AN ABSTRACT OF THE THESIS OF
John J. Baker
for the degree of
Master of Science
Agricultural and Resource Economics presented on
in
December 11,
Title:
19811.
Multiple Use Resource Allocation:
An Empirical
Analysis of Selected Forest Resources.
Redacted for privacy
Abstract approved:
Ronald A. Oliveira
Forested watersheds are classical examples of multiple
use
natural
resource
areas
which
simultaneously
supply
timber, water, range, fisheries and wildlife, and a variety
of recreational and esthetic experiences.
forest
ecosystem
to
brings
about
resource
other
multiple
benefit
use
one
concomitant
resources.
A change in the
forest
multiple
changes
which
Forest
multiple
resources, while abundant by many standards,
limited.
are
use
affect
in
use
fact
As a result, choices have to be made regarding
combination
and levels of forest multiple use resources
to be provided.
The complexity of multiple use management
the
requires
the
need
multiple
use
resources
consider,
to
approximate
production
simultaneously,
a
large
complex
and
relationships
number
of
dynamic
and
to
different
management strategies for a heterogeneous set of resources
for alternative planning horizons.
objectives
The
analytical
framework
regarding
multiple
empirically
joint
test
production
(Timber
Schmidt
of
Resource
and
which
use
are
resource
the
allocations
Economic
1980))
Estimation
was
used
an
decision-making
and
theory
information provided
Economic
Gourley,
define
to
facilitates
methodology.
this
and
study
this
(Tedder,
construct
to
of
TREES
by
System
to
the
analytical framework.
The analytical approach was tested utilizing physical
data
from
Watershed
the
of
upper middle
the
National Forest.
Hebo
This
portion
Banger
study
of
the
District
of
also
examines
Drift
Siuslaw
the
the
Creek
projected
physical and economic impacts on the allocation of timber,
deer,
elk,
cattle grazing,
anadromous fisheries,
spotted
owl and bald eagle multiple use resources within the study
area of seven Forest Service management strategies.
MULTIPLE USE RESOURCE ALLOCATION:
AN EMPIRICAL ANALYSIS OF
SELECTED FOREST RESOURCES
by
JOHN J. BAKER
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Completed December 11,
19814
Commencement June 1985
ACKNOWLEDGEMENT
I would like to thank the many people who have made
the completion of this thesis possible. To those who have
provided moral support and who have guided my work with
their experience and assistance:
My major professor, Dr. Ronald (Ron) A. Oliviera for
his guidance and continued patient support throughout my
graduate program;
Dr. Philip (Phil) Tedder for his perceptive and timely
suggestions and continued assistance during the course of
research completion;
The
other members of my committee,
Dr.
R.
Bruce
Rettig, Dr. Michael (Mike) V. Martin and Dr. Ray Northam
for reading and offering their helpful comments on the
preliminary draft of this thesis;
Judith (Judy) Sessions who typed the manuscript and
whose
editorial
suggestions
were
important
to
the
completion of the thesis;
Special friends; Clarence and Sue Rose, Gary and. Mary
Smith, Bob and Sandi Larison, Dan and Annette Youngberg,
Everette and Julie Carpenter, Cliff and Esther Sturtevant
and Darryl, Kenneth and Helen Berry for the many minor and
major things they have done to help me complete my degree
program;
Members of my family, Charles and Dorothy Baker, Dean
and Frances Seaney, Jim and Diana Hight, Billie McCurry,
Elana Pitts, and Isebelle Bryan Sparks who were always
there to help in whatever ways they could;
And, finally, to Deanna, my wife.
Without her love,
support, assistance, patience and understanding this thesis
and my program of graduate studies could never have been
completed;
To
all
these
people,
I
extend
my
deepest
and
everlasting gratitude.
And to Katie, my daughter,
who
provided the final inspiration for project completion, this
thesis is lovingly dedicated.
APPROVED:
Redacted for privacy
Associate Professor, Courtesy, of the Department of
Agriculture and Resource Economics in charge of major
Redacted for privacy
Head of Department of Agricultural and Resource Economics
Redacted for privacy
Dean of the
raduate S4 001
Date thesis is presented
December 11,
19814
Typed by Judith Sessions for John J. Baker
TABLE OF CONTENTS
Chapter
Introduction
Research Problem
Thesis Objectives
Research Approach
Study Area
Resources Considered
Period of Analysis
Method of Analysis
Organization of the Thesis
I
II
III
1
1
2
2
8
8
9
9
10
Literature Review
Introduction
Historic Overview
Term Definition
Economic Interpretation
Joint Production
Economic Optimization
Problems
Applications
The Upper Middle Drift Creek Watershed
Introduction
Drift Creek Watershed
Study Area
Climate
Soils
Timber Resource
Water
Streams
Fisheries Resource
Wildlife Resources
Recreation
13
13
11
18
21
22
2
28
3L
48
1&8
50
.....
....
Minor Forest Products
IV
Empirical Estimation of Multiple Use Joint
Production Relationships for Study Area
Resources
Introduction
External Ecological Effects of
Timber Management Activities
Timber
Non-timber Multiple Use
Resources
Multiple Use Joint Production
Relationships
52
52
53
5'
55
56
56
57
57
59
59
60
62
62
63
69
Chapter
V
VI
Page
Allocation of Multiple Use Resources of the
Upper Middle Drift Creek Waterhed: A
Case Study
Introduction
Forest Management Models
Trees: A Brief Description
Trees: Operationalizing Data
Analysis Methodology and
and Simulation Runs
Simulation Results and
Implications
Interpretation of Results
Economic Implications
Interpretation of Results
Employment and Income
Interpretation of Results
Summary and Conclusions
Introduction
Research Summary
Research Conclusions
An Appraisal of the Research
83
83
814
85
87
87
1014
120
128
1140
148
153
162
162
162
166
167
BIBLIOGRAPHY
172
Appendix
Appendix
Appendix
Appendix
205
209
226
A
B
C
D
2314
LIST OF FIGURES
Figure
Page
The Drift Creek Watershed
149
Upper Middle Drift Creek
51
LIST OF TABLES
2.1
'4.1
'4.2
14.3
14'4
14.5
14.6
14.7
14.8
4.9
JOINT PRODUCTION APPLICATIONS
146
EMPIRICAL YIELD TABLE HEBO RANGER DISTRICT .. .
614
DEER PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(CURRENT LEVEL OF MANAGEMENT
INTENSIFICATION)
STUDY AREA ELK PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(CURRENT LEVEL OF MANAGEMENT
INTENSIFICATION)
73
714
CATTLE PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(CURRENT LEVEL OF MANAGEMENT
INTENSIFICATION)
75
SALMONID PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(CURRENT LEVEL OF MANAGEMENT
INTENSIFICATION)
76
STUDY AREA DEER PRODUCTION COEFFICIENTS
PER ACRE AT VARYING CATTLE GRAZING
INTENSITIES (BEUTER ET AL. TARGET A
OR BEUTER ET AL. TARGET B
LEVEL OF
MANAGEMENT INTENSIFICATION)
77
STUDY AREA ELK PRODUCTION COEFFICIENTS
PER ACRE AT VARYING CATTLE GRAZING
INTENSITIES (BEUTER ET AL. TARGET A
OR BEUTER ET AL. TARGET B LEVEL OF
MANAGEMENT INTENSIFICATION)
78
STUDY AREA CATTLE GRAZING PRODUCTION
COEFFICIENTS PER ACRE AT VARYING CATTLE
GRAZING INT-ENSITIES (BEUTER ET AL. TARGET A
OR BEtJTER ET AL. TARGET B
LEVEL OF
MANAGEMENT INTENSIFICATION)
79
SALMONID PRODUCTION POTENTIALS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(BEUTER ET AL. TARGET A OR BEUTER ET AL.
TARGET B LEVEL OF MANAGEMENT
INTENSIFICATION)
80
P aj
5.1
UPPER MIDDLE DRIFT CREEK INVENTORY DATA
88
5.2
ACREAGE INVENTORY DISTRIBUTIONS
89
5.3
ACREAGE INVENTORY DISTRIBUTIONS
90
5.14
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD ...
914
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD
...
95
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD
...
96
5.5
5.6
5.7
5.8
5.9
5.10
5.11
5.12
5.13
5.1's
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD
97
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD
98
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD
99
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST
VOLUMES PER PLANNING HORIZON DECADEPERIOD
100
RESOURCE PRODUCTION COEFFICIENTS PER ACRE
(CURRENT MANAGEMENT PRESCRIPTIONS)
101
RESOURCE PRODUCTION COEFFICIENTS PER ACRE
BEUTER ET AL. TARGET A MANAGEMENT
PRESCRIPTIONS
102
RESOURCE PRODUCTION COEFFICIENTS PER ACRE
BEUTER ET AL. TARGET B MANAGEMENT
PRESCRIPTIONS
103
RESOURCE AVERAGE ANNUAL PRODUCTION LEVELS PER
ROTATION DECADEPERIOD
5.15
5.16
5.17
105
RESOURCE AVERAGE ANNUAL PRODUCTION LEVELS PER
ROTATION
108
ANNUAL AVERAGE AUMS OF CATTLE GRAZING PER RUN
AT VARYING CATTLE GRAZING LEVELS
111
AVERAGE ANNUAL DEER HARVEST POTENTIALS PER
ROTATION DECADEPERIOD
112
TABLE
5.18
5.19
5.20
5.21
5.22
5.23
5 .21
5.25
5.26
5.27
5.28
5.29
5.30
5.31
P
AVERAGE ANNUAL ELK HUNTING DAYS PER
ROTATION DECADE-PERIOD AT VARYING CATTLE
GRAZING LEVELS
113
AVERAGE ANNUAL ELK HUNTING DAYS PER RUN
AT VARYING CATTLE GRAZING LEVELS
11k.
AVERAGE ANNUAL ESCAPEMENT PER ANADROMOUS FISH
SPECIES AT VARYING LEVELS OF GRAZING
115
ANNUAL AVERAGE ANGLER-DAYS FOR STEELHEAD TROUT
AT VARYING LEVELS OF CATTLE GRAZING
116
AVERAGE ANNUAL OUTPUT EFFECTS OF ALLOCATION
CHANGES
118
AVERAGE ANNUAL OUTPUT EFFECTS OF ALLOCATION
CHANGES
119
AVERAGE ANNUAL EFFECTS OF INCREASE CATTLE
GRAZING FROM THE NO CATTLE GRAZING INTENSITY
LEVEL
'126
ECONOMIC VALUES OF STUDY AREA NON-TI14BER
MULTIPLE USE RESOURCES
132
PRESENT NET WORTH OF THE AVERAGE ANNUAL
CATTLE GRAZING POTENTIALS AT ALTERNATIVE
AUM VALUATIONS AND LEVELS OF CATTLE GRAZING
INTENSITIES
135
PRESENT NET WORTH OF THE AVERAGE ANNUAL DEER
PRODUCTION AT ALTERNATIVE HARVESTED ANIMAL
VALUATIONS AND ALTERNATIVE GRAZING POTENTIAL
HARVEST RATES
136
PRESENT NET WORTH OF THE AVERAGE ANNUAL ELK
PRODUCTION AT ALTERNATIVE GRAZING POTENTIAL
HARVEST RATES AND LEVELS OF CATTLE GRAZING
INTENSITIES
137
NET PRESENT WORTH OF SALMONID ESCAPEMENTS
AT VARYING LEVELS OF CATTLE GRAZING
138
NET PRESENT WORTH OF STUDY AREA MULTIPLE USE
RESOURCE ALLOCATIONS AT ALTERNATIVE LEVELS OF
CATTLE GRAZING INTENSITIES
139
RESOURCE PRESENT NET WORTH CHANGES AT VARYING
LEVELS OF CATTLE GRAZING
111.1
TABLE
5.32
AVERAGE OUTPUT EFFECTS OF ALLOCATION CHANGES
5.33
AVERAGE OUTPUT EFFECTS OF ALLOCATION CHANGES
145
5.3I
AVERAGE ANNUAL FOREST INDUSTRY EMPLOYMENT
150
5.35
TIMBER EMPLOYMENT AND INCOME IMPACTS
151
5.36
NON-TIMBER RESOURCE INCOME IMPACTS
15I
5.37
PHYSICAL AND ECONOMIC IMPACTS OF ALTERNATIVE
STUDY AREA MULTIPLE USE RESOURCE ALLOCATIONS
.
160
MULTIPLE USE RESOURCE ALLOCATION:
AN EMPIRICAL ANALYSIS OF
SELECTED FOREST RESOURCES
I. INTRODUCTION
Forested
which
watersheds
simultaneously produce
water,
timber,
big game and opportunities for
a
use areas
multiple
typical
are
range,
fish,
variety of recreational
and aesthetic experiences. A change in the forest ecosystem
to benefit one forest land multiple use resource use brings
about concomitant changes that affect other uses.
multiple use resources, while abundant by
are indeed limited.
regarding the
As a
Forest
many standards,
result choices have to be made
levels and combinations of forest multiple
uses to be provided.
Research Problem
The
economic
problem
in
allocating
multiple
use
resources is a classic case of allocating limited resources
among competing uses.
The economic criteria for maximizing
the net returns of a production facility or process which
simultaneously
produces
two
or
outputs
more
is
clearly
defined if acceptable market values exist for each joint
production
resource
product.
allocation
In
which
such
cases,
equates
the
the
multiple
marginal
use
value
products in each use, given the objectives and associated
metrics involved, identifies the appropriate level of joint
2
production.
allocating
However, serious problems are encountered in
forest
multiple
use
absence of information about
and
outputs
of
forest
resources
because
the relationships
ecosystems
and
of
of
inputs
lack
the
an
of
information about the provision costs and relative values
of multiple use resource outputs.
Thesis Objectives
There are
first is
two basic objectives of this
thesis.
The
to define an economic framework which facilitates
decisions
regarding
resources.
The second objective is to empirically test the
the
allocation
of
multiple
use
derived analytical framework.
A
prerequiste
framework
is
a
development
the
to
comprehensive
of
review
of
the
analytical
the
approach
theoretical foundations and discussion of applications of
joint production theory.
the
research
approach
Before reviewing the literature,
is
briefly
summarized
and
the
organization of the thesis is outlined.
Research Approach
A wide variety of analytical methodologies have been
applied
in
multiple
use
decision
resource allocations have been
techniques
(Clawson,
1975;
O'Connell,
1972;
Multiple
use
examined using descriptive
Hills;
benefit-cost analysis (Clawsori,
making.
1966;
McHarg,
1969),
1976; H. M. Treasury, 1972;
O'Connell and Brown,
1972;
O'Connell and
3
197k; U.S.D.A. Forest Service,
Boster,
programming techniques such
1977;
1976),
mathematical
linear programming
as
(Bell,
1980; Leuschner, Porter, Reynolds and Burkhart,
Kent,
1975; Navon, 1967, 1971;), integer programming (Bell, 1977;
1975),
Kirby,
goal programming
Meador and White,
Meadows,
1977),
Meadows
and
1977; Field,
1976;
Schuler,
linear
1973; Navon
Adams and
Kao,
Riitters,
Brodie
(Adams and
Ek,
1979)
and
1968; Harzard and Promntiz,
1974;
Scheurman
Burt,
196k;
and
Hann,
1982),
197k,
1975;
Bell,
programming
and
Scheurman,
Schmidt
and
Gourley,
(Kalbacher,
techniques
McKillop,
Schweitzer,
1977;
Kao
(Johnson
1976;
1977;
(Leven,
(Beuter,
Convery,
1973),
Blanch and Stoevener,
Ives and
1966;
et
1973;
1968;
Youmans,
Tedder,
shift-share
1976;
analysis
1976),
stages-
1980),
economic
Connaughton
1975;
formulations
Fight and Darr,
1977;
(Beuter,
1966;
Gustafson,
input-output
Scheurman,
simulation
Schallau,
al.,
1980;
Brodie,
and
and
Chappelle,
1980),
Brodie,
(
nonlinear programming
1979; Ledeboer, 1982; Marousek,
of-growth theory
1975;
Maloney,
Hann and Brodie,
1975),
Johnson,
Johnson,
base
1969;
(Armstrong,
1978;
and
197k),
1967), polyperiod programming
MeConnen,
quadratic
1978;
separable
1971; Tanner, 197k), dynamic programming
(House,
Dane,
(Cohen,
1978),
Steuer,
programming
and
1976;
1973; Schuler, Webster and
multiobjective programming
programming (Harzard,
parametric
1975,
(Bell,
Roberts and
and
Maki and
(Bromely,
1974;
Rettig,
Flick,
1975;
Rohy and Lovegrove, 1970) and econometric analysis (Adams,
4
19714;
Adams and Haynes,
1973;
Oliveira
1980; Cjcchettj, Fisher and Smith,
1977;
Rausser,
and
1983;
Sandrey,
Shih,
1981).
The analytical approach employed in this research is
to examine multiple use resource allocations from a joint
production
theoretical
framework.
useful on three accounts.
Such
approach
an
is
First, it provides a conceptual
framework which integrates the
objectives
of management,
the biological and physical characteristics of multiple use
resource
production
evaluation
of
allocations.
emphasizes
relationships,
alternative
joint
A
critical
the
multiple
production
economic
the
and
use
resource
conceptual
framework
importance
of
correctly
understanding and representing the underlying and operative
resource production and technical relationships.
joint
production
conceptual
approach
Second, a
satisfies
the
statutorily stated objectives of multiple use management
(Multiple Use-Sustained Yield Act,
with
the
directives
legislation
Resource
Planning
Management Act,
provisions
and
(Multiple
Act,
1960) and is consistent
Use-Sustained
19714;
1976).
and
of
multiple
Yield
Act,
National
the
And finally,
use
1960;
Forest
a joint production
approach provides an analytical framework for objectively
identifying,
examining,
and
evaluating
multiple
use
resource allocation alternatives consistent with multiple
use and economic principles.
5
A joint production approach
to multiple use resource
allocation problems presents few conceptual problems.
one
accepts
efficiency
economic
appropriate
an
as
If
then maximization of
determinant of management decisions,
differences between benefits and costs makes sense whether
measured in dollars, social welfare values, physical units
Objections to
or in units of psychological satisfaction.
the use of a joint production approach result not from the
validity
of
possible
achieved,
conclusions
from
but
problems associated with applications.
First,
there
does
exist
not
a
current
consensus
regarding the appropriate output units of measurement for
even the
outdoor
five principal multiple use resources:
recreation,
range,
timber,
Without
fisheries.
watershed
accepted
commonly
wildlife
and
units
of
and
output
measurements for the various renewable surface resources of
national
forests,
a
comprehensive
resource allocations within
economic
analysis
joint production framework
a
cannot be initiated or objective results derived.
the
complex
and
dynamic
of
joint
production
Second,
relationships
among renewable forest land resources are little understood
and
have
received
little
quantitative
(Davis, 1976; Teeguarden, 1977).
considerations
Without acceptable units
of production measurement, the problem of determining the
production
relationships
among
multiple
use
resources
necessary for economic analyses cannot be seriously tackled
(Gregory, 1955,
1976).
Third, the extra-market
nature of
6
many
multiple
results In an absence
resources
use
of
information about the relative values of provided outputs.
Universally accepted resource values exist for only a few
multiple
resources;
use
optimizing
or
objective
without
resource
cannot
decisions
allocation
values
output
be
easily made or evaluated.
The possible application of a joint production theory
multiple
to
discussed
1963;
(Black,
1938;
Ciricacy-Winthrup,
been
1976;
1977;
Clawson,
Lynne,
1974;
1969; Muhlenberg, 196)4; O'Connell and Brown, 1972;
Miller,
Pavelis,
Johnson,
and
flutters,
Brodie,
Hann,
Turner,
has
Brown,
1976; House, 1971; Gregory, 1955, 1972;
Davis,
1982;
O'Connell
and
Teeguarden
(1971),
House
Brown
(1975),
1961;
Shrader,
1971).
1975,
flutters
(197)4)
Miller
al.
et
Worley
and
1969,
1977;
Only Black (19614),
(1974)
Lynne
(1972),
Turner
Pearse,
Teeguarden,
197)4; Worley and Patric,
(1976),
Brown
problems
allocation
various authors
by
1966;
Castle,
resource
use
and
(1969),
(1982),
Patric
(1971) have actually employed a joint production framework
examine
to
actual
multiple
resource
use
allocation
problems.
