, often anastomosed

pathways with large expanses of barren or

nearly barren silt and sand bars. Nearly constant wind redistributes this loess across the

landscape, with major influence on patterns

of vegetation composition and productivity

(Walker and Everett 1991, Walker et al.

1998). The Alaska boreal forest has little wind

compared to the Arctic, and although there

are active sand and silt bars associated with

medium and large rivers, much of what is

blown off is effectively trapped by the riparian

and flood-plain vegetation.
50

Figure 1—Major ecosystems of Alaska. Source: Markon, C. 1991. US Geological Survey digital map of the major ecosystems

of Alaska. Based on the map unit boundaries delineated by the Joint Federal-State Land Use Planning Commission for

Alaska in 1973. Scale 1: 2,500,000.
51

Table 1–Structural characteristics of major arctic-boreal vegetation and ecosystem zones

Mean July

Zone Vegetation structure temperature

Polar desert Mainly herbaceous or nonvascular, discontinuous scattered plants. 1-3 °C

Mosses, when present, limited to acrocarpous species or small

hummocks of individual clones.

High arctic Mainly herbaceous (Graminae and Cyperaceae); woody species in 4-6 °C

genera Salix and Dryas with woody sections limited to below ground

or 5 cm above ground, areas of semicontinuous cover in protected

areas. Increasing diversity of pleurocarpous mosses in small clusters

of plants.

Low arctic Codominated by herbaceous (mainly graminoids of Cyperaceae) and 7-9 °C

woody species in the Ericaceae family and in genera Salix, Dryas, and

Betula. Woody sections to as high as 40 cm above ground. Continuous

cover. Development of full moss and lichen carpet underlying vascular

species with high nonvascular species diversity. Sphagnum spp. dominate

moss carpets in certain regions.

Treeline or Tall shrubs from 1 to 2 m tall representing four to five families, with 10-12 °C

woody tundra graminoids of Cyperaceae subdominant. Scattered islands of coniferous

trees, occasional stands of poplar (Populus spp.) or tree birches (Betula

spp.). Increased moss biomass and production.

Boreal forest Uplands completely dominated by fully developed forest, mainly of Picea, 12-15 °C

Betula, Populus, and Larix. Graminoid-dominated stands of Cyperaceae

limited to areas of permafrost in lowlands. Moss biomass and production

extremely variable depending on forest type and condition, from none in

deciduous upland forests to thickest development of carpets in open,

permafrost lowlands.
52

Figure 2—Arrangement of major structural-dominance vegetation types along gradients of

megascale climate and mesotopography (catenas) in Alaska and western Canada. (Latitude is

shown for each location.) Symbols: P–polar desert, see table 1; H–heath, ericaceous and

rosaceous prostrate and dwarf shrubs with lichens; W–fen (wet meadow) dominated by species of

Carex (s) or grasses (g), mainly Dupontia fisheri R.Br.; T–tussock tundra, Eriophorum vaginatum

L., Carex bigelowii Torr. ex Schwein. with low and prostrate shrubs; S–shrub tundra, species of

erect Salix L., Betula L., and sometimes Alnus P. Mill. with an understory of prostrate shrubs,

graminoids, and mosses; O–open woodland/muskeg, combination of sparse black spruce Picea

mariana (P. Mill.) B.S.P. with tussock tundra; F–forest, mainly Picea glauca (Moench) Voss as well

as Populus tremuloides Michx. and Betula papyrifera Marsh.
53

The increased importance of fire and animals is a

direct result of the presence of trees but also is a

function of climate. Climate sets an ultimate limit

on tree growth and in some cases animal distribution (particularly insects; Chapin and Danell

2001), but the presence of trees also drives both

insect and fire regimes. In the Arctic, patterns of

vegetation and major differences in ecosystem

function can be clearly linked to a series of mostly

abiotic controls (Walker et al. 1994, Walker et al.

1998). Although the arctic biome in Alaska has

varied significantly in spatial extent and appearance over the past million years, most of its flora

formed in major glacial refugia and has since

been redistributed to form existing patterns

(Hultén 1937). The Alaska boreal ecosystem, in

Figure 3—Spatial and temporal domains of the major landscape-forming natural disturbances in

boreal and low arctic ecosystems, respectively (adapted in part from Walker and Walker 1991).

Timber harvest is overlain on the boreal system to show its extent relative to other disturbances.
54

contrast, had its dominant species invade only

within the past 10,000 years, in a series of

“waves” that represented almost instantaneous

appearance over large areas (Anderson and

Brubaker 1994, Hu et al. 1993). Existing patterns

within the Alaska boreal zone can be explained

almost completely by a combination of mesotopography and succession following disturbance

(Van Cleve et al. 1983, 1996).

The ability of a few species to play a dominant

role in ecosystems processes has major implications for many management issues as well as for

our ability to comprehend the potential for change

in the system under changing climate. Because

arctic systems are controlled by fairly fixed sets

of regimes, developing comprehensible models

of landscape change related to climate change

should be possible (Epstein et al. 2000). In the

boreal system, however, the strong interaction

between biota, climate, and disturbance regime

makes for a much more chaotic system (Rupp et

al. 2000, Starfield and Chapin 1996). Getting fire

management “right” is perhaps the single most

important management question in Alaska’s interior region today. Fire has more than major ecological consequence in Alaska; fire fighting is a

major source of cash economy in many small

villages.2

 The Alaska Fire Service’s current policy

is to control human-caused fires and to let natural

fires (started by lightning) burn unless they

threaten life or property.3 Their goal is to support a

natural regime, with the idea that ultimately such a

regime will maximize all major economic landscape uses: wildlife habitat, recreation, and timber

harvest. Because fire regime is so closely tied to

both climate and vegetation, it seems unlikely that

any policy other than the current one could be

justified by scientific evidence. A natural fire regime will forever be a moving target, however,

and thus management goals need to follow the

regime rather than dictate it.

Forest harvest in the Alaskan interior represents a

scale issue mainly in the sense that current forest

harvest is on a scale small enough that it can be

considered ecologically insignificant. A closer examination indicates this view to be somewhat of a

falsehood, however. Most harvest is on private

lands owned by regional corporations. Forest

industries on these lands are not economically

viable from a market perspective but are subsidized as a way of getting local timber and firewood and providing employment in small villages.4

Harvest on public lands is primarily within the

Tanana Valley State Forest and to a lesser degree

on Bureau of Land Management lands. Current

harvest rates on these lands are at about 800

acres per year, and many offered sales are not

purchased (Crimp et al. 1997). Forest harvest is a

public concern, however, for the following reasons: (1) Sustainability of the harvest resource,

mature white spruce stands, is little understood

and highly variable in time and space. There has

been no systematic analysis of forest practices

over the last 30 to 50 years to analyze changes in

composition following harvest, but there is some

evidence that certain harvest practices may result

in a long-term dominance of deciduous species,

an undesirable management outcome if white

spruce harvest is to be sustained. Natural reseeding and successful establishment of white spruce

are dependent on timing of cone crops and herbivore population levels, both of which vary in time,

creating an uncertainty that is beyond management possibility. (2) Most harvests are in highly

visible areas near roads and along rivers, and

thus engender public scrutiny and debate. Although the level of harvest is essentially invisible

relative to large timber industries, it is of great

concern locally. (3) The Alaska economy is almost

completely dependent on natural resources, both

from extraction and tourism viewpoints. Changing

global markets for fiber and new technologies that

make fiber use more practical could potentially

lead to a regional fiber industry that would not be

so dependent upon certain vegetation types.

Thus, although the current timber industry effect

is masked by the effects of fire, fiber extraction on

large scales could change this. A firm ecological

2 Chapin, S.F., III. 2001. Personal communication. Professor,

University of Alaska, Fairbanks, P.O. Box 757520, Fairbanks,

AK 99775.

3 Jandt, R. 2001. Personal communication. Ecologist, Alaska

Fire Service, Bureau of Land Management, P.O. Box 35005,

Fort Wainwright, AK 99703. 4 Wurtz, T. 2001. Personal communication. Research

ecologist, U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station, Boreal Ecology Cooperative Research Unit, P.O. Box 756780, University of Alaska

Fairbanks, Fairbanks, AK 99775-6780.
55

understanding of how disturbances operate in this

system in time and space is therefore essential to

our ability to provide input on sustainable management practices.

In conclusion, Alaska is considerably different

from other states in terms of having extensive,

remote landscapes that are mostly undeveloped.

Management of Alaska landscapes must consider

the interactions between the spatial and temporal

scales of various disturbances. Both long-term

data collection and retrospective analysis are

important tools for understanding the frequency

and importance of certain types of events. Managing for sustainability must consider that the range

of variability in key disturbances will rarely match

with the affected spaces and timeframes required

for most management decisions.

Metric Equivalents

1 acre = 0.405 hectares

Degrees Fahrenheit = 1.8 °Celsius + 32

Literature Cited

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their division into geobotanical areas. Cambridge, United Kingdom: Cambridge University

Press. 247 p.

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Allen, T.F.H.; Starr, T.B. 1982. Hierarchy: perspectives for ecological complexity. Chicago,

IL: University of Chicago Press. 394 p.

Anderson, P.M.; Brubaker, L.B. 1994. Vegetation history of northcentral Alaska: a mapped

summary of late-Quaternary pollen data. Quaternary Science Reviews. 13: 71-92.

Barber, V.A.; Juday, G.P.; Finney, B.P. 1998.

Tree-ring data for climate reconstruction and

indication of twentieth century warming and

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Chapin, F.S.; Danell, K. 2001. Scenarios of

biodiversity change in the boreal forest. In:

Chapin, F.S.; Sala, O.; Huber-Sannwald, E.,

eds. Global biodiversity in a changing environment: scenarios for the 21st century. New York:

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Crimp, P.M.; Phillips, S.J.; Worum, G.T. 1997.

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Delcourt, H.R.; Delcourt, P.A.; Webb, T., III.

1983. Dynamic plant ecology: the spectrum of

vegetational change in space and time. Quaternary Science Reviews. 1: 153-175.

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57

In this presentation, we describe perspectives

about landscapes and scales of analysis appropriate to understanding the nature of relationships

between people and the environment of which

they are a part. We also discuss how to improve

integration of human and biophysical considerations in the study and management of landscapes. Given the purpose of this conference, the

paper is not in the format of a formal review or

synthesis of the literature. This paper reflects the

experience of the authors whose work has collectively spanned several decades and a variety of

topics related to people and natural resource interactions. Our observations might best be considered as propositions to aid discussion rather

than scientific conclusions or testable hypotheses.

Landscapes Are in the Eye of the

Beholder

Landscapes come in many sizes. There is no one

right definition for what a landscape is (or what it

means to different people) 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,

other times by forest managers, and yet other

times by citizens. Technical definitions are important for technical analyses but not necessarily

important to everyone; they are a means to oftenunclear ends. The 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 most important, yet

least well-done step, particularly if all interested

parties are not included up front.

In a sense, the meanings that landscapes hold

are constructed by those viewing the landscape or

interacting with it in other ways. Each meaning is

different, not better or worse. Full understanding

of the values and meanings landscapes produce

requires that analyses be inclusive of the people

who interact with the landscape. The implication

of different types of meanings is that conflict is

likely to occur where such meanings collide.

People Think and Act at Multiple

Scales for Many Reasons

No one way to divide time and space 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 summarized below.

Many values are important to people. Many

values are important to people as they think about

and use forests and other landscapes. These

include a variety of commodity, public use, amenity, environmental quality, spiritual, and health

values. Such meanings 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. And 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, expertise beyond

the biophysical sciences is required.

Landscape Perspectives

Roger N. Clark,1 Linda E. Kruger,2 Stephen F. McCool,3 and George H. Stankey4

1 Research social scientist, U.S. Department Agriculture,

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 400 N 34th Street, Suite 201, Seattle,WA

98103; Tel: 206-732-7833; e-mail: rnclark@fs.fed.us.

2 Research social scientist, U.S. Department Agriculture,

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 400 N 34th Street, Suite 201, Seattle,WA

98103; Tel: 206-732-7832; e-mail: lkruger@fs.fed.us.

3 Professor, School of Forestry, University of Montana,

Missoula, MT 59812; Tel: 406-243-5406; e-mail:

smccool@forestry.umt.edu.

4 Research social scientist, U.S. Department Agriculture,

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, Corvallis, OR 97331; Tel: 541-737-

1496; e-mail: ghstankey@fs.fed.us.
58

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 (political, economic, cultural) people hold in the landscape at

different scales and the decisions they make

about how they interact with it 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 units. There are often mismatches between these organizational units and biophysical

scales that need to be reconciled before any

analysis begins if an integrated solution is desired. Putting the pieces together later has proven

to be difficult.

People act at multiple spatial scales. These

include microsites, areas (e.g., a grove of trees,

meadows), drainages, watersheds, landscapes

(e.g., “the valley”), regions (e.g., Puget Sound),

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 or scientific needs. Meanings cannot 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.

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

public acceptance of forest management practices.

We must beware of the ecological fallacy

when drawing conclusions about people.

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. Looking up and down this sort of scale is not Photo by Roger Clark
59

simply an aggregation or disaggregation issue. 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. And what may be acceptable at

one scale may not be so at another.

Human habitats are definable. Concepts that

help explain why some wildlife species behave as

they do also help explain the behavior of people.

For example, we have found in studies of

recreationists that home ranges exist for both

residents and tourists (a migratory species!).

Edges, particularly along water, affect use. Critical

habitats are definable and include attributes that

relate to many temporal and spatial scales. Human habitats—for recreation, spiritual, and aesthetic purposes—are dynamic in time and space.

Travel corridors and how they are accessed influence patterns of use. Place attributes and meanings (at multiple scales) influence choices people

make. However, the meanings people attach to

specific places, and how they define their critical

habitat needs, often are not correlated with certain

types of biogeographical features mapped by

biologists. 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.

Corridors channel energy. Natural topography

and features and human-created corridors channel air, water, critters, and people. The intersections of corridors (water crossings, power

corridors, dams) or flows within them often reveal

conflicts and compatibilities between public values

and uses and other resource values.

Acceptance of change varies both in time and

space. Judgments about the acceptability of

changes depend on their nature, extent, cause,

and location with respect to the meanings and

values people attach to specific places and landscapes. Photo by Linda Kruger
60

Problem Framing Is the Key to

Success

It is important not to “start” until one gets the

issues and questions right. This usually means

we need to step back from individual, disciplinary

definitions and join with other “–ologies” and interests. We need to be sure we are not solving

“solutions” or solving the “wrong” problem. We

must learn from one another about how we “see”

and define landscapes so that we can jointly construct opportunities and redefine problems and

issues and then develop explicit questions to

drive joint actions. Action in today’s society requires multiple actors, and joint agreement on

problems and opportunities is needed before

effective action can be implemented. It is important to determine where questions require “broad

and integrated” as well as “narrow and deep” approaches. Picking the wrong boundaries and

scales is inevitable unless driven by questions.

Because integrated approaches require a full

range of interests, types of knowledge, and points

of view, such approaches will challenge the power

and authority normally accorded to experts and

specialists.

Problem Framing and Resolution Must

Include Various Value Systems

Because landscape values and meanings differ

by time, scale, and individual or group, 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. Although we “look at” the same places

we “see” them differently, so to really understand

them we need to look at them together and describe what we see and why. But this is not an

easy task. Planning processes that are inclusive

raise the possibility of increased understanding,

improved representativeness in public participation, an opportunity to learn, and eventually identifying ways to get to a desired future.

What’s Getting in the Way?

As we think about and conduct analyses of landscapes from multiple perspectives, it becomes

evident that to develop a more holistic approach is

difficult. A number of things make designing and

implementing integrated approaches challenging.

Ideologies and beliefs (worldviews) condition how

we think. The common focus on getting answers

and solutions before clarifying the questions and

problems often leads us in the wrong direction.

The language of science and expertise makes it

difficult for interested citizens to easily engage in

processes and activities that affect them and to

contribute the knowledge they have about the

complex systems we all value. Technology can be

both a means and an end but often drives us in

directions that later prove to be less than effective. For example, more and better geographic

information system technology can be a hindrance if the wrong questions are under study.

Conclusions

All landscape definitions are human conventions–

they do not “exist” in any objective sense. We

carry expectations and definitions with us. And

these expectations and definitions are dynamic.

What often divides diverse interests and needs

are assertions that there is one best way to describe landscapes and scales.

Integrated multiscale approaches will link humans

with biophysical landscapes. But social and biophysical considerations often are not in sync at

least initially. Improved problem framing before

any action to collect data will improve the integration of human consideration, values, and uses into

landscape analyses.

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).

Legacies on the land affect judgments in a different way. It is hard for some people to relate to

large landscapes when they are concerned about

favorite places.

So, landscapes are socially defined in multiple

ways for multiple purposes from multiple perspectives. They are complex—socially and biophysically. These definitions are dynamic. Landscapes

at multiple scales can be used as a means to

unite and understand interactions among biophysical and social systems.

We need to take a more holistic view when thinking about landscapes. Boundaries matter—they

define time and space for many relevant purposes. The trick is to look across boundaries on

the map and in the mind.
61

Abstract

Forest managers and researchers are now working at a landscape level, but is our public with us? For

most people, landscape-level management is not a clear concept. To better understand how citizens

view landscapes, we need to go beyond attempts to “educate the public” and instead interact with citizens to promote learning, find appropriate outreach activities and simulation techniques, and directly

address questions about risk and uncertainty. Various scales of analysis will be necessary, including the

geographic, temporal, and normative contexts and their relevance to citizens.

Landscape-Level Management: It’s All About Context1

Bruce Shindler2

1 Shindler, B. 2000. Landscape-level management: it’s all

about context. Journal of Forestry. 98 (12): 10-14. Reprinted

with permission from the Society of American Foresters.

2

 Associate professor, Department of Forest Resources,

Oregon State University, Corvallis, OR 97331; Tel: 541-737-

3299; e-mail: Bruce.Shindler@orst.edu.
62

Introduction

The purpose of this paper is to describe recent

and ongoing work that contributes to understanding social and economic change at broad scales.

In particular, the paper focuses on a recently released atlas on human adaptation to environmental change at the county level. The paper also

discusses issues pertaining to data availability

and geographic and temporal scales.

Issues of scale are important to understanding

social and economic change. Two important considerations affect social and economic analyses

at the broad scale. First, there is the wealth of

secondary data collected by an array of federal,

state, and, in some cases, local government

agencies (Salant and Waller 1995). Frequently

these data sets provide information for specific

variables across multiple scales and on a relatively consistent basis for extended periods of

time. Examples include the decennial census

information that is available from individual census “blocks” or “block groups” and additive to the

county, state, and national levels and the employment information collected at the firm level by

employment security departments and provided at

a range of geographic and industrial sector scales

and levels of detail. The second consideration is

that most of this secondary information is available only at scales defined by political units of

government. Physical and biological effects often

are relevant only indirectly as they have shaped

the boundaries of government entities such as

cities, counties, and states. Understanding the

relevant secondary data available is a prerequisite

to primary data collection efforts.

Winnowing this mass of information on social and

economic variables and selecting the appropriate

data to address the research or policy issues at

hand is a formidable task. Also, there is the need

to provide meaningful tabular, graphical, and geographical displays of this information as an aid to

understanding and interpretation. It is in this arena

that the work of the Rural Communities and

Economies Team of the USDA Forest Service’s

Pacific Northwest Research Station has been

concentrated. A related issue of interest is how

different scales of the social and economic variables are hierarchically related and how these

relationships impact the interpretation usefulness

of the variables. Team work has focused on these

three areas: (1) the collection of data on key social and economic variables for the Pacific Northwest; (2) the development of geographical displays (atlases) that include interpretations of

these variables (Christensen et al. 2000, Raettig

et al. 2001); and (3) the exploration of theoretical

issues concerning social and economic variables

and the linkages between different spatial and

temporal scales.4

Recently in the West, several interagency,

multidisciplinary, broad-scale assessments were

conducted in response to, or in anticipation of,

changes in resource management. These assessments include the Forest Ecosystem Management Assessment Team (FEMAT 1993), the

Sierra Nevada Ecosystem Project (SNEP 1996),

Human Adaptation to Environmental Change: Implications at

Multiple Scales

Ellen M. Donoghue,1 Terry L. Raettig,2 and Harriet H. Christensen3

1 Research social scientist, U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, P.O. Box 3890, Portland, OR 97208-

3890; Tel: 503-808-2018; e-mail: edonoghue@fs.fed.us.

2 Economist, U.S. Department of Agriculture, Forest Service,

Olympic National Forest, 1835 Black Lake Blvd. SW,

Olympia, WA 98512-5623; Tel: 360-956-2449; e-mail:

traettig@fs.fed.us.

3 Research social scientist (retired), U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research

Station, Forestry Sciences Laboratory, 400 N 34th, Suite 201,

Seattle, WA 98103; Tel: 206-732-7824; e-mail:

chchristensen@fs.fed.us.

4 Raettig, T.L. [N.d]. Spatial and temporal scale issues in

Northwest Forest Plan monitoring and evaluation activities.

Manuscript under review. On file with: USDA Forest Service,

Pacific Northwest Research Station, Forestry Sciences

Laboratory, P.O. Box 3890, Portland, OR 97208.
63

and the Interior Columbia Basin Ecosystem

Management Project (Quigley and Arbelbide

1997). Social assessments at the county and

community level were conducted as part of these

bioregional assessments (Doak and Kusel 1997,

Harris et al. 2000, Horne and Haynes 1999).

Many dimensions of human life were reported on

including culture, the history of human-natural

resource interactions, socioeconomic conditions

and trends, and measures of community resiliency and community capacity. This work expands

on these efforts, by depicting other variables over

different geographic and spatial scales. It also

contributes to meeting the requirements for social

and economic monitoring and forest planning. For

instance, in the Northwest Forest Plan (NWFP)

region, the record of decision for the NWFP directs agencies to conduct three types of monitoring—implementation, effectiveness, and

validation—to detect desirable and undesirable

changes as a result of ecosystem management

(USDA and USDI 1994). Planning rules for National Forest System land also have requirements

for social and economic sustainability (see for example, USDA Forest Service 1999). Finally, the

work reflects appropriate roles for scientists in

assessments, analyses, and monitoring activities

associated with forest management.

Data Collection

The atlases focus on county-level information. For

many of the social and economic indicators available from secondary sources (except for the decennial census), the county is the smallest unit for

which information is disseminated or published. In

the case of the commonly used economic variables such as employment and income, information cannot be disclosed or published that can be

traced to an individual firm or employee (Washington Employment Security Department 1997).

For other variables, such as those collected in the

Current Population Survey (CPS), small sample

sizes may preclude the calculation of data for

smaller geographical areas. County-level data can

be easily aggregated into larger scale areas such

as planning regions, states, and even multistate

regions. They also provide useful context for socioeconomic assessments at smaller scales, although in and of themselves may not be adequate

proxies for conditions and trends at smaller scales

(Beckley 1998).