The infrequency of applications of a joint production
framework to
is due
with
real multiple use resource allocation issues
to empirical problems.
respect
to
its
appropriateness
approach, however,
is
lacking.
is general consensus
There
For example,
as
a
conceptual
information on critical inputs
there
is
a
general absence of
7
qualitative
and
quantitative
information
measurement of output units,
and physical relationships.
to
effectively apply
input costs,
regarding
the
output values,
This information is necessary
joint production theory
to
multiple
use resource analysis.
Notwithstanding the application difficulties presented
by
informational deficiencies,
production
affords
formulation
more
a
resource
consideration
of
evaluation
alternatives.
allocations
from
a
multiple
use
addition,
the
of
In
joint
measurements,
imperfect
using
inclusive
allocation
the employment of a
joint
production
perspective permits the examination of resource allocation
over the long run. It also affords an opportunity to assess
the
congruency
allocations.
In
proposed
managerially
of
short,
a
production
joint
resource
conceptual
approach focuses attention upon multiple use resource data
deficiency problems and possible solutions.
application
The
framework
to
the
of
a
allocation
production
joint
of
multiple
use
analytical
resources
involves a relatively straight-forward set of activities.
First, the study area selected for analysis is identified.
Second,
the multiple use
identified.
Finally,
resources
to
be
considered are
Third, the time period of analysis is defined.
the method of analysis is specified.
Area
7,890 acre portion
The area selected for study was a
of
the
Forest.
Drift
Creek
Watershed
of
Siuslaw
the
National
The study area is typical of national forest land
of the central portion of the Oregon Coast Range.
Portions
of the Study area demonstrate a timber producing capacity
that is
contains
among the highest in the nation.
important
fishery species,
agricultural
spawning
is
supplies
hundreds of wildlife
most
popular
big
distributions
species,
game
domestic and
provides
and
including
animals,
deer
anadromous
of
source of municipal,
a
water
The study area
habitat
the
and
for
state's
two
and
two
elk,
threatened avian species, the Northern bald eagle and the
Northern spotted owl.
with
multiple
concepts
and
use
is
The area is managed in accordance
and
sustained
administered
yield
for
principles
recreation,
and
range,
watershed, fish, wildlife, and timber purposes (Hebo, FEIS,
1978, p. 5;
Siuslaw FEIS,
1979, p. 17.)
Resources Considered
Five major forest multiple use resources and two minor
forest renewable surface resources are considered during
the
course
resources
of
are
analysis.
timber,
anadromous fisheries.
The
deer,
five
elk,
major
multiple
use
cattle
grazing
and
The two minor multiple use resources
are spotted owl and bald eagle pairs.
9
The resources identified for
represent
restricted
a
sample
multiple use resources.
data
availabilty
traditionally
The
on
a
desire
forest
number
of
manageable
to
forest
study
arid
area
Resource selection was based on
considered
resources.
restricted
and
of
analysis
examine
to
renewable
resources
less
surface
considered
proportions and
to
was
magnitude
a
considered sufficient to test the analytical approach.
Period of Analysis
The general period
current
100
year
of analysis
timber
rotation
analysis period coincides with
planning horizon
study
area
and
for
the
the
period.
study area's
examination
encompassing
the
of multiple
use
resource production levels and relationships as
proceeds through various successional
rotation
length
of
80
years
year
100
A
the current Forest Service
planning unit
the
permits
is
is
stages.
considered
forest
a
A
to
reduced
reflect
intensified forest management practices and to permit the
examination
lengths
of
upon
the
impact
resource
of possibly
productivities
changed
and
rotation
study
area
multiple use resource allocations.
Method of Analysis
Joint
production
relationships
and
production
coefficients for the considered multiple use resources are
developed from study area data, comparable area information
10
and
general
resource
study
findings.
Resource Economic Estimation System),
and harvest
scheduling
a
TREES
(Timber
forest management
simulation model developed
by
K.
Norman Johnson, H. Lynn Scheurman and John H. Beuter (1976)
is used to project timber harvests, stumpage revenues and
costs,
and
objectives,
timber inventories
intensity
Non-timber resource
practices
production
with TREES inventory and
multiple
use
management
for alternative management
and
harvesting
coefficients
policies.
are
harvest volume data
production
levels
strategies.
for
Derived
develop
alternative
seven
multiple
to
combined
use
resourpe
production figures are combined with alternative resource
valuations to project total resource value, revenue, income
and employment impacts of alternative multiple use resource
allocations.
Projected resource production levels, output
valuations and economic impacts are compared and contrasted
with
Forest
Service projections
various empirical studies and
and
are
results
evaluated
reported
in
in
terms of
overall consistency with general multiple use and economic
principles and concepts.
Organization of the Thesis
The research is organized into six chapters, but can
be considered in two sections.
consists
of
Chapters
I
and
background for the thesis.
II,
The first section, which
provides
the
conceptual
Chapter I introduces the reader
11
to
multiple use
the
resource allocation problem and
its
possible investigation from a joint production perspective.
The
historic
review of
literature,
development
definitional
economic
multiple
of
problems
joint
presented.
discussed.
are
concludes
with
reported
review
a
the
and
An
framework
considerations
problems
chapter
The
discussed.
analytical
production
Applicational
Conceptual
and
an
and
recounts
II,
use.
examined
are
interpre tation
incorporating
Chapter
are
and
and
discussion of joint production applications to multiple use
decision
making.
applications
brief
A
denoted
is
summary
production
joint
of
chronological
in
order
in
focuses on
the
Table 2.1.
The second
joint
section,
production
resource
describes
analysis
allocations
the
physical
Chapters IlI-VI,
for
alternative
of
study
the
area selected
study
characteristics,
area.
multiple
use
Chapter
III
for evaluation.
endowments
resource
Area
and
productivities are examined and discussed.
Chapter IV develops the joint production multiple use
relationships
salmonids
for
to
timber,
be
used
allocation analysis.
measurement
of
deer,
in
the
cattle grazing
multiple
use
and
resource
General problems associated with the
multiple
use
resource
interrelationships and
specific
development
multiple
the
elk,
of
productivities
problems associated
use
joint
and
with
production
12
relationships for deer, elk,
cattle grazing arid salmonids
are reviewed and discussed.
Chapter V describes the simulation model, (TREES) and
the methodology used to project study area joint production
multiple use resource allocations.
seven
strategies
Empirical
output
forest
of
quantities
Empirical results for
management
combined
are
presented.
are
output
with
valuations and employment and income information to project
resource arid allocation economic values and employment and
income impacts.
Reported empirical results are compared
and contrasted with results reported in current management
planning documents and in comparable area studies.
The final section, Chapter VI, presents the summary,
conclusions, and recommendations for further research.
Supplemental
presented
in
the
information
used
appendices.
the
in
A
research
description
of
is
the
management intensification assumptions used in the analysis
and TREES simulation runs is given in Appendix A.
B
Appendix
contains a review of studies considering the impact of
forest management activities upon big game and anadromous
fishery resources.
A
description of
resource production coefficients used
presented in Appendix C.
and
the development
of
the analysis
is
in
In Appendix D the stumpage value
regeneration/cultural treatment
simulation runs are listed.
costs used
in
TREES
13
II. LITERATURE REVIEW
Introduction
Forest lands, as indeed virtually all lands, have "an
inherent capability
goods and
to produce one or more resources,
services,
allow one
or
219.3.
under natural conditions" (Sec.
1976).
or
or
resource uses
more
Public Law 914_588,
It is the capacity of forest land to simultaneously
provide more than one resource output or service which is
the central concern of' multiple use management.
use"
in
part means,
"the management
renewable resources of the national forests
various
the
all
of
"Multiple
so
that they
are utilized in the combination which best meets the needs
86-517, 1960).
of the American people" (Sec. !, Public Law
Multiple
use
more
is
Simultaneously,
it
statutory
definition.
philosophical
management
than
is
a
a
orientation historically identified with
Service,
social
a
prescription.
objective.
of
present
and
chapter has
Forest
an
economic
a
threefold
The first, is to provide an historical overview
multiple
definitional
The
prescription,
U.S.
the
use
and
problems.
multiple
The
economic interpretation and
use
second,
is
present
to
and
an
an analytical framework which
incorporates joint production theory.
are reviewed and discussed.
conceptional
And
Application problems
the final,
is
to review
and discuss joint production applications to multiple use
resource allocation problems.
14
Historic Overview
The
origins
European
of multiple use
forest
management
are traceable
practices
early
to
which
often
subordinated timber production to hunting considerations or
water supply protection.
The concept of multiple use was
clearly embodied in Secretary Wilson's 1905
first
letter to the
Chief Forester officially transferring
"Forest
the
Reserves" from the Interior Department to the Department of
Agriculture:
"In the administration of the forest reserves it
must be clearly borne in mind that all land is to
be devoted to its most productive use for the
permanent good of the whole people, and not for
the
temporary
benefit
of
individuals
or
companies.
All the resources of forest reserves
are for 'use,'
under such restrictions only
as will insure the permanence of the resources of
the
reserves
is
therefore
indispensable
to
continued prosperity, and the policy of this
department for their protection and use will
invariably be guided by this fact, always bearing
in mind that the
'conservative use' of these
resources
in
no
way
conflicts
with
their
permanent value...and where conflicting interests
must be reconciled the question will always be
decided from the standpoint of the greatest good
of
the
greatest
number
in
the
long
run."
.
(Pinchot,
The
forestry
Chief
term
19147,
September 1,
and
.
p. 261)
"multiple
literature
Forester
.
in
the
use"
1933
first appeared
in
Senate.
reports
In
in
American
prepared
his
report,
by
the
dated
1933, Chief Forester Robert Y. Stuart reviewed
Forest Service History by saying:
15
"The Forest Service had to find a principle to
govern the use of land valuable for more than one
purpose.
The principle decided upon was that if
a choice must be made between conflicting forms
of
use,
the
which
one
will
make
the
land
of
greatest public utility must be provided for; but
that if 'multiple-purpose use'
a
is
feasible,
plan for coordinated use must be worked out,
contrived as to yield the largest net total of
public benefits.
...it is through demonstration
of the workability of the principle of 'multipleuse'
that
the
national forest experiment has
perhaps had its greatest value." (Report of Chief
Forester 1933 p.1)
1933 Senate Document "A National Plan for American
The
Forestry" commonly called
multiple
use
in
the
introducing
Copeland Report,
report's
the
refers
to
'Forest-land
Resource' section.
In the first section of this part of the report
the extent and character of' our forest lands are
outlined by major forest regions and as to broad
classes of ownership.
Here is emphasized the
peculiar
and
highly
'multiple-use'
important
characteristics of forest land' and the five
major uses involved--timber production, watershed
protection, recreation, production of forage, and
conservation of wildlife (p. 119).
Used with increasing frequency during the Forties and
Fifties, multiple use was specifically established as U.
S.
Forest Service Policy and statutorily defined by the United
States
Congress
"Multiple
when
it
Use-Sustained
passed,
Yield
on
Act"
June
(Public
12,
Law
1960
86-517,
1960).
it
is
the policy of the Congress that the
national forests are established and shall be
administered
for
range,
outdoor
recreation,
timber,
watershed,
fish
wildlife
and
and
pu rp 0
the
s e s.
'Multiple Use' means the management of all the
various
renewable
surface
resources
of
the
national forests so that they are utilized in the
16
combination that will best meet the needs of the
American people, making the most ,judicious use of
the land for some or all of these resources or
related
provide
services
over areas
large
sufficient
latitude
for
enough to
periodic
adjustments in use to conform to changing needs
and conditions; that some land will be used for
less than all of the resources; and harmonious
and
coordinated
resources,
each
management
with
the
various
without
the
of
other,
impairment of the productivity of the land, with
consideration being given to the relative values
of the various resources, and not necessarily the
combination of uses that will give the greatest
dollar
return
or
the
greatest
unit
output.
(section 14)
Subsequent legislation has focused on the development
and
adoption
of
management
practices
and
procedures
consistent with multiple use concepts and principles.
Forest and
19714
Rangeland Renewable Resources Planning Act
(Public
Law
19714),
93-378,
Resources Planning Act or RPA,
study
of
economic
all
forest
analysis
of
based
the
commonly
calls
for
outputs
impacts
and
of
known
as
The
of
the
the simultaneous
the
intensive
programs.
The
Resources Planning Act directs the Secretary of Agriculture
to:
"Perform an analysis of present and anticipated
uses,
demand for, and supply of the renewable
resources,
with
consideration
of
the
international resource situation, and an emphasis
of
pertinent
supply
and
demand
and
price
relationship trends;" (Sec. 2. (1))
"identify
specific
Program
outputs,
results
anticipated,
and
benefits
associated
with
investments in such a manner that the anticipated
costs can be directly compared with total related
benefits
and
direct
returns
to
the
Federal
Government." (Sec. 3. (2))
"take
such
action
as
will
ensure
that
the
development and administration of the renewable
17
resources of the National Forest System are in
full accord with the concepts for multiple use
and sustained yield of products and services as
set forth in the MulttpleUse Sustained-Yield Act
of 1960." (Sec. 8)
The National Forest Management Act of 1976 (Public Law
94-588) generally known as
Forest Management Act
the
or
NFMA, provides direction for the Forest Service planning
process.
In accordance with the Resource Planning Act, the
Forest Management Act requires the development and adoption
of various land and resource management planning practices
and
procedures
physical,
for
estimating
biological,
and
economic,
evaluating
social
and
changes
in
conditions
associated with alternative natural resource combinations
for units of the National Forest System which:
"provide for multiple use and sustained yield of
the products and services obtained therefrom in
accordance with the Multiple Use-Sustained Yield
of
and
1960,
in
particular,
include
coordination
of
outdoor
recreation,
range,
timber,
watershed,
wildlife
and
fish,
and
wilderness; and " (Sec. 6. (e) (1))
Act
"determine forest management systems, harvesting
levels and procedures in light of all the uses
set forth in subsection (c)(1), the definition of
the terms "multiple use' and 'sustained yield' as
provided in the Multiple Use-Sustained Yield Act
of
1960,"
(sec.
6 (e)(2))
That multiple use is to be a guiding concept in the
management
of
national
forests
is
without
question.
Federal statutes and regulations governing national forests
are all explicit in requiring land and resource management
consistent with multiple use principles.
While there
is
18
general acceptance of multiple use as a
principle,
there
has
been,
forest management
continues
and
be,
to
considerable disagreement as to what multiple use precisely
means.
Term Definition
early
As
1938,
as
Ciriacy-Wantrup
observed
that
multiple use had at least two meanings:
"the administration or management of several uses
(1)
of wild
single
land
by
unit
single agency" and
a
(acre)
of
wild
(Ciriacy-Wantrup,
1938,
interpreted
the
under
land
p.665).
first
(2)
"the use
several
If
multiple
it
was
a
purposes"
for
meaning,
of
use
was
workable
a
principle; if multiple use was defined in accordance with
the second, it was rejected as being "wholly unsound."1
Dana
(193)
management
of
and
each
(1953)
MoArdle
acre
of
forest
proposed
land
to
that
tñe
produce
the
combination of products that maximized net returns to the
owners, either public or private, and whether measured in
monetary
or
non-monetary
units,
interpretation of multiple use.
1
reflected
Pearson
the
proper
(19LL) asserted
The necessity of making constantly new combinations of
uses in view of changing economic conditions invalidates
the multiple use principle, in the sense of the
desirability of several or all uses on the same acre of
wild land, because the optimum use might require a single
use or at least the exclusion of several subordinate uses
in favor of the dominant use or uses. (Ciriacy-Wantrup,
1938, p.665)
19
that multiple use must
be interpreted primarily,
or even
solely, in terms of large areas with single (primary) uses
identified for subdivisions.
Secondary uses for specific
subdivisions
as
were
permitted
long
they
as
did
not
conflict in any way with the area's identified primary use.
Various authors
have
categorized multiple
vague and ambiguous concept (Zivnuska,
1972).
Gregory,
use
as
a
1961; Pearse, 1969;
Others have identified multiple use as
a
term with significant emotional appeal and a meaning which
often varies according to its user (Clawson,
19714;
Duerr,
1975; Fairfax, 1977).
The
general,
somewhat
imprecise
and
even
somewhat
contradictory, language of the Multiple Use-Sustained Yield
Act
evidence
is
of
ambiguity
the
definition of multiple use.
multiple use
"to mean
renewable surface
prefaced
by
Congress
that
shall
timber,
be
the
the
resources
of
declaration
national
and
a
precise
The statutory definition of
the management
administrated
watershed,
surrounding
national
the
that
"it
forests
for
outdoor
wildlife
of all
and
is
are
the various
forests"
is
policy
of
the
established
recreation,
and
range,
fish purposes." The
definitional phrases "some or all of these resources" and
"some
land
will
be
used
for
lese
than
all
of
these
resources" further narrows the range of forest resources
required to be conceptually encompassed by the term.
The
phrases "best meet the needs of the American people" and
with consideration being given
to the relative values of
20
the various resources" may be interpreted as
for economic
efficiency.
However,
the
a
directive
establishment of
economic efficiency as a definitional goal or objective of
multiple use is successively contradicted by the rejection
of "the
dollar
combination of uses that will give
return
or
the
combinations which
greatest
provide
the
unit
the greatest
output,"
greatest
though
dollar value
or
unit output are suggested as possible multiple use goals or
objectives under certain circumstances.
In American forestry, multiple
different
multiple
things
use
is
to
different
legislative
a
use has come to mean
people.
Congress,
To
directive which
specifies
that national forest lands are to:
"be administered for outdoor recreation,
timber,
watershed,
purposes. ...in the
and
wildlife
range,
fish
and
combination that will best
meet the needs of the American people, ...without
impairing the productive capacity of the land,
with consideration being given to the relative
values
of
the
various
resources,
not
and
necessarily the combination of uses that will
give the greatest dollar return or the greatest
unit output." (Public Law 56-517, 1960. Sec.
)
To
the
Forest Service,
multiple use
forest land management which provides,
to
the greatest number in
Manual,
American
1982,
p.
119).
Foresters,
is
a
"the greatest good
the long run"
(u.s.
adopted
the
As
"multiple
use
system of
by
is
a
Government
Society
strategy
of
of
deliberate land management for two or more purposes which
utilize, without impairment, the capabilities of the land
to
meet
different
demands
simultaneously"
(SAF,
1973).
21
Buffington
Ripley
and
(197!!)
multiple
define
use
as
a
management philosophy which does not stress dominant use,
"multiple
use,
simplified,
close
is
what
to
operations
research people call optimization" (Buffington and Ripley,
117).
p.
197!!
Christiansen
Duerr,
Teeguarden,
Guttenberg,
and
(1979) identify multiple use as a popular term
for integrated management and define multiple use as:
program
of
managerial
inputs
rationally
selected to produce a desirable set of forest
services. What combination of services a manager
chooses
depends
upon
context:
resource
capabljty, technology of production, relative
values of inputs and outputs,
laws governing
land-use practices, management objectives, and so
forth.
One
use
may
be
emphasized,
or
a
"a
multiplicity of uses"
(Duerr,
6!!-65)
The
interpretation
et
of multiple
1979, pp.
al,
adopted
use
this
in
analysis is that multiple use denotes the administration of
a particular unit of forest land to simultaneously provide
two or more forest renewable surface resources.
Economic Interp re ta tion
The administration of a specific unit of forest land
to
simultaneously
surface
provide
resources
can
which
more
a
from
or
more
interpreted
be
production process
outputs
two
simultaneously
single
forest
as
renewable
economic
an
produces
production
facility.
two
or
The
production of more than one output from a single production
facility
or production process
production economics
under
the
is
treated
in traditional
general heading
of
joint
22
production (Carison,
Ferguson,
1965;
Henderson and Quandt, 1971).
production
processes
Gregory,
1971;
1972;
Frisch (1965) discusses joint
under
general
the
heading
of
"Multiware Production"; Dillion (1968) examines production
processes of a joint production nature under the heading of
"multiple
response
with
input
control"
and
"multiple
response without input control"; Naylor and Taylor
review
joint
"Multiproduct
production
processes
Production";
under
Lynne
and
the
(197)4)
(1969)
heading
discusses
production processes of a joint production nature under the
heading "Multiple Output Production."
Joint Production
Joint
production
occurs
whenever
given
multiple
product outputs depend not only upon the quantity of inputs
used but also upon the output levels of one or more of the
joint products.