An important consideration in collecting secondary data is the specific definition for the variable of

interest. Employment information, for instance, is

based on place of employment in the employment

security and regional economic information system, but is based on place of employee residence

for the decennial census and CPS. Temporal

scale also is a consideration. Employment Security Department employment and wage information is often available on a monthly as well as

annual basis. The decennial census collects information only once per decade with estimates provided for key census variables in intervening

years.

The key economic variables depicted in the atlas

include employment, income, unemployment, and

economic diversity. The key social variables include population (and characteristics of the population, such as race and ethnicity), migration,

education, poverty, and crime. These variables

reflect key indicators that are used in social and

economic assessments and studies on socioeconomic well-being. In addition to spatial and temporal scale issues, the atlases focus on absolute,

trend, and relative change in the values of the

variables. An example has been the documentation and interpretation of how different sectors of

the wood products industry have been impacted

by changes in timber harvest in the Pacific Northwest (Raettig and McGinnis 1996).

For the Pacific Northwest, work also has begun

on the collection of community-level data incorporating the secondary data that are available and

may ultimately include the collection of selected

primary data items (Donoghue 2003). The social,

economic, and resource data, such as timber

harvests, assembled by the team have provided

the basic information in an analysis of the Northwest Economic Adjustment Initiative (Raettig and

Christensen 1999). The data and analytical work

also have been resources for continuing efforts

related to Northwest Forest Plan social and economic monitoring.

Atlases

The Atlas Of Human Adaptation to Environmental

Change, Challenge, and Opportunity for the Pacific Northwest (Christensen et al. 2000), and the

Atlas of Social and Economic Conditions and

Change In Southern California (Raettig et al.

2001) provide geographical expression of change
64

in social, economic, and timber-related variables

at the county level. The Pacific Northwest atlas

was designed to provide Northwest Forest Plan

managers and planners with a comprehensive

reference depicting the dimensions, location,

magnitude, and direction of social and economic

change in the Northwest Forest Plan region. Included are displays that show patterns of the social and economic diversity and health of the

region. This atlas focuses on change during the

period of timber harvest reduction and initial economic restructuring in the region. Most maps are

based on changes in variables between 1989 and

1994.

The first section of the Pacific Northwest atlas

(Christensen et al. 2000) contains five base maps

that depict the region, the Northwest Forest Plan

provinces, counties, population distribution, major

transportation routes, and the public land ownerships. Six sections follow that address:

1. What kinds of social and economic changes

have taken place in the face of reduced timber harvest? Are Pacific Northwest communities changing? If so, how?

2. What changes have occurred in the timber

industry since 1990? Has timber employment

changed? Is private harvest increasing?

3. Have changes in federal harvest had a significant effect on county revenues?

4. Are western Oregon and Washington and

northern California singularly dependent on

natural resources?

5. What federal assistance has aided cities and

rural areas?

6. How have the population characteristics

changed? What are the trends in migration,

educational attainment, and changes in

ethnicity?

7. What have been the changes in selected

social issues such as rates of poverty, property and violent crimes, and alcohol-related

incidences?

Specific maps displayed in these sections:

• Section 2: Change in timber harvest and wood

products employment

Change in public timber harvest

Change in public and private timber

harvest

Change in wood products employment

Federal lands-related payments to

counties

• Section 3: Change in economic conditions:

economic performance

Unemployment rate compared to

region

Change in total employment

Wage trends

Wage level

• Section 4: Structural economic change

Economic diversity

Fastest growing nonfarm industries

Slowest growing nonfarm industries

• Section 5: Characteristics of the population

Change in county population

Change in unincorporated and

incorporated population growth

Migration status and trends

Change in ethnicity

Educational attainment

• Section 6: Social issues

Change in income maintenance

Change in poverty rate

Changes in violent crime

Changes in property crime

Alcohol-related incidences

• Section 7: Federal assistance

Northwest Economic Adjustment

Initiative
65

Accompanying the maps are text, supporting

graphics, and tabular displays that interpret the

information and patterns on the maps, explore

the relevant issues in more depth, and provide

a working tool for managers and planners.

A similar atlas was prepared as part of the socioeconomic assessment for the Southern California

Conservation Strategy, a broad-scale planning

effort for the four national forests in southern California (Raettig et al. 2001). This atlas covers 26

counties in southern California and includes maps

for the same variables displayed for the Northwest

Forest Plan region, except timber harvest information was not displayed owing to the relative

insignificance of timber harvest on the four national forests of that region. Both atlases are available on CD-ROMs that include some interactive

features.

Theoretical Issues and the Linkages

Between Different Spatial and

Temporal Scales

If social and economic variables are to be useful

for managers and planners, a thorough understanding is necessary of the implications of the

information displayed and the relationship between decision processes and different scales of

the variables. Work has been done exploring the

relationships between individual and aggregate

data (the “ecological fallacy”) (King 1997, McCool

and Troy 1998) in political science and other social sciences. Still, other work has explored the

issues of spatial data, unit definition, and scale in

geographic and geographic information systemsrelated problems (Fotheringham and Wong 1991,

Longley and Batty 1997). The Rural Economies

and Community Team has work in progress that

will produce a synthesis of the theoretical work

that has been done in these areas (see footnote

4). Ultimately this theoretical work will provide the

basis for understanding scale issues and how

these issues impact the use and interpretation of

social and economic variables in the planning,

monitoring, and management settings that are

part of the ecosystem management processes

now being implemented.

Literature Cited

Beckley, T.M. 1998. The nestedness of forest

dependence: a conceptual framework and

empirical exploration. Society and Natural Resources. 11: 101-120.

Christensen, H.H.; McGinnis, W.J.; Raettig,

T.L.; Donoghue, E. 2000. Atlas of human adaptation to environmental change, challenge,

and opportunity: northern California, western

Oregon, and western Washington. Gen. Tech.

Rep. PNW-GTR-478. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 66 p.

Doak, S.; Kusel, J. 1997. Well-being assessment

of communities in the Klamath region.

Taylorsville, CA: Forest Community Research;

contract 43-91W8-6-7077. Report prepared for

the USDA Forest Service, Klamath National

Forest.

Donoghue, E.M. 2003. Delimiting communities in

the Pacific Northwest. Gen. Tech. Rep. PNWGTR-570. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest

Research Station. 51 p.

Forest Ecosystem Management Assessment

Team [FEMAT]. 1993. Forest ecosystem management: an ecological, economic, and social

assessment. Portland, OR: U.S. Department

of Agriculture; U.S. Department of the Interior

[et al.]. [Irregular pagination].

Fotheringham, A.S.; Wong, D.W.S. 1991. The

modifiable areal unit problem in multivariate

statistical analysis. Environment and Planning

A. 23: 1025-1044.

Harris, C.C.; McLaughlin, W.; Brown, G.;

Becker, D. 2000. Rural communities in the

inland Northwest: an assessment of small

communities in the interior and upper Columbia River basins. Gen. Tech. Rep. PNW-GTR477. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station. 120 p.
66

Horne, A.L.; Haynes, R.W. 1999. Developing

measures of socioeconomic resiliency in the

interior Columbia basin. Gen. Tech. Rep.

PNW-GTR-453. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 41 p. (Quigley,

T.M., ed.; Interior Columbia Basin Ecosystem

Management Project: scientific assessment).

King, G. 1997. A solution to the ecological inference problem: reconstructing individual behavior from aggregate data. Princeton, NJ:

Princeton University Press. 342 p.

Longley, P.; Batty, M. 1997. Spatial analysis:

modeling in a GIS environment. New York:

John Wiley and Sons. 392 p.

McCool, S.F.; Troy, L.R. 1998. Estimating effects

of natural resource policy: the impact of the

ecological fallacy. RJVA 97-8016. Missoula,

MT: U.S. Department of Agriculture, Forest

Service, Rocky Mountain Research Station.

34 p.

Quigley, T.M.; Arbelbide, S.J., tech. eds. 1997.

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. 2066 p.

Raettig, T.L.; Christensen, H.H. 1999. Timber

harvesting, processing and employment in the

Northwest Economic Adjustment Initiative region; changes and economic assistance. Gen

Tech. Rep. PNW-GTR-465. Portland, OR: U.S.

Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 16 p.

Raettig, T.L.; Elmer, D.M.; Christensen, H.H.

2001. Atlas of social and economic conditions

and change in southern California. Gen. Tech.

Rep. PNW-GTR-516. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 66 p.

Raettig, T.L.; McGinnis, W.J. 1996. Wood products employment in the Pacific Northwest:

emerging trends. In: Proceedings of the 30th

annual Pacific Northwest regional economic

conference. Portland OR: Pacific Northwest

Regional Economic Conference and Center for

Urban Studies, Portland State University: 45-

50.

Salant, P.; Waller, A.J. 1995. Guide to rural data.

Revised ed. Washington, DC: Island Press.

140 p.

Sierra Nevada Ecosystem Project [SNEP].

1996. SNEP final report to Congress: assessments and scientific basis for management

options. Davis, CA: University of California,

Centers for Water and Wildland Resources.

1528 p. Vol. 2.

U.S. Department of Agriculture, Forest Service. 1999. National Forest System land and

resource management planning. Federal Register. 64(192): 54074-54112.

U.S. Department of Agriculture, Forest Service; U.S. Department of the Interior, Bureau

of Land Management. 1994. Record

of decision for amendments to Forest Service

and Bureau of Land Management planning

documents within the range of the northern

spotted owl. [Place of publication unknown].

74 p. [plus attachment A: standards and guidelines].

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information. Olympia, WA: Labor Market and

Economic Analysis Branch. 32 p.
67

Introduction

Given interactions among terrestrial, aquatic,

and socioeconomic systems, planning at the landscape level could benefit from including information from different scales. This paper offers examples of broader systems views that may inform

natural resource managers and policymakers

dealing with restoring and maintaining healthy

ecosystems while addressing the demands of

people. World growth in human populations and

income has resulted in social, economic, and

technological changes that profoundly affect the

global management and use of natural resources.

The world population will continue to grow, possibly from 5.9 billion in 1998 to 8.9 billion by 2050.

The U.S. population also will continue to grow,

particularly in the southern and western regions,

with a projected increase of more than 120 million

people by 2050. Projected increases in population

and income will, in turn, increase demands for

renewable resources. Demographic shifts, such

as the aging of the population and increasing ethnic and racial diversity, will affect the patterns of

demand for natural resources.

Growing human populations and associated use

and consumption of the Earth’s natural resources

are placing more pressure on the chemical, biological, and ecological systems of the planet.

Human activities are significant drivers of environmental changes on the mosaic of land uses and

land ownerships (e.g., Cohen et al. 2002). Analysis of the ecosystem response to changes in

these human-derived environmental factors is

warranted at multiple scales, depending on the

policy-relevant questions. Changes in societal

values are part of the dynamics affecting forest

ecosystems and influencing land management

strategies (e.g., Franklin 1989), warranting a more

explicit treatment of the human system in conjunction with ecosystem properties. Integrating the

human dimension more directly into analysis systems is critical, as choices made by resource and

land managers become increasingly important for

the long-term sustainable use of our natural resources (e.g., biodiversity, wildlife habitat, carbon

sequestration) within the context of suitable human welfare.

Examining the state of the land is a key part of

sustainability and livability analyses. Land use

changes can provide opportunities to help society

adjust to changing demands for and supplies of

renewable resources from the Nation’s forest and

aquatic ecosystems. Interfaces between land

uses, such as riparian zones on forest and agricultural land, should be considered alongside

growing urban areas and increased fragmentation

of some forests. In this paper, I examine drivers of

changes in the large private forest land base, and

discuss changes in land use and land cover by

major categories.

Land Base Changes Over Time

From 1800 to 1930, forest land area in the United

States declined by some 300 to 350 million acres

(Clawson 1979), primarily in the East. This was

about a one-third loss in forest cover. Some of

this land was employed for urban and infrastructural developments, but the largest portion was

cleared and converted to agriculture. These land

use changes reflected federal policies of the time

to transfer the original public domain to private

hands and to expand agricultural production. With

the closing of the public domain, establishment of

permanent federal forest reserves, conversion of

most suitable nongovernment forest lands to

some form of cropping or pasture, and dramatic

improvements in agricultural productivity, the net

movement of land between forestry and agriculture has become far less marked. Since 1950,

Land Use and Land Cover Dynamics: Changes in

Landscapes Across Space and Time

Ralph J. Alig1

1 Team leader and research forester, U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research

Station, Forestry Sciences Laboratory, 3200 SW Jefferson

Way, Corvallis, OR 97331; Tel: 541-750-7267; e-mail:

ralig@fs.fed.us; Ralph.Alig@orst.edu.
68

U.S. forest land has declined about 4 percent,

with the largest losses being to developed uses

(Alig et al. 1999b).

Although the large amount of forest land clearing

for agriculture of the last century is probably a

phenomenon of the past, continued expansion of

urban and developed areas is likely (e.g., Alig and

Healy 1987). In 1994, forests covered 65 percent

of nonfederal land in the Pacific Northwest, and

these forests are under increasing pressure of

conversion. Oregon’s and Washington’s populations have increased faster than the national average over the last decade. Most of the increase

was in the western part of the region, especially

along the I-5 corridor. For example, Portland

was one of the fastest growing cities in the United

States over the last decade. Projections are that

the Pacific Northwest’s share of total population

will increase, as the Nation’s population also

expands.

Urban sprawl and livability are issues receiving

increased attention around the Nation, as the

Nation becomes more urban, with more than 75

percent of U.S. residents now living in cities

(USDC Bureau of the Census 2002). In the Pacific Northwest (PNW), approximately 400,000

acres of forest were converted to urban and developed uses between 1982 and 1997 (USDA

NRCS 2001). Such changes can interact with

other environmental alterations, such as habitat

fragmentation, wetland loss, loss of biodiversity,

and water pollution, and the cumulative impacts

on any particular ecosystem need to be considered carefully.

Socioeconomic Trends

A number of socioeconomic trends affect options

for restoring and maintaining ecosystems, and

affect the supply and demand of land-based

goods and services. Along with the move to cities,

more and more people are moving to the Nation’s

coasts. Some 53 percent of the U.S. population

lives in the 17 percent of the land in the coastal

zone (within 50 miles of a coast). Further, the

largest population increases over the next several

decades are projected to continue to be in coastal

areas. Increases in population and personal income tend to lead to reductions in aggregate forest area (e.g., Alig and Healy 1987). Such trends

need to be factored into landscape analyses,

given implications for fish habitat, riparian areas,

wetlands, and recreational opportunities.

In addition to an expanding population, the U.S.

population is aging. Early in the 20th century, 1 in

25 Americans was over age 65. In 2000, 1 in 8

was over 65 (USDC Bureau of the Census 2002).

Other demographic changes include continuing

shifts in ethnic and racial compositions. The

changing U.S. demographic composition likely

will impact demands for forest and range resources and how resources are managed (USDA

Forest Service 2001).

Americans’ incomes have grown substantially (in

real terms or constant dollars) in recent decades,

and average per capita personal incomes in Oregon have increased more than 75 percent over

the last 30 years. Projected increases in discretionary income will increase demands for renewable resources, but may also lead to further conversion of forests for developed uses.

The United States in the last decade of the 20th

century was in a period of economic growth, as

stock markets experienced relatively large gains.

In the new millennium, wealthier nations are likely

to have a greater ability to accommodate restoration and maintenance of ecosystems than are

those nations with economies under serious

stress. However, some development patterns may

increase vulnerability of land-based systems in

spite of greater wealth. With more assets and

infrastructure located in coastal areas, this may

complicate rehabilitation of ecosystems home to

Pacific salmon. Such trends also may increase

vulnerability of coastal areas to pollution and to

extreme events that are under study for any linkages to global climate change (e.g., Easterling

et al. 2000).

The United States is also currently in the midst of

rapid changes and advancements in technology

capabilities in many economic sectors. The new

information technology has affected agricultural

production and the forest sector to a lesser degree. Socioeconomic conditions will influence

how the technology is disseminated, and this will

affect how well our region and country can effect

improvements in the state of the land. With growing and wealthier populations, development pressures and recreational use stresses on forests,

wetlands, and riparian areas are likely to increase.
69

Types of Land Use and Land Cover

Dynamics

Five categories of change involving the land base

are (1) afforestation, (2) deforestation, (3) ownership, (4) forest type transitions, and (5) land management intensity (Alig and Butler 2002, Alig et al.

2002). Such changes arise from an interaction of

biophysical, ecological, and socioeconomic processes and forces, often operating at a variety

of scales. For example, market forces tend to

operate at much larger scales than biophysical

processes commonly studied at microlevels such

as stands or reaches of a stream. I will provide a

brief overview of the types of land base changes,

with illustrations of temporal and spatial considerations drawn from empirically based studies. The

example studies range in geographic scope from

the Oregon Coast Range province (Spies, this

volume) to the global level of analyses for current

investigations of climate change.

Afforestation

Afforestation is the forestation, either by human

or natural forces, of nonforest land. Two examples

are planting conifers on former cropland and

former Christmas tree plantings that are allowed

to revert to “wild” forest. In the Pacific Northwest

(Oregon and Washington), most afforested acres

were formerly in pasture and range use. Tree

planting is a major component of afforestation.

Approximately 10 percent of the area of U.S.

private tree planting in 1994 was in the Pacific

Northwest in contrast to more than 80 percent in

the South. Most tree planting in the South was on

nonindustrial private lands, whereas in the PNW

region, the majority was on forest industry lands.

Nonfederal forest area in both Washington and

Oregon has steadily declined between 1982 and

1997 surveys by the USDA Natural Resources

Conservation Service (2001), indicating that conversions of forest to other uses, primarily developed uses, have in net been larger than the

amount afforested. The regional net loss has

been more than 300,000 acres of forest over that

15-year period.

Tree planting has been a target of various policies. The United States has a long history of forest policies that jointly pursue both economic and

ecological objectives, often involving policy instruments designed to affect land use or cover. Public

policies aimed at one sector have impacts, either

expected or inadvertent, on another (e.g., forest

sector vs. agriculture sector). In recent years policies have increasingly focused on riparian zones

and incentives for promoting more favorable

aquatic habitat for salmonid stocks. Many past

studies have examined policy impacts by either

(1) ignoring spillovers in other sectors or (2) simply “adding up” impacts across the two sectors,

ignoring feedbacks or interactions through the

markets for land. At times, this also has included

ignoring linkages between resource conditions on

public and private lands, and associated interconnections via markets.

Deforestation

Deforestation is the conversion from forest to

nonforest use. Between 1982 and 1992, about

250,000 acres were deforested on nonfederal

land in the region. The annual rate of conversion

of forests to urban/developed uses increased in

the 1990s to 32,000 acres, from the approximately 25,000 acres in the 1980s (USDA NRCS

2001), with stronger population growth and more

economic activity. In total, between 1982 and

1997, the net outcome of land use shifts was

a regional loss in forest area of approximately

400,000 acres. The destination of most converted

forested acres was to urban and developed uses.

Ownership Change

The main ownership change between traditional

ownership categories has been between forest

industry (FI) and nonindustrial private forest

(NIPF) owner classes. The FI land is owned by

companies for the purpose of timber production

(see for example, Zheng and Alig 1999). The

NIPF lands compose the remainder of the private

forest land base. Forest industry owns most of the

private timberland in the PNW region, and generally manages forest land intensively for timber

production. Land exchanges among private owners have been more common than exchanges

between private and public owners (Zheng and

Alig 1999). For example, Forest Inventory and

Analysis (FIA) surveys in western Oregon indicate

a net shift of 750,000 acres from NIPF to FI owners for 1961-94. Such changes in ownership can

result in notably different land management, particularly as some private owners respond to market changes prompted by reductions in federal

timber supply.
70

With mergers, acquisitions, and other institutional changes, there also have been significant

changes within the industrial ownership category

(e.g., combining Willamette and Weyerhaeuser

companies in 2002). The diverse NIPF owner

category also continues to change in composition. Along with this, forest fragmentation and

parcelization and other factors may result in more

noncorporate individual owners (e.g., Sampson

2000), but they are likely to have smaller tract

sizes on average. Accompanying changes in tract

size may be changes in the values and perceptions of forest landowners. New owners sometimes bring different land management attitudes

compared to traditional owners, with changing

values often the result of exurbanization, or urban

residents moving to rural settings.

Forest Type Transitions

Within the land base retained in forests over time,

changes in forest cover types are caused by a

combination of natural and human-related forces.

Earlier literature dealing with forests focused on

forest succession and natural disturbances, with

emphasis on natural forces prompting forest type

changes. However, human-caused disturbances

such as timber harvests now dominate in most

PNW forests (Alig et al. 2000, Cohen et al. 2002).

Over the last FIA survey cycle, human-caused

disturbances were more frequent, by at least an

order of magnitude, than recorded natural disturbances. The probability of harvesting on private

lands was about 2 to 10 times more likely than

full- or partial-replacement disturbances from wildfire, the primary natural disturbance agent of the

past. In the approximatly 10 years between FIA

measurements, timber harvests affected about

20 percent of private timberland, whereas fire

affected less than 1 percent.

Given this disturbance backdrop, clearcutting

Douglas-fir (Pseudotsuga menziesii (Mirb.)

Franco) stands on FI lands resulted in 15 percent

being replaced by hardwood (primarily red alder

[Alnus rubra Bong.]) stands, and another 3 percent went to other types. Clearcutting red alder

stands on FI lands resulted in 72 percent being

replaced by other forest types. In contrast, only

42 percent of red alder stands on NIPF lands

changed forest types after clearcutting, reflecting

fewer intentional type-conversion efforts after

harvest. Even for those stands not disturbed,

12 percent of Douglas-fir stands on FI lands and

23 percent on NIPF lands changed forest type.

Such findings suggest that recognition of ownership differences can be important, beyond the

public vs. private classifications sometimes used.

Land Management Intensity

Within a given forest type, investments in forest

management can significantly influence options

for different mixes of goods and services. Management intensity includes the timing and type of

harvests, which have differed notably over time by

ownership in this region. Investments in improved

planting stock on private land have allowed higher

forest production per acre in some areas, lessening pressures on other areas looked upon for

nontimber goods and services. From a broad

perspective, demands for different mixes of landbased goods and services are likely to shift over

time with a growing and wealthier population.

Because some forest-based processes are decades or centuries in length, planning such investments with adequate lead time is critical.

Assessments of Land Base Changes

The 2000 Resources Planning Act (RPA) assessment by the USDA Forest Service (2001) is designed to examine the current situation of the

Nation’s forest and rangeland ecosystems and

assess the prospective situation over the next five

decades. In support of that national assessment,

research pertaining to drivers of land use change

at macroscales indicates that major determinants

of land use changes are population, personal

income, and potential profits from land enterprises

such as forestry or agriculture (Alig et al. 2002).

For example, the Forest and Agricultural Sector

Model (Adams et al. 1996a, Alig et al. 1998) has

endogenous determination of land use changes.