Xn;
(x1, x2,
q
(2.1)
or in implicit form
Fk (q1, q7,
wherei, k,
... q; x1, x2,
=
x
n
)
(2.2)
0
1,2, ...,m; ik
products,
Xj
...
inputs
(j
(I
=
=
1,
2,
1,
2,
..., n)
.
. . ,
in)
The functional forms expressed by (2.1) and (2.2) are
perfectly
generalized
and,
as
a
result
can
be
used
to
represent all joint production processes involving two or
23
more products.
For example, consider
process that produces two outputs qi
variable
input
From
(x).
(2.1),
joint production
a
and q2 and uses one
joint
the
production
functions for q1 and q2 are given by:
q1
(x, q2)
q1
(2.3)
= q2 (x, q1)
For the unlimited case of joint production where m products
are produced using
inputs (2.1) produces the following
n
system of equations:
q1 (X1, X2,
= q2 (x12
,
(X1,
x
q2, q3, .q
x22 ,..., x2; q1, q3,
.,
2m
where 1, k,q. and x,
X;
q1,q2,
(2.11)
"m-1
are defined as before
x.. represents the amount of the
th
resource allocated to the 1th product.
Traditionally,
distinguished
joint
being
as
production
with
different
products
production processes have been
one
technically
and
of
two
fixed
types:
proportions
joint
(2)
joint
(1)
of
production
the
with
technically variable proportions of the different products
(Carison, 1956,
two
products,
pp. 75-76; Gregory, 1972, pp. 256-260).
q1
and
q2,
technically fixed proportions,
are
a
always
produced
If
in
single combined unit can
be defined to replace individual output levels for q1 and
24
The evaluation of joint
production with technically
fixed proportions can always be reduced to a single product
case.
If
two
products,
q1
and
technically variable proportions,
the products,
The
q1
evaluation
and
q2,
of
joint
q2,
are
produced
in
the proportions in which
can be produced may be varied.
production
variable proportions always
with
technically
requires the employment of
a
multiproduct optimization framework.
Economic Optimization
From a purely theoretical standpoint, joint production
with
technically
fixed
proportions
can
be
considered
a
special case of simple (single) production and covered by
the same kind of analysis.
aggregated
to
derive
a
Separate product demands can be
combination product demand.
And
since outputs always hold a fixed ratio to each other, the
constant combination of products can be treated as a single
homogeneous output quantity to which productivities, costs
and revenues can be related.
Production of the technically
fixed joint products is continued as long as the marginal
revenue
for
the
combination
of output
unit
marginal cost of unit production
exceeds
the
and profit is maximized
when the marginal revenue of the combination unit equals
the marginal cost of the combination unit production.
The
with
analytical
technically
similarity
fixed
production does not
between
proportions
and
joint
simple
production
(single)
imply that they are also similar in
25
other respects.
For example, the joint production nature
of a technically fixed proportion production relationship
destroys the
total
cost
output
divided
by
the
makeup
when
changing
effects
production
with
general price
output,
and
pp.
output
technically
Moreover,
production
equilibrium are
different
quite
the
joint
and
proportions
fixed
by
constantly
is
263_611).
simple
of
divide
cannot
one
that
of
1972,
(Gregory,
individual
"average cost" equals
idea of average cost;
upon
a
Where
.
there is jointness in production, there is also jointness
in
supply.
(1970)
Kahn
supply produces
demonstrates
general price
a
that
quite
jointness
different
from
in
a
simple production situation.
When
the
proportions
between
the
different
joint
products varies with different levels, there ceases to be a
possibility for formulating a composite homogeneous output
quantity
to
which productivities,
the
different
Nor
is
and revenues of
production products can
joint
possible
it
costs,
to
relate
the
magnitudes
be
related.
of changes
separately to the different multiple output products and to
their
calculate
problems arise
individual
costs
since a change in one variable proportion
product will generally influence the
demand
relations
technically
economic
framework.
These
revenues.
and
of
variable
evaluation
the
others.
proportions
within
a
technical,
Joint
cost and
production
always
multiproduct
with
necessitates
optimiztion
26
Alternative approaches
economic optimization
to
for
multiproduct production are thoroughly discussed by various
authors (Dillion, 1968; Frisch, 1965; Renderson and Quandt,
1980; Lynne,
1974; Naylor and Taylor,
involves the assumption that each q
assumed independent;
be
deduced
combination
i.e.,
from
of
any
One approach
1969).
production function is
no one production function can
other
functions
production
(Dillion,
function
1965,
411).
p.
or
The
underlying production functions reflecting this assumption
for a two product and a two input variable proportion joint
production case are given by:
q1
= q1(x11, x21; q2)
(2.5)
q2(x12, x22; q1)
where
q1
are
q2
production costs
products,
and
x1,
revenues
x2
for
are
inputs.
products,
production of both products 4s increased
and
q2,
long as
the
q1
as
Given
marginal revenue product exceeds the marginal product cost
for each product.
Profit is maximized when the marginal
revenue product equals the marginal product cost for each
product. (Frisch, 1965, p. 285).
Thus
far,
the
economic
optimization
of
joint
production processes have been absent of any input, output
or
expenditure
however,
restrictions
economic
constraints.
or
op timizatjon
limitations.
is
subject
Generally,
to
important
The constraints to which profit maximization
is subject are variations of two principal types (Dillion,
27
p.lI)4).
1977,
First,
the
of output
level
fixed
is
and
economic optimization involves identifying the input array
that has the least cost for the required level of output.
Or,
secondly,
the total outlay may be
fixed and economic
optimization involves determining the most profitable array
of outputs under the expenditure limitation.
Numerous
fixed
output
and
fixed
outlay
constraints
influence the allocation of forest multiple use resources.
For example, annual production levels for all multiple use
resources
are
limited
output
to
consistent with sustained-yield
Sustained Yield
Forest
1960;
Act,
Management
Act,.
quantities
principles
which
(Multiple Use-
Resources Planning Act,
1976).
"threatened" or "endangered"
are
Production
197)4;
levels
for
species are not permitted to
fall below current levels (Endangered Species Act,
1973).
Output quantities of fishery
resources are required to be
increased
over
to
five
percent
(Resources Planning Act, 19714).
resource
production
program
Though funding levels
products and
areas,
197)4
levels
by
1990
In addition, multiple use
enjoys
unlimited
funding.
may vary greatly between and among
all multiple use resource management
programs are conducted within the confines of established
expenditure limitations.
The neo-classical approach to joint production assumes
that production functions can be accurately specified and
that factor and product markets
outputs.
When
production
exist for all inputs and
functions
are
reasonably
28
representative
relationships
of
of
biological
the
production
the
technical
and
process(es)
and
market
prices are reasonably representative of the true economic
value of all inputs and outputs,
economic
When
optimum
production
is
a
fairly
functions
the determination of an
straightforward
inaccurately
are
activity.
specified
or
market values are not available for all inputs and outputs,
the
determination
of
an
economic
optimum
becomes
a
problematic or impossible activity.
Prob lems
The problem of applying
a
joint production economic
framework to multiple use resource allocation questions is
twofold.
between
First,
and
understood.
biological
among
multiple
and
use
technical
resources
relationships
are
little
Second, market values or values representative
of the true economic worth of resources exist for only a
few forest land inputs and outputs.
Perhaps
the
most
obvious
and
limiting
problem
influencing the application of joint production theory
to
multiple use resource allocation questions is the lack and
near
non-existence
of
available
data
on
multiple
use
physical and technical production relationships (Davis 1976
and Teeguarden, 1977).
One underlying cause of the absence of physical and
technical
production
relationship
data
is
the
problem
29
*
associated with units of measure for the outputs of some
multiple use
resources.
for measuring timber and
Units
forage are well known and
in
although one
everyday use,
might argue the relative merits of board feet, cubic feet,
cords,
International or Scribner
log
weight, Animal Unit Months, etc.
of dry
tons
scale,
Water is more difficult
to measure since quality and timing aspects must also be
considered.
Quantities, however, can be measured in acre
feet or in gallons, cubic feet or cubic meter per minute,
hour,
recreation
wildlife
But there
day.
or
should
and
is
far
measured
be
fishery
and
production
on how
less agreement
has
the
measurement
not
proceeded
beyond the making of simple population counts.
of
much
Units for
measuring some other products of forests such as non-game
wildlife and
non-commercial plant
species are
even
less
well-defined.
One of the most difficult problems in applying joint
production
theory
multiple
to
use
allocation
evaluation is that of resource valuation.
issue
Computation of
an optimum multiple use resource allocation requires the
use
of product values
reasonably
products' true economic values.
representative
of
the
Of the five most commonly
cited multiple use resources, only timber is market-priced
or
exhibits
evaluation.
price
a
Outdoor
which approximates
recreation,
a
range,
true
economic
watershed
and
wildlife and fisheries are provided by the government free
of
charge
or
at
administratively
determined
rates
30
nonreflective of the full values of the resources (Clawson,
1976).
absence
The
market
of
values
or
values
representative of the true economic worth of the resources
for
many
forest
institutionalized
social
commitment
various multiple
use resources to
irrespective
their
of
consequences
arising
externalities,
the
various
multiple
reflects:
products
land
ability
from
"public"
or
to
provision
of
the nation's citizenry
pay
and
economies
(2)
economic
of
scale,
goods
"merit"
resources
use
the
to
an
(1)
and
nature
market
of
power
concentrations
The absence of reasonable approximations of accurate
market-prices for most multiple use resources requires the
modification
of
or
a
departure
from
the
usual. economic
allocation process. Typically, "implicit values" or pseudo-
prices are
utilized
non-marketed multiple
to
satisfy optimality conditions for
use
resources.
The
derivation
of
implicit resource values for non-marketed forest land goals
and services generally reflects one of two basic valuation
approaches.
Under the first approach, the value of a non-
market good or service is derived from the observed value
2
For discussion relating to the social value of multiple
use resources see Bishop (1978), Convery (1977) and Row
(1977). For comprehensive considerations of externalities
see Baumol (1975), Castle (1965) and Holterrnan (1972); for
discussions of externalities associated with multiple use
resources see House (1971) and Krutilla and Fisher (1975).
For a through review of public and merit goods see Bator
(1958), Buchanan (1968), Holterinan (1972), McKean (1968)
and Musgrave (1969).
31
of
market-valued
a
valuation
good
approach,
value
the
Under
service.
or
of
second
the
non-market
a
good
or
service is derived from an observed market value produced
by the establishment of a hypothetical market.
examples of the first approach
Foremost
(the indirect method)
are
formulations of the "travel cost method" Brown, Singh and
Castle,
196'i;
Clawson and
Shorus,
Cesario
and
The
1970;
Clawson,
1959;
Driver,
1972;
Shallof,
1981;
1966;
Knetsch,
1980).
Knetsch,
most common examples
the
of
second
approach (the direct method or survey valuation method) are
iterative bidding
value
questions
(Dwyer,
Kelly
games,
experiments,
and
and
contingent
Bowes,
1977;
open-ended
auctions,
substitution
and
Randall
and
prices
are
games
Brookshire,
1978).
Occasionally,
administrative
utilized
to
satisfy optimality conditions for non-marketed multiple use
resources.
The usage of administrative prices to allocate
forest land products provides little likelihood that the
satisfaction
of optimization
conditions
optimal allocation of the resources.
coincidental
instances
of
will
produce
an
With the exception of
equivalency
of
administrative
charges and a good approximation of the true economic value
of the resources, the utilization of administered prices to
satisfy optimality conditions practically ensures resource
misallocations.
administratively
For
example,
zero-priced,
where
the
rules
resources
of
are
marginal
analysis indicates that no quantity of a resource should be
32
provided
if
there
is
any
involved
cost
making
in
it
available, no matter how great the demand for the resource
might actually be.
Where forest land products are public
goods, there is no incentive for consumers to reveal their
true evaluation, of a resource's worth, since consumption is
not conditioned by individual contributions.
pricing
with
provide
an
(Musgrave,
of
uniform prices
optimal
allocation
1969, p. 9).
additional
an
payable
by
public
of
Marginal cost
everyone
cannot
natured
goods
By definition, the marginal cost
consumer
of
public
a
good
is
zero;
therefore, marginal cost pricing requires a zero price for
the good once it has been provided.
Where resources are
administratively priced below the marginal cost of resource
provision, resources are utilized to a greater extent than
the real costs would warrant.
only by consumers who
Resources are utilized not
value the resource approximate to a
real price but also by consumers whose marginal evaluation,
while less than a proximate real value, is greater than the
administered
fee.
Therefore,
larger
quantities
of
resources are demanded than would be at real cost pricing
levels.
This may
pressures
1976),
to
lead
expend
to
such things as congestion and
recreational
facilities
(Reiling,
livestock overgrazing, etc.
One approach to the economic allocation process, given
the existence of non-market resources,
operative
resource
resource
production
combinations
can
is
conditions.
then
be
to identify the
Alternative
presented
to
the
33
appropriate
Assuming
decision
that
the
making
decision
entity
group
consideration.
for
accurately
reflects
society's preferences, selection of a particular resource
combination gives an implicit value for a non-market valued
resource.
The production conditions important to this
allocation approach are
relationships.
output
Given
trade-off
production
function and
transformation
the
ratios)
along
resource
a
iso-cost
ratios
production
(input-
function
surface, selection of a point on the surface provides an
implicit input-output price ratio.
transformation
ratios
along an iso-cost
Similarly, given the
(product-product
surface,
seaection of
trade-off
a
ratios)
surface point
identifies an implicit product-product price ratio.
The absence of market values for one or more resources
necessitates that
resource
the decision making entity determining
allocations
be
especially
concerned
with
the
effects of various actions on the eventual product-product
trade-off ratio.
Product-product trade-off ratios
to
be
accurate must be calculated along the correct curve; trade-
off ratios
cannot
curves
between
or
be
calculated
curves.
Any
along
effects
internal
of
iso-cost
intermediate
product relationships must be identified and isolated.
is
of
crucial
importance
that
the
underlying
It
technical
relations among the products which determine the manner in
which resource outputs respond to a given level of resource
application are correctly specified.
Trade-off ratios will
34
be
misleading
unless
the
underlying
technical
relations
have been accurately identified.
Applications
The possible application of joint production theory to
forest land outputs was first discussed
Ciriacy-Waritrup (1938).
and dismissed by
While acknowledging that a single
unit (acre) of forest land can be used for several purposes
and that alternative uses, although generally competitive,
can be complementary or supplementary (independent) under
certain economic conditions,
Ciriacy-Wantrup rejected the
classification of forest land uses as joint products in the
economic sense.3
Gregory (1955) was the first to actually suggest the
direct application of joint production theory to multiple
use allocation problems.
Using two forest land products,
timber and forage, Gregory developed a theoretical productproduct
model
of
a
continuously
functional
trade-off
between the two forest outputs.
The theoretical product-
product
illustrated
model
graphically.
by
a
was
initially
and
solved
The geometric presentation is then replaced
mathematical
treatment,
and
the
hypothetical
two-
3Joint products were defined by Ciriacy-Wantrup to exist
whenever the increase or decrease in the production of one
product increases or decreases the production of others or
at least makes it more economical to do so (CiriacyWantrup, 1938 p. 665).
35
product model is presented and solved mathematically using
generalized expressions for production and cost functions:
= f(x1, x2,
..., x; Qf)
Qf = f(x1, x2, ..., xn;
TC
Qe)
wh e re
Quantity of timber in bd. ft.
Qf = Quantity of forage in lbs.
x.
variable inputs (j
..., n)
1
TC = summation of various input costs for
outputs
The
product-product
considerations
of:
and
model
(1)
an
Qf
(Gregory,
presentation
increase
in
1955 pp.
9-11)
concludes
with
model
numbers, (2) product value quantification problems,
product
(3) the
relaxation of the assumption of instantaneous production,
and
(34)
the contribution which the product-product model
can have in identifying values of non-marketed forest land
outputs.
Black
(1963)
described
a
joint
product
production
model developed to evaluate the complementary relationship
between the forest land production of timber and water for
a 150 sq. mi study area.
The allocation model was a three-
dimensional response surface which
identified
the
timber
and water production levels which maximize net revenues for
different cutting schedules
(Maas and
Hufschmidt,
1959).
Study area research data and empirical research findings
36
were utilized to define timber and water yield production
relationships.
Timber
function
fixed
of
a
production
average
expressed
was
per
volume
acre,
as
a
fixed
a
acreage, and rotation length, i.e.,
f(x1,
Qt
2
x3).
Water production was expressed as
length,
average
interval,
and
ru off
per
a
function of rotation
length
acre,
of
cutting
an ext apolated relationship describing the
reaction of water yield to timber regrowth, i.e.,
Qw
where
f(x3,
Tt
extrpolated relationship of water yield
Tt
and timber regrowth for time period t of
the rotation period length
Timber and water pr.duct values were derived from market
sources while product costs were extrapolated.
value
of
product
net
revenues
The present
presented
were
for
alternative rotation lengths and cutting schedules using 3
and
6
percent discou t rates.
The cutting schedule which
maximized product net revenues for a given discount rate
was found to be inde.endent of the rotation length.
When a
3 percent discount r.; te was employed, the cutting interval
which
maximized
determined
to
be
the
13
present
value
years.
The
of
net
cutting
revenues
interval
was
which
37
maximized the present value of net revenues for a 6 percent
discount rate was foud to be 9 years.
Castle
(1965)
d scussed
possible application of
the
joint production the.ry to evaluating the effects of two
types of timber har esting practices upon
other
aquatic
Essentials
reso roes
multiple
of
application problems
Muhlenberg
small
output
theory
streams.
coastal
reviewed
and
modification
of
were
ere discussed.
(196
Gregory's
theoretica
(Gregory,
1955)
simplified
of
fisheries and
discussed
)
the
continuous
ccept
to
two-prod ct
product-product
empirical
discrete
example
of
model
data.
discrete
a
A
data
formulation was tabul..rly presented for pulpwood (cords per
acre)
and
deer
per
(lbs.
acre).
Assumed
values
were
provided for each out.ut and production costs were imputed
form
value
changes
stock levels.
various
associated
with
alternative
growing
The two-product example was evaluated for
levels
of
ustainable
growing
stock.
A
first
approximation of the *ptimum combination of the product mix
and
degree
differentiated
of
c:pital -
from
The basic two-produc
'lotted
tabular
was
graphically
output points and discussed.
model was expanded to include water
and aesthetic conside ation.
a
intensity
presentaton
of
The discussion concludes with
quasi-physical
transformation
functions for cordwoo, deer, water, and aesthetics.
Worley and Patri
(1971) developed a graphic multiple
output model to eval ate streamflow increases in terms of
38
timber growth foregone.
record
timber
of
alternative
The model was based on a 10-year
:rowth
manageme t
and
streamfiow
practices.
Timber
response
growth
to
and
streamfiow increase w-re expressed in terms of seven input
variables:
f(x1,
f(x1,
x7),
2'
x7),
2'
where
= timber growth (Bd Ft/Acre/Year)
Q
= stream low increase (In./Acre/Year)
xj = input
ariables (j=1, ..., 7)
(Of the sevn variables, the percent of cubicfoot volume removed (trees 5 inches dbh and
greater) wa
Four
distinct
stage
most closely related to
of
product
and Qw.)
substitution
were
identified and discused:
A supplemen ary (independent) stage when
zero to one third of the timber volume is
removed,
A competiti e stage when one-third to one
half of the cubic-foot volume is removed,
A weakly conpetitive stage when one-half to
three-fourt s of the cubic-foot volume is
removed, an
39
An antagonitic (strongly competitive) stage
I.
when more t an three-fourths of the cubic
foot volume is removed.
(Worley and Patric,
1971, p. 81).
The model was present d as a case study only and no optimal
product allocation or management program was suggested.
(1971) utilized a joint production framework to
House
develop a mathematical model for allocating timber, water,
fish,
wildlife,
forested
study
recreational viewing
and
area
Washington.
in
resources
of
model
The
a
was
constructed using poli periodic programming to simulate the
dynamic
and
long term
interrelationships.
quality
of
the
model,
Citing
physical
between timber and
little
nature
the
unavailability
describing
data
multiple
of
and
o her uses as a major disadvantage of
-ttention
is
devoted
to
identifying
forest
Hypot etical resource potentials for game,
fish, and sediment ar
impacts
poor
relationships
the
production relationships between timber and other
land products.
use
provided to illustrate the resulting
of alternati e
non-timber outputs.
timber
management
practices
upon
Production yields for outputs were
developed for 20-year intervals and a planning horizon of
200 years was establshed.
The
cursory
treat"ent
Economic values were assigned
of
non-timber
resources
was
substantiated by a reported result of the study that nontimber resources hav
"small economic value compared to
timber" (House,
1971, p. vi).
40
to all multiple use
roducts except viewing and the model
was optimized by max mizing present net worth subject
sustained yield
timb r
management
and
the
to
protection or
non-protection of rec eational viewing.
O'Connell and Br wn (1972) employed a multiple output
production
framework
evaluate experimental vegetative
to
treatments designed t
increase water yield. Their analysis
was within a multipl
use resource setting that included
timber,
wildlife
environmental
abitat,
quail y.
production functions
single
Pre liminary
for
sediment,
herbage,
water,
timber,
and
and
product
herbage and
product-product functions for water and timber, herbage and
water, and herbage an.
timber were developed from observed
test area data and were graphically presented.5
product relations
were
evaluated
technical relationships.
in
terms
Product-
of underlying
To account for the dynamic nature
of forest land production, outputs and costs were evaluated
over
a
proposed
90-'ear
figures were totaled
rotation.
Output
production
or the 90-year period and converted
to a average annual v..lue.
Costs were discounted to their
present value and convrted to an annuity which in turn was
averaged
over
the
pl:nning
period.
Alternative
5flesource
resource
produc tion
functions
and
product-product
relationships were exp essed in terms of alternative levels
of strip cutting.
P oduction functions for water (i:1),
timber (i2), and herb:ge (i3) were of the form
f(x.)
where Q
products
i 1,2,3)
level of st ip cutting (j = 1,2,...,5)
41
allocations were
exa
med in
of cost minimization
terms
criteria and in terms of resource trade-off associated with
a given level of ma agement practice expenditure. Output
pricing consideration
the extension
and
to
include non-
marketed forest land products were deferred to subsequent
studies.
pp.
(1972,
Gregory
geometric treatment
model.
393_1405)
presented
expanded
an
his 1955 theoretical product-product
Hypothetical
were
relationships
product-product
graphically illustrat;d for timber and forage, timber and
recreation,
sawtimbe
wildlife.
Consider-ble
impacts
that
attention
under ying
timber
and
recreation
and
was
focused
and
the
on
relationships
technical
and
relative price relaVonships may have, on product-product
combinations maximizig net
Values
revenues.
and
costs
were assumed for all considered inputs and outputs, and all
optimization solutions were derived geometrically.
Lynne
(197L1.)
ba-ed
the
development
of
conceptual
a
trade-off model for evaluating alternative water resource
allocations upon mult iple output production theory.
of joint products,
theore tical concepts
resource
defined
examined
independence
and
to
calculating
and
interdependence were
illustra ed.
Several
illust ate
problems
water
r:source
affecting hydrologica
joint costs,
empirical
and
trade-off
The
and
concisely
cases
procedures
ratios.
were
in
Elements
resource allocations and trade-off
ratios were identifie. and thoroughly discussed.
Optimal
42
resource allocations were predicated on the identification
of the operative resource production function relationships
and were derived graphically and mathematically.
Turner
described
(19714)
allocation
model
which
planning
a
incorporated
methodology
and
production
joint
relationships of selected multiple use resources. Turner's
model
maximized
net
revenues
subject
management production goals and
targets.
model was
model
essentially
developed
changes.
by
replication
a
House
(1971)
of
with
alternative
to
The allocation
the
mathematical
several
important
First, silvicultural practices were specified as
independent
Second,
variables
equal
productivity
rather
emphasis
was
relative
and
than
placed
dependent
variables.
resource
on
valuation.
Third,
physical
ranges
of
economic values rather than single values were provided for
products.
Finally,
the
maximized
worth
net
for
each
solution was another relative indicator of a given resource
allocation strategy
goals and
timber
site),
targets.
(bd.
ft.
forage
for alternative management production
Products included
sawtimber),
(AUMs),
preference ranking).
in
the model were
water (acre inches runoff on
and
aesthetics
appeal
(visual
Annual average production yields were
established for 10-year periods and the rotation length was
specified as
water
over
120 years.
time
and
The relationships of timber and
resource
prQduct
density were graphically illustrated.
given
to
identifying
and
yield
and
timber
Little attention was
evaluating
the
underlying
43
technical
were
relationships
primarily
between
focused
upon
Discussions
resources.
allocation
the
model,
its
description, its solutions, and proposed refinements.
Teeguarden (1975) applied joint production theory
previous
case
study
data
examine
to
the
to
underlying
technical relationships (Beady approach) between (1) timber
and
water
(Worely
and
Patric,
1971),
(2)
timber
and
recreation (Amidon and Gould, 1962), and (3) timber, water,
forage
and
Underlying
sediment
(O'Connell
technical
relations
four
and
stages
Patric,
of
1971),
technical
1972).
approach)
(Heady
thoroughly discussed and illustrated.
(Worley
Brown,
and
were
With case (1)
data
demonstrated
that
Teeguarden
relationships
between
timber
growth and water yield could be identified depending upon
the percentage of timber harvested.
Worley
and
Patric
in
While concurring with
number
the
of
identifiable
relationship stages, Teeguarden differed with the authors
in relationship classification and boundary identification.
For example, stage one (0-33 1/3%
Cu. ft. volume removal)
identified by Worley and Patric as an independent stage was
shown
as
removal)
a
by
complementary
Teegauarden;
stage
stage
3
(0-20%
(50-75%
Cu.
cu.
ft.
ft.
volume
volume
removal) shown as a weakly competitive stage by the authors
was identified as a strongly competitive stage (14O8O%) by
Teeguarden.
Teeguarden
timber
and
With case (2) data (Amidon and Gould,
demonstrated
recreation
that
the
changes
relationship
from
1962),
between
competitive
to
44
independent as recreational development was increased given
existing
the
physical
characteristics
of
resources of the Sierra National Forest.
forest
the
The opportunity
cost in foregone timber for exclusive recreation usage of
the study area was shown to be 8 cents per 1962 visitor-day
and only
$100
16 cents per visitor-day at
thousand
per
board
(O'Connell and Brown,
feet.
a
stumpage price of
With
case
(3)
data
1972), Teeguarden demonstrated that
if only timber, water and herbage benefits were at issue,
underlying technical relationships suggested that maximum
net benefits were realized by selecting either
a
33 percent
cutting or a clearcutting. If only water and herbage were
of
value,
technical
the
clearcutting
was
presentation
concludes
the
relationships
optimal
with
harvesting
implied
that
practice.
The
overview
an
of
land-use
planning in relation to management principles of dominantuse, multiple use and incrementalism.
Riitters, Brodie,
and Hann (1982) incorporated
joint
production considerations in an analyt.ical model designed
to
simultaneously
rotation
for
determine
ponderosa
pine
the
that
thinning
intensity
and
jointly
maximized
the
returns from both grazing and timber harvest
unit
of
land.
Independent and
on
the same
joint product production
relationships were defined for timber and grazing in terms
of four descriptors:
age, basal area, number of trees, and
time since last thinning.
determine
the
Dynamic programming was used to
optimal thinning and rotation of even-aged
45
ponderosa pine for:
(1) grazing only, (2) timber only, (3)
grazing
at
timber
and
current
prices,
grazing
(II)
and
timber with stumpage increasing one percent per year and
(5) grazing and timber with beef prices increasing at one
percent per year.
The authors demonstrated that depending
on relative prices and discount rates, the maximum value of
area production was provided by timber alone, grazing alone
or
an
optimal
illustrated
schedule
of
possible
the
joint
production.
expansion
They
also
optimization
of
to
include water and concluded that the developed methodology
could
applied
be
estimated
from
to
the
any
set
number
of
of outputs
that
descriptors
state
can
(i.e.
be
age,
basal area, number of trees, and time since thinning).
A
review
of
joint
production
applications
in
chronological order is presented in Table 2.1.
This chapter concludes the first segment of research
which served to introduce the reader to multiple use and
the
possible
perspective.
the
analyses
investigation
from
a
joint
production
The remainder of the thesis is concerned with
of
alternative
multiple
use
resource
allocations of selected resources for the identified study
area.
Table 2.1
REVIEW OF JOIN1 PRODUCTION APPLICATIONS IN CHRONOLOGICAL ORDER
Resources
Considered
Analytical
Ap2roach
Year
Author(s)
1938
Ciricoy-Wantrup
1955
Gregory
An Economic Approach to
Multiple Use
Timber and forage
Geometric
Mathematical
1963
Black
Timber and Water Resource
Management
Water and Timber
Three-dimensional
response surface
1963
Castle
Multiple Use RelationshipsProduction and Fishery
Timber and
Fisheries
Geometric
Title
Re source
196
Muhienberg
A Method for Approximating
Multiple-Use Optima
Pulpwood and Deer
Geometric
1971
Worley and Patrio
Economic Evaluation of Some
Management Alternatives on
Forest Land in West Virginia
Water and Timber
Geometric
1971
Mouse
An Economic Model for
Allocation of Multiple-Use
Natural Resouroes
Polyperiodio
Programming
1972
O'Connell and
and Drown
Use of Production Functions
to Evaluate Multiple-Use
Treatments on Forested
Watersheds
Water, Timber,
Deer, Salmon,
and recreational
viewing
Timber, Water,
1972
Gregory
Forest Eoonomioe
Use" Chapter)
1 97I
Ly nr. 0
Multiple Objective Planning
Procedures in Water Resource
Development and the Trade-off
Ratio
("Multiple
Mathematical
Ilerbage and
Sediment
timber, forage
Geometric
Water for irrigation, water for
municipal and
and industrial usa
Geometric
and mathematical
Table 2.1
Tear
(cont.)
Author(s)
Title
Considered
A22roach
197q
Turner
Allocation of Forest
Management Practices on
Public Lands
Timber, Water,
Forage and
esthetic appeal
Polyperiodic
Programming
1975
Teeguarden
Multiple Services
Evaluation of
case study data
cited by: Amidon
and Gould, 1962
Morley and Patrio,
O'Connel and Brown,
fleady Approach
to technical
relationship
classification
1972
1982
flutters, Brodie
and Mann
Dynamic Programming
for Optimization of
Timber Production and
Grazing in Ponderosa Pine
Timber and Grazing
Dynamic Programming
48
III.
THE UPPER MIDDLE DRIFT CREEK WATERSHED
Introduc tion
The
objectives
of
this
research
cannot
fully
be
satisfied simply by defining multiple use in terms of an
analytical framework of joint production.
To be an asset
in multiple use decision making and problem solving,
analytical framework must be operational.
is
tested
applying
by
the
the
Operationality
analytical
approach
to
the
allocation of multiple use resources of a particular area.
The purpose of the present chapter
is
to more completely
describe the study area selected for analysis.
Drift Creek Watershed
Drift Creek is located in the Coast Range,
of Lincoln City and
into Siletz
Bay
30,100 acres,
timberland,
(Figure
the
two
the
is
southeast
second major stream emptying
Encompassing approximately
1).
Drift Creek watershed
municipal watersheds,
contains prime
important
salmonid
spawning and rearing areas, and is inhabited by upwards of
306
wildlife
species
mammals,
(birds,
amphibians
and
reptiles) (Hebo FEIS, 1978, pp. 21425).
For
Watershed
the
purposes
was
divided
of
into
analysis,
four
the
Drift
Creek
sections:
lower,
lower
middle, upper middle, and upper (Figure 1).
upper
portions
are
primarily
privately
The lower and
owned
while
the
FIGURE 1.
12
LIY'J COLN
7
DRI?J' CREEK WATERSHED
I0
9
8
II
12
fl
CITY
I?
13
IS
13
14
9
L!
13
6
I?
20
23
a)
22
hO BA C I'
I1N
24
211
29
2â
28
26
8?
I
\2S(IJ
II
.11
31
32
33
MID1LE
3
r
I
-
3
yr
21
ci
33
21
UPPE
MT
a
uI.EtEUEN
BEACH
14
IS
24
is
20
14
22
Scale:
=l Mile
DRIFT CREEK WATERSHED
I)
4
12
50
lower
middle
publicly
and
owned
upper
lands
middle
sections
administrated
by
are
the
principally
U.S.
Forest
Service.
The upper middle portion of the Drift Creek drainage
was selected for the focus of attention of this study.
The
area typifies National Forest acreage of the Oregon Coast
Range
and
is
representative
of
a
multiple
use
natural
resource producing area.
Study Area
The upper middle portion of' the Drift Creek watershed
is located in the northeast corner of the southwest corner
of the Hebo Ranger District of the Siuslaw National Forest.
The
upper middle
Drift
Creek area contains
7,890
acres;
6,730 acres of National Forest land and 1,160 acres owned
and/or managed by other agencies, private organizations and
individuals6
(Figure
management of
the area
National
Forest
Hebo
Proposed
2).
is
described
Planning
Unit
in
Forest
the
Final
1978
Service
Suislaw
Environmental
Statement.
6The
1,160 acres of other ownership has been designated
proposed acquisition acreage by the Siuslaw National
Forest.
For the purposes of this study, 580 other
ownership acres will be treated as being acquired by the
Forest Service at the beginning of each of the first two
planning period decades.
a
51
UFFR MIDDLE DRIFT CREEK
FIGURE 2
//'
LCOLN
I
2
14
3
9
9
0
II
8
*7
'6
5
II
31
32
54
35
7
*2
CITY
/
VL
I
I
33
WhiZ
jBAY
6
5
7
9
4
3
I
II
2
____
3LENEDE N
3ECH
(1
22
EACH
(I
.4
::
Scale:
l Mile
LEGEND
SITJSLAW NATIONAL FOREST FOUNDARY
I
I
3
23
74
!D
LNCOLN
::
4
UPR MIDDLE DRIF' CREEK
LANDS SC}DULED FOR ACQUISITION
7
52
Cl i ma t e
Mean
from
annual
52°F
to
1490F
temperatures
throughout
1i.10C).
to
(9.140C
the
area
Average
range
annual
precipitation varies between 100 to 120 inches of rainfall
(Hebo FEIS, 1978, p.8).
Soils
Study area soils range in depth from one to eight feet
and
are
one
formation,
mixed
of
five
mixed
major
volcanic
volcanic
rocks
rock
types:
marine
and
sedimentary
intrusive
and
sandstone
type
rocks,
rocks,
marine
sedimentary rocks, and intrusive rocks that form sills and
dikes
(Hebo
middle Drift
FEIS,
1978,
Creek area
Elevation
p.5).
ranges
from zero
of
to
the
1 ,500
upper
feet
above sea level, with the majority of acreage falling into
the 1,001 to 1,500 feet elevation category.
lands varies from 0 to
145
Slope of area
percent, with 142 percent of area
acreage exhibiting slopes in excess of 25 percent.
The
middle
Forest
Drift
Service
Creek
currently
acres
as
identifies
possessing
a
320
high
upper
risk
rotation failure potential, 730 acres as medium high risk
rotation failure potential acreage,
160 acres as high risk
debris avalanche areas and 320 acres as medium high risk
debris avalanche acreage.
twenty
acres
are
One thousand, one hundred, and
classified
as
marginal
acreage
(land
53
identified as incapable of producing 20 cubic feet of tree
growth per acre per year).
Timber resource
Study area
Coast
Range,
National
timber
Hebo
the
Forest.
Of
merchantable size
the Coast Range,
stands are
Planning
the
or occur
timber
typical of the
Unit,
and
species
Oregon
Siuslaw
the
attain
which
in merchantable quantities on
four, Douglas-fir (Pseudotsuga menziesii)
western hemlock (Tsuga heterohylia), sitka spruce (Picea
sitchensis), and red alder (Alnus rubra or Alnus oregona)
are found within the study area.
Two climax forest zones
prevail within the upper middle Drift Creek area:
(1) the
Picea sitchensis zone and (2) the Tsuga heterophylla zone.
Presently the hemlock zone occupies 97 percent of the study
area and the sitka spruce zone the remaining 3 percent.
The
1973-714 Suislaw National Forest timber inventory
(U.S.F.S., 1974)
indicates that the National Forest portion
of the upper middle Drift Creek area qontains 5,6143 acres
timber
of - standing
stands which
volumes).
have
and
not
1 ,O4O
yet
plantation
acres
attained merchantable
(conifer
size
or
Pure conifer stands (hardwood species comprise
less than 20 percent of the total stand volume) occupy 74
percent of
species
the inventoried Forest Service acreage.
(hardwood
total plot
volume)
species
occupy
comprise
114
20-80
percent of
percent
the
Mixed
of
the
inventoried
acreage and pure hardwood species (conifers comprise less
54
than 20 percent of total stand volume) occupy 12 percent of
inventoried acreage.
In general, timber stands of the Hebo
Ranger District
are relatively young as a result of mid-nineteenth century
fires.
(not
Of the District's 115,000 acres of standing timber
including
plantations),
approximately
acres
79,000
(75%) range between 50-100 years, and approximately 29,000
acres (25%) are 100 years and older (Hebo FEIS,
p.
the
3,1140
study area's 5,6140 non-plantation acres,
(56%) range between 50-100 years and
100 years and older.
Of the
16).
Of
acres
1,1490 acres (26%) are
1,1490 acres of 100 year old
and older stands, 790 acres are old growth stands (stands
over 200 years old).
Site
index
levels
for
area range from 120-190.
the
upper middle
Drift
Creek
The mean site index value for the
study area is 170.
Water
Two municipalities,
Lincoln City
and
Kernville,
and
several domestic users obtain drinking water supplies from
the
upper
percent of
(85-102
middle
the
second (cfs),
Creek
area.
Approximately
85
study area's average annual precipitation
inches)
Creek's average
Drift
is
low
discharged
flow
as
stream
discharge of
50
flow.
cubic
Drift
ft.
per
or 32 million gallons per day, would satisfy
the municipal water requirements of approximately 320,000
people.
Drift
Creek's
mean
annual
discharge
of
110
cfs
55
could satisfy the municipal requirements of nearly 700,000
residents, if evenly regulated (Hebo FEIS, 1978, p. 9).
Streams
Approximately
27
miles
of Drift
Creek
is
currently
classified as Class I or Class II stream mileage.7
Besides Drift Creek, portions, or the entire drainages
of
three
Creek,
major
tributory
and Fowler Creek)
creeks
(Wildcat
Creek,
North
and numerous minor and un-named
creeks are within the study area.
7The
U.S.F.S. categorizes stream mileage into one of four
class types according to the present and foreseeable uses
made of the water, and the potential effects of on-site
changes to downstream uses (Hebo FEIS, 1978, xii).
Class
1
-
Perennial
or
intermittent
streams
or
segments thereof that have one or more of the following
characteristics:
(1) Direct source of water for domestic
use, i.e., cities, recreation sites, etc. (2) Used by large
numbers of fish for spawning, rearing or migration.
(3)
flow enough water to have a major inf1uence on water
quality of a Class
stream.
1
Class
2
-
Perennial
or
intermittent
streams
or
segments thereof that have one or both of the following
characteristics:
(1) Used by moderate though significant
numbers of fish for spawning, rearing, or migration.
(2)
Flow enough water to have only a moderate and not clearly
identifiable influence on downstream quality of a Class
stream, or have a major influence on a Class 2 stream.
1
Class 3 - All other perennial streams
thereof not meeting higher class criteria.
or
segments
Class
- All other intermittent streams or segments
thereof not meeting higher class criteria.
11
56
Fisheries Resource
A majority of the
19 species of anadromous and fresh
water fish known to inhabit the Hebo Planning Unit and Hebo
Ranger District are found
the
Drift
Creek
important
tshawytscha),
trout
trout
(Salmo
of'
(Sa].mo
and
has
(Oncorhynchus
sea-run
airdneri),
rainbow
cnow
salmon
Chinook
salmon
Coho
clarki)
area
study
The
distributions
steelhead
kisutch),
cutthroat
drainage.
spawning
(Oncorhynchus
in the upper middle portion of
trout
(Salmo
£airdneri).
Wildlife Resources
Seventeen
of
eighteen
major
non-oceanic
wildlife
habitat types identified for the Hebo Planning Unit and the
Hebo Ranger District can be found within the study area.