The linked model of the U.S. agriculture and forest sectors has land demands and supplies in

both sectors that are endogenous and determined

simultaneously with demands and supplies for

products from those lands. One possible objective

function in the model is economic maximization

(Adams et al. 1996b). Examination of land use

changes within a multisector context is important

for assessing alternative futures of “sustainable

forestry,” “sustainable agriculture,’’ “sustainable

communities,’’ or some composite.
71

Owner Behavior

A long-standing issue in forest resource supply

studies is the likely behavior of private owners

and how behavior may be affected by incentives

and institutional factors. In addition to changing

characteristics of the owner population over time,

we also need to consider how changes in ownership objectives may impact the resources. The

larger, publicly owned companies are affected by

shareholder expectations, as well as pursuing

acceptable rates of return on investment within a

changing institutional environment of incentives

and regulations. The NIPF owners, in particular,

possess multiple objectives, causing them to respond to socioeconomic forces and policies in

complex and sometimes unpredictable ways.

Nontimber services likely could be enhanced effectively by targeting incentive programs toward

select groups of NIPF owners (Kline et al. 2000).

Other research has found that financial incentives

are not as critical to owners’ decisions in foresting

riparian zones as some have suggested, and

other factors include “neighborly concerns’’ and

concerns about restrictions on land management

and loss of flexibility (Kingsbury 1999). Behavior

by the diverse NIPF owner group also is affected

by whether owners live on their forested property

in contrast to absentee owners. Another factor is

increasing density of people per forested unit,

especially in areas such as the Puget Sound area.

Future Directions

The landscape comprises a mosaic of the major

land uses, which reflects and warrants a wide

view of forces at work in shaping the landscape,

in both temporal and spatial dimensions. Projections indicate that demographic and other forces

will continue to affect that mosaic of land uses.

If the U.S. population increases by 126 million

people over the next 50 years, along with a rise

in personal income, that could result in a net loss

of 15 million acres of timberland (Alig et al. 2002,

2003). Future improvements in policy could be

facilitated by acknowledging different ownership

characteristics and a broader representation in

analyses and policy deliberations of those with

competing interests in the land, including public

information about actions and possible consequences. With increasing populations and pressures and conflicts on the land, relationships

among major land uses, such as forestry, agriculture, and urban/developed uses, are becoming

more evident. Natural resource policy issues now

often involve forest and nonforest components in

the overall system. For example, the condition of

riverine systems is affected by a broad range of

land uses, and opportunities for improvements

exist on both wildlands and other lands (e.g.,

pastureland in riparian zones). Efforts to better

understand how systems function, especially terrestrial, aquatic, and socioeconomic systems,

should bear in mind policy-relevant questions and

consider the marginal costs versus marginal benefits of undertakings.

From a long-term conservation perspective, pursuit of new options for improvements in natural

resource conditions is increasingly faced with

compatibility issues among competing interests

in the land and incentives for owners. Efforts to

better align commercial uses of the forests with

other conservation objectives has led to increased

interest in what is being called sustainable forestry, although there are similar efforts tied to

other major competing interests in the land,

such as sustainable agriculture or sustainable

communities.

When one looks at managing forested systems

for multiple uses within ecological limits, then

consideration of capital markets and other interconnections between sectors of the economy

become more important. Policy issues associated

with sustainability and planning information to aid

in collective decisions about managing natural

resources are affected by changing product market and institutional conditions, as in recent decades with changes tied to marked reallocation

of rural land. Improvements in U.S. agricultural

production technology allowed expanded agricultural production on a fairly constant land base.

Less pronounced and in a lagged fashion, forest

volumes have increased on a timberland base

that is 4 percent smaller than the one in 1952.

Demand for wood products is expected to keep

growing, driven by the same population increases

and economic development that affect demands

for other major land uses. However, intensified

timber management on the supply side represents some of the largest projected changes involving private timberland (Alig et al. 1999a,

2002), and could act to moderate or temper upward pressure on future wood prices. Private timberlands have the biological potential to provide
72

larger quantities of timber in an environmentally

sound manner than they do today. Many of the

opportunities for intensified forest management

can be undertaken with positive economic returns,

but changing social and institutional aspects may

affect actualization. Most of the timber management intensification opportunities in the United

States are in the South and the Pacific Northwest

west side. Further, more forests around the world

are managed today compared to earlier decades,

and this includes an expanding area of relatively

productive plantations. Even if projected intensification were implemented, most of the NIPF

timberland would still be concentrated in low management-intensity classes that involve naturally

regenerated stands. Sustainability analyses can

be enhanced if both land use and land investment

options are examined. Analyses should be explicit

with respect to timing of tradeoffs in addition to

the growing attention given to spatial details. This

would increase the usefulness of such tools in

policy analyses, such as in the 2000 RPA assessment and forest carbon analyses.

Metric Equivalents

1 acre = 0.405 hectares

Literature Cited

Adams, D.; Alig, R.; McCarl, B. [et al.]. 1996a.

The forest and agricultural sector optimization

model (FASOM): model structure and policy

applications. Res. Pap. PNW-RP-495. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research

Station. 60 p.

Adams, D.; Alig, R.; McCarl, B.A. [et al.].

1996b. An analysis of the impacts of public

timber harvest policies on private forest management in the U.S. Forest Science. 42(3):

343-358.

Alig, R.; Adams, D.; Chmelik, J.; Bettinger, P.

1999a. Private forest investment and long-run

sustainable harvest volumes. New Forests. 17:

307-327.

Alig, R.; Adams, D.; McCarl, B. 1998. Impacts of

land exchanges between the forest and agricultural sectors. Journal of Agriculture and

Applied Economics. 90(5): 31-37.

Alig, R.; Benford, F.; Moulton, R.; Lee, L.

1999b. Long-term projections of urban and

developed land area in the United States. In:

Otte, K., ed. Balancing working lands and development [CD-ROM]. Philadelphia, PA: American Farmland Trust and Land Trust Alliance:

[Pages unknown]

Alig, R.; Butler, B. 2002. Land use and forest

cover projections for the United States: 1997-

2050. In: Proceedings of the 2001 national

Society of American Foresters (SAF) convention. Bethesda, MD: Society of American Foresters: 93-115.

Alig, R.; Healy, R. 1987. Urban and built-up land

area changes in the United States: an empirical investigation of determinants. Land Economics. 63: 215-226.

Alig, R.; Mills, J.; Butler, B. 2002. Private timberlands: growing demands, shrinking land base.

Journal of Forestry. 100 (2): 32-37.

Alig, R.; Zheng, D.; Spies, T.; Butler, B. 2000.

Forest cover dynamics in the Pacific Northwest

west side: regional trends and projections.

Res. Pap. PNW-RP-522. Portland, OR. U.S.

Department of Agriculture, Forest Service,

Pacific Northwest Research Station. 22 p.

Alig, R.J.; Plantinga, A.J.; Kline, J.D. 2003.

Land use changes involving forestry in the

United States: 1952 to 1997, with projections

to 2050. Gen. Tech. Rep. PNW-GTR-587.

Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research

Station. 92 p.

Clawson, M. 1979. Forests in the long sweep of

American history. Science. 204: 1168-1174.

Cohen, W.; Spies, T.; Alig, R. [et al.]. 2002.

Characterizing 23 years (1972-1995) of stand

replacement disturbance in western Oregon

forests with Landsat imagery. Ecosystems. 5:

122-137.

Easterling, D.; Evans, J.; Groisman, P. [et al.].

2000. Observed variability and trends in extreme climate events: a brief review. Bulletin

of the American Meteorological Society. 81:

417-425.
73

Franklin, J.F. 1989. The “new forestry.” Journal of

Soil and Water Conservation. 44(6): 549.

Kingsbury, L. 1999. Oregon’s conservation reserve enhancement program: likely participation and recommendations for implementation.

Corvallis, OR: Oregon State University. M.S.

thesis.

Kline, J.; Alig, R.; Johnson, R. 2000. Fostering

the production of nontimber services among

forest owners with heterogenous objectives.

Ecological Economics. 33: 29-43.

Sampson, N. 2000. People, forests, and forestry:

new dimensions in the 21st century. In:

Sampson, N.; DeCoster, L., eds. Proceedings,

forest fragmentation 2000. Washington, DC:

American Forests: 53-59.

U.S. Department of Agriculture, Forest Service. 2001. 2000 RPA assessment of forest and

range lands. Report FS-687. Washington, DC.

78 p.

U.S. Department of Agriculture, Natural Resources Conservation Service. [NRCS].

2001. The national resources inventory, 1997.

Revised. Washington, DC.

www.nhq.nrcs.usda.gov/NRI/1997. [Date last

accessed unknown].

U.S. Department of Commerce, Bureau of the

Census. 2002. Gateway to census 2000.

Washington, DC. www.census.gov.

(10 November 2003).

Zheng, D.; Alig, R. 1999. Changes in the nonfederal land base involving forestry in western

Oregon, 1961-1994. Res. Pap. PNW-RP-518.

Portland, OR: U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research

Station. 22 p.
74

Worldviews Panel
75

Presentation Objectives

Mason, Bruce & Girard has been asked to give

you our impressions of the private landowner perspective on landscape management. To do this

subject justice, we need to discuss private landowner goals and objectives, state and federal

regulations, and forest land management issues

as they relate to landscape management. As I

prepared these remarks, I have drawn on my

nearly 30 years of experience within the forest

products industry while with Georgia-Pacific Corporation and through the contacts I have made

while with Mason, Bruce & Girard. I have tried to

capture questions we hear being asked and to

hopefully give you an understanding of why these

questions are important to the private forest landowners within our region. This region needs diversity, flexibility, room for dissension, and more

nonbureaucratic processes. Any perceived benefits of landscape management, at this point in

time, are being viewed as far outweighing the

costs, which will be borne, in a large part, by the

individual forest-land owner.

Private Landowners’ Goals and

Objectives

The first question we need to ask is, Why do

people own forest land? What is their driving motivation? Is it profit, is it enjoyment of being able to

manage a forest based on their own interests, is it

for recreational purposes, or is it ownership for

the beauty of it?

Although there are some who own timberland to

enjoy it, most private landowners manage their

lands with the objective of profiting from it in

some manner, whether on an annual basis or

over some other timeframe. There are many different ideas on what forest land management

should look like, from very intensive to a hands-off

approach.

These reasons for ownership will shape the landowners’ goals and objectives and thus how they

will proceed with operations on their property.

Ultimately, these reasons also will shape how they

will form any perspectives on landscape management.

State and Federal Regulations

The three Western states (Washington, Oregon,

and California) have very comprehensive laws

governing timberland operations. These laws

primarily regulate forest management operations

that have the potential to impact public resources

such as fish and wildlife habitat and clean water.

They may be modified somewhat, depending on

the size of a given ownership, although generally

speaking most will apply to all landowners if management activities occur.

Landowners, regardless of size of holdings, must

determine how best to fit their goals and objectives with how these laws impact their individual

ownership. For example, a landowner with small

acreage with fish-bearing streams flowing through

the property may have few management options

as compared to a landowner whose property contains only non-fish-bearing streams and, who

therefore, may have several management options. Corporate ownerships generally are large

enough to work around the regulations and still

meet corporate mandates.

As an example of how regulations can impact the

management of our private forest lands, Mason,

Bruce & Girard completed a study for the Oregon

Forest Industries Council in the early 1990s to test

the requirements of Oregon Senate Bill 1125. This

bill, which was backed by forest landowners, set

new requirements designed to spread timber harvest over the landscape by restricting clearcut

areas to 120 acres in size and requiring regeneration to be 4 feet high, 4 years old, and “free to

grow” before harvesting an adjacent timber stand.

“Free to grow” is defined as “a tree or stand of

well-distributed trees, of acceptable species and

good form, with a high probability of remaining or

Private Landowner Perspective on Landscape Management

Carl F. Ehlen1

1 Forestry consultant, Mason, Bruce & Girard, Inc., 707 SW

Washington Street, Suite 1300, Portland, OR 97205; Tel: 503-

224-3445; e-mail: cehlen@masonbruce.com
76

becoming vigorous, healthy, and dominant over

undesired competing vegetation.” For the purpose

of this definition, trees are considered well distributed if 80 percent or more of the area contains at

least 200 trees per acre and not more than 10

percent contains fewer than 100 trees per acre.

The study determined that the “free to grow” requirement, when combined with leave areas between harvest units and maximum regeneration

harvest unit size, created the following:

1. Significant impacts on the size, number, distribution, and timing of regeneration harvests.

2. A slowing of the rate of harvest on individual

tracts.

3. The potential for significantly increasing the

miles of roads, which not only adds to a landowner’s cost but also adds to the probability

for increased environmental damage.

4. Land being taken out of production.

5. Increased stand fragmentation as the maximum regeneration harvest size is further reduced, thus potentially jeopardizing the ability

of a landowner to fully harvest the annual

growth on the property.

6. A significant reduction in the size of regeneration harvest units with the average always

being less than the maximum allowed.

7. More broken ownership, which makes it more

difficult to efficiently schedule harvesting activities.

8. More dispersion of regeneration units over the

landscape.

Private landowners have long supported forest

regulations backed by scientific evidence. Now,

however, as regulatory proposals pass from scientific to political, private landowners are becoming more and more leery of what might be expected of them as they continue to manage

their property and risk the potential loss of their

investments.

Will more regulations, particularly if seen as political, drive more disinvestment of forest land?

Landscape Management Perspectives

and Questions

Just as management goals and objectives differ

among private landowners, so do their perspectives, and therefore their definitions, of landscape

management. To our knowledge, there is no objective, all-encompassing definition of landscape

management or what it means to the individual

landowner in terms of impacting their timber resource.

Is “landscape management” providing for all public resources on every acre, or is it providing for all

public resources through a mosaic of age and

size classes of forests across the landscape?

Is it important that all landowners provide this

mosaic, regardless of size of ownership?

Does landscape management include all landowners—private, state, and federal alike—in a

given watershed or viewshed or larger area?

Are all landowners to be treated equally?

Will a landowner be able to factor in individual or

corporate goals and objectives?

Given the above, we believe that the following, at

a minimum, must be studied and analyzed before

private landowners would even consider buying

into any landscape management scheme.

Economic Analysis

“Land” or “soil” expectation is an indicator of the

value of a piece of bare land as a forestry investment. As additional regulations are imposed, soil

expectation values on low-site lands begin to become marginal, particularly east of the Cascade

crest, but the same is true on the west side as

well. This concern begins to beg the issue of disinvestment of lower site lands.

Current state and federal regulations are costly to

the private landowner. To date we know of no

analysis to determine the additional costs and

benefits to the private landowner operating under

any landscape management framework. An economic analysis is imperative, as any regulations
77

in addition to what we have today would be extremely costly. As environmental regulation increases, we arrive at the point of getting small

marginal benefits at an enormous cost, most of

which will be borne by the landowner.

Has anyone taken the time to do an analysis of

this sort?

Rotation Length Issues

Landowners must be able to determine the requisite rotation length for their property based on the

productive capacity of the land and their goals

and objectives, while at the same time being able

to harvest their timber in response to market

changes in accordance with current regulations.

How will landscape management schemes allow

for this within the required timing?

How will final rotations be impacted?

Will landowners be allowed to set their own rotations and harvest ages depending on silvicultural

objectives and market fluctuations?

Silvicultural Issues

With the serious decline in federal timber sale

volume, combined with the continuing demand for

wood products, many private landowners are endeavoring to harvest timber equal to the growth

rates of their property. Many private landowners

are investing heavily in various silvicultural activities to assure that their forest land is producing

timber at its productive capacity. These activities

include, among others, planting genetically improved seedlings, brush control, early and midrotation fertilization, and midrotation thinning. We

are seeing a quality of forest management activities that is unprecedented. And yet, landowners

continue to improve on these efforts.

Will these efforts and investments go for naught?

In other words, will the financial investments in

planting, vegetation control, precommercial thinning, etc. made early in the life of a rotation be

lost if a landowner is not allowed to harvest his

crop?

How does even-age management fit with landscape management goals and objectives?

Are we as a society only interested in how our

private forest lands look and their resource protection attributes as opposed to keeping them

productive and profitable while continuing to protect our public resources?

Is there a balance that can be reached between

private timber production and habitat requirements?

Administration of Landscape

Management Requirements

A great deal of thought must go into how landscape management issues are to be administered. These issues must be examined by each

landowner rather than on a watershed or landscape basis. Problems will erupt as soon as one

landowner is restricted or impacted to a greater

degree than other landowners.

Who will be the regulator?

Who determines if landowners are complying with

the requirements?

How will anyone be able to make a determination

in an objective and legal manner?

Summary Comments

Our principal issue at this point is that we do not

know what landscape management looks like nor

do we know what, if anything, a private landowner

will have to give up. Is this another attempt to

further regulate the private landowner? Will landscape management become a form of “centralized planning?”

We do not know of any private landowner in the

Northwest who does not embrace the need for the

protection and the sustainability of public resources. The current regulatory framework is

inherently designed to provide for both.

How one landowner’s goals fit with an adjacent

landowner’s goals and how a given landowner’s

operations fit within the definition of managing on

a landscape scale, we assume, are still to be determined. In the end, however, private landowners

must be included in any discussions of landscape

management, particularly if regulatory proposals

are being considered. There is too much value at

stake for discussions on this issue to proceed

otherwise.
78

Describing past conditions is part of a coarse-filter

management strategy for sustaining biological

diversity (Cissel et al. 1994, Haufler 1994, Haufler

et al. 1996, Hunter et al. 1989, Swanson et al.

1994). A description of past ecosystem structure

and its variability is useful in exploring the causes

and consequences of change in ecosystem characteristics over time, and thus for understanding

the set of conditions and processes that sustained

ecosystems prior to their recent alterations by

humans. It provides a context for interpreting

natural processes, especially disturbance, and it

allows variability in patterns and processes to be

understood in terms of a dynamic system. Natural

resource managers can use such information to

evaluate the magnitude, direction, and causes of

landscape change, especially change induced by

people. An assessment of current conditions relative to the historical range of variability (HRV),

also called natural variability, also can be used to

identify management goals, particularly where

those goals encompass sustainability, ecological

restoration, conservation of biological diversity,

and maintenance of natural processes (Hann and

Bunnell 2001, Landres et al. 1999, Morgan et al.

1994, Swanson et al. 1994, White and Walker

1997). The concept is less useful when management objectives are narrowly focused on maximizing commodity production or sustaining the

population of an endangered plant or animal

(Landres et al. 1999).

In this paper, I give a brief overview of the HRV

concept, which is also called natural variability

and reference variability, and its use in understanding and managing dynamic landscapes. I

briefly discuss the value and limitations of history,

and then summarize what we have learned from

historical ecology that is of use to managers of

dynamic landscapes.

Defining Historical Range of Variability

Historical range of variability characterizes fluctuations in ecosystem conditions or processes

over time (Landres et al. 1999, Manley et al. 1995,

Morgan et al. 1994, Swanson et al. 1994), and

thus provides researchers and managers with a

reference against which to evaluate recent and

potential ecosystem change. Landres et al. (1999)

defined natural variability as “the ecological conditions and their variability over space and time

relatively unaffected by people.” Thus, HRV defines bounds of system behavior that remain relatively consistent over time. It is described for a

timeframe relevant to understanding the behavior

of contemporary ecosystems and the implications

for management, usually prior to the intensive

influence of European-Americans and with relatively consistent climate. Many people use a

timeframe of 100 to 700 years before present to

interpret successional dynamics and to characterize past variation in forest structure and composition, but that depends on the available historical

information and the ecosystem of interest. Historical data on disturbance occurrence and effects

are increasingly limited the further back in time we

look. Using recent centuries includes burning and

other actions of American Indians, and encompasses climatic variability, such as the Little Ice

Age. Hann et al. (1997) used the last 2,000 years

as the timeframe for HRV for the interior Columbia River basin.

Utility of This Concept

The utility of this concept is based on two concepts: (1) past conditions and processes provide

context and guidance for managing ecological

systems today, and (2) spatial and temporal variability caused by disturbance is vital to ecosystem

integrity (Landres et al. 1999). However, the utility

will also depend on the management issues and

the social and ecological context for decisions

(Landres et al. 1999). The HRV often is used in

Back to the Future: The Value of History in Understanding

and Managing Dynamic Landscapes

Penelope Morgan1

1

 Professor, College of Natural Resources, University of

Idaho, Moscow, ID 83844-1133; Tel: 208-885-7507; e-mail:

pmorgan@uidaho.edu.
79

combination with societal values and other information to identify desired future conditions

(Haufler et al. 1996, Landres et al. 1999). Historical information has been used to guide management of waterflow on the Colorado River (Poff et

al. 1997) and in the Everglades (Harwell 1997),

and in management of fire (Brown et al. 1994,

Skinner and Chang 1996) and forest structure

(Baker 1992, Camp et al. 1997, Cissel et al. 1999,

Gauthier et al. 1996, Hann and Bunnell 2001,

Keddy and Drummond 1996, Ripple 1994). It also

has been used in ecological restoration (Allen et

al. 2002, Covington and Moore 1997, White and

Walker 1997), and to deepen our understanding

of the processes driving forest change (Lertzman

et al. 1997; Lesica 1996; Mladenoff and Pastor

1993; Swetnam and Betancourt 1990, 1998;

Wimberley et al. 2000). Ecosystem management

often relies heavily on a description of past variability in defining desired future conditions

(Christensen et al. 1996, Kaufmann et al. 1994,

Manley et al. 1995).

The greatest values for characterizing HRV are

understanding (1) how the processes and factors

driving ecosystem change differ from one place

and time to another, (2) the influence of driving

variables in the past, and (3) how those driving

variables might influence ecosystems today and

in the future (Landres et al. 1999). Managers developed the HRV concept in a search for legally

defensible strategies for sustaining biological diversity and ecological integrity.

Data for describing HRV differ in temporal and

spatial scale (Morgan et al. 2001, Swetnam et al.

1999). Both natural (fire-scarred trees, pollen,

charcoal, etc.) and human archives (old photographs, early survey data, etc.) are sources of

historical data (Swetnam et al. 1999). Although

we know more about fire history than about other

disturbances, none of our fire history data are

comprehensive across both time and space, and

most are better at describing frequency than severity, size, or spatial pattern of disturbances. Few

adequately inform us about spatial pattern and

dynamics at the landscape scale (Morgan et al.

2001, Swetnam et al. 1999). Also, we have more

data for points and small areas than we have for

landscapes and watersheds (Landres et al. 1999,

Morgan et al. 2001, Swetnam et al. 1999). Thus,

extrapolation is required, but extrapolation from

points to large areas, and from short time intervals (years and decades) to long time intervals

(centuries) is problematic and fraught with error

(Morgan et al. 2001). We can more readily reconstruct past vegetation structure than past processes, and when we reconstruct past forest

structure, we are more confident about the number of large trees than we are about how many

small trees there were (Allen et al. 2002). Hierarchy theory can be helpful in interpreting data from

different spatial and temporal scales.