Most of the 230 species of birds, 56 species of terrestial
mammals, 12 species of amphibians, and 12 species of snakes
known
to
inhabit the Hebo Planning Unit and Hebo Ranger
District can be located within the Uppe'r Middle Drift Creek
Watershed
(Hebo
FEIS,
1978
pp.
214-25).
All
non-avian
wildlife species presently classified as game animals
or
furbearers and many of 140 bird species currently classified
as game animals are found within the study area.
The study
area includes a known bald eagle nesting site and contains
one of only two known spotted owl nesting sites for the
57
151,200-acre Hebo Ranger District and the 1130,000-acre Hebo
Planning Unit.8
Recreation
The
moderate
other
upper
use
middle
by
portion
hikers,
recreationists.
of
campers,
The
Creek
Drift
hunters,
study
receives
fisherman and
area
is
readily
accessible via a combination of gravel and dirt roads from
State Highways 101, 229, and 18.
people
reside
within
FEIS, 1978, p.5).
100
Approximately 1.7 million
miles of
study
the
srea
(Hebo
The closest coastal population center is
Lincoln City; the nearest major inland population center is
Salem.
Minor Forest products
A variety of minor forest products are provided or can
readily
obtained
be
produceable minor
firewood
floral use;
the
study
forest products
(hardwood
blackberries,
from
sword
and
fern
include:
softwood),
and
area.
Produced
posts,
poles,
huckleberries
evergreen
moss for horticultural use;
or
and
huckleberry
for
cascara bark
for
pharmaceutical use; cones for reforestation; seedlings for
landscaping; and range acreage for livestock grazing.
8Bald
eagles are one of four bird species nationally
recognized as endangered or threatened. Spotted owls are
presently identified as a threatened.
Spotted owls are
presently identified as a threatened species by the Oregon
Fish and Wildlife Department and as an endangered species
by Oregon State University
58
The description of the
study area presented
in
this
chapter has considered all the renewable surface resources
and resource products of the Drift Creek Watershed.
For
the purposes of analysis only seven study area multiple use
resources are considered for evaluation.
The determination
of joint production relationships for timber,
cattle
grazing
following chapter.
and
salmonids
are
deer,
considered
in
elk,
the
59
IV.
EMPIRICAL ESTIMATION OF MULTIPLE USE
JOINT PRODUCTION RELATIONSHIPS
FOR STUDY AREA RESOURES
Introduction
management
of
principles.
form
of problems
number
A
forest
a
management
one
accordance
in
considers
the
multiple
use
with
Timber, as the predominant forest vegetational
principal
and
when
arise
market
typically
product,
considerations.
Other
dominates
multiple
forest
use
resources--water, range, outdoor recreation, fisheries and
wildlife--are generally considered only as they relate to
timber.
Historically,
central
the
purpose
of
forest
management has been to organize a forest for the continued
production of timber.
periodic
outputs
activities.
The production of timber occurs in
and
responds
Non-timber multiple
water, outdoor recreation,
provide
annual
quicker
to
flows
of
consideration
of
however,
regarding
of
use
the
forest
outputs
and
resources,
such
as
non-timber
multiple
does
relatively
use
not
responses
preclude
resources.
considerable
that
interrelated
respond
The prevailing timber
management
indicate
management
to
range, wildlife and fisheries,
management activities.
orientation
does,
slowly
It
information
to
management
activities of non-timber forest renewable surface resources
is
needed.
assess
the
This
short
information
and
is
long-term
necessary
impacts
to
of
accurately
alternative
60
allocations of multiple use resources and to realistically
extend
multiple
use
resource
allocation
alternativies
beyond timber management alternatives.
A conceptual framework for dealing with these problems
was presented in Chapter I and reviewed in Chapter II. The
objective
of
present
the
chapter
determine
to
is
the
multiple use
joint production relationships for the major
study
resources
area
Chapter
I.
identified
Considerations
and
for
consideration
problems
associated
in
with
resource and joint production relationship measurement are
discussed.
Multiple
expressed
as
resource
identified
for
timber,
use
joint
production
production
deer,
elk,
relationships
coefficients
cattle
are
grazing
and
salmorijds.
External Ecological Effects of
Timber Management Activities
A forest is a dynamic ecosystem composed of a plethora
of plant and animal species interacting
with one another
and their abiotic (physical and chemical)
environment. The
interrelationships among the biotic and abiotic components
of a forest ecosystem are complicated in nature, virtually
countless in number, and change diurnally,
over
time.
The
seasonally, and
complex and dynamic nature of
a
forest
ecosystem presents significant problems in quantifying the
production and
interrelationships of forest multiple
use
resources. A change in the forest ecosystem to benefit one
61
resource brings about concomitant changes that affect other
surface resources.
Of all
the factors that influence the
interrelationships of forest resources,
activities
become
have
most
the
forest management
significant.
Forest
silvicultural and harvesting activities not only determine
timber
yield
but
also
Worley and Patric,
1972;
Sassaman,
and
populations
(Black,
Skovljn
Keniston,
1980;
recreational
Forest
management
Alternative" for
at
increase
the
water
and
197Z;
Harris,
1970;
wildlife
and
and
1967),
Gibbons and
opportunities,
activities
Salo,
Young,
fishery
1973;
Lyons,
aesthetic appeal,
applied
etc.
"Preferred
the
in
the Hebo planning unit are reported
increase stand volume production by
per acre
yield
1971) forage yields (Gibbons and Salo,
Hendricks,
(1)
water
1969; Brown, 1961; Rich and Thompson, 197k;
quality (Black,
1973;
influence
95
age
(Hebo Draft FEIS,
population
of
46
to:
51,000 board feet
1977 p.
wildlife
21),
species
(2)
(An
intensive elk management enhancement program is expected to
increase Hebo resident elk herd populations by 550 percent.
(Hebo FEIS,
species
domestic
1978, p.
(Hebo
FEIS,
forage
)) and adversely affect 98 wildlife
1978
p.
59,
169-171);
production potential
percent (Hebo FEIS,
1978 p. 57),
by
less
(3)
than
reduce
four
and () decrease resident
trout and anadromous fisheries by five to ten percent (Hebo
FEIS,
1978 p. 59).
The
upon
impacts
resource
which
forest
production
and
management
activites
interrrelationships
have
depend
62
upon pre-existing conditions and the timing, the activities
employed, the resources considered, and the time period of
concern.
As a forest proceeds through various successional
stages the interrelationships among forest resources will
also change.
The significance of the changedepends on the
perspective taken.
for example, the unit of analysis
If,
is a so-called "normal" forest with equal acreage in each
age
class
of
the
rotation,
harvesting,
while
very
disruptive to the multiple use interrelationships withing a
a particular forest stand, is in fact necessary to maintain
the
general
multiple
use
nature
of
the
larger
forest
system.
Considerations and problems encountered in quantifying
the
impacts
o'
productivitjes of
forest
the
management
activities
on
the
timber and non-timber multiple use
resources of the study area are discussed below.
Timber
Of all forest multiple use resources, timber has been
the most extensively and intensively researched resource in
terms of productivity, potential productivity and response
to
management activities.
The practice of forestry has
traditionally been based, to a large degree, on predictions
of forest growth and yield.
provides
the
basis
for
Growth and yield information
determining
rotation
periods,
establishing short-run harvest volumes and projecting longrun harvest levels.
63
Numerous
tables
yield
(and
been
have
formulas)
developed for estimating the amount of wood to be found on
an acre.
"Normal yield tables" represent the generalized
productivity
forested
of
land.
extensively
"Empirical
unmanaged,
yield
stocked
fully
(regular
tables"
and
managed) describe the observed average productivity of a
forest's actual growing stock (extensively or intensively
managed). "Managed yield tables" illustrate the generalized
productivity of intensively managed timber stands. "Revised
tables"
yield
predict
the
productivity
generalized
stands based on the observed average stand diameter.
of
Table
14.1 presents the empirical yield tables for extensively and
intensively managed Douglas fir stands of the Hebo Ranger
District used in the analysis.
Extensively managed volume
values identify the timber volumes associated with current
area management intensification prescriptions.
managed
volume
associated
defined
by
discussion
with
values
marigement
Beuter
of
identify
Beuter
et
timber
the
intensification
al.
et
(1976).
al.
Target
Intensively
A
A
volumes
prescriptions
comprehensive
and
Target
B
management intensification levels is contained in Appendix
A.
Non-Timber Multiple Use Resources
Historically, the productivity, potential productivity
and
management
response
of
non-timber
multiple
use
resources have received little qualitative and quantitative
TABLE
11.1
EMPIRICAL YIELD TABLE
HERO RANGER DISTRICT
(Cu. ft. Per core)
TIMBER
AGE CLASS
-1201-tioF
(-10)-0
0-10
10-20
20-30
30-I0
l0-50
50-60
60-70
10-80
80-90
90-100
100-110
110-120
120-130
1301110
1110-150
150-160
160-170
170-180
180-190
190-200
200-210
210-220
220-230
CURRENT MANAGEMENT
INTENSIFICATION
PUESCIPTIONS
BEUTER ET AL. TARGET A
MANAGEMENT INTENSIFICATION
PIIESCIPTIONS
0
0
0
0
100
1000
100
1002
3333
33115
'1676
6188
80311
9715
11558
131110
151111
16775
181166
20328
22008
23706
211387
26028
26028
26028
26028
26028
26028
26028
'1680
7359
BEUTER ET AL. TARGET B
MANAGEMENT INTENSIFICATION
PRESCIPTIONS
0
0
107
1002
3528
l937
7612
90115
91111
10553
110211
1211011
1111116
1611110
181166
206119
22680
2'$528
25228
26028
26028
26028
26028
26028
26028
26028
26028
12976
15078
11112
191165
21128
23811
25819
26695
27533
21533
27533
27533
21533
21533
27533
27533
65
consideration.
resources
demands
were
and
the
In
past,
generally
exhibited
the
supplies
sufficient
satisfy
to
significant
no
non-timber
of
market
consumer
valuations.
There existed little incentive for research regarding the
productivity,
potential
productivity
response
and
to
management activities of non-timber forest land resources.
The non-timber resource productivity studies that have been
conducted
are
generally
site-specific
focusing
the
on
short-term effects of a specific management activity upon a
particular
non-timber
resource
(i.e.
harvest
upon forage production or water production) or,
case of various wildlife and fishery species,
ecological requirements and
information
potential
activities
on
the
short
productivity,
of
species behavior.9
and
non-timber
long-run
and
response
multiple
quantitatively and qualitatively
USDA Forest Service,
1979).
use
treatments
as in the
focused on
Overall,
productivity,
to
management
resources
deficient (Davis,
is
1976;
Data on the output interactions
and joint production levels of multi-resource production on
the same acre is practically non-existent (Davis,
1976).
The absence of commonly accepted units for measuring
the productivity of non-timber resources precludes an early
resolution
of
data
deficiency
problems.
Before
9For a comprehensive review of research studies considering
the impacts of forest managmen'c activites upon deer, elk
and fishery resources, the reader is directed to Appendix
B.
66
quantitative
and
qualitative
research
on
short
the
and
long-term productivity, potential productivity and response
to management activities can be initiated, resource metrics
which have been correctly specified must receive general
acceptance.
The measurement of three major multiple use resources,
watershed, outdoor recreation, and wildlife and fisheries,
illustrates
timber
the unresolved problems associated with non-
multiple
resource
use
productivity
metrics.
Watershed productivity is typically measured in acre feet,
gallons,
cubic
cubic meters per second,
feet,
minute
or
hour; a correct specification of a water measurement unit
should
include
water
quality
considerations.
timing
and
Outdoor recreation is commonly measured in terms of user or
visitor days,
extremely
"an
imprecise,
measure
gross
of'
recreation service abstracting from the known interaction
between volume
of use
and
the
quality of the recreation
experience
"(Teeguarden,
specified,
the quantification of recreational experiences
must
1977,
incorporate measurement
aspects.
Wildlife
and
p.
111).
of both
fishery
To
volume
resources
properly
be
and
are
quality
generally
measured in terms of species numbers per acre, pounds per
acre, or recreational use days.
of
wildlife
measurement
and
in
fishery
terms
The correct specification
resource
of
both
recreational activity potential.
productivity
physical
requires
numbers
and
67'
The ultimate productivity of non-timber multiple use
resources
not
is
only
influenced
by
timber
management
activities but is affected by other non-timber multiple use
resource production
levels
management
and
programs.
For
example, the intensity of the recreational utilization of
an area influences grazing activities and the density and
distribution
of
deer,
emphasis
elk
herd
on
elk
Managerial
fisheries.
and
enhancement
can
affect
domestic
grazing and deer herd levels and management activities. The
development
of
influences
resident
a
watershed's
hydroelectric
trout
and
potential
anadromous
fishery
populations.
Competition and the possibility of competition between
domestic livestock grazing and deer, elk and fisheries has
been
recognized
and
a
matter
of
concern
to
wildlife,
fisheries and range managers and scientists for many years
(Duff,
1977;
Everest and Meehan,
1981;
Hansen and Clark,
1977,
Mackie,
Smith
(1977) reported that livestock grazing is the single
1978;
Skovlin, Edgerton and Harris,
1968).
most important factor limiting wildlife production in the
West. Behnke and Zarn
(1976) identified livestock grazing
as the greatest threat to the integrity of fishery habitat
in
the western U.S..
(1977) reported that the
Galliziolj
single most important range management problem limiting the
attainment
of
potential
fis-h
and
Arizona is livestock overgrazing.
wildlife
Saltzman
benefits
(1976)
in
charged
68
that
overgrazing
one
is
of
most
the
serious
least
and
understood ecological problems in the western states.
Livestock grazing can reduce forage and
for deer and elk (Hansen and Clark,
cover values
1977; Julander,
1958;
Skovlin et al.
1968), interfere with deer and elk habitat
usage (Mackie,
1978; Skovlin, et al.
elk
interrelationships
predator
and
vegetational
prey
1976,
(Mackie,
relationships
patterns
1968), alter deer and
1978),
1978),
(Mackie,
1977),
(Gallizioli,
influence
alter
encourage
and
disease and parasite transmission from domestic animals to
wild
ungulates
livestock
(Mackie,
grazing
upon
1978).
deer
The
and
actual
elk
influence
population
is
function of existing forage and habitat conditions,
and
elk
densities
and
distribution,
duration and
the
wildlife,
grazing,
distributions,
the
timing of livestock
and
timber
of
a
deer
rate,
stocking,
management
practices
employed and the time period under consideration (Mackie,
1978; Skovljn et al. 1968).
Forest streams
are
typically
the
primary
source
of
livestock water and streamsjdes are important feeding and
resting areas (Platts,
1978,
The
livestock
concentration
results
of
excessive
in
1979,
usage
1980; Saltzman,
along
of
1976).
streamsides
riparian
often
zones
and
significant reductions in fishery populations (Everest and
Meehan,
1981; Gunderson, 1968;
Livestock
vegetation,
grazing
increase
can
Lorz,
reduce
stream
or
1974; Marcuson, 1977).
eliminate streamside
temperatures,
alter
channel
69
morphology and increase stream sedimentation (Armour, 1977;
Behnke and
1979).
Zarn,
1976;
Meehan and
Platts,
Platts,
1978;
The actual impact of livestock grazing upon fishery
populations depends upon the existing stream and riparian
conditions,
livestock
the
intensity and
fishery and
species
grazed,
timing,
the
duration of livestock grazing,
range,
the
timber management practices employed and
the
time period under consideration.
Multiple Use Joint Production Relationships
The influences of forest management programs upon non-
timber multiple use resources and the influences of nontimber resource production levels and management activities
upon
other
non-timber
multiple
independent occurrences.
use
resources
are
not
Moreover, non-timber multiple use
production levels and management programs are not without
important
possible
management
activities.
influences
The
timber
upon
possible
yields
influence
of
and
non-
timber resource levels and management programs upon timber
yields and management activities ranges from insignificant
or minor to highly significant or completely antagonistic.
Light
deer,
seedlings
and
elk,
the
or
cattle
retention
browsing
of
narrow
of
Douglas-fir
buffer
strips
composed primarily of non-merchantable tree species have at
most only minor affects upon timber yields and management
activities.
retention
Heavy
of
wide
deer,
buffer
elk,
strips
cattle
or
comprised
browsing,
primarily
the
of
70
merchantable timber species and the designation of an area
as a protected bald eagle or spotted owl habitat can have
profound
impacts
activities.
upon
timber
yields
The designation of an area
wilderness
precludes
timber
management
and
as recreational
productivity
and
management
activities altogether (Black, 1969, 1974; Berg,
1970; Hebo,
FEIS, 1978; McGreer, 1975; Ponce and Brown,
Ideally,
the
economic
allocation
1973).
of
multiple
use
resources should be based on resource joint production
relationships which concurrently specify over time the
impacts of forest management activities upon timber and
non-timber multiple use resources, the impacts of nontimber
multiple
use
resourbes
levels
management
and
programs upon other non-timber multiple use resources and
the reciprocal impacts of non-timber multiple use resource
production
levels
productivity.
and
management
programs
upon
timber
Multiple use joint production relationships
of the form:
(x1, x2,
=
where i
=
.
k :1,2,..
.
.
.,
x;
m;
k
multiple use resource products ,(i
=
t
=
inputs,
=
1, 2,
1, 2,.., m)
.. .n)
rotation time period or age class, (t
1,
2,
.
.
.,
r)
when combined with economic production information could be
utilized to identify optimal multiple use resource output
levels. Unfortunately the current absence of sufficient
71
quantitative and qualitative data regarding the complex and
dynamic relationships between and among multiple use
resources precludes the specification of accurate and
reliable multiple use joint production
economic
An
resource
allocation
with an absence of data necessary
reliable multiple use
four
analytical
options:
resource
analyst
confronted
empirically derive
to
joint production relationships has
wait
(1)
qualitative and quantitative data
reliable
relationships.
to specify
is available
production
joint
sufficient
until
relationships;
(2)
derive resource joint production relationships or relative
output levels
information
multiple
output
through
(Ripley
levels
professional
Buffington,
and
joint
use
production
through
opinions
use
relative
levels
information and
expert
the
the
short
multiple
run,
use
synthesis
a
develop
(3)
relative
or
subjective
of
()
or
1972);
published
construct
joint production relationships
of
(Teeguarden,
should
production
basis
the
on
judgment
test
joint
197k);
relationships
(Dalkey,
synthetic multiple
product
of existing
synthesis
a
riot
relationships
output levels describe everything
available
1977).
whether
be
in the
or
or
For
derived
relative
real world,
but
instead whether for the minimum degree of aggregation they
are
plausible
and
consistent
information (Teeguarden, 1977 p.
with
general
empiric
O1).
The approach adopted in this analysis was to develop
joint
production
multiple
use
resource
relationships
72
representative
of
physical
the
ecological
and
characteristics of the study area from existing published
information.
livestock
related
Research has shown that big game populations,
forage
to
and
anadromous
of years
number
the
fisheries
that have
directly
are
elapsed
since
logging and to the programs of forest management employed.
For example,
Black
Brown
19714),
(1969,
and Hines
(1961)
(1973) have observed that the deer carrying capacity of an
area increases dramatically after logging.
From
pre-
a
logging annual average carrying capacity of 20-30 deer per
square
mile,
the
increases to
carrying
capacity
of
area
an
100-160 animals per square mile 10-30 years
after logging.
decline
deer
Area
deer carrying
pre-logging
to
harvesting.
levels
potentials gradually
100-110
years
after
If thinning is performed, area deer carrying
capacities are observed to increase by seven to ten percent
(Brown,
1961;
Hines,
non-timber
The
1973).
resource
production coefficients used in the analysis are developed
in Appendix C.
Tables 14.2,
14.3,
I.14
and
14.5 present the study area
joint production output coefficients for deer,
grazing
and
intensities
salmonids
of
associated
cattle grazing
management intensification.
and
the
Tables 14.6,
with
elk cattle
alternative
current
14.7,
14.8
level
and
of
'1.9
present the study area joint production output coefficients
for deer, elk, and cattle grazing and salmonids associated
with
alternative
intensities
of
cattle
grazing
and
the
TABLE 11.2
DEER PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(CURRENT LEVEL OF MANAGEMENT INTENSIFICATION)
TIMBER
AGE CLASS
-(2o)-(lo)
(-1O)-.O
0-10
10-20
20-30
30_lb
40-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
13011b0
1I0-150
150-160
160-170
170-180
180-190
190-200
200-210
210-220
220-230
NO CATTLE
GRAZING
DEER GRAZING POTENTIAL
.0156
.0156
.0*69
.1172
.1172
.0183
.0183
.0547
LIGHT GRAZING POTENTIAL
MODERATE CATTLE GRAZING
DEER GRAZING POTENTIAL
DEER GRAZING
.05117
.0156
.0156
.0469
.1172
.1172
.0183
.0183
.0547
.0547
.01147
.01147
.04117
.0*47
.0313
.0234
.0234
.023*
.0234
.0234
.0234
.0234
.023*
.0234
.0234
.0234
.0313
.0234
.02311
.0234
.02311
.023*
.0234
.0234
.0234
.0234
.02311
.0234
.023*
.0234
POTENTIAL
HEAVY CATTLE GRAZING
DEER GRAZING POTENTIAL
.0156
.0156
.0469
.1172
.1172
.0183
.0103
.0547
.0547
.0447
.0156
.0156
.04117
.011*7
.0313
.023*
.023*
.0234
.0234
.0313
.0234
.02311
.02311
.0234
.0234
.02311
.023*
.023*
.0234
.02311
.02311
.0234
.02311
.0234
.0234
.023*
.0234
.02311
.01169
.1172
.1172
.0183
.0183
.05117
.05117
.011*7
.02311
.0234
.02311
.02311
.0234
.0234
TABLE
.3
STUD! AREA
ELK PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(cURRENT LEVEL OF MANAGEMENT INTENSIFICATION)
TIMBER
AGE CLASS
-(20)-(1O)
-10-0
0-10
NO CATTLE GRAZING
LIGHT GRAZING POTENTIAL
ELK GRAZING POTENTIAL
ELK GRAZING POTENTIAL
200-210
.0100
.0100
.0030
.0310
.0230
.0230
.0195
.0195
.0175
.0175
.0130
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
2 10-220
.0 100
220-230
.0100
.0070
.0070
.0021
.0022
.0161
.0161
.0136
.0136
.0122
.0122
.0091
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
10-20
20-30
30110
lO-50
50-60
60-70
70-80
80-90
90-100
100-1 10
110-120
120-130
1301110
1$0-150
150-160
160-170
170-180
180-190
190-200
MODERATE CATTLE GRAZING
HEAVY CATTLE GRAZING
ELK GRAZING
ELK GRAZING POTENTIAL
POTENTIAL
.0050
.0050
.0015
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0015
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
TABLE 11.11
CATTLE PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE CRAZING INTENSITIES
(CURRENT LEVEL OF HANACEHENT INTENSIFICATION)
TIMBER
AGE CLASS
NO CATTLE GRAZING
CATTLE GRAZING POTENTIAL
-(20)-(1o)
0
0
0
-(1O)-O
0-10
10-20
20-30
0
0
0
0
0
30110
110.50
50-60
60-70
70-80
80-90
90-100
0
0
0
0
100-1 10
110-120
120-130
130-1'IO
1IIO-150
150-160
160-170
170-180
180-190
190-200
200-2 10
210-220
220-230
0
-
0
0
0
0
0
0
0
0
0
0
0
0
LIGHT CRAZING POTENTIAL
MODERATE CATTLE GRAZING
CATTLE GRAZING POTENTIAL
.02311
.02311
.02311
.02311
CATTLE GRAZING
.01168
.01168
.01160
.01168
.001111
.001111
.0087
.0087
.0022
.0022
.0022
.0022
.0030
.0030
.0030
.0030
.0030
.0030
.0030
.0030.
.0030
.0030
.0030
.0030
.0030
.0030
.0030
.00115
.00115
.00115
.00115
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
POTENTIAL.
HEAVY CATTLE GRAZING
CATTLE GRAZING POTENTIAL
.0730
.0730
.0730
.0730
.0130
.0130
.0068
.0068
.0068
.0068
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
TABLE I$.5
SALIIONID PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(CURRENT LEVEL OF MANAGEMENT INTENSIFICATION)
TIMBER
CLASS
-(20)-tm)
(-1O)-O
0-10
10-20
20-30
30J10
110-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130-140
1110-150
150-160
160-170
170-180
180-190
190-200
200-210
210-220
220-230
NO CATTLE GRAZING
SALMONID
ESCAPEMENT
POTENTIAL
.1300
.1300
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
LIGHT CATTLE GRAZING
MODERATE CATTLE GRAZING
HEAVY CATTLE GRAZING
SALIIOtIID
ESCAPEMENT
POTENTIAL
SALMONID
POTENTIAL
ESCAPEMENT
SALMONID
ESCAPEMENT
POTENTIAL
.1300
.1300
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1170
.1170
.0960
.1170
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.1380
.10110
.10110
.0860
.10110
.1122
.1122
.1122
.0860
.10110
.1122
.1122
.1122
.1122
.1122
.1122
.1122
.0860
.1040
.1122
.1122
.1122
.1122
.1122
.1122
.1122
TABLE '1.6
STUDY AREA
DEER PRODUCTION COEFFICIENTS PER ACRE
AT VARYING CATTLE GRAZING INTENSITIES
(BEIJTER KY AL. TARGET A OR BEUTEII KY AL. TARGET B)
(LEVEl. OF MANAGEMENT INTENSIFICATION)
TINBER
NO CATTLE GRAZING
LIGHT CATTLE GRAZING
AGE CLASS
DEER GRAZING POTENTIAL
DEER GRAZING POTENTIAL
-(20)-tm)
(-10)-b
0-10
10-20
20-30
30110
110-50
.0156
.0156
.0156
.0156
.01169
.1253
.1253
.0886
.0886
MODERATE CATTLE GRAZING
DEER GRAZING
POTENTIAL
HEAVY CATTLE GRAZING
DEER GRAZING
.0156
.0156
.0156
.0156
.01169
.01169
.01169
.1253
.1253
.0886
.0886
.063I
.1253
.1253
.0886
.0886
.1253
.1253
.0886
.0886
.06311
.063's
.063's
.06311
.011117
.011117
.011117
.011117
.011117
.011117
.011117
.011117
.0313
.0313
.0313
.02311
.02311
.02311
.0313
.023I
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.023's
.02311
.0234
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.02311
.0234
.02311
.02311
.02311
.023I1
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
1301110
1l0-15O
150-160
160-17o
110-180
180-190
190-200
200-210
.06311
.06311
.02311
.02311
.02311
.02311
.02311
.0234
.02311
2 10-220
.0234
.02311
.02311
220-230
.02311
.02311
.02311
.0234
.0234
.06311
.02311
.02311
.02311
POTENTIAL
TABLE 4.7
STUDT AREA
ELK PRODUCTION COEFFICIENTS PER ACRE
AT VAluING CATTLE GRAZING INTENSITIES
(BEUTER ET AL TARGET A Oh BEUTER ET AL. TARGET B)
(LEVEL 0? I4ANAGEIIENT INTENSIFICATION)
TIKUER
AGE CLASS
-(2o)-(1O)
(-10)-0
0-10
10-20
20-30
30-40
110_50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
130_lab
1bb0150
150-160
160-170
170-180
180-190
190-200
200-210
210-220
220-230
NO CATTLE GRAZING
ELK GRAZING
.0100
.0100
.0030
.0310
.0230
.0230
.0195
.0195
.0175
.0175
.0130
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
POTENTIAL
LIGHT CATTLE GRAZING
EK GRAZING
.0070
.0070
.0021
.0022
.0161
.0161
.0136
.0136
.0122
.0122
.0091
.0010
.0010
.0070
.0070
.0070
.0070
.0010
.0070
.0070
.0010
.0070
.0010
.0010
.0010
POTENTIAL
HODERATE CATTLE GRAZING
ELK GRAZING
.0050
.0050
.0015
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
POTENTIAL
IIEAVV CATTLE GRAZING
ELK GRAZING
.0050
.0050
.0015
.0016
.0120
.0120
.0099
.0099
.0088
.0080
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
POTENTIAL
TABLE 11.8
STUD! AREA
CATTLE GRAZING PRODUCTION COEFFICIENTS PER ACRE
AT VAI1T1NO CATTLE GRAZING INTENSITIES
(NEUTER ET AL. TARGET A OR NEUTER ET AL. TARGET a)
(LEVEL OF MANAGEMENT INTENSIFICATION)
TIMBER
AGE CLASS
-(2o)-(lo)
(-10)-u
0-10
NO CATTLE GRAZING
CATTLE GRAZING POTENTIAL
0
0
0
LIGHT CATTLE GRAZING
CATTLE GRAZING
.01168
.02311
.01168
.01168
0
30-110
0
.00118
110-50
0
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
0
0
0
0
0
0
0
0
0
.0025
.0025
.0025
.0025
.0025
0
0
CATTLE GRAZING POTENTIAL
.02311
.02311
.00118
150-160
160-170
110-180
180-190
190-200
200-210
210-220
220-230
CATTLE GRAZING POTENTIAL
.01168
0
0
HEAVY CATTLE GRAZING
.02311
10-20
20-30
130-1110
1'10-150
POTENTIAL
MODERATE CATTLE GRAZING
.00110
.00110
.00110
.00110
.00110
.00110
.00II0
.00110
0
0
0
0
0
.00110
0
.00110
.00110
.00110
.00110
.00110
.0097
.0097
.0050
.0050
.0050
.0050
.0050
.0080
.0080
.0080
.0080
.0060
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0730
.0730
.0730
.0730
.Ol'i6
.01116
.0075
.0075
.0075
.0075
.0075
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
TABLE 11.9
SAL}IONID PRODUCTION POTENTIALS PER ACRE
AT VARYING CATTLE GRAZING INTENSiTIES
(iiEuTcn ET AL. TARGET A OR BEUTER El AL. TARGET 0)
(LEVEL OF MANAGEMENT INTENSIFICATION)
TIMBER
NO CATTLE GRAZING
SALIIONID
AGE CLASS
-(20)-(1o)
(-lo)-O
0-10
10-20
20-30
30-40
110-50
50-60
60-70
70-80
80-90
90-100
100-110
110-120
120-130
1301110
1110-150
150-160
160-170
170-180
180-190
190-200
200-210
210-220
220-230
ESCAPEMENT
POTENTIAL
.IOO
.1300
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1Q70
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
LIGHT CATTLE GRAZING
SALHONID
ESCAPEMENT
POTENTIAL
MODERATE CATTLE GRAZING
$ALNONID
ESCAPEMENT
POTENTIAL
.1300
.1300
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1170
.1170
.0960
.1170
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.1380
.0960
.1170
.1380
.1360
.1380
.1380
.1380
.1380
.1380
HEAVY CATTLE GRAZING
SALMONID
ESCAPEMENT
POTENTIAL
.10110
.10110
.0860
.10110
.1122
.1122
.1122
.0860
.10110
.1122
.1122
.1122
.1122
.1122
.1122
.1122
.0860
.1OIIO
.1122
.1122
.1122
.1122
.1122
.1122
.1122
81
Beuter et al. Target A or the Beuter et al. Target B level
of
management
intensification.
Appendix
(See
A
for
discussion of these levels.)
The resource joint production coefficients reported in
Tables
acre
identify the expected resource levels per
study area
of
alternative
acreage
levels
of
for
any given age
management
class
intensification.
at
For
example, for each 100 acres of the study area in the 60-70
year timber age class, Tables !I..2IL5 indicate that at the
current
of management
level
potential
(resource
intensification
production
adversely impact timber or
level
the
which
grazing
does
for deer
forage resources)
not
is
5.L7 animals at all levels of cattle grazing intensities.
The grazing- potential for elk
is
1.75 animals at the no
level of cattle grazing intensity. The grazing potential
for cattLe
grazing
fish
is 0.22 animals at the
intensity.
available
fish
11.70
intensity
at
and
for
escapement potential
The
spawning
moderate
the
10.10
light level of cattle
fish
at
purposes)
level
the
for
of
heavy
(number
of
salmonids
is
cattle
level
of
grazing
cattle
grazing intensity.
For each 100 acres of the study area in the 60-70 year
timber
age
class,
Tables
14.6LI.g
indicate
that
at
the
Beuter et al. Target and Beuter et al. Target B levels of
management intensification the grazing potential for deer
is
animals
intensities.
at
all
levels
The grazing potential for
of
cattle
elk is
grazing
1.75 animals
82
at the
level of cattle grazing
riO
intensity.
The
grazing
potential for cattle is 2.5 animals at the light level of
cattle
grazing
salmonids
grazing
is
intensity.
11.70
intensity
fish
and
The
at
10.kO
escapement
potential
for
moderate level of cattle
the
fish
at
the
heavy
level
of
cattle grazing intensity.
The joint production relationships estimated in this
chapter
identify
production
levels
the
of
expected
deer,
elk,
study
area
cattle
resource
grazing
and
salmonids per acre for any given age class at alternative
forest management and cattle grazing intensification.
next - chapter
considers
the
allocations
of
study
The
area
resources for seven strategies of mutltiple use management.
83
V.
ALLOCATION OF MULTIPLE USE RESOURCES
CF THE UPPER MIDDLE DRIFT CREEK WATERSHED:
A Case Study
Introduc t ion
In the development of the analytical framework, it was
intended
that
should
it
management area or region.
the analytical
approach
applicable
be
is
As
a
any
to
forest
test of operationality,
applied
the allocation
to
seven multiple use resources of the upper middle portion of
the Drift Creek Watershed.
chapter is
resource
The objective of the present
to determine and evaluate
allocations
of
deer,
the joint production
elk,
cattle
grazing,
salmonids, timber, bald eagle and spotted owl pairs for the
study area.
The chapter is presented in six parts.
The
first section describes the forest management model used in
the analysis.
The second portion discusses the analysis
methodology and the seven strategies of study area multiple
use manaement considered.
multiple
use
resources
and
management.
valuation
allocations.
income
output
levels
strategies
The
of
fourth
the
The
impacts
allocatjo.s.
The
third
estimated
of
section
alternative
alternative
for
multiple
study
the
study
reviews
the
use
discusses
fifth part reviews
of
part,
the
area
the
selected
resource
economic
resource
employment and
area
resource
The sixth and final portion of the chapter
84
summarizes the physical and economic impacts of alternative
allocations of the considered resources of the Upper Middle
Drift Creek Watershed.
Forest Manaement Models
Numerous quantitative models have been developed and
employed to estimate future harvest volumes and the ensuing
effects on forest inventories of forested areas or regions
(ARVOL
1971),
(Chappelle,
MUSYC
MAXMILLION
1966),
1980),
(Johnson and Jones,
SIMAC
1971,
(Navon,
Tedder, et al.,
1975),
1980)).
TREES
(Beuter,
et
land
considered
resources
even
in
the
Timber
al.,
1976;
The effects of alternative forest
management strategies and harvest policies
forest
(Sussaman,
1966),
I-bit and Bergsvick, 1972), SORAC (Chappeile,
RAM
Cutler,
and
(Ware
are
on non-timber
estimated
not
or
comprehensive
most
directly
quantitative
formulation.
In contrast to previous analyses, this study attempts
to
simultaneously
effects
of
harvest
polices
multiple
use
estimate
alternative
on
an
resources.
physical
the
forest
array
management
of
and
programs
National
Non-timber
economic
resource
Forest
and
land
production
parameters are combined with timber inventory and harvest
volume
data
to
project
the
joint
alternative management activities,
production
impacts
of
management intensities
and harvest policies on the timber, cattle grazing, deer,
85
elk,
and
salmonid
fishery resources of
the upper middle
portion of the Drift Creek Watershed.
TREES:
A Brief Description
Of the
numerous forest management inode.s capable of
producing timber inventory and harvest data, TREES (Timber
Resource
Economic
Estimation
research utilization because
and
general
System)
of its
comprehensiveness.
was
selected
for
relative flexibility
Developed
by
Norman
K.
Johnson, H. Lynn Scheurman, and John H. Beuter to provide a
means of answering questions about future timber harvests
in Oregon and resulting
impacts
(Beuter,
al.,
et
1976),
TREES can respond to a diverse array of management problems
at
reasonable cost
a
from
the
national
local-woodlot
to
level (Tedder, et al., 1980).
Within
the
TREES
framework,
managed as either even-aged
forest
stands
may
or uneven-aged units.
be
Stand
growth and yield information is user specified and a user
can select from three options to calculate periodic volume
yields
for
additional
after
unthinned
options
thinning.
to
even-aged
stands
calculate
even-aged
Uneven-aged
periodic
from
and
stand
three
growth
volume yields
are
determined from a diameter growth algorithm.
Users can select from three harvest priority schedules
and from seven basic harvesting
fixed
(absolute
amount,
percent
scheduling methods: three
of
inventory,
and
area
control) and four variable (even-flow of volume, even-flow
86
of a function of volume, present net benefit, and present
net worth).
During a simulation, a fixed scheduling method
switched
to
variable
a
scheduling
method.
may be
Individual
stands may be kept separate to demonstrate growth and yield
changes resulting from specific management strategies and
harvest policies.
inventory
Acres may be shifted into and out of the
(land-base
changes)
from
and
management
one
intensity level to another to simulate urban encroachment,
wildlife
fisheries
and
construction,
standards
or
may
other
habitat
activities.
changed
be
management,
over
Volume
time
road
utilization
to
reflect
of
two
altered
technological and economic conditions.
TREES
A
activities.
simulation
run consists
The first,
the processing and storage of
is
inventory and control data.
of processed
perform
data
and
harvest
TREES run include:
The second, is the utilization
harvest
scheduling
simulation reports.
operational
scheduling
information
calculations
and
to
prepare
The possible reports provided
by
a
An Allowable Cut Table for each period
(of the simulation run length), a Cut-Proportion Table for
each
period,
an
Inventory
Report
each
for
period,
A
Regeneration/Cultural Treatment Report for each period, and
a Total Harvest/Economic Report.
For even-aged stands, TREES provides a full accounting
of management harvest cost and revenues in current dollars
or
in
dollars
discounted
according
to
a
user
specified
87
discount
rate
(harvest
economic
data
currently
not
is
produced for uneven-aged stands).
TREES:
O'rationa1izing data
Users
establish
specifying
wide
a
information.
beginning
variety
timber
inventories
management
of
growth
and
Acres and volumes per acre are entered by
specifying stand management method,
site class,
type,
management
species
Table 5.1
by
type,
presents
age
class
and
land-base
intensity.
the management and growth information
obtained from the Siuslaw National Forest headquarters for
the
study area.
Tables 5.2
and
define
5.3
the
acreage
inventory distributions for the grouped resource units used
in TREES simulation runs.
Information regarding management
intensity assumptions of the TREES model and regeneration
and
cultural
treatment
costs
used
TREES
in
analyses
is
contained in Appendices A and D.
Analysis Methodology and Simulation Runs
Seven timber inventory and harvest volume data bases,
generated by the TREES model,
were combined with multiple
use resource joint production coefficients to project seven
alternative
resources.
allocations
The
of
purpose
study
of
area
selecting
multiple
these
use
seven
simulations runs was to compare results based on different
harvest
policies,
management
intensities
and
forest
TABLE 5.1
UPPER MIDDLE DRIFT CREEk INVENTOR! DATA
Plot No.
Species
Age
Class
Other
Owners
Acres
Marginal
Acres
C
C
OIl
066
10
200
$66
C
I69
C
C
08
08
09
6110
1170
062
C
10
068
C-Plant
C-Plant
03
I7I
Alder
13
lillO
067
Mixed
15
80
11110
1,160
1,120
063
1162
TOTAL
2110
360
2110
80
03
Site
Class
Stocking
Level
Management
Intensity
Volume
Acres
Cu. FL/Acre
1
1
5
1013
567.6
1
2
3
3110
11,120.1
2
2
2
2
2
3
596
1
11
160
5,113.2
8,058.1
1
11
857
11,1168.0
3
3
6110
11,525.7
2
1
3
720
2
2
5
2110
0.0
39.8
2
2
2
260
11,0118.3
2
3
2
787
6,1117.7
TOTAL STUD! ACRES
5,613
7,893
89
TABLE 5.2
ACREAGE INVENTOR! DISTRIBUTIONS
DRIFT
1
11110101 (GRU)
2140 Marg. A.
3140 Beg. A.
(A.C. 10)
(A.C. 10)
200 Other Owner A.
1013 Beg. A.
(A.C. 10)
(A.C. 01$)
2140 Marg. A.
200 Other Owner A.
1353 Beg. A.
11110102
360
80
2140
596
6140
720
2140
787
80
160
857
Marg. A.