Historical Range of Variability and

Desired Future Conditions

Comparing current and desired future conditions

(DFCs) to HRV is useful for identifying management strategies and priorities (fig. 1). I sometimes

demonstrate this with a ball (existing conditions)

rolling around on a large plate (HRV). When conditions are within the HRV, the ball rolls around on

the plate. The edges of the plate keep the ball on

the plate (the system is bounded), until something

pushes it over the edge (outside of HRV). Then

the ball drops (change is rapid, and though it may

be somewhat predictable, the ball might not return

to the plate). Further, I can hold the ball steady,

but doing so takes energy on my part (an external

subsidy to the system in the form of human action). Now imagine a small plate representing

DFCs. This plate is smaller because DFCs are

typically more limited than HRV. It is possible to

have all three stacked up: the ball on the small

plate and both on the large plate. We do have

forest ecosystems where current conditions are

within the DFCs and those are within HRV. This

includes, for example, some subalpine forests. In

such cases (row 1 of fig. 1), our management

decision might be to maintain this desirable condition, which we view as sustainable. We can, however, imagine other combinations. Many urban

and agricultural areas, for instance, would be

characterized with the ball on a small plate (current conditions within DFCs) but both separate

from the large plate (both outside of HRV).

Whether or not such conditions are sustainable

depends on whether we as a society are willing to

assume the external subsidies (e.g., financial

subsidies to farmers, and fertilizer and herbicide

made from fossil fuels), effects (e.g., quality of life

and environment), and risks (e.g., climate

changes).
80

Thus, current conditions, DFCs and HRV may

or may not overlap. All three or any two might be

similar, or all might be different. Depending on

social, economic, and political issues, restoration

is suggested where desired conditions are within

HRV, but current conditions are different (row 2

of fig. 1). When DFCs differ from HRV or current

conditions, desired future conditions may need to

be reevaluated (rows 3, 4 and 5 of fig. 1). External

subsidies will be required to maintain such a condition, but people can choose to bear both the

subsidies and the risk of change to the system.

Ideally, scientists and managers can quantify the

implications of different choices as the basis for

informed decisions by the stakeholders. Haufler et

al. (1996) suggest combining knowledge of HRV

with knowledge of species needs to identify “adequate representation” of elements of ecosystem

diversity.

Examples of Applications of Historical

Range of Variability in Landscape

Management

Hann and Bunnell (2001) describe the development of landscape management prescriptions

based upon assessment of changes from HRV.

They give examples at several spatial scales,

including the mapping of historical fire regimes,

current fire regimes, and condition classes reflecting the degree of change for the conterminous

United States done by Hardy et al. (2001) and

available on the Web (http://www.fs.fed.us/fire/

fuelman). Hann and Bunnell (2001) also describe

the use of HRV description, modeling succession,

and identifying areas of departures from HRV as

a means for prioritizing for restoration in Colorado.

Their approach is similar to one applied in the

Sierras by Caprio and Graber (2000). Cissel

et al. (1999) contrast two approaches to landscape management in the Blue River watershed

in Oregon. An approach based on using logging to

approximate past disturbance regimes while also

maintaining stream buffers created less forest

fragmentation than an alternative based on matrix

and corridors under the Northwest Forest Plan.

What Have We Learned?

Historical ecology provides many lessons. For

instance, we now understand that disturbance

was and is ubiquitous. At any given time, most

ecosystems are in some state of recovery from

disturbance. Directly and indirectly, disturbances

strongly influence the structure, composition,

diversity, and function of the ecological systems

we manage. Further, disturbances interact, and

the relative importance of disturbances varies with

scale. For instance, it is likely that at some broad

spatial scales, regional and global climate

supercedes local fuel and topography in determining fire patterns (Swetnam and Betancourt 1998).

It is likely, for instance, that El Niño drives fire

patterns across the Southwestern United States

(Swetnam and Betancourt 1990) and in the

Patagonian region of South America (Kitzberger

and Veblen 1997). The results of historical analysis can sometimes be surprising. For instance,

Status Graphical representation Management action 

HRV ≥ DFC ≥ CC |...xxx...| 

|__________________| 

Maintain 

HRV ≥ DFC ≠ CC |...........| xxx 

|__________________| 

Restore 

HRV ≠ DFC ≥ CC |__________________| |...xxx...| 

HRV ≥ CC ≠ DFC |________xxx_______| |...........| 

HRV ≠ DFC ≠ CC 

 

|_________________| |.........| xxx 

Evaluate carefully to assess

risks, sustainability, and the

external subsidies of DFC; 

reevaluate DFC 

 

Figure 1—Comparing both current ecological conditions (CC, xxx) and desired future conditions (DFC |———|), to historical

range of variability (HRV, |_____|) is useful for identifying management actions. (Redrawn from Landres et al. 1999).
81

Swetnam and Lynch (1993) found that spruce

budworm (Choristoneura occidentalis Freeman),

a defoliating insect in conifers, is more prevalent

during wet than during dry years, counter to the

commonly held notion that defoliation occurs in

drought-stressed trees.

Scale matters. Wimberley et al. (2000) modeled

the historical range of variability of old forests in

the Oregon Coast Range. The historical range of

variability was progressively narrower as they

increased the analysis area by orders of magnitude from a small watershed to a large watershed

and then to a region.

Changes in forests at the landscape scale are

great and variable (Hann et al. 1997). Forests

at high elevation have changed in different ways

than forests at low elevations over the last 60

years, and both biophysical and social factors

are correlated with different types and degrees

of change (Black 1998). Although changes in

fire regimes are extensive, the changes are not

the same everywhere (Hardy et al. 2001, http://

www.fs.fed.us/fire/fuelman).

Rigorous testing of hypotheses by using historical

data has even greater potential for rapidly advancing ecological understanding. Time series analysis, comparative case studies, and analyzing

synchronous events across broad spatial scales

have taught us a great deal about the relative

influences of climate, land use, topography and

vegetation on fire regimes (Rollins et al. 2000a,

2000b, 2001; Swetnam 1993; Swetnam et al.

1999; Swetnam and Betancourt 1998), and about

the interactions between insects, forests, and

climate (Swetnam and Lynch 1993).

Through modeling (e.g., Miller and Urban 1999,

Wimberley et al. 2000), comparison of managed

and unmanaged landscapes, and examination of

historical data, we are coming to understand how

and why landscapes change. That understanding

is very important to managers of dynamic landscapes, even when those landscapes are subject

to introduced species, structures, and processes.

Implications and Challenges for

Managers

We need new approaches to landscape planning

that effectively integrate the three very different

approaches currently applied.2 Traditional approaches to evening out the flow of commodities

have taught us a lot about modeling complex and

interacting systems, but it is often difficult to incorporate ecological uncertainty and change into this

approach. Conservation planning based upon

corridors and matrices accommodates the needs

of many species but doesn’t recognize that landscapes are dynamic. Basing landscape management prescriptions on disturbance regimes builds

upon our knowledge of how and why landscapes

change (Cissel et al. 1994, 1999) but may not

provide for the needs of species and people.

Thus, we need to develop approaches to landscape planning that accommodate multiple species and processes in ecosystems subject to

introduced species, processes, and human

population pressure. For whitebark pine (Pinus

albicaulis Engelm.) ecosystems, for instance,

landscape planning must incorporate the needs

and dynamics of grizzly bears, Clark’s nutcrackers, squirrels, fire, the introduced blister rust, and

climate change, along with scenic values and

watershed protection. Historical information can

help us to understand this system and to build

models, which are then used to compare alternative futures for this ecosystem (Keane and Arno

2001).

Human-induced changes to our global, regional,

and local environments pose great challenges to

natural resource managers. Our climate is changing (IPCC 2001). Introduced species have altered

our environment as well (Vitousek et al. 1996).

Some will find HRV less useful in addressing

management of ecosystems that are clearly

undergoing changes that are to some degree

unprecedented when coupled with human population pressures. However, effective management

2

 Swanson, F. 1998. Personal communication. Research

geologist, U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station, Forestry Sciences

Laboratory, 3200 SW Jefferson Way, Corvallis, OR 97331;

Tel: 541-750-7355; e-mail: fswanson@fs.fed.us.
82

will continue to depend on our understanding of

ecosystems. The ecological implications of climate change and the dynamics of ecosystems

reinforce the need for a broader focus on restoring ecological integrity, resilience, and sustainability, rather than on restoring some “vignette”

or past condition (Landres et al. 1999, White and

Walker 1997).

The potential consequences to biological diversity

are great if current forest conditions are outside of

and remain outside of the historical range of variability. Consequences include increased vulnerability to stand-replacing fires where few ever

occurred historically, which can put soils, streams,

and fish at risk (Hann et al. 1997). This does not

mean, however, that we must return our forests

completely to historical conditions to sustain biological diversity. Thoughtful evaluation of change

from historical conditions; evaluation of social

needs; presence of exotic species, structures,

and processes; and future climate all should play

a role in identifying DFCs and the management

alternatives to achieve them (Landres et al. 1999).

Acknowledgments

I am deeply indebted to the many creative and

thoughtful managers and scientists who helped

me develop my ideas. Wendel Hann was one of

the managers who originated the HRV concept.

Discussions with him and with Tom Swetnam,

Peter Landres, Dave Parsons, Bob Keane, Art

Zack, Steve Bunting, and many others have

helped me shape my ideas. Lee Harry, a silviculturist on the Beaverhead National Forest, originated the bowl, ball, and plate demonstration,

and thus his ideas were the genesis for figure 1.

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86

Case Studies
87

In the early 1990s, the forest industry in the Pacific Northwest was in a condition that has been

described as “gridlock” (FEMAT 1993). Because

of mounting evidence that old-growth forest ecosystems were declining in health and integrity,

and because of the listing or potential listing of

species (such as the northern spotted owl (Strix

occidentalis caurina) and various salmon stocks)

by the U.S. Fish and Wildlife Service as endangered or threatened, forest management practices were under intense criticism. Research

suggested that a large proportion of the historical

acreage of old growth had been lost to timber

harvest, and that the remaining stands were

heavily fragmented, causing risks to old-growthdependent species (FEMAT 1993). In addition,

habitat loss from roads, culverts, and degradation

of riparian areas was contributing to problems

with fish populations. On federal forest lands

(those lands managed by the USDA Forest Service and USDI Bureau of Land Management

[BLM]) within the range of the northern spotted

owl (western Washington and Oregon, and northern California), a series of court injunctions

against logging and delays from appeals of timber

sales had resulted in a dramatic decline of timber

harvest operations, with major economic, social,

and political consequences.

In 1993, President Clinton convened a large

group (ultimately over 100 contributors) of federal agency and university scientists, the Forest

Ecosystem Management Assessment Team

(FEMAT), and gave them the task of producing a

plan that would both provide for viability of oldgrowth ecosystems and their associated species

and provide for a sustainable level of economic

benefits from forest products (Johnson et al.

1999). Led by Jack Ward Thomas (later Chief of

the USDA Forest Service), the FEMAT group developed several options for consideration by

agency officials; the selected alternative was

adopted in 1994 (USDA USDI 1994) and became

what is now known as the Northwest Forest Plan

(NFP) (fig.1). The NFP guides management of 24

million acres of federal forest lands (including

national forest and BLM lands, as well as national

parks) within the range of the northern spotted

owl.

The Northwest Forest Plan–An

Ecosystem Management Approach

The Northwest Forest Plan was one of the earliest

and largest attempts to implement what was at

that time a relatively new concept in public land

use planning–that of managing whole systems,

including broad-scale vegetation patterns, biophysical processes, and whole suites of species.

This approach has become widely known as “ecosystem management.”

The NFP treats the land base as a system of interconnected parts, providing a single conservation biology strategy for wildlife, plants, fish, and

fungi associated with late-successional and oldgrowth forests. The old-growth orientation of the

NFP distinguishes it from other biodiversity conservation efforts. It weaves together efforts targeted at individual species potentially at risk (the

“survey and manage” component, described in

the next section), with broad-scale strategies that

sweep in groups of species and ecological processes (reserves, special guidelines for actively

managed areas). It specifically provides for active

management for both commodity production and

restoration. And finally, it is a long-term plan (100-

year timeframe in which target conditions become

fully implemented) with checkpoints along the way

to determine if adjustments are needed in order to

meet the goals.

A primary feature of ecosystem management is

that it is science based. To achieve sustainability,

plans must be built with an understanding of the

Northwest Forest Plan

Nancy M. Diaz1

1

Chief, Branch of Physical Sciences, OR/WA State Office,

U.S. Department of the Interior (USDI) Bureau of Land

Management, P.O. Box 2965, Portland, OR 97208-2965; Tel:

503-808-6036; e-mail: ndiaz@or.blm.gov
88

interactions and possibilities among the components of forest ecosystems and their associated

human communities. The NFP not only incorporated science, it was developed largely by scientists. This mode of plan development helped gain

the scientific credibility needed to reverse the

court injunction against timber harvest, and as

the plan proceeded to be implemented, resulted

in significant growth in scientist-manager collaborations.

The NFP includes three major facets:

• A strategy (composed of land allocations and

standards and guidelines) for managing 24

million acres of federal forest land.

• The Northwest Economic Adjustment Initiative, a $1.2 billion program (spread over

5 years) that provides support to timber-dependent communities, tribes, and businesses.

• An interagency model of policymaking,

wherein the participating federal agencies act

as partners in formulating policies and major

implementation steps. The participating agencies are:

o USDA Forest Service—Pacific Northwest

and Pacific Southwest Regions, and Pacific Northwest and Pacific Southwest

Research Stations

o USDI Bureau of Land Management

o USDI National Park Service

o USDI Fish and Wildlife Service

o USDI Geological Survey

o U.S. Environmental Protection Agency

o USDC National Marine Fisheries Service

o U.S. Army Corps of Engineers

o USDI Bureau of Indian Affairs

o USDA Natural Resources Conservation

Service

Northwest Forest Plan Land Allocations, Standards, and Guidelines

The heart of the NFP is in the system of reserves,

actively managed lands (matrix), and operational

guidelines it lays out. The key features are:

• Matrix lands–Making up about 16 percent of

the total NFP acreage, matrix lands are where

most active timber harvest is expected to

occur. Within managed areas, special standards and guidelines protect elements of latesuccessional and old-growth forests to provide

connectivity for old-forest-dependent organisms across the landscape, and provide refugia for them during the time that managed

areas are in earlier successional stages.

These standards include leaving 15 percent

of mature green trees in managed areas and

specific requirements for protection of snags

and large down wood.

• Late successional reserves (LSRs)–About 7.5

million acres (31 percent of the total) of federal

forest lands within the NFP area are in large

reserves within which late-successional and

old-growth forest structures and processes

are maintained and protected. The purpose of

LSRs is to provide large blocks of habitat for

species associated with old forests. The LSRs

Figure 1–Federal land allocations within the range of the

northern spotted owl.
89

are scattered throughout the NFP area such

that organisms can disperse among them

across the entire area (standards for intervening matrix areas help provide connectivity

across managed lands). Significant acreage in

LSRs is currently in younger stands (former

plantations); up to age 80, silvicultural treatments may be used to foster old-growth stand

structures and habitats. Once a stand reaches

age 80, no further management typically occurs.2

 All activities (for example, recreation) in

LSRs must be neutral or beneficial with regard

to late-successional and old-growth qualities.

When LSRs are combined with other types of

reserves (congressionally and administratively

designated areas, such as wilderness areas

and national parks), the resulting acreage is

approximately 78 percent of the total NFP

area.

• Aquatic conservation strategy (ACS)–The

NFP provides for the viability of native fish

stocks and overall riparian values through the

ACS. There are four components to this element of the NFP:

o Riparian reserves–Similar in policy and

intent to LSRs, riparian reserves consist

of buffers of varying widths (generally 100

to 300 feet) adjacent to all streams and

wetlands in the matrix. About 11 percent

of the total NFP acreage is in riparian

reserves. Besides providing benefits to

both riparian and aquatic habitats and

processes, riparian reserves also provide

late-successional habitat connectivity

across the matrix between LSRs.

o Key watersheds–Selected watersheds

within the NFP area are designated as

“key watersheds,” with special requirements for the protection of at-risk fish

stocks and water quality.

o Watershed analysis–A “systematic procedure to characterize the aquatic, riparian,

and terrestrial features within a watershed,” used to “refine riparian reserve

boundaries, prescribe land management

activities, including watershed restoration,

and develop monitoring programs” (USDA

USDI 1994).

o Restoration–Special emphasis has been

placed on proactively identifying and restoring degraded aquatic and riparian

sites (e.g., road crossings with inadequate culverts or stream reaches with

insufficient large instream wood.

• Monitoring and adaptive management–A

prime goal of the NFP is to learn from experience, and adjust the plan when appropriate.

This cycle of doing, learning, and adjusting is

termed “adaptive management.” Much of

adaptive management application occurs informally and opportunistically. Two “institutionalized” facets of adaptive management in the

NFP are:

o Monitoring–The NFP calls for monitoring

at multiple scales for an array of factors.

The most formalized monitoring occurs

at the NFP area-wide scale, in ongoing,

systematic assessments of northern spotted owl populations, marbled murrelets

(Brachyramphus marmoratus), aquatic

and riparian conditions, late-successional

and old-growth habitats, and adherence

to NFP guidelines in implementation of

land management activities. Monitoring

for biological diversity, socioeconomic

factors, and tribal relations is being

planned as well.

o Adaptive management areas (AMAs)–

Ten areas were designated AMAs in the

NFP, constituting about 6 percent of the

total acreage. The AMAs were geographically located to capitalize on opportunities

to develop partnerships (“collaborative

stewardship”) with local communities, and

were intended to be places where experimentation outside the matrix standards

and guidelines would be allowed (to test

the adequacy of the standards and guidelines) and where new management approaches could be developed and tested.

2 There may be exceptions to this rule on a case-by-case

basis, if needed, to reduce risk to old-growth characteristics.

For example, without thinning or other mechanical treatments

for fuels reduction and enhancement of stand structure, some

stands on the eastern flank of the Cascades with a highfrequency, low-intensity natural fire regime may be at risk of

stagnation, insect and disease outbreaks, or destruction by

wildfire. Conceivably, treatments after age 80 could be

allowed in these stands; however, such exceptions have not

been widely sought.
90

• Survey and manage (S&M) mitigation–When

the consequences of implementing all the

components listed thus far were evaluated, it

was determined that there were still approximately 400 species of old-growth-associated

plants, animals, and fungi whose persistence

was still uncertain. For many of the species,

lack of information on distribution and abundance was a major factor in their being included. This is not surprising, as the group

contains many rather obscure nonvascular

plants, fungi, invertebrates, and arthropods, in

addition to the better known flora and fauna.

The NFP sets out a special set of rules mandating surveys for S&M species prior to implementing management activities, and various

degrees of protection, depending on the

needs. Provision was made for S&M species

to be evaluated periodically as new information is obtained, with the goal of eventually

either determining that species should not

have been included in the first place, or providing an adequate plan of protection.

Has the NFP Succeeded?

For the most part, it is too early to tell whether the

NFP has succeeded in meeting its goals. Certainly, the harvest levels envisioned have not been

achieved, largely because of recent lawsuits, lack

of political support for harvest of old-growth forests on matrix lands, and other factors. Results of

monitoring efforts for species and aquatic/riparian

systems are still several years away. Agencies are

still struggling with adaptive management, both as

a concept, and in the context of the AMAs. On the

other hand, the injunction against timber harvest

was lifted, the agencies involved are working together proactively and collaboratively, and communities are increasingly involved in management

decisions.

In 1998, the Interagency Steering Committee

(ISC) commissioned a review of the NFP (Pipkin

1998). The report identified several elements of

the NFP as “useful and proven models” worthy of

inclusion in future assessments:

• A common regional “vision” for forests and the

timber economy that all participants can work

toward.

• “Institutionalized” collaboration (standing committees and chartered groups with specific

mandates) among agencies and the public.

• Provision for direct participation by nonfederal

governments including tribes.

• Consistent data collection and mapping

across ownerships.

• Specific inclusion of research and monitoring

for decisionmaking and adaptive management.

Challenges

The NFP was the first plan of its kind to attempt

such a comprehensive, ecologically based effort

with diverse agencies on a large land base. As

plan implementation has proceeded, questions

and issues have emerged that present significant

challenges to the interagency partners.

At the head of the list of compelling questions is

that of meshing ecosystem-based and singlespecies approaches to conserving late-successional and old-growth biological diversity. Except

for the survey and manage component, the NFP

assumes that providing for adequate habitat, connectivity, and ecological processes across the

landscape will protect biological diversity. The

FEMAT group viewed this assumption as a hypothesis that would be tested through monitoring,

with subsequent plan adjustments if necessary.3

However, an experimental approach to land management presumes that some degree of risk is

acceptable, a point around which there clearly is

lack of consensus. On the other hand, attempting

to manage a large set of cryptic species at a very

low level of risk is far beyond the resources of any

of the agencies; in fact, it is probably an unattainable goal to begin with. Strategies that minimize

risk to individual species by focusing on providing

habitat may be the only practical solution to

biodiversity conservation concerns. How to create

such strategies that are scientifically sound and

legally defensible remains a productive avenue for

further exploration.

3 To date, a framework for testing this hypothesis has not

been developed.
91

The need to work at multiple scales was explicitly stated as a goal for the NFP (FEMAT 1993).

However, technological tools for sliding up and

down the continuum of scales of space and time

have been slow in coming. Such tools would have

to provide the ability to both scale up (for example, assemble the cumulative effects of finer

scale phenomena) and scale down (disaggregate

larger scale phenomena into smaller temporally or

spatially explicit fragments). Currently, the NFP is

being implemented at several scales (stand, watershed, landscape, province, region), but it is

often impossible to translate data, findings, or

effects to larger or smaller scales because of

inconsistencies in methodologies, assumptions,

and so on.

There is an apparent tension between what I will

term static versus dynamic approaches to defining target conditions for a variety of ecosystem

elements within the NFP. The static approach is

manifested in the creation of rules, standards, and

guidelines that set a threshold or narrow range of

conditions that must be achieved and maintained.

This approach often has the terms “regulatory” or

“statutory” applied to it. In contrast, the dynamic

approach is evidenced in the notion of adaptive

management (experimental management with a

specific goal of learning and potentially adjusting

practices), and in the idea that because ecosystems are themselves dynamic, a wider range of

conditions will naturally (and should be allowed to)

exist through time. Both approaches have a place

in the NFP, but the extent to which each applies to

the various components of the NFP has yet to be

resolved. The main difference between the approaches is the perception of risk associated with

variation.

One of the most problematic examples of the

tension between the two approaches has been in

adaptive management areas. Although AMAs

were delineated with the express purpose of

evaluating the assumptions of the NFP through

testing a wide range of practices (some of which

may fall outside standards and guidelines), land

managers have been understandably reluctant to

venture outside the prescriptions of the NFP because of the very real threat of appeals, lawsuits,

and other forms of resistance from outside entities that may lack confidence in managers’ abilities to meet broad NFP goals. There are also

differing points of view among the agencies regarding how much and what type of experimentation is appropriate within AMAs.

Another example is fire-prone late-successional

reserves on the east flank of the Cascade crest,

where managers have hesitated, again because

of the risk of appeals and lawsuits, to seek exemptions from LSR guidelines in order to implement prescriptions that may reduce the risk of

stand damage from fire and insects. Both of these

examples illustrate that application of a static set

of rules to an inherently dynamic situation may

actually increase risk in the long run (through lost

opportunities for learning and improved management in the case of AMAs, and through increased

threat to old-growth values in LSRs).

Finally, because the NFP applies exclusively to

federal lands, the role of nonfederal lands, especially private lands, in the overall ecological,

social, economic, and political context of the region cannot be fully assessed. It is especially difficult to understand how private lands contribute to

the overall whole when large elements are unregulated and landowner behavior is difficult to

predict.

The federal agencies involved in the NFP have

set in motion numerous efforts to resolve these

and other issues. The NFP has not proved to be

the ultimate solution to conflicts over the use and

management of federal forest lands in the Pacific

Northwest. Although the agencies have achieved

major successes, small and large, the challenges

listed above, combined with the continuing need

to build public trust, have constituted real barriers.

The NFP’s strength lies in the strong science underpinnings on which it is founded, in the scope of

the ecological, social, and political issues it attempted to address, and in its built-in flexibility to

adapt and improve. It remains to be seen whether

the agencies and public together can capitalize on

these strengths to overcome the difficulties cited

here and realize the NFP’s promise of protection

for old-growth ecosystems while contributing to

regional economic health.

Metric Equivalents

1 foot = 0.304 meters

1 acre = 0.405 hectares
92

Literature Cited

Forest Ecosystem Management Assessment

Team [FEMAT]. 1993. Forest ecosystem management: an ecological, economic, and social

assessment. Portland, OR: U.S. Department

of Agriculture; U.S. Department of the Interior

[et al.]. [Irregular pagination].

Johnson, K.N.; Swanson, F.J.; Herring, M.;

Greene, S. 1999. FEMAT assessment–case

study. In: Johnson, K.N.; Swanson, F.J.; Herring, M.; Greene, S., eds. Bioregional assessments. Washington, DC: Island Press: 87-116.

Pipkin, J. 1998. The Northwest Forest Plan revisited. Washington, DC: U.S. Department of the

Interior, Office of Policy Analysis. 117 p.

U.S. Department of Agriculture, Forest Service; U.S. Department of the Interior, Bureau

of Land Management. 1994. Record of decision for amendments to Forest Service and

Bureau of Land Management planning documents within the range of the northern spotted

owl. [Place of publication unknown.] 74 p. [Plus

attachment A: standards and guidelines].
93

Abstract

We characterized recent historical and current vegetation composition and structure of a representative

sample of subwatersheds on all ownerships within the interior Columbia River basin and portions of the

Klamath and Great Basins. For each selected subwatershed, we constructed historical and current vegetation maps from 1932 to 1966 and 1981 to 1993 aerial photos, respectively. Using the raw vegetation

attributes, we classified and attributed cover types, structural classes, and potential vegetation types to

individual patches within subwatersheds. We characterized change in vegetation spatial patterns using a

suite of class and landscape metrics, and a spatial pattern analysis program. We then translated change

in vegetation patterns to change in patterns of vulnerability to wildfires, smoke production, and 21 major

forest pathogen and insect disturbances. Results of change analyses were reported for province-scale

ecological reporting units (ERUs). Here, we highlight significant findings and discuss management implications.

Twentieth-century management activities significantly altered spatial patterns of physiognomies, cover

types and structural conditions, and vulnerabilities to fire, insect, and pathogen disturbances. Forest land

cover expanded in several ERUs, and woodland area expanded in most. Of all physiognomic conditions,

shrubland area declined most due to cropland expansion, conversion to semi- and non-native herblands,

and expansion of forests and woodlands. Shifts from early to late seral conifer species were evident in

forests of most ERUs; patch sizes of forest cover types are now smaller, and current land cover is more

fragmented. Landscape area in old multistory, old single story, and stand initiation forest structures declined with compensating increases in area and connectivity of dense, multilayered, intermediate forest

structures. Patches with medium and large trees, regardless of their structural affiliation are currently

less abundant on the landscape. Finally, basin forests are now dominated by shade-tolerant conifers,

and exhibit elevated fuel loads and severe fire behavior attributes indicating expanded future roles of

certain defoliators, bark beetles, root diseases, and stand replacement fires. Although well intentioned,

20th-century management practices did not account for landscape-scale patterns of living and dead vegetation that enable forest ecosystems to maintain their structure and organization through time, or for the

disturbances that create and maintain them. Improved understanding of change in vegetation spatial

patterns, causative factors, and links with disturbance processes will assist managers and policymakers

in making informed decisions about how to address important ecosystem health issues.

Recent Changes (1930s–1990s) in Spatial Patterns of Interior

Northwest Forests, USA1

P.F. Hessburg,2 B.G. Smith,3 R.B. Salter,2 R.D. Ottmar,4 and E. Alvarado5

1 Hessburg, P.F.; Smith, B.G.; Salter, R.B.; Ottmar, R.D.; Alvarado, E. 2000. Recent changes (1930s–1990s) in spatial

patterns of interior Northwest forests, USA. Forest Ecology and Management. 136: 53-83. Reprinted with permission from

Elsevier.

2 Research ecologist, (Hessburg) and geographer (Salter), U.S. Department of Agriculture, Forest Service, Pacific Northwest

Research Station, Forestry Sciences Laboratory, 1133 N Western Ave., Wenatchee, WA 98801; Tel: 509-662-4315; e-mail:

phessburg@fs.fed.us, bsalter@fs.fed.us.

3 Quantitative ecologist, U.S. Department of Agriculture, Forest Service, 1230 NE 3rd St., Suite 262, Bend, OR 97701;

Tel: 541-383-4023; e-mail: bgsmith01@fs.fed.us.

4 Research forester, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Forestry Sciences

Laboratory, 400 N 34th, Suite 201, Seattle, WA 98103; Tel: 206-732-7828; e-mail: rottmar@fs.fed.us.

5

Research forester, U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, Forestry Sciences

Laboratory, 400 N 34th, Suite 201, Seattle, WA 98103; Tel: 206-732-7842; e-mail: ealvarado@fs.fed.us.
94

Landscape Methodology
95

Introduction

Several broad-scale ecoregional assessments

have been conducted in the United States in recent years (Everett et al. 1994, FEMAT 1993,

SNEP 1997, USDA FS 1996), and several more

are in progress. Each assessment has used a

now well-standardized approach to define the

analytical problem. A scoping process was used

to identify and evaluate critical issues deserving

consideration. A needs assessment was performed to identify data requirements and analytical methods needed to respond to the issues. A

wide array of statistical, simulation, and optimization procedures has been used to address various

components of the overall assessment problem.

To assert that the suite of analyses used in these

assessments was conducted ad hoc would be a

disservice. However, it is fair to say that, although

assessment teams may have carefully coordinated the conduct of analyses with integration in

mind, there is little evidence in the reports that

effectively integrated analysis was achieved.

Landscape Analysis With Ecosystem

Management Decision Support

The USDA Forest Service Pacific Northwest Research Station released the first production version of the ecosystem management decision

support (EMDS) system in February 1997. The

EMDS integrates a knowledge-base engine into

the ArcView3 (Environmental Systems Research

Institute, Redlands, CA) geographic information

system (GIS) to provide knowledge-based reasoning for landscape-level ecological analyses

(fig. 1). Major components of the EMDS system

include the NetWeaver knowledge-base system,

the EMDS ArcView application extension, and the

assessment system (Reynolds 1999a, 1999b;

Reynolds et al. 1996, 1997a, 1997b).

A knowledge base is a formal logical specification

for interpreting information and is therefore a form

of meta database in the strict sense (Jackson

1990, Waterman 1986). Interpretation of data by

a knowledge-base engine (a logic processor)

provides an assessment of system states and

processes represented in the knowledge base as

topics. Use of logical representation for assessing

the state of systems frequently is desirable or

necessary. Often, the current state of knowledge

about a problem domain is too imprecise for statistical or simulation models or optimization, each

of which presumes precise knowledge about relevant mathematical relations. In contrast, knowledge-based reasoning provides solutions for

evaluating this more imprecise information, and

some knowledge-based systems can provide

useful analyses even in circumstances in which

data are incomplete.

Knowledge-based solutions are particularly relevant to ecosystem management because the

topic is conceptually broad and complex, involving

numerous, often abstract, concepts (e.g., health,

sustainability, ecosystem resilience, ecosystem

stability, etc.) for which assessment depends on

numerous interdependent states and processes.

Logical constructs are useful in this context because the problem can be evaluated as long as

the entities and their logical relations are understood in a general way and can be expressed by

subject matter authorities.

Analysis and Communication of Monitoring Data With

Knowledge-Based Systems

Keith M. Reynolds1 and Gordon H. Reeves2

1 Research forester, Pacific Northwest Research Station,

Forestry Sciences Laboratory, 3200 SW Jefferson Way,

Corvallis, OR 97331; Tel: 541-750-7434; e-mail:

kreynolds@fs.fed.us.

2 Research fisheries biologist, Pacific Northwest Research

Station, Forestry Sciences Laboratory, 3200 SW Jefferson

Way, Corvallis, OR 97331; Tel: 541-750-7314; e-mail:

greeves@fs.fed.us

3 The use of trade of firm names in this publication is for

reader information and does not imply endorsement by the

U.S. Department of Agriculture of any product or service.
96

Nestucca Basin Example: Evaluation

of Salmon Habitat Suitability

The Nestucca basin is a 5th-code hydrologic unit

located in the northern portion of the Oregon

Coast Range province (fig. 2) and contains 45

true and composite 6th-code watersheds. In 1998,

a watershed assessment team from the Siuslaw

National Forest rated each true 6th-code watershed in the basin with respect to its suitability for

providing salmon habitat, following the rating system of the decision matrix of the National Marine

Fisheries Service (NMFS). In subsequent discussions with the authors, assessment team members expressed a number of reservations about

the approach that had been used for rating watershed condition.

To improve on the basic approach to watershed

evaluation for salmon habitat suitability as required to implement the Aquatic Conservation

Strategy of the Northwest Forest Plan, the authors

designed a prototype knowledge base suitable for

application to true 6th-code watersheds in the Oregon Coast Range province (fig. 2). Starting with

basic requirements identified in the NMFS matrix,

Reeves summarized logical requirements for the

knowledge base. The authors then worked together to implement the knowledge-base design

in NetWeaver, and then reviewed the initial design

with the assessment team to make refinements,

corrections, and additions to the initial version.

The most basic outputs from an EMDS analysis

are maps of evaluated indices for topics included

in an analysis. In our example, the primary map of

interest (fig. 3) displays the evaluated index for

salmon habitat suitability for each 6th-code watershed in the basin. Composite watersheds, for

which the knowledge base was not designed, are

Figure 1—Architecture of EMDS system. The acronym, GUI, indicates a graphic user interface through which a user

interacts with components of the EMDS application. The assessment system uses a custom GUI to manage communication between the NetWeaver logic engine and code internal to the EMDS ArcView extension. ESRI = Environmental Systems Research Institute.
97

Figure 2—The Nestucca basin is in the central

Oregon Coast Range.

Figure 3— Salmon habitat suitability in 6th-code watersheds in the Nestucca basin.

Patterned features are composite watersheds for which the knowledge base is not

appropriate. The scale expresses strength of support for the proposition that the

biophysical condition of a watershed provides suitable salmon habitat. The extremes of

the scale, -1 and 1, indicate no support and full support, respectively. Intermediate values

express some degree of support.
98

displayed with a lined pattern. All information that

is logically antecedent to topics selected for analysis also must be evaluated by the logic engine

and so is displayable either in maps, graphs, or in

tabular output generated by the logic engine.

Maps characterizing landscape condition are powerful communication tools, but it is at least as

important to be able to explain the basis for observed results in a clear, intuitive manner. One of

the most significant features of knowledge-base

systems is their ability to display a logic trace that

explains the derivation of conclusions. In this example, the top portion of the browser window

displays an expandable outline of knowledgebase structure, and the bottom portion displays

the logic structure of the topic currently selected in

the outline (fig. 4).

The NetWeaver logic engine reasons with incomplete information, when needed, by using fuzzy

math (Zadeh 1965, 1968), and the engine evaluates the influence of any missing information with

respect to its contribution to completeness of an

analysis. Input data for the Netsucca basin analysis contained a few missing observations on data

fields (fig. 5). However, the engine implements

evidence-based reasoning, producing partial

evaluations of topics with incomplete information

(figs. 3 and 4). The knowledge base is, in effect, a

mental map of the problem. Its structure contains

information that can be used to compute the influence of missing information (fig. 6). The computation of influence is based on the level at which

information enters the logic structure, how many

references there are to it, and how frequently the

associated database field contains missing observations. The assessment system in EMDS also

includes tools to optionally synthesize information

about data influence and the logistics of acquiring

data to prioritize data needs (Reynolds 1999a).

Finally, the logic engine generates tabular output

from which an analyst can summarize additional

information such as the frequency distribution of

index values (fig. 7) or the frequency with which

data substantially contribute to a particular conclusion (figs. 8 and 9). Frequency distributions of

indices provide a simple synoptic view of conditions over an assessment area at a point in time

(fig. 7), and useful statistical inferences about the

efficacy of restoration programs, for example,

could be drawn from comparisons of such frequency distributions over consecutive assessment times. Similarly, more detailed summaries of

conditions in an assessment area (figs. 8 and 9)

provide useful background information for design

of restoration programs as well as a basis for

more detailed statistical inferences about the efficacy of these programs.

Identifying Restoration Objectives and

Criteria

Problem specification for ecological assessment

may well deserve to be classified as a wicked

problem (Allen and Gould 1986). Evaluation monitoring must consider potentially numerous states

and processes of biophysical, social, and economic components of an ecosystem. Many entities may have both deep and broad networks of

logical dependencies as well as complex interconnections. Although constructing such complex

representations in NetWeaver is not trivial, it is at

least rendered feasible by the precision and compactness of fuzzy logic relations, and by the

graphic, object-based representation of logic networks in the system interface. No subject-matter

authority, nor for that matter any group of authorities, is capable of holding a comprehensive cognitive map of such a complex problem domain in

their consciousness. On the other hand, the

graphic, object-based form of knowledge representation in NetWeaver is highly conducive to the

incremental evolution of knowledge-base design

from simple to complex forms.

Two essential aspects of the knowledge-based

approach to evaluation monitoring that we have

described and illustrated are its goal orientation

and use of formal logic in problem specification.

The implications for realizing truly integrated

analysis are significant. Knowledge-base design

begins with identification of the questions (formulated as propositions) that the analysis ultimately

is designed to address. Specification proceeds by

identifying lines of reasoning that decompose the

original propositions into progressively more concrete ones until links to data are identified. The

result, effectively, is a mental map of the problem,

including not only identification of all topics pertinent to the problem, but their logical interdependencies. The final specification thus not only

provides logical links between data requirements

and the original motivating questions, but provides

a specification for how the data are to be interpreted, taking into account interrelations among

pieces of information.
99

Figure 4—The knowledge base with the EMDS hotlink

browser tool displays the state of the knowledge base

for features (e.g., watersheds) selected in the EMDS

Assessment View.

Figure 5—Frequency of missing data fields in the input data table for the Nestucca basin analysis.
100

Figure 6—Influence of missing information in the Nestucca basin analysis calculated by the NetWeaver logic engine.

Figure 7—Frequency distribution of the salmon habitat suitability index for the Nestucca basin analysis. Truth value interval is

a measure of the degree of support that data provide for a proposition. This index also can be interpreted as a measure of

suitability.
101

Figure 8—Frequency with which data in high-gradient drainages contributed to the conclusion of a compromised

or degraded biophysical condition. Drainages with an average reach gradient greater than 4 percent were

classified as high gradient; in-channel conditions were not available.

Figure 9—Frequency with which data in low-gradient drainages contributed to the conclusion of a compromised or degraded biophysical condition. Drainages with an average reach gradient less than or equal to

4 percent were classified as low gradient; data on in-channel conditions were available.
102

Performing Evaluations With

Incomplete Information

It is probably fair to say that almost all significant

monitoring and assessment programs start out

with significant data gaps. The NetWeaver logic

engine is particularly well suited for use in applications such as evaluation monitoring in particular

and ecosystem analysis in general because it is

able to reason with incomplete information and

still provide meaningful results, and because it

can evaluate the influence of missing information.

We noted earlier that the number of topics in any

reasonably realistic problem and the number of

interdependencies among them can easily overwhelm the capacity of the human brain to reason

effectively about such questions as, What is the

most useful information that I could acquire at this

point in time to improve the completeness of my

analysis? It is important to appreciate that the

influence of information is highly dynamic: the

influence of what is missing depends both on the

observations that are currently available, and on

the values in those observations. Consequently,

use of iterative analysis of data influence in EMDS

following successive, incremental additions of

new data could conceivably reduce resources

devoted to data collection on the order of 50 percent in typical applications.

In our very small example, the distributions of

missing data (fig. 5) and data influence (fig. 6)

mirror each other. More generally, and particularly

for larger and more complex logic models, the two

distributions may be very different owing to interdependencies among data elements. Even in this

simple case, however, it is clear that missing data

on water temperature are the largest source of

uncertainty in the current analysis (fig. 6). It also is

quite possible that if some of the missing water

temperature observations were acquired, pool

quality, fines, and farm use might no longer have

nonzero influence.

Explanation of Monitoring Results

The ability to explain monitoring results to colleagues, line officers, interested publics, etc. is at

least as important as the ability to perform an

analysis in the first place. If the logic of underlying

models cannot be presented in clear, unambiguous terms to such audiences, results will not be

trusted. Powerful and sophisticated linear programming systems such as FORPLAN largely

failed on this account.

Our experience to date with EMDS, and with its

knowledge-base browser interface in particular,

has been that the presentation of results from

logic models is easy to grasp at an intuitive level

so the results are accessible to broad audiences

with only limited explanation. An analyst can easily

run the browser interactively in front of an audience, navigating the structure of the evaluated

knowledge base, and explaining the derivation of

the logic as he or she goes. The earlier logic diagram (fig. 4) provides a good example. Composite

watersheds (WS type = 1) are screened out of the

analysis with a logic switch and remain in an undetermined logic state. For true watersheds, the

right-hand path under the WS type logic switch is

followed. Biophysical condition of a true watershed evaluates as suitable to the degree that

there is suitable riparian vegetation and a suitable upland environment. A second logic switch

checks whether the data for the watershed include an evaluation of in-channel conditions.

If a low-gradient stream survey was performed

(lowGradSurvey > 0), then the evaluation includes

the upland, in-channel, and riparianVeg topics;

otherwise the evaluation of biophysical condition

only depends on the upland and riparianVeg topics. Each of the three topics, upland, in-channel,

and riparianVeg, has its own logic specification

(not shown).

Evaluation Within Larger Contexts

Almost all landscape analyses are performed

within the context of some broader scale. Our

knowledge base for evaluation of salmon habitat

suitability is a prototype constructed for the specific context of the Oregon Coast Range. Consequently, it is unlikely that the current version is

sufficiently general for application throughout the

planning region of the Northwest Forest Plan,

which encompasses the range of the northern

spotted owl (Strix occidentalis caurina).

Fortunately, it is not difficult to generalize prototypes such as ours for broader applicability. In

some cases, for example, it may be sufficient to

replace hard-wired arguments with a calculated

one that contains a more general fuzzy membership function whose parameters vary with additional context information. For more dramatic
103

variations in logic structure, it may be necessary

to add new logic switches that similarly select

alternative logic pathways based on additional

context information. In a technical sense, knowledge-base generalization is a relatively minor

issue. On the other hand, it leads naturally to discussion of the more interesting question of

multiscale implementations.

Extending Ecosystem Management

Decision-Support Applications to

Multiple Spatial Scales

It is relatively easy in principle to extend integrated

analysis via knowledge-based reasoning over

multiple spatial scales (fig. 10). Data from finescale landscape features such as 6th-code watersheds are first processed by a knowledge base

designed for that scale. Knowledge-base output,

shown as evaluated states in the middle of the

figure, then go through an intermediate filter (typically implemented in a spreadsheet or database

application) to synthesize information for input to

the next coarser scale. A second knowledge base

processes the synthesized information to provide

an assessment of landscape-level attributes at

the top of the figure. Finally, knowledge-base outputs at the broader landscape scale may feed

back to the fine scale as context information that

influences evaluations at the fine scale. This

simple conceptual model provides the basis for a

formal logical specification of analyses that are

consistent across scales. Hierarchies, or even

networks, of knowledge-based analyses as suggested would be highly consonant with ecosystem

theories concerning the hierarchical organization

ecosystems.

English Equivalents

1 kilometer = 0.62 miles

Figure 10—An example of knowledge-based

integration across spatial scales.
104

Literature Cited

Allen, G.M.; Gould, E.M., Jr. 1986. Complexity,

wickedness, and public forests. Journal of

Forestry. 84: 20-23.

Everett, R.; Hessburg, P.; Jensen, M.;

Bormann, B. 1994. Eastside forest ecosystem

health assessment. 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.

Forest Ecosystem Management Assessment

Team [FEMAT]. 1993. Forest ecosystem management: an ecological, economic, and social

assessment. Portland, OR: U.S. Department

of Agriculture, Forest Service; U.S. Department

of the Interior, Bureau of Land Management;

[et al.]. [Irregular pagination].

Jackson, P. 1990. Introduction to expert systems.

Reading, MA: Addison-Wesley Publishers.

526 p.

Reynolds, K.; Cunningham, P.; Bednar, L.

[et al.]. 1996. A design framework for a knowledge-based information management system

for watershed analysis in the Pacific Northwest

U.S. AI Applications. 10: 9-22.

Reynolds, K.M. 1999a. EMDS users guide (version 2.0): knowledge-based decision support

for ecological assessment. Gen. Tech. Rep.

PNW-GTR-470. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 63 p.

Reynolds, K.M. 1999b. NetWeaver for EMDS

user guide (version 1.1): a knowledge base

development system. Gen. Tech. Rep. PNWGTR-471. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest

Research Station. 75 p.

Reynolds, K.M.; Saunders, M.; Miller, B. [et

al.]. 1997a. An application framework for decision support in environmental assessment. In:

GIS 97 Proceedings of the eleventh annual

symposium on geographic information systems. Washington, DC: GIS World: 333-337.

Reynolds, K.M.; Saunders, M.; Miller, B. [et

al.]. 1997b. Knowledge-based decision support in environmental assessment. In: Proceedings 1997 ACSM/ASPRS annual convention and exposition. Bethesda, MD: American Society for Photogrammetry and Remote

Sensing: 344-352. Vol. 4

Sierra Nevada Ecosystem Project [SNEP].