(A.C. 09)
Marg. A.
(A.C. 03)
Other Owner A. (A.C. 03)
Beg. A.
(A.C. 08)
Other Owner A. (A.C. 08)
Beg. A.
(A.C. 03)
Beg. A.
(A.C. 03)
Reg. A.
(A.C. 15)
Other Owner A. (A.C. 15)
Beg. A.
(A.C. 08)
Beg. A.
(A.C. 09)
14140 Marg. A.
960 Other Owner A.
14,000 Beg. A.
11110152
41$O Marg. A.
(A.C. 13)
260 Beg. A.
(A.C.
13)
14140 Marg. A.
260 Beg. A.
Total Mar. A.
Total Other Owner A.
Total Beg. A.
1,120
1,160
5,613
Total Study Area Acres 7,893
"Abbrevjations:
GRU
Marg. A
-
Other Owner A
-
Other Objective A Beg. A
-
A.C.
-
Grouped Resource Unit - collection of
Basic Resource Units (OBUs).
Sufficiently siiliar with respect to
manageeent, growth, and yield to be
considered as a single unit.
Marginal acres - acres incapable of
producing 20 cubic feet of tree growth
per acre per year.
Acres not owned by the Forest Service
at the start of the simulation but
identified for acquisition.
Acres devoted to non-tisber production
objective.
Regular acres
acres currently sanaged
for tisber production.
Age Class
90
TABLE 5.3
ACREAGE INVENTOR! DISTRIBUTIONS
DRIFT 2
11110101
240
20
50
290
200
993
(GRU)
Marg. A.
(k.C. 10)
Other Objective A (A.C. 04)
Other Objective A (A.C. 10)
Beg. A.
(A.C. 10)
Other Owner A
(A.C. 10)
(A.C. 04)
Beg. A.
240
70
200
1283
11110102
360
40
556
640
160
657
Marg. A.
Other Objective A.
Other Owner A.
Beg. A.
Marg. A.
(A.C. 09)
Other Objective A.(A.C. 08)
(A.C. 08)
Beg. A.
Other Owner A.
(A.C. 08)
Beg. A.
(A.C. 08)
Beg. A.
(A.C. 09)
360 Marg. A.
40
Other Objective A.
640 Other Owner A.
2213 Beg. A.
111 10122
80
720
240
240
Marg. A.
Beg. A.
Other Owner A.
Beg. A.
(A.C.
(A.C.
(A.C.
(A.C.
03)
03)
03)
03)
80 Marg. A
240 Other Owner A
960 keg. A.
11110126
300 Other Objective A. (A.C. 15)
487 Reg. A.
(A.C. 15)
80 Other Owner A
(A.C. 15)
-
300 Other Objective A.
80 Other Owner A
'487 Beg. A.
11110152
440 Marg. A
260 Beg. A.
(A.C. 13)
(A.C. 13)
440 Marg. A
260 Beg. A.
Total
Total
Total
Total
Mar. A.
Other Objective
Other Owner A.
Beg. A.
1,120
'410
1,160
5,203
Total Study Area Acres 7,893
1Abbreviations:
- Grouped Resource Unit - collection of
Basic Resource Units (GRUs).
sufficiently sisiliar with respect to
management, growth, and yield to be
considered as a single unit.
- Marginal acres - acres incapable of
Marg. A
producing 20 cubic feet of tree growth
per acre per year.
- Acres not owned by the Forest Service
Other Owner A
at the start of the simulation but
identified for acquisition.
Other Objective A - Acres devoted to non-timber production
objective.
- Regular acres - acres currently managed
Beg. A
for timber production.
A.C.
- Age Class
GRU
91
managemeni; programs. The resource production levels of each
simulation
run
reflect
the
adoption
of
particular
a
rotation length, harvest policy, management intensity and
program
of
forest
management.
considered in the analysis
simulation
The
runs
are described in the following
paragraphs.
Runi illustrates the status quo projection (no-action
allocation alternative).
No adjustments are made
producing inventory during
The
even-f1ow
of
volume
100-year rotation period.
the
harvest
schedule area timber harvests.
95
years
and
no
changes
method
is
employed
to
Thinning occurs at 75 and
are
intensification
during
illustrates the
sustained yield
made
planning
the
the
to
in
management
period.
management of
Run
the
1
Upper
Middle Drift Creek Watershed at a low level of management
intensification.
While providing a legislatively required
and useful base-run solution,
study
area
Forest
acreage
Service
Run
expansion
riparian
1
assumptions contradict
plans
and
and
wildlife
violate
habitat
current
management
policies and practices.
Run2 is an adjustment of the status quo projection.
The
study
area
acreage
is
adjusted
existing Forest Service acreage
Forest
Service
prescriptions.
riparian
and
in
expansion
wildlife
Study area acreage
is
accordance
with
plans and current
habitat
enlarged
management
by
1,160
acres, riparian and wildlife habitat is withdrawn at a rate
of five
chains per mile of stream mileage supportive of
92
anadromous fishery species,
older growth acres per bald
14Q
eagle nesting site and 300 older growth acres per pair of
spotted owls (Hebo, FEIS,
Area timber
78, 212).
1978 pp.
harvest are scheduled using the even-flow of volume method.
Regular
acres
are
managed
at
existing
the
level
of
management intensification for the first three periods and
at
the
Beuter
al.
et
study
Target
A
levels
for
the
remaining seven periods of the 10-period planning horizon.
Run
illustrates
.2
management of
timber
and
the
intensified
sustained
yield
the Upper Middle Drift Creek Watershed for
wildlife
and
fisheries
habitat
protection
inventory
projection
purposes.
Run
3
is
disaggregated
a
utilizing the same assumptions as Run 2 with the exception
that
proportional
wildlife
acreage
protection
withdrawals
purposes
for
replaced
are
riparian
and
acreage
with
withdrawals from stand inventories representative of actual
riparian, bald eagle, and spotted owl habitat locations.
Run
aggregated
is
a
projection
Run
3
with
the
which
is
exception
the
same
as
that
less
timber
producing acreage is shifted to other objectives.
Run
an
I
presumes that upwards of 80 percent of riparian and nonspotted
adversely
(Everest,
owl
conifer
impacting
1975,
1978).
habitat
can
wildlife
Runs
and
3
and
be
harvested
fishery
without
resources
were generated
to
demonstrate the locational capabilities of the TREES system
93
and
the
possible
impacts
intensified
of
wildlife
and
fisheries habitat management programs.
Run 5 is a projection which uses the same assumptions
as Run
in
with the exception that regular acres are managed
accordance
with
the
management intensities.
Beuter
et
study
al.
Target
B
Run 5 was generated to illustrate
the study area effects of timber management at a high level
of management intensification.
Run 6 employs the same assumptions as Run 5 with the
exception
that
rotation
the
length
changed
is
from
100
years to 80 years.
Run 7 also utilizes the same assumptions as Run 5 with
the
exception
harvest
that
the
scheduling
is
even
flow
replaced
by
volume
of
the
method
absolute
of
amount
method of harvest scheduling for the first three periods of
the
10-period planning horizon (target harvest levels 25
percent greater the evenflow of volume values of Run
specified for the first three periods).
generated
to
demonstrate
are
Runs 6 and 7 were
effects
the
5
management
of
decisions to shorten forest rotations and to deviate from
sustained-yield harvest policy
for
local area
a
employment
and income considerations (NFMA, 1976 Sec. 219.10).
Tables
5.4-5.10
present the harvest volumes and timber
inventory data bases for Runs
5.13
present
coefficients
the
that
multiple
were
through 7.
1
use
combined
resource
with
Tables
5.11-
production
simulation
timber
inventory data to project study area grazing potentials for
TABLE 5.11
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES
PER PLANNING HORIZON DECADE-PERIOD
RUN 1
1981
1991
2001
2011
2021
2051
2061
2071
2112.2
238.0
2118.5
2115.7
379.8
3011.7
38'I.6
269.7
379.8
3011.7
380.1
1152.0
3211.9
1152.0
3211.9
379.8
3811.6
3011.7
2031
20111
333.2
276.5
3211.9
1152.0
3211.9
AGE CLASS
ACREAGE
3
10110
769.2
1*
1013
10110.0
301.7
898.5
1013.0
10110.0
182.0
380.1
898.5
1013.0
1OlO.O
380.1
898.5
1013.0
10110.0
898.5
380.1
1013.0
10110.0
898.5
1Oi0.0
898.5
1013.0
10110.0
380.1
898.5
1013.0
10110.0
898.5
1013.0
10110.0
5
6
7
8
9
10
756
1217
1220
11
12
13
756.0
1217.0
1220.0
756.0
1217.0
1016.8
700
756.0
1217.0
756.0
806.11
1217.0
330.3
678.0
111
15
16
17
18
19
1013.0
787
11110.0
39.8
756.0
862.0
290.0
11110.0
380.1
1152.0
3211.9
1152.1
3211.9
380.1
963.0
756.0
516.5
290.0
11110.0
612.0
360.0
290.0
11110.0
216.9
360.0
290.0
11110.0
20
21
360.0
290.0
11110.0
11110.0
22
TOTAL
379.8
11110.0
6733
6733
6733
6733
6733
6733
6733
6733
6733
6733
HARVEST
VOLUMES
IVIP CUBIC
1*1
SCRIBNER
11.96
2I.75
'1.96
11.96
11.96
25.116
26.12
27.55
11.96
25.311
11.96
211.75
11.96
211.75
'1.96
11.96
26.69
29.76
'1.96
29.76
TABLE 5.5
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES PER PLANNING HORIZON DECADE-PERIOD
RUN 2
1981
1991
2001
1160
1013
696.8
1280.0
1013.0
284.3
149.5
1280.0
1013.0
2011
2021
2031
20'Il
2051
2061
2071
263.8
408.3
341.2
401.0
292.8
342.5
430.5
336.2
3119.9
1157.4
1177.4
440.1
l'19.5
1108.3
401.0
'157.11
430.5
1117.11
1280.0
1013.0
749.5
1108.3
7119.5
401.0
1157.4
1101.0
430.5
457.4
337.5
465.1
440.1
477.4
1108.3
7119.5
1101.0
AGE CLASS
ACREAGE
3
4
5
6
7
8
1076
1217
1320
9
10
1396.0
1217.0
11120.0
11
12
1396.0
1217.0
1105.0
700
13
lIt
1396.0
1217.0
739.2
678.0
827
15
16
1280.0
1013.0
1396.0
1005.8
4911.0
656.0
1396.0
618.8
49l1.0-
6311.0
192.2
18
1280.0
1013.0
1038.9
517.7
1194.0
612.0
192.2
17
1280.0
1013.0
1108.3
7119.5
589.8
517.7
494.0
590.0
192.2
19
1280.0
1013.0
198.0
517.7
11911.0
568.0
192.2
20
408.3
749.5
1280.0
1013.0
1280.0
542.3
198.0
517.7
119I.0
5211.0
192.2
22
23
192.2
502.0.
192.2
24
TOTAL
'108.3
7119.5
5116.0
192.2
21
1130.5
1157.4
1101.0
7313
HARVEST
VOLUMES
MMF CUBIC
MM SCRIRNER
'1.96
2I.75
7893
11.96
26.511
7893
7893
7893
7893
7893
7893
7893
192.2
7893
'1.96
11.96
11.96
'1.96
l.96
8.96
'1.96
'1.96
26.86
26.83
24.75
24.75
24.75
24.911
29.76
29.76
TABLE 5.6
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES PER PLANNING HORIZON DECADE-PERIOD
RUN 3
1981
1991
1160
1013
610.6
1280.0
1013.0
2011
2021
2031
20li1
2051
2061
2071
195.0
172.5
285.2
232.7
6811.9
259.1
285.0375.2
6811.9
259.3
1280.0
1013.0
6811.9
203.3
310.5
375.2
285.0
259.3
187.2
273.8
310.5
375.2
285.0
259.3
232.0
277.7
273.8
310.5
375.2
285.0
259.3
218.0
316.2
277.7
273.8
310.5
375.2
285.0
259.3
2001
AGE CLASS
ACREAGE
3
'1
5
6
1280,0
1013.0
7
8
9
10
1076
1217
1320
11
12
13
1396.0
1217.0
1075.3
700
1396.0
1217.0
860.3
678.0
lii
15
16
17
18
19
1396,0
1217.0
1282.6
1280.0
1013.0
1396.0
1217.0
11811.8
656.0
827
1115.8
285.0
259.3
6811.9
1280.0
1013.0
6811.9
1280.0
1013.0
992.11
1108.7
1396.0
733.3
l08.7
612.0
1197.5
1108.7
11011.8
1188.3
'108.7
568.0
375.8
375.8
20
5211.0
502.0
375.8
22
23
375.8
211
TOTAL
8211.6
'$88.3
1108.7
5116.0
375.8
21
6811.9
1280.0
1013.0
1396.0
590.0
375.8
6811.9
1280.0
1013.0
1396.0
6311.0
375.8
6811.9
1280.0
1013.0
7313
7893
7893
7893
7893
7893
7893
7893
7893
375.8
7893
HARVEST
V OLU H ES
MMF CUBIC
tIN SCRIBNER
3.72
18.56
3.72
19.53
3.72
19.71
3.72
20.82
3.72
19.07
3.72
18.56
3.72
18.56
3.72
18.72
3.72
22.26
3.72
22.32
TABLE 5.7
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES PER PLANNING HORIZON DECADE-PERIOD
RUN
1981
1991
2001
2011
2021
1160
1013
650.0
1280.0
1013.0
205.0
722.9
1280.0
1013.0
172.5
270.1
772.9
1280.0
1013.0
285.2
311.2
270.1
772.9
1280.0
1013.0
11
2031
20111
2051
2061
2071
232.7
203.3
332.1
187.2
293.5
332.1
232.0
251.5
293.5
332.1
218.0
336.6
251.5
293.5
332.1
AGE CLASS
ACREAGE
3
11
5
6
7
8
9
10
1076
1217
1320
11
12
13
1396.0
1217.0
1093.1
700
1396.0
1217.0
877.5
678.0
iii
15
16
17
18
19
1396.0
1217.0
1299.0
360.0
311.2
270.1
772.9
1280.0
1013.0
1396.0
1217.0
1396.0
1175.6
10117.8
656.0
827
1109.7
309.6
6311.0
1109.7
311.2
270.1
772.9
1280.0
1013.0
1396.0
767.1
309.6
612.0
310.0
310.0
310.0
1396.0
511.7
309.6
1109.7
311.2
270.1
772.9
1280.0
1013.0
1257.1
376.3
309.6
568.0
1109.7
311.2
270.1
772.9
1280.0
1013.0
956.5
376.3
309.6
5116.0
310.0
310.0
21
5211.0
310.0
22
23
24
HARVEST
VOLUMES
MMF CUBIC
MM SCRIBNER
311.2
270.1
172.9
1280.0
1013.0
590.0
20
TOTAL
I109.7
502.0
310.0
7313
7893
1893
1893
11.03
11.03
11.03
11.03
20.11
21.10
21.29
22.58
7893
U.0
21.25
7893
7893
11.03
11.03
20.11
20.11
7893
11.03
22.110
7893
11.03
211.11
310.0
7893
11.03
211.18
TABLE 5.8
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES PER PLANNING HORIZON DECADE-PERIOD
RUN 5
1981
1991
2001
1160
1013
22.0
1280.0
1013.0
163.0
82.3
1280.0
1013.0
2011
2021
2031
20111
2051
2061
2071
397.2
353.1
538.7
317.11
3011.1
276.1
285.1
1179.111138.6
3-8-9.2
275.11
3911.1
323.11
538.7
1179.11
Il12.9
'$38.6
82.3
1280.0
1013.0
323.11
538.7
1179.11
1112.9
1138.6
82.3
1280.0
1013.0
323.11
538.7
1179.11
1112.9
1138.l
82.3
1280.0
1013.0
323.11
538.7
1179.11
82.3
1280.0
1013.0
323.11
538.7
82.3
1280.0
1013.0
323.11
AGE CLASS
AC RE AGE
3
11
5
6
7
8
9
10
1076
1217
1320
1396.0
1217.0
11120.0
11
11120.0
12
13
82.3
1280.0
1013.0
1396.0
1217.0
12110.1
700
678.0
111
15
16
1396.0
1217.0
323.11
1396.0
1217.0
757.5
656.0
827
1396.0
3115.8
8119.9
1396.0
309.6
1187.0
6311.0
867.0
612.0
665.7
17
18
19
1396.0
1217.0
309.6
590.0
310.0
568.0
310.0
310.0
20
1130.5
376.3
309.6
768.1
376.3
309.6
5211.0
502.0
310.0
22
23
310.0
211
TOTAL
82.3
1280.0
1013.0
5116.0
310.0
21
389.2
7313
7893
7893
7893
7893
7893
7893
7893
7893
310.0
7893
HARVEST
VOL U PIES
PIHF CUBIC
till SCRIBNER
'i.68
'4.26
'1.26
11.26
'4.26
15.77
20.73
2I.93
23.67
23.66
11.26
21.111
11.26
11.26
11.26
'1.26
23.85
211.26
211.70
25.113
TABLE 5.9
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES PER PLANNING HORIZON DECADEPERIOD
HUN 6
1981
1991
2001
1160
1013
22.0
1280.0
1013.0
170.2
85.5
1280.0
1013.0
2011
2021
AGE CLASS
ACREAGE
3
5
6
7
8
9
10
1076
1217
1320
11
12
13
1396.0
1217.0
1420.0
100
333.9
85.5
1280.0
1013.0
1396.0
1217.0
1220.1
678.0
lii
15
1396.0
1217.0
1420.0
'103.5
827
1396.0
1217.0
738.9
656.0
861.0
16
17
18
19
358.7
548.0
333.9
85.5
1280.0
1013.0
2031
20l1
2051
322.3
481.7
311.1
'i'16.4
280.3
I22.2
5'18.O
1187.7
11116.11
333.9
85.5
1280.0
1013.0
548.0
333.9
85.5
1280.0
1013.0
1187.7
1396.0
1217.0
309.6
6311.0
1396.0
803.8
309.6
612.0
655.3
310.0
1396.0
11311.4
309.6
590.0
310.0
20
568.0
310.0
21
546.0
310.0
22
23
24
TOTAL
548.0
333.9
85.5
1280.0
1013.0
310.0
7313
7893
7893
7893
7893
7893
7893
7893
lIAR V EST
VOLUMES
MMF CUBIC
'1.68
MM SCRIRNER 15.77
4.311
4.311
11.311
11.311
11.34
21.12
25.32
211.10
2l1.09
21.56
I.34
211.28
4.311
24.60
TABLE 5.10
AVERAGE AGE CLASS DISTRIBUTIONS AND HARVEST VOLUMES PER PLANNING HORIZON DECADE-PERIOD
RUN 7
1981
1991
2001
1160
1013
235.1
1280.0
1013 0
261.3
338.0
1280 0
1013.0
2011
2021
2031
20111
2051.