1997. Final report to Congress, addendum.

Davis, CA: University of California, Centers for

Water and Wildland Resources. 328 p.

U.S. Department of Agriculture, Forest Service. 1996. The Southern Appalachian assessment summary report. Tech. Pap. R8-TP-25.

Atlanta, GA: Southern Region [Region 8].

118 p.

Waterman, D.A. 1986. A guide to expert systems.

Reading, MA: Addison-Wesley Publishers.

419 p.

Zadeh, L.A. 1965. Fuzzy sets. Information and

Control. 8: 338-353.

Zadeh, L.A. 1968. Probability measures of fuzzy

events. Journal of Mathematical Analysis and

Applications. 23: 421-427.
105

Introduction

The appearance of forested landscapes and individual stands after forest management activities

is critical to public acceptance of these activities.

Even with thorough planning, detailed site-specific

analysis, and careful monitoring, many management activities will not be truly successful if the

public views the resulting landscape as an eyesore. Unfortunately, many people judge the success or failure of management activities based on

the visual impact of the activity to an otherwise

“natural” landscape.

Forestry professionals have long used visualization techniques to address a variety of forest

management problems. Prior to the advent of

computerized methods, they used “artists’ renditions” to communicate the effects of land management activities. Perspective sketches and

scale models continue to help communicate the

spatial arrangement and extent of management

activities to the lay public. However, current management practices use more detailed silvicultural

prescriptions involving small treatment areas scattered over larger landscapes and the removal or

modification of specific stand components. In

addition, treatment regimes are designed to

achieve a desired condition over long timespans

by using a series of treatments. Given the broad

range of treatments considered and changes to

stand conditions over time, it is difficult to produce

traditional artists’ renditions that reflect the expected condition accurately and with a minimum

of artist-contributed bias. In addition, the time

required to produce artists’ renditions limits their

use when depicting several alternative treatment

strategies.

Foresters charged with selecting stands for treatment and designing silvicultural prescriptions often find it difficult to comprehend the complex

spatial and temporal interactions that occur

across landscapes. Traditional work methods

involving fieldwork, maps, and aerial photographs

provide enough information to assess individual

treatments but may not provide adequate information to fully evaluate the cumulative impact of

treatments or the impact of treatments implemented over time. Computer-based landscape

simulations are a recognized tool for assessing

the potential visual impact of land use decisions

and management activities. Visualization tools

that include a stand projection component or provide linkages to such models can simulate and

depict stand and landscape changes over time.

Such presentations help to communicate stand

and landscape conditions and how these conditions change as a result of management activities,

natural disturbances, and growth over time. During the treatment design process, visualizations

depicting treatments within their landscape context provide important feedback. Such feedback

can help resource specialists develop and implement better landscape management plans. Furthermore, visualizations help communicate

management activities to other resource specialists and public stakeholders.

Overview of Visualization Techniques

Computerized visualization methods range from

simple diagrams to complete virtual realities. Four

methods, described in detail and compared in

McGaughey (1998), are commonly used to produce visual representations of forest operations:

• Geometric modeling

• Video imaging

• Geometric video imaging

• Image draping

Geometric modeling methods build geometric

models of individual components (ground surface,

trees, other plants, and structures) and then assemble the component models to create a scene

that represents a forest stand or landscape.

Seeing the Forest and the Trees: Visualizing Stand and

Landscape Conditions

Robert J. McGaughey1

1 Research forester, U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station, University of

Washington, P.O. Box 352100, Seattle, WA 98195-2100; Tel:

(206) 543-4713; e-mail: mcgoy@u.washington.edu,

rmcgaughey@fs.fed.us
106

Video imaging uses computer programs to modify

scanned full-color video or photographic images

to represent changes to stand and landscape

conditions. To portray a wide range of landscape

conditions, video-imaging techniques use a library

of images that represent different forest conditions to replace portions of an original image.

A hybrid approach, called geometric video imaging by this author, combines geometric modeling

and video-imaging techniques to produce realistic

images that accurately represent data describing

the effects of forest management activities. Operators use geometric modeling to produce images that specify the location, arrangement, and

scale of stand or landscape features. These images then guide video-imaging manipulations that

modify a photographic image to reflect proposed

stand or landscape changes. By combining the

precise spatial location capabilities of geometric

modeling and the photo-manipulation capabilities

of video imaging, hybrid methods result in spatially accurate, photo-quality images. However,

hybrid techniques, like video imaging, require

extensive libraries of tree and stand images to

represent an appropriate range of species, tree

sizes, growth forms, landscape positions, and

treatment options.

Image draping mathematically “drapes” an image

over a digital terrain model to create a textured

surface. The draped image is typically a satellite

scene, aerial photograph, orthophoto, or scanned

map sheet.

Of the four methods, geometric modeling provides the most consistent link between data describing stand and landscape conditions and

features in a generated image. In general, there is

a one-to-one relationship between data elements

and objects in the final image. Geometric modeling produces images that are generally less realistic than images produced from photographs.

However, if photographic icons are used to represent individual trees and other objects, geometric

modeling can produce images that contain many

of the details normally associated with photographs.

Visualization of Stand/Plot-Scale

Areas

Foresters use stand tables, showing the relative

abundance of plant species and size classes, and

simple graphs, showing single or multiple stand

attributes as a function of stand age, to present

information describing forest stands and stand

conditions. These communication tools, suitable

for conveying simple data relationships to scientific and professional audiences, do not always

provide an easily understood representation of a

forest stand or the changes in stand structure that

can occur after disturbances or natural processes.

The Stand Visualization System (SVS) was designed to help foresters understand and communicate stand conditions and changes in stand

conditions resulting from management activities

or natural processes (McGaughey 1997).

The SVS uses geometric modeling techniques to

create images depicting stand conditions. As part

of the stand construction process, SVS converts

tables describing the population of standing trees,

down material, and understory shrubs into a list of

individual stand components, e.g., trees, down

logs, and shrubs. Standing trees and down material are defined by using the number of trees or

logs per hectare. Understory shrubs can be defined by using the number of plants per hectare

but are more commonly defined by using a percentage of cover. The SVS generates enough

plants to achieve the desired cover. Plant locations are generated by using a variety of spatial

patterns including patterns that mimic natural and

planted stands. The SVS also reads output from

the Forest Vegetation Simulator (Wykoff et al.

1982) and ORGANON (Hester et al. 1989). The

images produced by SVS, although abstract, provide a readily understood representation of stand

conditions and help communicate silvicultural

treatments and forest management alternatives to

a variety of audiences. The SVS provides the

following specific capabilities:

• Display overhead, profile, and perspective

views of a stand.

• Differentiate between stand components by

using different plant forms, colors, or other

types of marking as specified by users.

• Provide tabular and graphical summaries of

information represented in a stand image.

• Facilitate the design of silvicultural treatments

by allowing users to select individual stand

components and specify treatments.

• Display information describing individual stand

components as they are selected by the user.
107

Once an SVS tree list has been created, users

can simulate silvicultural treatments by selecting

individual trees or groups of trees and specifying

a treatment action such as removal or pruning.

As an alternative, treatment rules such as “remove 75 percent of the stand basal area from

below” can be applied to the entire stand. Figure 1

shows a 1-hectare stand before and after a simple

thinning treatment that removes all of the alder

(Alnus Hill.) trees and a portion of the Douglasfir (Pseudotsuga menziesii (Mirb.) Franco) trees.

Figure 2 shows the same stand after a treatment that removed all of the alder and six small

patches containing 30 percent of the Douglas-fir

basal area.

Visualization of Landscape-Scale

Areas

A wide array of techniques is available for presenting landscape-scale information ranging in

complexity from simple tables and graphs to

color-coded maps to photo-realistic computer

visualizations. Computer visualization techniques

are especially useful given the complexity of stand

treatments, the spatial distribution of treatment

units, and the desire to view landscape conditions

over time. Landscape visualization provides the

viewer with an easily identified image of a landscape complete with topographic features and

stand conditions. A new visualization system being developed by the author, EnVision, is designed to portray landscape conditions by using

data describing individual stands. EnVision provides several capabilities not previously available

or not available in the same application. For example, EnVision can fill individual polygons with a

texture derived from an aerial photograph while

rendering individual trees in other polygons.

An EnVision scene is based on a gridded digital

terrain model2

 that defines the ground surface.

EnVision provides a variety of methods to represent the ground including gridlines and contour

lines, with and without hidden area removal, and

as a shaded, lighted surface. Surface features

such as roads, streams, and points of interest can

be represented as points, lines, or polygons on

the ground surface or as solid walls or point markers sitting on the ground surface. To represent

ground surface texture, EnVision can fill polygon

features with textures derived from aerial photographs. This “synthetic aerial photo” capability can

be used to provide ground texture representing

vegetation under a canopy of larger trees that are

drawn as geometric models.

EnVision can use a variety of data to describe

conditions within individual stands. The simplest

form of stand data consists of the distribution of

tree sizes for each species present in a stand.

More complex data include individual tree records

from inventory plots that include species, diameter

at breast height, total tree height, live crown ratio,

crown width, and the number of trees per unit

area represented by the record. Stand data are

merged with data describing the growth form and

general crown shape for each tree species to

construct a geometric model for each tree in a

stand.

Multiscale Visualization

The ability to visualize individual stands by using

SVS has significantly enhanced a forester’s ability

to understand and communicate stand conditions

and the effects of silvicultural treatments on a

stand. Through linkages with the Forest Vegetation Simulator (Teck et al. 1996, Wykoff et al.

1982), SVS provides visualizations of stand

growth and development. However, understanding

the dynamics within an individual stand does not

necessarily lead to a better understanding of the

dynamics of an entire landscape. The complexity

of landscape management plans, variety of stand

treatments, and time period for which most plans

are developed make it difficult to understand and

communicate the plan’s impact on the landscape.

A system that links the design and visualization of

individual stand treatments with the ability to display the stands within their landscape context is

needed. EnVision provides this linkage by allowing the use of an SVS tree list to represent each

stand on a landscape. In operation, EnVision replicates the SVS tree list to fill the stand polygon by

2 Gridded digital terrain models that correspond to the U.S.

Geologic Survey’s 7.5-minute quadrangle series are available

for most areas in the United States. Other terrain model

types, e.g., TIN models, can be used to generate a gridded

model by using geograpic information system (GIS) software.
108

using a simple tiling algorithm. This linkage between SVS and EnVision makes it possible to

design spatially explicit treatments within SVS and

visualize that treatment within the landscape context. Figure 3 shows a landscape where the 1-

hectare stand in figure 2 has been used to fill a

21-hectare stand polygon. In this example, SVS

tile reflection has been used to minimize any pattern effects that might result when filling the stand

polygon.

Conclusions

This paper has discussed a variety of techniques

that can help land managers visualize, understand, and communicate stand- and landscapescale management actions. In particular, this

paper has highlighted the SVS and EnVision applications developed by the author.

Figure 1—SVS visualization of a 1-hectare stand (a) before and (b) after a uniform thinning treatment. The thinning removed

all of the alder and 25 percent of the Douglas-fir basal area from below.

Figure 2—SVS visualization showing an overhead view of the stand shown in figure 1 but

after a treatment that removed all of the alder

and six small patches containing 30 percent of

the Douglas-fir basal area.

Figure 3—Landscape visualization produced by EnVision

showing a stand polygon filled by using the SVS stand shown

in figure 2. Individual trees have been rendered only in the

polygon of interest. Other stand polygons have been filled

with textures that represent the stand structure.
109

Experience with SVS, UTOOLS/UVIEW landscape analysis and visualization system (Ager

and McGaughey 1997), and Vantage Point prototype (Bergen et al. 1998) indicates that such visualization tools help resource specialists and land

managers make better decisions. However, such

tools also can produce photo-realistic images that

can mislead viewers. Practitioners must be careful when using such tools that they do not intentionally or unintentionally misrepresent existing or

expected conditions (Wilson and McGaughey

2000). Failure to do so will seriously limit the usefulness of these visualization techniques for future

projects.

English Equivalents

1 hectare (ha) = 2.47 acres

Literature Cited

Ager, A.A.; McGaughey, R.J. 1997. UTOOLS:

microcomputer software for spatial analysis

and landscape visualization. Gen. Tech. Rep.

PNW-GTR-397. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 15 p.

Bergen, S.D.; McGaughey, R.J.; Fridley, J.L.

1998. Data-driven simulation, dimensional

accuracy and realism in a landscape visualization tool. Landscape and Urban Planning. 40:

283-293.

Hester, A.S.; Hann, D.W.; Larsen, D.R. 1989.

ORGANON: southwest Oregon growth and

yield model user manual, Version 2.0.

Corvallis, OR: Oregon State University, Forest

Research Laboratory. 59 p.

McGaughey, R.J. 1997. Visualizing forest stand

dynamics using the Stand Vsualization System. In: Proceedings of the 1997 ACSM/

ASPRS annual convention and exposition.

Bethesda, MD: American Society of Photogrammetry and Remote Sensing: 248-257.

Vol. 4.

McGaughey, R.J. 1998. Techniques for visualizing the appearance of forestry operations.

Journal of Forestry. 96(6): 9-14.

Teck, R.; Moeur, M.; Eav, B. 1996. Forecasting

ecosystems with the Forest Vegetation Simulator. Journal of Forestry. 94(12): 7-10.

Wilson, J.S.; McGaughey, R.J. 2000. Presenting

landscape-scale forest information: What is

sufficient and what is appropriate? Journal of

Forestry. 98(12): 21-28.

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.
110

Introduction

Interest in the management of forests at the landscape level has increased dramatically over the

past several decades. An area where this has

recently received much attention is on lands managed by the USDA Forest Service in the Pacific

Northwest. Prior approaches to forest management on these lands focused landscape-level

planning on development of a road network to aid

in wildfire suppression and dispersion of harvest

activities. Stand treatments were primarily clearcuts designed to meet several objectives including

rapid stand regeneration and the creation of edge

and early seral wildlife habitat. Fueled by change

in public perception of clearcuts and a growing

concern over the effect of forest fragmentation

on the loss of old-growth forest habitat on wildlife, especially the northern spotted owl (Strix

occidentalis caurina), and water quality during the

late 1980s, all Forest Service timber sales were

temporarily suspended. To end the suspension,

the Northwest Forest Plan (USDA and USDI

1994) was developed and is the guiding plan for

9.7 million ha of federally managed forest land.

The Northwest Forest Plan (NWFP) is based on a

system of static reserves, riparian corridors, and

general forest land called matrix lands. A criticism

of the NWFP is the use of static reserves on a

A Method to Simulate the Volume and Quality of Wood

Produced Under an Ecologically Sustainable Landscape

Management Plan

Glenn Christensen,1 R. James Barbour,2 and Stuart Johnston3

Abstract

Adopting the Northwest Forest Plan into federal land management brought with it many new challenges

to forest planning. One challenge is to determine what effect using new and untested silvicultural treatments to meet ecologically based objectives will have on the production of wood or other products that

society values. Determining the quantity and quality of potential outputs as a consequence of ecological

restoration activities is important to helping understand the cost to society of implementing such a plan.

The difficulty comes from the scale of the problem. No longer are short-term stand-level analyses adequate; evaluation of forest outputs has to be at meaningful spatial and temporal scales. To be successful, new methods will have to be developed.

The objective of this paper is to present a method used to evaluate wood removals from a landscape

management plan that was developed to meet ecological objectives by mimicking past disturbance

cycles. This required extending stand-level techniques for simulating quality and quantity of wood to 980

stands in the Blue River watershed of western Oregon. Silvicultural prescriptions include a range of thinning intensities and frequencies combined with extended rotation ages (100 to 260 years).

Study results include the range of products that might be manufactured under different silvicultural alternatives and evaluate the volume as well as the quality of primary and secondary products. Primary product quality estimates include log attributes such as diameter, branch size, juvenile wood, and growth ring

count. Secondary product estimates include lumber or veneer volume recovered by grade and likely end

use.

1 Forester, U.S. Department of Agriculture, Forest Service,

Pacific Northwest Research Station, Forestry Sciences

Laboratory, P.O. Box 3890, Portland, OR 97208; Tel: 503-808-

2064; e-mail: gchristensen@fs.fed.us

2 Research scientist, U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, P.O. Box 3890, Portland, OR 97208;

Tel: 503-808-2542; e-mail: jbarbour01@fs.fed.us

3 Forester, U.S. Department of Agriculture, Forest Service,

Siuslaw National Forest, Mapleton Ranger District, 4480

Highway 101, Building G, Florence, OR 97439; Tel: 541-902-

6958; e-mail: sjohnston@fs.fed.us
111

dynamic landscape. Recently, however, considerable interest has emerged as a different approach

to landscape-level planning, and two studies have

been initiated in the central Willamette National

Forest of Oregon. Both the Augusta Creek study

(Cissel et al. 1998) and the Blue River landscape

plan (Cissel et al. 1999) have focused upon integrating historical disturbance regimes into landscape- and watershed-level management plans.

These approaches use information on historical

and current landscape conditions, disturbance

history, and social goals to set objectives for future landscape structures that provide desired

habitat, watershed, timber supply, and other functions (Cissel et al. 1999). The intent is not to

mimic historical conditions but rather to use them

as a reference in developing and evaluating management alternatives to meet these goals.

The Blue River landscape plan is an integrated

landscape management strategy that was developed to achieve both ecological and social objectives. As stated in the plan, the “primary goal is to

sustain native habitats, species, and ecological

processes while providing sustained flow of wood

fiber for conversion to wood products” (Cissel et

al. 1999). The key underlying concept is that by

simulating certain aspects of the historical fire

regime through forest management activities, we

can sustain the historical range of variability necessary to preserve these native habitats, species,

and ecological processes while still providing a

predictable flow of timber.

Regardless of which approach is used, methodologies and protocols are needed that describe

the quantity, quality, and value of the wood produced under landscape-level plans. Managers

also need to know when wood will be removed

and from what locations on the landscape. In addition to difficulties from planning at large spatial

and temporal scales, most modern forest management requires the use of complex silvicultural

prescriptions in the form of thinnings, group selections, and individual tree selections to meet specific stand structure objectives. To address these

complexities, the Landscape Management System (LMS) was developed at the University of

Washington (McCarter 1997).

Study Area

The 23 900-ha Blue River watershed is almost

entirely managed by the USDA Forest Service

and includes the H.J. Andrews Experimental Forest, an area with an extensive history of ecosystem research. Of the 298 million ha of forest land

within the United States, 19 percent (56 million

ha) is managed by the USDA Forest Service

(Smith et al. 1994). The Blue River watershed is

located in the Willamette National Forest within

the McKenzie River watershed, a tributary of the

Willamette River in western Oregon (fig. 1).

The landscape is steep, highly dissected volcanic

terrain of the Cascade Range. Annual precipitation exceeds 2500 mm falling mostly in October

through April as rain at lower elevations and snow

in higher areas. The landscape ranges from 317

to 1639 m in elevation and is covered largely by

coniferous forests dominated by Douglas-fir

(Pseudotsuga menziesii (Mirb.) Franco), western

hemlock (Tsuga heterophylla (Raf.) Sarg.), and

Pacific silver fir (Abies amabilis Dougl. ex Forbes)

(Cissel et al. 1999).

Approach

The approach for this analysis is to use the Blue

River landscape plan as the basis to determine

scheduling of stand treatments and silvicultural

prescriptions. The analysis focuses on wood production as trees are harvested to meet broader

ecological objectives. The main tool used for

simulation is the LMS, a computerized system

that integrates landscape-level spatial information,

stand-level inventory data, and distance-independent individual tree growth models to project

changes though time across forested landscapes

(McCarter 1997). Once current conditions are

determined for each stand as accurately as possible, silvicultural treatments are scheduled and

growth projections made. As stands are grown

and treatments made, information is collected on

individual tree volume and quality characteristics.
112

This analysis uses methods similar to those developed by Christensen (1997) and Barbour et al.

(1996) to evaluate the volume and quality of wood

from a range of silvicultural regimes. Tree volume

and quality information is analyzed with the

TREEVAL (Briggs 1989, Sachet et al. 1989)

model to estimate potential lumber volume and

grade recovery. The TREEVAL model was developed by the USDA Forest Service, Pacific Northwest Research Station to provide financial information and analysis of product recovery to

support silvicultural decisions in coast Douglas-fir

(P. menziesii var. menziesii). Analyses conducted

by Christensen (1997) and Barbour et al. (1996)

are temporally explicit, evaluating wood produced

from individual stands through time. They are

spatially implicit in terms of where the wood came

from. The current analysis adds the spatial dimension to this process, providing not just wood production information as a stand develops over

time, but also providing information on the source

of wood from across many stands within a watershed. This gives planners the ability to understand

how stand treatments will interact to provide a

predictable flow of wood in terms of volume and

grade recovery from a defined landscape.

Modeling Wood Production by Using

the Landscape Management System

The LMS model was chosen for its landscapelevel analysis capabilities, as well as its integration of various component programs to provide

detailed tree volume and wood quality information.

Of particular interest is the ability to choose

among several different growth and yield models

within the program to allow maximum flexibility in

the number of species, kinds of silvicultural treatments, and output produced. Included in LMS are

stand- and landscape-level visualization programs

that permit, in addition to traditional quantitative

analysis, generalized visual representations of

different management options.

A detailed description of the methodology for each

part of the project can be found in Christensen et

al.4 For this paper, a brief overview is provided

giving the basic approach used during each

phase of the study.

Figure 1—Location of Blue River watershed.

4 Christensen, G.A.; Stuart, J.; Malinick, T.E. [In preparation].

Simulating the volume and quality of wood produced under

an ecologically sustainable landscape management plan in

the Oregon Cascade Range: results from the Blue River

Landscape Plan. Res. Pap. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest Research

Station.
113

Current Stand Conditions

As part of the analysis for the Blue River Landscape Plan, much basic information had already

been assembled. The most important of this information was geographic information system (GIS)

data files. From the GIS data, we knew the stand

type, vegetation association, and how the stand is

to be managed. Now we needed an inventory for

each stand with specific tree measurements. The

LMS software requires specific stand inventory

data including stand or polygon number, species,

diameter at breast height, height, crown ratio, and

expansion factor, on a per-acre basis. The spatial

data requirements vary depending upon the

growth-and-yield model selected but can include,

by stand or polygon number, number of plots,

regional location, site index, habitat type, age,

slope, aspect, and elevation. Among the available

data sets, it was determined that the inventory

plots maintained by the current vegetation survey

(CVS) in the Willamette National Forest had the

most applicable stand inventories in addition to

providing the most widely distributed sample plots.

By using CVS data for stand inventories we were

able to determine current vegetation condition for

many stands. However, a significant number of

stands remained that had no available tree-level

data. To overcome this, we used all available information to assign inventory data to these

stands. By using a combination of vegetation association, stand type (tree species and structure),

age, elevation, slope, aspect, and site index we

were able to select the closest match from stands

that had inventory data. Once this process was

complete, we had an intact inventory for 980

stands giving us the current vegetation condition

of the entire watershed.

Silvicultural Prescriptions, Stand

Treatment Scheduling, and Growth

Projections

As part of the Blue River Landscape Plan, the

watershed was divided into two basic management categories, reserves and landscape areas.

Reserves were established to protect special interest areas such as late-successional spotted

owl habitat and riparian areas along fish-bearing

streams. Landscape areas are the areas designed to meet a variety of ecological and social

objectives where some level of timber harvest will

occur (fig. 2).

For this study, reserve areas were assumed to

receive no timber harvest and are not included in

the analysis. Landscape areas were divided into

three types based on interpretation of historical

fire-return intervals and intensity. The three landscape areas are (Cissel et al. 1999):

• Landscape area 1–Frequent fire-return interval and moderate severity (40 to 60 percent

mortality).

• Landscape area 2–Moderate fire-return interval and moderate-to-high severity (60 to 80

percent mortality).

• Landscape area 3–Infrequent fire-return interval and high severity (>80 percent mortality).

Cissel et al. (1999) developed silvicultural prescriptions for each landscape area to closely

mimic natural stand development following a fire

(table 1). Treatments were designed to produce

stand structures and wildlife habitat closely resembling historical conditions within the watershed. These prescriptions were used in the LMS

model for this analysis. It is assumed that for each

prescription, reforestation (through replanting) will

succeed under some level of overstory. It is also

assumed that, as after a natural fire, overstory

retention will be nonuniform and distributed as

patches and scattered individual trees throughout

the stand. Patchy overstory retention also will

stimulate understory growth in the gaps aiding

replanting success and development of vertical

structural diversity. Further structural diversity,

both horizontal and vertical, will be developed

through several thinning entries prescribed for

each landscape area.

Simulation of stand growth within LMS used the

ORGANON growth and yield model (Hann et al.

1994). ORGANON has the advantage of allowing detailed silvicultural treatments and provides

quantitative estimates of important stand attributes such as percentage of crown cover following a thinning. Another advantage of ORGANON

is that it provides estimates of tree quality characteristics as an optional output. Tree characteristics

estimated by ORGANON include height to each

branch, largest branch diameter, diameter of the

juvenile wood core at each branch whorl, and

diameter inside bark of the stem at each branch

whorl. A similar output from LMS has been developed but has not been fully tested. A limitation of
114

Figure 2—Blue River Landscape Plan

treatment areas (Cissel et al. 1999).
115

Table 1—Blue River silvicultural prescriptions

Prescription elements Landscape area 1 Landscape area 2 Landscape area 3

Rotation age (years)/%

regeneration harvested

annually 100/1.0 180/0.56 260/0.38

Landscape block sizes

<40 ha (% of area) 60 20 20

40-80 ha (% of area) 20 40 40

80-160 ha (% of area) 20 20 40

Retention level (% of existing

overstory crown closure) 50 30 15

Retention mixture Shade intolerant – Shade intolerant – Shade intolerant –

(% of species dependent 65 80 95

on plant association) Shade tolerant– Shade tolerant– Shade tolerant–

35 20 5

Reforestation density

(trees per hectare) 500 750 1000

Reforestation mixture Shade intolerant– Shade intolerant– Shade intolerant–

(% of species dependent 40 60 75

on plant association) Shade tolerant– Shade tolerant– Shade intolerant–

60 40 25

First thinning (tph)a 500 at year 35 500 at year 20 to 25 500 at year 12 to 15

Second thinning (tph) 250 at year 35 275 at year 40 275 at year 40

Third thinning (tph) 150 at year 65 200 at year 70 200 at year 60

Fourth thinning (tph) Not planned 125 at year 100 125 at year 100

Low-severity fire (in Not planned Once between years 100 Twice between years

addition to fuel and 180 100 and 260

treatments)

aTph = trees per hectare.

Source: Cissel et al. 1999.

growth models is the inability to simulate patches

and gaps within a stand. To accurately estimate

the effect of these treatments on tree growth and

quality, models will need to have this failing corrected. Currently the best we can do is to use

spatially uniform stand treatments and assume

the effect on overall stand growth and quality is

negligible.

A key part of the Blue River Landscape Pan is

when and where stand treatments occur. To move

away from further forest fragmentation, Cissel et

al. (1999) applied treatments to areas designated

as landscape blocks. An individual block ranges

in size from about 40 to 160 ha and may contain

several stands. Harvest entries were scheduled

with an area-control approach by using the landscape block as the basic unit. Blocks were designated for entry in 20-year periods over 200 years.

Scheduling of harvest entries in LMS is accomplished through a scenario file that contains the

year of treatment, stand number, and treatment

description. By using this file, silvicultural treatments can be programmed for multiple stands

across the entire landscape through time. De-
116

spite being able to simulate the growth of many

stands for a large area, the current model cannot

simulate interactions among stands.

Analysis of Wood Volume and Quality

Analysis of wood production is completed after

stands have been grown and silvicultural treatments applied by using the LMS model. LMS can

be configured to simulate bucking of trees into

user-defined log lengths. Currently, logs can be

defined by only diameter and length, but work is

being completed that incorporates additional quality characteristics such as number of branches,

branch diameter, growth ring count, and diameter

of juvenile wood core. For this study we focused

on lumber production from each regime and differences in tree characteristics. Tree-quality characteristics are summarized for each regime from

information in the ORGANON wood quality output

file. To simulate lumber production, the TREEVAL

model is used. TREEVAL is designed to accept

ORGANON wood-quality output files as input.

TREEVAL calculates financial information allowing comparisons of different silvicultural regimes.

For this study we were interested primarily in the

volume and quality of lumber recovered for each

regime. Lumber recovery equations from Fahey et

al. (1991) have been programmed into the model

estimating yields of veneer and lumber. Lumber

recovery can be combined for visually graded and

machine-stress rated (MSR) lumber. TREEVAL

simulates the bucking of trees to a nominal log

length of 4.9 m and a minimum small-end diameter of 13 cm. Volumetric lumber grade recoveries

were estimated for each log by using the

TREEVAL model.

Conclusion

For this paper, we wanted to demonstrate that by

linking existing simulation models, a detailed

analysis can be made from a landscape-scale

perspective of wood volume and quality from

many individual stands. This information can be

used to evaluate wood removals based on different approaches to planning on a large scale. Timber production comes from tree removals as part

of stand treatments used to develop specific

structural attributes through time. All approaches

have an eventual rotation age that is longer than

that used in traditional management for timber

production. The combination of using unique

stand treatments with long rotations will have an

effect on the volume and quality of wood available

for commodity production. It is unknown what the

magnitude of this effect will be, and simulation

models give us an opportunity to look at potential

trends.

English Equivalents

1 hectare (ha) = 2.47 acres

1 millimeter (mm) = 0.039 inches

1 centimeter (cm) = 0.39 inches

1 meter (m) = 3.28 feet

Literature Cited

Barbour, R.J.; Johnston, S.; Hayes, J.P.;

Tucker, G.F. 1996. Simulated stand characteristics and wood product yields from Douglas-fir

plantations managed for ecosystem objectives.

Forest Ecology and Management. 91(1997):

205-219.

Briggs, D.G. 1989. Tree value system: description and assumptions. Gen. Tech. Rep. PNWGTR-239. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest

Research Station. 24 p.

Christensen, G.A. 1997. Development of Douglas-fir log quality, product yield, and stand

value after repeated thinnings in western

Oregon. Corvallis, OR: Oregon State

University. 176 p. M.S. thesis.

Cissel, J.H.; Swanson, F.J.; Grant, G.E. [et al.].

1998. A landscape plan based on historical fire

regimes for a managed forest ecosystem: the

Augusta Creek study. Gen. Tech. Rep. PNWGTR-422. Portland, OR: U.S. Department of

Agriculture, Forest Service, Pacific Northwest

Research Station. 82 p.
117

Cissel, J.H.; Swanson, F.J.; Weisberg, P.J.

1999. Landscape management using historical

fire regimes: Blue River, Oregon. Ecological

Applications. 9(4): 1217-1231.

Fahey, T.D.; Cahill, J.M.; Snellgrove, T.A.;

Heath, L.S. 1991. Lumber and veneer recovery from intensively managed young-growth

Douglas-fir. Res. Pap. PNW-RP-437. Portland,

OR: U.S. Department of Agriculture, Forest

Service, Pacific Northwest Research Station.

25 p.

Hann, D.W.; Olsen, C.L.; Hester, A.S. 1994.

ORGANON users manual. Corvallis, OR: Department of Forest Resources, Oregon State

University. 113 p.

McCarter, J.B. 1997. Integrating forest inventory,

growth and yield, and computer visualization

into a landscape management system. In:

Teck, R.M.; Moeur, M.; Adams, J., eds. Proceedings of the Forest Vegetation Simulator

conference. Gen. Tech. Rep. INT-GTR-373.

Ogden, UT: U.S. Department of Agriculture,

Forest Service, Intermountain Research

Station: 159-167.

Sachet, J.K.; Briggs, D.G.; Fight, R.D. 1989.

Tree value system: users guide. Gen. Tech.

Rep. PNW-GTR-234. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific

Northwest Research Station. 45 p.

Smith, W.B.; Faulkner, J.L.; Powell, D.S. 1994.

Forest statistics of the United States, 1992,

metric units. Gen. Tech. Rep. NC-GTR-168.

St. Paul, MN: U.S. Department of Agriculture,

Forest Service, North Central Forest Experiment Station. 147 p.

U.S. Department of Agriculture, Forest Service; U.S. Department of the Interior, Bureau

of Land Management. 1994. Record

of decision for amendments to Forest Service

and Bureau of Land Management planning

documents within the range of the northern

spotted owl. [Place of publication unknown].

74 p. [Plus attachment A: standards and

guidelines].
118

Transforming Information From Many Perspectives to

Action on the Ground
119

Scale and the Human Frame of

Reference

As Allen and Hoekstra (1992), among others,

have noted, scale is a social construction. This

means that scale is not something that is out

there on the ground that exists apart from humans

but rather it is something we create by assigning

defining attributes to it. A particular scale does not

exist in reality and has no meaning until we give it

meaning (Tuan 1974). Thus, those who select a

particular scale have a responsibility to clarify its

meaning to others.

In addition, scale only has meaning relative to the

human frame of reference. Recall the relation

Gulliver had to the lands and people he visited.

The differences in scale that he experienced were

all relative to his own size and personal past experience. Because each of us brings a different

past experience with us, we will see the same

things differently. This means that we need to look

at places and projects together so we can share

with each other what each of us “sees” rather

than assuming we are all seeing and experiencing

a place in the same way.

Most of us (as humans) experience places at the

scale of a site–a place we go fishing, camping, or

hiking, for example. Some of us may experience

a sense of place or special attachment to certain

places, usually at small scales. However, when

asked to comment on a forest plan at the scale of

a national forest, many of us (as citizens) may be

at a loss as to how to express how we feel about

those special places. Thus, both agency planning

processes and research questions need to recognize the interconnectedness across multiple

scales and scale down to smaller scales so that

citizens can better understand the implications of

a decision or finding on “their place.” Often the

boundaries identified for purposes such as planning and research are not socially significant or

meaningful to citizens.

Nassauer (1997) suggests that landscape scale

does not have a universal definition. She identifies

two common uses of the concept:

(1) a heterogeneous combination of ecosystems, which affect each other across

space and time, and (2) a “middle” scale,

within a hierarchy, of ecological processes

that affects smaller-scale processes and

is affected by larger-scale processes. Both

the concepts of heterogeneity and hierarchy emphasize the connectedness of the

landscape across space and time. Connectedness, then, is an essential property

of the landscape scale. (Nassauer

1997: 73)

Nassauer (1997: 73) goes on to suggest that “at

the scale of human beings, connectedness refers

to landscape structure that allows flows of water,

nutrients, energy or species that people have

noticed and believe to have ecological value.”

A Social Science Perspective on the Importance of Scale

Linda E. Kruger1

All ecological processes and types of ecological structure are multiscaled. Each particular structure relates to a particular scale used to observe it such that, at the scale of perception, the entity

appears most cohesive, explicable, and predictable. The scale of a process becomes fixed only

once the associated scaled structures are prescribed and set in their scaled context. Scaling is

done by the observer; it is not a matter of nature independent of observation. (Allen and

Hoekstra 1992: 11, emphasis added.)

This paper offers a very brief introduction to some scale-related considerations from the perspective of a

social scientist. The paper does not provide an indepth discussion, but my hope is that enough information is provided to provoke thought and additional exploration in these areas.

1 Research social scientist, U.S. Department of Agriculture,

Forest Service, Pacific Northwest Research Station, Forestry

Sciences Laboratory, 400 N 34th Street, Suite 201, Seattle,

WA 98103; Tel: 206-732-7800; e-mail: lkruger@fs.fed.us
120

From this perspective, landscape scale is a cultural concept based on what we determine to

have value. Because we as humans manage

landscapes, we often arrive at a definition of landscape scale by identifying what we perceive as

management units (Nassauer 1997). Based on

this perspective, landscape scale could mean

someone’s backyard, a watershed, ranger district,

or national forest. “In each case, the ecological

functions of individual patches of lakes, streams,

turf, fields, forests, or even pavement are connected to one another” (Nassauer 1997: 73).

Thus, landscape as a scale of analysis is similar

to the social concept of community in that landscapes, like communities, are nested and embedded in each other at various scales, rather than

representing one specific scale.

It is this connectedness of ecological functions

across space that makes working across landscapes essential. However, working across landscapes is often easier said than done. Patchwork

ownership patterns put landscape-level decisions

in conflict with our culture’s belief in private property rights. More work is needed to develop tools

and incentives for working across boundaries in

ways that minimize the threat to people’s sense of

private property rights. (See Kalinowski’s [1996]

discussion of Leopold’s land ethic, specifically his

differentiation between land as property and land

as territory.)

The ability to take a cross-boundary perspective—

looking across management jurisdictions, ownerships, and administrative and legal boundaries—

expands the possibility of considering questions at

the appropriate scale (Knight and Landres 1998).

Like scale, boundaries are created by society for

a variety of social purposes. Boundaries organize

space. They often cut across other social relations

that define space. For example, the city I live in

lies within a school district that includes two other

cities. It is bisected by a county line. Boundaries

define to whom we pay taxes, for whom we can

vote, and who will represent us in government,

where our kids go to school, where our water

comes from, and in some parts of the world even

where people can and cannot travel. Creating

boundaries is a process of place-making or constructing an identity that differentiates what and

who are inside the boundary from what and who

are outside the boundary.

Determining appropriate planning or study boundaries is important. Just as important is keeping in

mind that boundaries are always porous and open

across time and space (Massey 1995). The identities of places are products of links to other times

and places. Although each place is unique, its

interconnections to other times and places are

important in defining its uniqueness.

Appropriate Scale

Scale is an important consideration for both managers and scientists. Every resource issue and

question has a spatial and temporal component

or context. In choosing the appropriate scale, we

must consider at what scale our knowledge is

reliable and at what scale we are most comfortable making predictions (Haskell et al. 1992).

What the appropriate scale is depends on the

question(s) being asked and can range from a

small personal space (How will this plant look on

my desk?) to the entire earth (How might this

activity influence global change?). For social inquiry the most common scales are community,

county, state, and region. Counties are frequently

used for analysis because they are a major unit

used by the USDC Bureau of the Census. Machlis

et al. (1995) participated in the social assessment

process portion of the Interior Columbia Basin

Ecosystem Management Project (ICBEMP). They

suggest the county as the best scale for social

analysis, noting that data are readily available and

that counties are increasingly involved in resource

policy through planning and zoning activities. They

also suggest that the county scale fits best with

landscape-level analysis (Machlis et al. 1995:

13-16).

Although there are advantages to the county scale

and major studies such as ICBEMP and Forest

Ecosystem Management Assessment Team

(FEMAT) do not support higher resolution community-level studies, there also are limitations to

working at the county scale. The effects of resource decisions are often felt at the local level,

and communities within a county can differ dramatically, particularly in a county that has a mix of

urban and rural areas. Working at the larger,

county-level scale also tends to disenfranchise

people whose interests are more local. These

are often the people who will feel a study “has

been done to them.” It also can be hard to make

county-level data meaningful to a community. As
121

a society, we need to explore methodologies that

enable people to learn about themselves and their

places at a variety of scales that are meaningful to

them.

The ability to consider a question at the appropriate scale may be constrained by a variety of factors including the scale at which data are available, time or funding, political considerations,

logistical problems, and project location (Committee on the Applications of Ecological Theory to

Environmental Problems 1986). In many cases,

ownership, management jurisdiction, or another

administrative or legal constraint instead of the

question or issue itself determines the spatial area

that is considered.

Working across disciplines or multiple types of

information may require synthesizing finer scale

information to a coarser scale common with others. For example, socioeconomic data may be

available only at the county scale, whereas biophysical data may be available at a combination

of scales including the watershed, stream reach,

stand, or province. The identification of a crosscutting question may be a helpful first step in identifying an appropriate scale at which to integrate

across disciplines.

The Committee on the Applications of Ecological

Theory to Environmental Problems (1986: 97)

determined that a “fundamental problem in predicting and controlling cumulative effects is the

frequently large mismatch between the scales or

jurisdictional boundaries of management authority

and the scales of the ecological phenomena involved or their effects.” The committee notes that

an affected environment often crosses several

jurisdictions. In addition the impacts of an action

may be felt in a different jurisdiction far from

where the offending action took place.

Thus, the scale that is chosen must be large

enough to encompass interactions, larger scale

processes, and cumulative effects (over time and

space) without losing sight of important details,

smaller scale processes, and interactions. At

broader scales, important variability can be

masked; at narrower scales important effects,

levels, and nature of impacts can be missed; and

at scales that are mismatched, it can be impossible to develop linkages between human communities and forests.

Considerations in Choosing a

Particular Scale

In choosing a particular scale to use when designing a study or planning area, asking the following

questions may be helpful.

• What assumptions underlie the choice of this

scale? Are these reasonable assumptions?

• What is the justification for choosing this scale

over others?

• What is being overlooking or ruled out by

choosing this scale over others? Are we missing any critical questions?

• Are we choosing a particular scale because

we have data available or because measurement is easier than at other scales?

• What are the implications of working at this

scale?

• Does our choice of scale match our

objectives?

How does the choice of a particular scale affect

ecosystem management efforts? In an attempt to

begin to address this issue, Norton (1992) identifies four ways in which scale affects ecosystem

management.

1. Spatial boundary issues. Jurisdictional boundaries usually do not correspond to natural

features or biogeography.

2. Temporal perspective. Biological (and social)

systems are dynamic. Thus managers may

have to decide whether to manage for current

social values, production of “essential services,” or features that are critical to maintaining natural processes.

3. Organizational structure and scale. This aspect of scale has to do with substructure.

Once a whole system is defined, subunits,

each with their own boundaries, must be identified. Taking an example from social science,

a nation may be made of states, which might

be subdivided into counties, which have within

them cities and towns and neighborhoods

where families and individuals live.
122

4. Scale and degree of impact. The degree of

impact an action may have on a system depends both on the scale of the activity and the

scale of the system. Activities that might degrade a small site might have negligible effect

at a larger scale. As the scale of the activity

increases, it might have higher degrees of

impact at ever increasing system scales. Often the effects of our actions have impacts at

a variety of scales.

So what happens if our choice of scale is less

than optimal? There are several possible outcomes of analysis or action at the wrong scale.

The following are drawn from the Committee on

the Applications of Ecological Theory to Environmental Problems report Ecological Knowledge

and Environmental Problem-Solving (1986).

1. Well-intended efforts can have minimal or

even adverse effects if planned for too short

a timeframe or too small an area.

2. Key processes might be overlooked at larger

temporal or spatial scales.

3. Averaging over larger areas can mask the

importance of processes at smaller scales

because it is more difficult to detect subtle

differences.

In addition to these concerns, a focus on single

actions at whatever scale can result in obscuring

cumulative effects over time and space. Cumulative effects can take several forms ranging from

activities that add materials to the environment,

such as discharging effluents, to those that remove materials from the environment, such as

harvesting timber. Cumulative effects can take the

form of changes over large areas for long periods

of time that result from management actions,

such as when a forest is managed based on

single stands. Cumulative effects also occur when

several actions compound each other; for example, when logging roads are built, logging, recreation, hunting, poaching, and other activities

increase and affect a variety of forest species.

The importance of understanding and considering

the implications of cumulative effects makes a

strong case for the consideration of multiple spatial and temporal scales.

The Inclusion of Citizens in Planning

and Decisionmaking

Transforming information into implementation on

the ground requires both recognition that humans

are part of ecosystems (rather than an outside

force) and the inclusion of citizens in planning

and implementation. This requires us to shift our

thinking from “unfortunately we have to work with

people” to “citizens are critical to an informed,

effective process.” Collaborative planning, when

used in Forest Service planning processes, requires participation of researchers, managers,

and citizens. It recognizes that citizens have

knowledge and real world experiences to contribute to the planning process. Frequently citizens

also bring a passion for action, and citizen participation can result in better decisions and an improved process. Land managers can share responsibility for environmental quality and health

with those outside the agency only if they provide

opportunities that include citizens as meaningful

participants in planning and decisionmaking processes.

It also requires an understanding of the various

scales at which people identify a landscape as a

place that they relate to. Geographer Gillian Rose

(1995) suggests that people develop a sense of

belonging or connection to places at multiple

scales including a local scale, a regional scale, a

national scale, a supranational scale, like Europe,

and even at a global scale, as our social and economic systems become more globalized. This

means that as managers consider who should be

involved in local planning processes, they must

think beyond the local geographic community.

“What kinds of evidence, scientific or otherwise,

are necessary to justify a given choice regarding

the scale on which environmental problems are

addressed?” Norton (1992: 35) answers his own

question by suggesting an interdisciplinary approach that acknowledges that questions of scale

involve value judgments. “The correct scale on

which to address a management problem is determined by what society wants to accomplish

with that system” (Norton 1992: 36). Norton joins

others in suggesting that citizen involvement in

dialogue and debate is necessary in order to facilitate consideration of alternative actions and

desired conditions.
123

Scale may influence citizen involvement in management and planning. It can be much more difficult for citizens to comment on large-scale

proposals that are not linked to specific smallscale places they can personally identify with.

Forest plans are at a scale many citizens find

difficult to respond to. We might speculate that

watersheds, especially at the local community

level, are a more meaningful scale as evidenced

by the number of grassroots watershed groups.

Frequently, federal land management agencies

conduct planning processes at the scale of a national forest. Ecosystem management is based on

planning at a large scale, often including areas

larger than a national forest. The FEMAT and the

ICBEMP each covered several states. At these

broad scales it is easy for people and their interests and concerns to get lost.

How meaningful public participation can be is

often a function of the scale at which a study is

initiated. The scale or scope of a place being

studied is important in the sense that it has to be

a scale that people can relate to. What is important is that the scale is appropriate to the question

or issue being addressed and that it does not

obscure what is meaningful and what people can

relate to.

We must also take care that the tools and techniques that we use do not obscure what it is that

is meaningful and important to people. Technology has provided us with tools that enable us to

create pictures of what a stand or landscape will

look like immediately after harvest and at intervals

thereafter. In addition to its use in presenting information, this technology is often used to solicit

public response to harvest practices (Shindler et

al. 1995). Although the technology can serve a

useful purpose in helping citizens visualize what

the land will look like over time as the forest

greens up, some researchers have concerns with

its use in measuring public judgments of acceptability.

Studies have found that judgments of acceptability

of management practices are based on more than

just looking at a scene and responding to what is

there (Brunson 1993, Shindler and Cramer 1999).

Research done by some of our collaborators has

identified a number of factors that play a role in

the acceptability of resource management decisions and actions. For example, the respondents’

personal experiences both with the specific place

and the agency proposing the activity and their

level of trust in the agency often play a role. A

sense that “too much has already been cut” or

general concerns over wildlife, recreation, or scenic values also may play important roles. Finally,

how the decisionmaking process is carried out is

important to some people. If people feel they

didn’t have opportunities for meaningful participation or if they didn’t feel heard, they may object to

an activity regardless of how the project looks on

the ground. I think a quote from the child’s story, A

Little Prince (Saint-Exupery 1943: 87) aptly describes this situation: “What is essential is invisible to the eye.” What is essential to understanding how acceptable a forest practice is may have

less to do with how the forest appears and more

to do with aspects of how and why it looks the

way it does and where it is located relative to

places people care about.

Literature Cited

Allen, T.F.H.; Hoekstra, T.W. 1992. Toward a

unified ecology. New York: Columbia University

Press. 384 p.

Brunson, M. 1993. “Socially acceptable” forestry:

What does it imply for ecosystem management? Western Journal of Applied Forestry.

8(4): 1-4.

Committee on the Applications of Ecological

Theory to Environmental Problems. 1986.

Ecological knowledge and environmental problem-solving. Washington, DC: National Academy Press. 388 p.

Haskell, B.D.; Norton, B.G.; Costanza, R. 1992.

What is ecosystem health and why should we

worry about it? In: Costanza, R.; Norton, B.G.;

Haskell, B.D., eds. Ecosystem health: new

goals for environmental management. Washington, DC: Island Press: 3-20.

Kalinowski, F.A. 1996. Aldo Leopold as hunter

and communitarian. In: Vitek, W.; Jackson, J.,

eds. Rooted in the land: essays on community

and place. New Haven, CT: Yale University

Press: 140-149.

Knight, R.L.; Landres, P.B., eds. 1998. Stewardship across boundaries. Washington, DC: Island Press. 371 p.
124

Machlis, G.E.; Force, J.E.; Dalton, S.E. 1995.

Monitoring social indicators for ecosystem

management. Walla Walla, WA: Interior Columbia Basin Ecosystem Management Project.

Unpublished report. On file with: Pacific Northwest Research Station, Human and Natural

Resources Interactions Program, Forestry

Sciences Laboratory, 400 N 34th Street, Suite

201, Seattle, WA 98103.

Massey, D. 1995. The conceptualization of place.

In: Massey, D.; Jess, P., eds. A place in the

world? Places, cultures and globalization. Oxford, United Kingdom: Oxford University Press:

45-85.

Nassauer, J.I. 1997. Cultural sustainability: aligning aesthetics and ecology. In: Nassauer, J.I.,

ed. Placing nature: culture and landscape ecology. Washington, DC: Island Press: 67-83.

Norton, B.G. 1992. A new paradigm for environmental management. In: Costanza, R.; Norton,

B.G.; Haskell, B.D., eds. Ecosystem health:

new goals for environmental management.

Washington, DC: Island Press: 23-41.

Rose, G. 1995. Place and identity: a sense of

place. In: Massey, D.; Jess, P., eds. A place in

the world? Places, cultures and globalization.

Oxford, United Kingdom: Oxford University

Press: 88-132.

Saint-Exupery, A. 1943. The little prince. New

York: Harcourt, Brace and World, Inc. 113 p.

Shindler, B.; Cramer, L.A. 1999. Shifting public

values for forest management: making sense

of wicked problems. Western Journal of Applied Forestry. 14(1): 1-7.

Shindler, B.; Peters, J.; Kruger, L. 1995. Social

values and acceptability of alternative harvest

practices on the Tongass National Forest.

101 p. Unpublished report. On file with: Pacific

Northwest Research Station, Human and Natural Resources Interactions Program, Forestry

Sciences Laboratory, 400 N 34th Street, Suite

201, Seattle, WA 98103.

Tuan, Yi-Fu. 1974. Space and place: humanistic

perspective. Progress in Human Geography.

6: 213-252.
125
126

Conclusion
127

I was asked not to prepare remarks ahead of the

workshop, but rather to respond to what I saw

and heard. Let me say at the outset, I have been

much impressed with the general thrust of this

workshop. Many of the papers were technical and

represented sound research, but the real strength

of the presentations as a whole was in the genuine eagerness in tackling big problems. The big

problem, as I see it, is that we have many largescale problems with regard to renewable resources, and that there is a huge divide between

how science prefers to work and what needs to

be done. We should be impressed with the high

level of appreciation for the difficulties, and the

vigor of the response in so many of the presentations. I saw courage in the presenters I heard.

As an example, we are really quite good at quantifying arcane models about cutting regimes. But

what is the use of this to the end consumer of

these results? The models mean nothing until we

visualize the landscape in images that anyone

can see and understand. I saw exactly that at this

workshop. The new gigabytes and gigahertz of

computer capability are powerful, because they

let us translate abstractions, such as a 10-percent

cut, into an image that the public can see and

evaluate. New technology really does change the

game, as we fly down streams and summarize

their condition with thermal imagery. The problems are large, but the new technology moves

human achievements upscale to meet many of

them. Even the papers that used no technological

“fancyware,” were generally very cognizant of the

need to serve the interface between humans on

the landscape and the biogeophysical landscape

itself. When we manage an ecosystem, we do not

manage the material ecological system itself;

rather we manage the presence of the people

who impact the system. And that does not mean

we manipulate the public covertly or dishonestly.

No. Ecosystem management will not work unless

it involves explicitly giving people options that they

are prepared to use, and a sound basis to select

among them.

What I have described above is what Silvio

Funtowicz and Jerry Ravetz call postnormal science (Ravetz 1999). Although normal, merely

modern science is meticulous as it tries to approach reality with its models; the postnormal

scientist cannot afford to be so idealistic. Postnormal situations are characterized by (1) high

stakes, (2) insufficient data, and (3) a short time

fuse. The data from normal science will not be

coming in time, for the issue will have passed, win

or lose, before meticulous experiments and confidence limits can be achieved. Even so, scientists

must offer their best advice anyway, and the manager must act on that best advice. Clearly finding

out what is the reality of the situation is irrelevant,

but, if it is any comfort, reality was never achievable anyway.

Beyond postnormal science is postmodern science. In the classical world and modern world the

novice became dexterous, and the apprentice

became a craftsman, while the master went beyond all to create something in a new framework.

The novice and apprentice achieve quality by

being meticulous, delivering exactly what is

needed every time. That is called structural quality. The master introduces a different quality, a

dynamical quality of good change, which itself

undermines the premises that underlie structural

quality. Quality classical work was approved by

common standards, where the external consensus was that everyone liked the picture of the

Patron. The difference between classical and

modern is that in the modern world, external reality becomes the external reference. Elites, be they

cubist painters or 20th-century scientists, assert

that by looking at the world their special way, ultimate reality may be approached. But in a

postmodern world there is no external reference,

be it consensus or reality. In postmodernity, it is

not that it is all in our heads and anything goes, it

is rather that we only deal with data, not with obSummary Remarks on Views From the Ridge

T.F.H. Allen1

1 Professor, Botany Department, University of Wisconsin,

Madison, WI 53706-1381; Tel: 608-262-2692; e-mail:

tfallen@facstaff.wisc.edu
128

jective reality. Without an external reference, the

postmodern scientist must make the process of

science justify itself, but how? The answer is that

we need to keep science a high-quality activity

in both structural and dynamic features. Even

though we cannot now pretend that science is

objective, it is quality that is endogenous to doing

science that continues to give science its deserved privileged position (Funtowicz and Ravetz

1992). Science is meticulous so it can repeat

anything it does, and that amounts to structural

quality. Science also challenges its products at

every level from the null hypothesis all the way to

fighting over new paradigms. That is dynamical

quality.

Structural and dynamical quality, that is, honest

carefulness and creativity, make science the best

game in town. And we saw lots of both sorts of

quality at this workshop. Some papers were technical and were splendid displays of structural

quality. Other papers were full of dynamical quality, as managers, politicians, scientists, and the

lay public made visionary statements of what to

do next, as we reach out to a world full of people

with values living in systems that are the purview

of the Forest Service.

It is good to see such courage and commitment

to dealing with the values of people in the biosphere, because the problems are huge. Joseph

A. Tainter (1988), of the Rocky Mountain Research Station, points out that societies are problem-solving units that elaborate processes or

approaches to deal with resource issues. It appears inevitable that problem solving proceeds to

greater cost and less benefit with vicious diminishing returns. Eventually societies lose either the

political will or the ability to deal with the last problem, whatever form it may take, and the people

just walk away from civilization.

Some societies on the edge of collapse find a new

lease on life by switching to some fundamentally

new resource, such as coal when Britain ran out

of wood. Looking at attoid ants, we see that the

primitive species farms fungi on grasshopper

droppings, which amounts to jet fuel for growing

fungi. The problem is that insect droppings are a

highly processed, scarce material, albeit of high

quality. Leaf-cutting ants have evolved further to

use leaves instead of guano, and so overcome

the scarcity issue. But leaves are a low-quality

resource, and so demand very organized processing. Diminishing returns on a high-quality

resource, such as guano, end in collapse when

the supply runs out. Diminishing returns on a lowquality resource, such as leaves, end in collapse

when the huge system grows into excessive demand. Counterintuitively, more capital is built on

diffuse, low-quality resources than on high-quality

resources.

It appears that human society often switches from

high-quality resources (HQR) to low-quality resources (LQR) in cycles of elaboration. The energetically easy entry to a general type of resource

is on HQR, and the elaboration upscale is on

LQR. Thus (1) hunting (HQR) leads to (2) agriculture (LQR). In an agricultural setting, (3) looting

neighbors (HQR) gives way to (4) imperial taxation of peasants (LQR). In the First World we live

on (5) industrialization (HQR). Without meaning to

describe any sort of grand historical narrative, we

note that some political arrangements collapsed

at various stages, e.g., Mongols in the West at

step 3, or the Romans at step 4.

We look as if we are about to come off the back

side of step 5, fossil carbon, and need a new LQR

phase. Because renewable energy sources are all

low quality, they will have to be extensively captured, rather like sun on crops. Much more ecological damage has been done by LQR agriculture

compared to HQR fossil fuels. The change to the

LQR hydrogen economy using wave, wind, biomass, and solar energy may be wrenching, as

human settlement decentralizes. The diffuse nature of high-technology information systems allows for energy self-sufficient production systems

scattered across the landscape. There are alternative scenarios of the move to renewable energy

where decentralization is delayed or circumvented, but these have their downside. They involve consumption of the mountains of dirty coal,

as a society builds massive LQR infrastructure

where forests of windmills sit on sculptured coastlines (Allen et al. 2001). Avoiding renewable energy appears to invite the four Horsemen of the

Apocalypse, so we cannot afford to fail. And fail
129

we will unless we can encourage the populace at

large that the transition is worth it. The human

focus and the emphasis on advice from lay opinion at this workshop are most encouraging at a

time when deep concern for public opinion is not

misplaced. The coming LQR society is set to devastate coastlines, deserts, forests, and wildlife. It

is for this reason that the visionary tone of this

workshop is so important. Even under the happiest outcome, ecological stress will be great. Precisely because of impending ecological disaster in

the move to extensive use of renewable energy,

only the best stewardship will do. The problem is

large, so the view of the stewards of natural resources such as forests, wildlife, and fisheries

must be at least as visionary as the most expansive view from the ridge.

Literature Cited

Allen, T.F.H.; Tainter, J.A.; Pires, J.C.;

Hoekstra, T.W. 2001. Dragnet ecology, “Just

the facts ma’am”: the privilege of science in a

post-modern world. BioScience. 51: 475-485.

Funtowicz, S.O.; Ravetz, J.R. 1992. The good,

the true and the post-modern. Futures. 24(10):

963-974.

Ravetz, J.R. 1999. What is post-normal science?

Futures. 31: 647-653.

Tainter, J.A. 1988. The collapse of complex societies. Cambridge, MA: Cambridge University

Press.
130

Key Drivers of Landscape-Level

Research

Station scientists at the Pacific Northwest Research Station (PNW) work to advance the basic

understanding of how systems function, especially

terrestrial, aquatic, and socioeconomic systems.

This provides the foundation of scientific understanding to better understand the consequences

and risks of choices made in managing the land.

It also provides the foundation on which to help

design new land management options.

In the 1990s, in response to key issues, Station

scientists increasingly focused their research on

the landscape scale. This workshop reflects a

body of work designed by PNW to consciously

examine this scale. In many ways, we have only

started to understand systems at the landscape

scale in the Pacific Northwest, but it is an important part of our research program that is already

demonstrating that it holds considerable promise.

We appreciate being able to share information

with those of you who make land management

decisions or affect those decisions and the scientists here who have validated and built on our

research results.

Much of our landscape-scale research has focused on national forest land issues because they

offer landscape-scale laboratories. Our researchers often work side by side with land managers as

we conduct studies and assessments on the very

large scales of the national forests. We also conduct landscape-scale research on other lands

such as the state lands of Washington. Much of

what we are learning is applicable to all ownerships. As we study forests at the landscape scale,

I believe we can find some additional options that

may create compatibility among interests and

across ownerships.

What put us on the landscape trek? In part, it was

the result of our fine-scale and single-discipline

research. Although often initiated from a single

disciplinary perspective, this research has produced important scientific findings. At the same

time, it has shown that some of those fine-scale

phenomena also were components of large systems. We have found that some relations exist

and manifest themselves only at a large scale.

As we examined outbreaks of insects and disease

during the past several decades, for example, we

began to understand the need to look beyond the

stand. Also our research on fire disturbance processes and smoke management led to a broader

perspective. The ecological effects of forest fragmentation and the interactions between fragmentation and habitat quality for some wildlife species

begged a landscape-scale view. Increasingly we

understand that pattern and patches across the

landscape affect relations such as those among

the nesting, feeding, and migrating of some wildlife species.

In addition to our fine-scale research, some defining land management issues helped us to look at

broader scaled relations. Issues such as management of old-growth forests, recovery of threatened

and endangered species, and forest health are

examples. These types of issues have been drivers of our research program, just as our scientific

understanding has helped shape the character of

these issues.

Land management issues such as these, reinforced by our past research, have led to the following overarching land management questions

that demand broader scale, functionally integrated

research: How do the effects of land management

actions accumulate over space and time? What

are the effects of interactions among different

land units, and how do those interactions affect

overall outcomes? Another related question, given

the inability to treat all parcels, is, How can we

prioritize among the numerous parcels to maximize our objectives?

The Future of Landscape-Level Research at the Pacific

Northwest Research Station

Thomas J. Mills1

1 Deputy Chief, Business Operations, U.S. Department of

Agriculture, Forest Service, 201 14th Street SW, Washington,

DC 20250; Tel: 202-205-1707; e-mail: tjmills@fs.fed.us
131

These questions require a landscape-scale perspective and integration among different scientific

disciplines. Moving to broader scale is usually

coupled with the need to study the interactions

among different components of the land, as well

as the interaction among the different land components within the landscape. Integration among

physical and biological disciplines is needed, but

integration between the biophysical and social

sciences also is essential if we are to understand

the full array of consequences of land management actions and to create new land management

options.

The Station has a deep history of long-term research studies and an emerging body of landscape-scale research, but research integrated

across disciplines at the landscape scale is only

now emerging. Although working across disciplines can be complicated and time consuming, it

is in the resulting comprehensive picture that

policymakers likely will find solutions to complex

problems.

Land Management Opportunities

Among the Challenges

Not only does the landscape-scale perspective

add significant complexity beyond what is apparent through a finer scale look at the land, it also

holds the promise of land management opportunities not apparent at the finer scale. For example,

if the focus is solely on the fine scale, a manager

or the public might conclude that only the area

being studied can provide some desired value.

They might also conclude that all such sites must

provide the same set of values. Our research has

shown, however, considerable variability across

the landscape. The land is not now uniform nor

was it ever, even when nature was managing it.

For example, not all sites on the west side of Oregon and Washington were prime salmonid habitat at any one time even in the past. And some of

the most constraining laws, such as the Endangered Species Act, require only that values be

provided on enough sites to meet an overall goal,

not that those values need to be provided from

every site. A landscape view helps us understand

how a mosaic of uses might be scattered across

the landscape. Each parcel might be devoted to

delivery of some set of values with the designated

uses moving across the landscape over time, as

nature moved them.

Policymakers have tried to solve this challenge by

implementing land allocations akin to land use

zoning. Land allocations in national forest plans

are a simple version of this. Our research challenge is to sufficiently understand the broad-scale

phenomena so that creative solutions may be

developed to provide an array of values that blend

uses across the landscape, and even shift uses

across time in a way that increases benefits and

reduces negative effects and risks.

Building on the Foundation of Past

Research

Many PNW scientists and their colleagues have

presented examples of landscape-scale research

at this workshop. The PNW Station is making a

concerted effort to address the landscape scale.

Broad-scale studies like that of land cover dynamics and land use changes described by Ralph Alig

and the study of the implications of scale for the

study of terrestrial wildlife populations by Martin

Raphael are only two examples of the work presented here. The poster session showed a variety

of projects related to landscapes that PNW has

underway. And yet during this workshop, although

we presented much, it was not all work conducted

at the landscape scale by the Station. Some landscape research spans decades for issues such

as insects and disease. Some of our research

has just begun, and information is yet to be

developed.

As with the rest of our research, much of this

work on the landscape scale is conducted with

colleagues at universities and through partnerships with land managers. John Cissel’s presentation of the Augusta Creek study was an example.

Critical in our success is the ability to work with

the National Forest System and other land managers on large tracts of land. The contribution we

have made so far, our continued cooperation with

universities, and our partnerships with land managers create a strong foundation from which to

continue studies at a broad scale.

Challenges to Landscape-Level

Research

In accomplishing landscape-level research, especially with research integrated across many disciplines, we face significant challenges. To make

meaningful progress, we need to face and overcome these challenges.
132

We need to fully develop concepts, models, and

especially testable hypotheses. For the most part,

these do not yet exist. Questions abound, but

rigorous scientific methods to answer the questions need to be developed further. Without the

benefit of stronger methods, there is always the

risk that the personal values of scientists will become embedded in the framing of questions or

the interpretation of results.

Landscape-scale research often but not always,

requires integration of several scientific disciplines. Success depends on our ability to understand interactions among biophysical components

and between biophysical and social systems. But

the science perspective of the different disciplines

often focuses at widely divergent scales, and typically with very different boundaries. For example,

most social science is conducted at broad scales

and creates behavioral models developed at the

broader spatial scales but still useful at smaller

scales. The biophysical sciences, on the other

hand, are challenged to “scale up” with both data

and models. For scientists to address landscape

issues, synthetic and interdisciplinary science

must overcome these technical and conceptual

difficulties. To date, we have mostly accomplished

integrated research by synthesis of knowledge

already gained. Instead, we need to plan for integrated approaches as we develop hypotheses,

concepts, models, and methods. We must gain

the ability to determine early in our research how

we want to address the pieces to understand the

whole.

Through its ability to bring together staff scientists

and those from universities, the Station has contributed to and will continue to work toward such

integrated research. The Station has an advantage in being able to bring scientists together, and

we need to exercise that advantage.

Landscape science requires at least some largescale experiments. Large-scale experiments are

challenges from several perspectives. One is the

difficulty of convincing land managers and the

public that the search for knowledge should require testing ideas, and we are testing them because we do not know what the outcome will be,

even as we are guided by a hypothesis. Even if

land managers are willing to accept and participate in these experiments, management with

uncertain outcomes is not consistent with the

emphasis to define objectives and hold managers

accountable for performance results. We have

overcome this challenge in some places, such as

the large-scale studies in the Willamette National

Forest, but we need to build on those few successes, including working across ownership

boundaries.

Even when we are successful with large-scale,

designed experiments, we invariably have few

replications. It is difficult to commit extensive

acreages, and it is hard to find enough comparable sites. We need to somehow develop means

of testing hypotheses that are not so dependent

on large sample sizes. We will never have the

sample sizes typical of fine-scale studies, but that

cannot stop us from drawing defensible inferences.

We need to expand our capability to draw inferences from other than designed experiments.

Modeling has long been a tool to learn about relations. Models will play an even more important

role in large-scale research, but we need to develop better means to measure the confidence we

can place in their results. We need to develop

new methods to reveal the confidence, or in turn,

the uncertainty, of our scientific information that

describes large-scale relations.

Landscape research requires vast amounts of

data. Other opportunities for collection of important landscape data may emerge as monitoring

data are generated, such as is proposed for the

federal lands in the range of the northern spotted

owl. We will have to develop more rigorous data

accumulation and data management systems

than customarily are needed for finer scale research. This technological challenge emerged

with the study of landscape relations in the interior

Columbia basin as in the work described by Paul

Hessburg. Just as important as the technology,

however, is the discipline to use it.

Successfully addressing landscape-scale issues

requires complex decisionmaking, often involving

multiple agencies and landowners. A willingness

to research transboundary effects is necessary,

and success in both science and implementation

will require public-private cooperation. These

transboundary challenges highlight the importance of socioeconomic landscape research.

Biophysical research alone simply will not be successful in providing the scientific information to

deal with larger scale issues.
133

Landscape science may be burdened with the

a priori expectation that it will produce more than

scientific information. Scientists, managers, and

the public may develop exaggerated expectations

about the nature of results of studies about landscapes, perhaps even more than about finer

scaled research studies. Sound scientific information is an essential ingredient to sound decisions,

but information alone does not make decisions.

Any decision invariably requires the integration

of multiple components that can only be accomplished by value-based weighing of tradeoffs

among those components. That is the stuff of

decisionmaking, not science. While insisting that

the available science must be fully and faithfully

considered in the decision process, those responsible for research results must be careful to avoid

the misperception that science “makes” decisions.

Conclusion

We have a strong foundation of research on

which to build future landscape-scale research,

and the PNW Station and others in the science

community have already begun to do landscapescale research. There are compelling scientific

and policy reasons for conducting landscapescale research, especially research integrated

across scientific disciplines. Working with our

research collaborators and land management

partners, we hope to build on this foundation and

make meaningful advances—advances that may

not only help us better estimate the consequences and risks of current management options but also help us all create new options that

might embody more compatibility among the

many values society seeks from the land.
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