2061
2071
1166.5
1152.2
32I1.4
311.8
251.6
156.11
11118.3
1109.9
223.6
337.9
205.11
596.2
338 0
1280.0
1013.0
1452 2
596 2
11118
3
1409 9
302.6
337 9
338.0
1280.0
1013.0
1452.2
596.2
11118.3
1109.9
262.9
302 6
337.9
338.0
1280.0
1013.0
l52.2
596.2
11118.3
1109.9
338.0
1280.0
1013.0
1452.2
596.2
11148.3
AGE CLASS
AC RE AGE
3
II
5
6
7
8
9
10
11
12
13
1076
1217
1320
11120.0
1396.0
1217.0
11120.0
700
1396.0
1217.0
786.3
678.0
lii
15
16
17
18
19
1396.0
1217.0
1396.0
1217.0
1396.0
3511.2
8117.9
656.0
827
653.9
309.6
6311.0
1396.0
520.2
309.6
612.0
311.7
310.0
338.0
1280.0
1013.0
1252.0
376.3
309.6
590.0
989.6
376.3
309.6
568.0
310.0
310.0
20
596.2
1152.2
338.0
338.0
1280.0
1013.0. 1280.0
1013.0
1152.2
5146.0
310.0
21
5211.0
502.0
310.0
22
23
310..0
2'l
TOTAL
797.7
376.3
309.6
7313
7893
7893
7893
7893
7893
7893
7893
7893
310.0
7893
HARVEST
VOLUMES
I*IF CUBIC
MM SCRIBNEH
6.08
22.77
5.33
26.05
5.11
3.90
28.110
21.65
3.90
19.60
3.51
17.28
3.16
16.63
2.84
16.00
2.27
13.10
1.59
9.I13
TABLE 5.41
RESOURCE PRODUCTION COEFFICIENTS PER ACRE
(CURRENT MANAGEMENT PRESCRIPTIONS)
AGE Cu ft
CLASS TIMBER
1
3
14
5
6
7
8
9
0
100
4000
3333
11676
6188
80311
9715
10 11558
11
12
DEER
0
.0456
0
.01169
0
0
.1172
.1172
.0813
.0813
.05117
.05117
.0'4'17
131110
151111
.014147
13 16775
26028
26028
26028
26028
.02311
.02314
.02311
.02311
.02311
.02311
.02311
.02314
.02314
.02311
.02311
211 26028
.02311
lii
181166
15 20328
16 22008
17 23706
18 211387
19 26028
20
24
22
23
CATTLE
.O15
.0313
Production ooeffioient
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
ELK
.0100
GRAZING
FISHERY
.1300
-O--1oO.13OO
.0030
.0310
.0230
.0230
.0195
.0195
.0175
.0175
.0130
.010
.010
.010
.010
.010
.040
.010
.010
.010
.010
.010
.010
.010
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.4070
.1300
.1530
.1530
.1530
.1530
.1530
.4530
MODERATE
CATTLE GRAZING
LIGHT
GRAZING
CATTLE
NO
CATTLE
CATTLE
.O23
ELK
FISHERY
.0070
.1300
.1300
.1070
.1300
.4530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.4530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.O2311.0070
.02314
.02311
.001114
.001111
.0022
.0022
.0022
.0022
.003
.003
.003
.003
.003
.003
.003
.003
.003
.003
.003
.003
.003
.003
.0021
.0022
.0461
.0161
.0136
.0136
.0122
.0122
.0091
.0070
.0070
.0010
.0070
.0070
.0070
.0070
.0070
.0010
.0070
.0070
.0070
.0070
CATTLE
.o'1
.01166
.01168
.01168
.0087
.0087
.00115
.00115
.00145
.00115
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
.0060
for deer, elk, and cattle are grazing potentiala per year.
Production coefficients for ealmonid fisheries are escapement potentials per year.
ELK
.005
.005
.0015
.0016
.0420
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
HEAVY
GRAZING
CATTLE
FISHER!
CATTLE
.1170
.1170
.0960
.1170
,1380
.1380
.1380
.0960
.4170
.1380
.4380
.1380
.1380
.1380
.1380
.4380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.0730
.0730
.0730
.0730
.0130
.0130
.0068
.0068
.0068
.0068
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
.0090
ELK
.005
.005
.Ot5
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
FISHER!
.io1Io
.10110
.08-60
.10110
.1122
.1122
.4122
.0860
.10140
.1122
.4122
.1122
.1122
.1122
.1122
.1122
.0860
.10110
.1122
.1122
.1122
.1122
.1122
.1122
TABLE 5.12
RESOURCE PRODUCTION COEFFICIENTS PER ACRE
BEUTER ET AL. TARGET A MANAGEMENT PRESCRIPTIONS
NO
CATTLE
Cu ft
TIMBER
AGE CLASS
0
2
3
0
100
DEER
.0156
.0156
.01169
4
1002
5
6
33115
11680
7
7359
8
9
90115
10553
.06311
.06311
10
1211011
.011117
11
1111116
.011117
12
13
161140
181166
14
15
206119
.0313
.0234
.0234
.0234
.0234
.0234
16
17
18
19
20
21
22
23
24
22680
24528
25228
26028
26028
26028
26028
26028
26028
26028
.1253
.1253
.0886
.0886
.02311
.0234
.0234
.0234
.0234
.0234
.0234
CATTLE
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
GRAZING
ELK
FISHERY
.0100
.0)00
.0030
.0310
.0230
.0230
.0195
.0195
.0175
.0175
.0130
.010
.010
.010
.010
.010
.010
.010
.010
.010
.010
.010
.010
.010
.1300
.1300
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.4530
.1530
.1530
LIGHT
GRAZING
CATTLE
CATTLE
.0234
.02311
.02311
.02311
.00118
.00118
.0025
.0025
.0025
.0025
.0025
.0040
.00140
.00410
.00110
.00110
.0040
.00110
.0040
.0040
.00110
.0040
.00140
.0040
MODERATE
CATTLE GRAZING
ELK
FISHERY
CATTLE
ELK
FISHERY
.0070
.0070
.1300
'.1300
.01168
.01168
.01168
.01168
.0050
.0050
.0015
.0016
.0120
.0120
.0099
.0099
.0080
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.1170
.1110
.0960
.1170
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.002)
.0022
.0161
.0161
.0136
.0136
.0122
.0122
.0091
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.1070
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.0097
.0097
.005
.0050
.0050
.0050
.0050
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
Production coefficients for deer, elk, and cattle are grazing potentials per year.
Production coefficients for salaonid fisheries are escapement potentials per year.
HEAVY
CATTLE
GRAZING
CATTLE
ELK
.0730.. 0050
.0730
.0730
.0730
.01116
.01116
.0075
.0075
.0075
.0075
.0075
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
FISHERY
.10110
.005G
-I014G
.0015
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0860
.10110
.1)22
.1122
.1122
.0860
.10110
.1)22
.1122
.1122
.1122
.1122
.1122
.1122
.0860
.1040
.1122
.1122
.1122
.1122
.1122
.1122
TABLE 5.13
RESOURCE PRODUCTION COEFFICIENTS PER ACRE
BEUTER ET AL. TARGET B MANAGEMENT PRESCRIPTIONS
NO
CATTLE
Cu ft
TIMBER
DEER
CATTLE
GRAZING
ELK
FISHERY
.0100
.OiOO
.0030
.0310
.0230
.0230
.0195
.0195
.0115
.0175
.0130
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.0100
.1300
.1300
.1070
.1300
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
LIGHT
GRAZING
CATTLE
CATTLE
ELK
FISHERY
.0010
.0070
.0021
.0022
.0161
.0161
.0136
.0136
.0122
.0122
.0091
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.0070
.1300
.1300
.1010
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
.1530
.1070
.1300
.1530
.1530
.1530
.1530
.1530
.1530
MODERATE
CATTLE GRAZING
CATTLE
ELK
FISHERY
CATTLE
ELK
FISHERY
.0050
.0050
.0015
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.1170
.1170
.0960
.1170
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.1380
.0960
.1170
.1380
.1380
.1380
.1380
.1380
.1380
.0730
.0730
.0730
.0146
.0146
.0075
.0075
.0075
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0120
.0050
.0050
OG15
.0016
.0120
.0120
.0099
.0099
.0088
.0088
.0065
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.0050
.10110
AGE CLASS
1
2
3
II
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
211
0
0
107
1002
3528
11937
7612
91111
110211
12976
15078
17172
19465
21728
23871
25819
26695
27533
27533
27533
27533
27533
27533
27533
.0156
.0156
.0469
.1253
.1253
.0886
.0886
.06311
.06311
.04117
.0447
.0313
.0234
.0234
.0234
.0234
.0234
.0234
.0234
.0234
.0234
.0234
.0234
.0234
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
0.0
.02311
.02311
.O23
.0048
.00118
.0048
.0025
.0025
.0025
.0025
.0025
.0040
.00110
.0040
.0040
.0040
.0040
.0040
.0049
.0040
.0040
.0040
.00110
.0040
Production coefficients for deer, elk, and cattle are grazing potentials per year.
Production coefficients for aalmonld fisheries are escapement potentials per year.
.01168
.0468
.0468
.0468
.0097
.0091
.0050
.0050
.0050
.0050
.0050
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
.0080
HEAVY
CATTLE
GRAZING
.1040
.08-60
.1040
.1122
.1122
.1122
.0860
.10110
.1122
.1122
.1122
.1122
.1122
.1122
.1122
.0860
.10110
.1122
.1122
.1122
.1122
.1122
.1122
104
cattle, deer and elk and salmonid escapement potentials for
study area anadromous fishery species.
the first decade of Run
point year number,
1
1981),
For example,
(identified by the decade midTable
5.14
indicates that
acres of the study area timber are in age class
years of age),
of age),
in age class
10
II
3
1,0140
(0-10
(10-20 years
(70-80 years of
700 acres are in age class 13 (100-110 years of age)
age,
and
1,013 acres are in age class
1220 acres are
for
787 acres are in age class 15 (120-130 years of age).
5.11
Table
indicates that
the
1,0140
acres of study area
timber in age class 3 for the first decade of Run
annual grazing potential of 0.01469deer
1
have an
per acre at all
levels of cattle grazing intensity.
Simulation Results and Implications
The
projected
average
annual
grazing potentials for deer,
escapement potentials
for
harvest
schedules,
elk and cattle and salmonid
(multiple use resource allocations)
each decade-period
of
summarized in Table 5.114.
the
seven simulation runs are
The average annual multiple use
production potentials for each simulation are presented in
Table 5.15.
Run 2
For example,
for the fifth decade period of
(2016-2025), Table 5.114 indicates the average annual
production of timber is
1496
in.
Cu.
ft.,
the average annual
grazing potential for deer is 1446 animals at all levels of
cattle
grazing
intensities, and the average.ànnual grazing
potential for elk is
122 animals at the no level of cattle
TABLE 5.111
RESOURCE AVERAGE ANNUAL PRODUCTION LEVELS PER ROTATION DECADE--PERIOD
NO
ROTATION
PERIOD
ft
U
N
1
1976-1985
1986-1995
1996-2005
1906-2015
2016-2025
2026-2035
2036-2045
2046-2055
2056-2065
2066-2075
1976-195
U
N
1986-1995
1996-2005
1906-2015
2016-2025
2026-2035
2
2036-20115
20'16-2055
8
2056-2065
2066-2075
197-195
R
U
N
3
1986-1995
1996-2005
1906-2015
2016-2025
2026-2035
2036-2045
2096-2055
2056-2065
2066-2075
HARVEST
VOLUME
MF(CUBIC)
CATTLE
GRAZING
MODERATE
CATTLE GRAZING
LIGHT
GRAZING
CATTLE
DEER
ELK
FISHERY
CATTLE
ELK
1196
365
896
1008
988
1013
75
89-6
11911
101
115
120
111
108
110
60
1196
511
61
41
811
111
107
102
9115
963
976
28
30
32
29
28
30
28
76
77
78
75
71
67
1008
988
1013
94$
926
95
3
I96
I$54
496
1126
'$96
381
365
371
356
348
$196
1196
'$96
496
496
Ti
496
3211
1122
5117
'$96
1196
529
496
496
496
1159
4116
'196
'196
496
372
372
372
372
312
372
372
372
372
372
$98
96
ii
138
137
126
122
1211
9111
926
961
64
96
l3
1182
1108
1088
1118
1123
1124
1130
40
38
96
88
125
1122
11
542
138
136
123
117
119
119
116
108
1118
1166
1185
1113
1113
1093
1130
1011
1117
520
474
426
liii
395
378
363
345
118
115
1
111l
1168
439
436
429
413
1211
78
110
87
87
67
Ill
83
112
80
'39
39
95
11110
85
1
62
III
32
36
37
35
35
37
38
97
95
86
82
83
83
81
16
73
FISHERY
9115
961
963
976
95
1114
1166
1182
1108
1088
1118
1123
1124
1130
ELK
FISHERY
119-
53
108
81
55
60
63
58
56
61
57
125
128
87
81
77
77
77
81
83
58
60
O7
908
899
912
CATTLE
56
132
1118
1166
1185
$113
1093
1130
1211
82
65
71
711
11116
69
69
1140
1117
74
77
8116
55
55
53
833
51
867
879
118
851
8611
5
69
68
63
1003
1052
61
997
979
62
62
62
59
57
811
95
54
10611
1006
1010
1012
1017
'
69
68
61
59
59
59
58
51$
52
1006
10119
1067
1002
983
1017
1031
1026
1006
HEAVY
GRAZING
CATTLE
CATTLE
1-19
162
122
83
90
95
87
89
91
85
188
192
130
121
115
116
116
121
129
126
198
185
122
ELK
53
58
60
56
54
55
55
53
51
48
58
69
68
63
61
62
62
62
59
57
58
69
68
91
107
110
104
104
111
61
115
52
59
59
59
58
54
FISHER
717
807
790
811
753
741
756
768
770
781
772
891
935
945
886
871
895
898
900
904
772
894
932
948
891
879
904
917
912
899
(oont.)
TABLE 5.111
RESOURCE AVERAGE ANNUAL PRODUCTION LEVELS PER ROTATION DECADE--PERIOD
NO
ROTATION
PERIOD
R
U
N
4
R
U
N
5
R
U
N
6
HARVEST
VOLUME
MF(CUBIC)
1976-1985
1986-1995
1996-2005
1906-2015
2016-2025
2026-2035
1103
1103
1103
1103
CATTLE
DEER
ELK
1122
5113
13's
116
1103
1103
479
433
420
133
119
118
120
2036-20115
1103
1105
121
20lI62055
2056-2065
2066-2075
403
403
403
389
368
1111
351
105
103
197-195
11
1122
11
1986-1995
1996-2005
1906-2015
2016-2025
2026-2035
426
426
531
1126
4211
426
426
421
2036-20I15
1126
418
20Il62O55
2056-2065
2066-2075
426
426
426
1109
405
386
143
123
114
115
133
120
119
113
111
197-195
11
1122
11
4311
531
434
1160
150
129
1134
4311
426
424
417
434
1121
121
115
120
521
15)3
)2J5
1986-1995
1996-2005
1906-2015
2016-2025
2026-2035
203620115
20116-2055
434
11315
5211
1160
4111
GRAZING
FISHERY
965
1116
1167
1186
1112
1092
1138
1154
5152
1100
CATTLE
ELK
66
63
81
112
93
83
83
84
84
80
32
36
37
35
35
36
39
95
1145
1168
1175
1103
1086
1150
1154
1129
1108
1168
1174
1104
1086
1150
1153
911
7l
72
1
50
28
40
43
41
39
39
40
39
95
11115
MODERATE
CATTLE GRAZING
LIGHT
CATTLE
GRAZING
100
86
80
80
93
8l
83
79
78
1
50
29
40
43
41
41
45
104
90
85
81
83
811
81
FISHERY
965
1116
1167
1186
1112
1092
1138
1154
1152
1100
95
11115
1168
1175
1103
1086
1150
1154
1129
1108
95
1145
1168
1174
1104
1086
1150
1153
CATTLE
132
125
83
65
72
75
70
70
73
77
132
ELK
58
67
66
60
59
60
60
51
53
52
FISHERY
868
1004
1051
1068
1001
983
10211
1039
1036
990
5
101
57
71
62
1031
1051
79
57
51
67
60
60
56
56
1057
992
978
1035
1039
1016
997
86
82
78
77
80
79
132
1
101
1011
57
90
85
80
87
83
82
82
81
83
85
87
1031
1051
1057
993
971
1035
1038
HEAVY
CATTLE
GRAZING
CATTLE
ELK
FISHERY
58
772
893
934
198
188
125
98
108
112
105
67
66
60
59
60
60
57
1011
9119
890
873
910
923
921
19
53
52
58
151
71
880
772
916
85
159
129
124
117
116
120
118
62
9311
57
4
940
882
869
920
923
903
886
772
916
0
9311
5
940
883
869
920
923
109
116
19
151
86
120
130
124
124
122
57
67
60
60
56
56
1
1
1
3
5
7
TABLE 5.14 (cont.)
RESOURCE AVERAGE ANNUAL PRODUCTION LEVELS PER ROTATION DECADE-PERIOD
NO
ROTATION
PERIOD
R
U
N
7
HARVEST
VOLUME
HF(CUBIC)
176-1985
608
I98-6-1995-
53-3
1996-2005
1906-2015
2016-2025
2026-2035
2036-2045
2046-2055
2056-2065
2066-2075
511
390
390
351
316
284
227
159
CATTLE
DEER
422
53&
489
465
'156
442
433
415
395
363
ELK
116
1t
128
120
121
123
124
121
113
109
GRAZING
FISHERY
CATTLE
ELK
11355499
965
1174
1169
1104
1081
1142
1147
1129
1115
MODERATE
CATTLE GRAZING
LIGHT
CATTLE
GRAZING
66
81
35
43
43
39
90
8l
85
86
31
36
36
35
87
85
79
76
FISHERY
9.65
1135
1174
1169
1104
1087
1142
1147
1129
1115
CATTLE
ELK
FISHERY
132
109
58
11
64
60
61
61
62
60
57
54
868
1022
1056
1052
7
86
85
79
73
71
73
70
9911
979
1028
1032
1016
1003
HEAVY
CATTLE
GRAZING
CATTLE
ELK
198
163
1U6
128
128
118
110
58
71
64
60
61
107
109
104
60
57
54
6i
62
FISHER!
772
908
939
935
883
870
913
917
903
892
TABLE 5.15
RESOURCE AVERAGE ANNUAL PRODUCTION LEVELS PER ROTATION
NO
HARVEST
VOLUME
MF(CUBIC)
CATTLE
DEER
GRAZING
LIGHT
CATTLE
GRAZING
MODERATE
CATTLE GRAZING
ELK
FISHERY
CATTLE
ELK
FISHERY
CATTLE
ELK
FISHERY
HEAVY
GRAZING
CATTLE
CATTLE
ELK
FISHER!
1196
383.1$
108.6
961.1
36.0
76.0
961.7
71.9
54.3
865.5
107.9
511.3
769.11
RUN 2
1196
1161.8
1211.3
1112.0
115.0
87.0
1112.0
89.9
62.2
1000.8
1311.9
62.2
889.6
RUN 3
372
1127.6
119.11
1117.2
Il1.8
83.6
1117.2
83.7
59.7
1005.5
125.5
59.7
893.8
RUN 4
'$03
1133.11
118.3
1118.2
112.1
82.8
1118.2
811.1
59.2
O06.II
126.2
59.2
8911.6
RUN 5
I130
1129.0
120.8
1118.2
42.6
814.6
1118.2
85.1
60.4
1006.11
127.7
60.11
8911.6
RUN 6
1138
439.3
124.3
1118.0
'$4.0
'87.0
1118.0
87.9
62.2
1006.4
131.9
62.2
8914.6
RUN 7
377
441.6
121.6
1116.6
42.4
85.1
$116.6
811.8
60.8
1005.9
127.2
60.8
893.3
RUN
1
109
grazing intensity. The average annual grazing potential for
38
cattle
animals at
intensity.
average
The
light
the
level
annual
of
escapement
cattle
grazing
potential
for
salmonids is 886 fish at the heavy level of cattle grazing
intensFty.
For the entire rotation of Run 2,
Table
5.15
indicates that the average annual production of timber is
1496
Cu.
m.
deer
is
ft.,
1461.8
the average annual grazing potential for
()462)
animals.
The average annual grazing
potential for elk is 1214.3 (12)4) animals at the no level of
cattle
grazing
intensity.
potential for cattle is
cattle
grazing
145
intensity.
annual
grazing
animals at the light level of
The
potential for salmonids is
average
The
average
escapement
annual
889.6 (890) fish at the heavy
level of cattle:grazing intensity.
The
multiple
resource
use
presented in Tables 5.114
study
area
and 5.15 provide one measure of
resource
productivities.
characteristic of multiple use
absence
of
singular
measurement criteria.
terms
of cubic
feet
potentials
production
common
A
resource analyses
universally
accepted
the
is
resource
Timber is conventionally measured in
or Scribner board
Forage
feet.
is
commonly measured in terms of Animal Unit Months (AtJM5) of
grazing or tons of dry weight forage per acre.
elk are alternatively quantified in terms of
acre
carrying
capacities,
population
per
area or per
area
capacities, numbers harvested per area or acre,
acre, or annual recreational activity days.
Deer and
or
lbs.
acre
per
And fisheries
110
are
alternatively
measured
terms
in
numbers,
catch
of
numbers per kilometer or mile of mainstream, lbs. per acre
or angler days.
The
derived
multiple
use
this
in
study
alternative units
5.16-5.21
Tables
resource
converted
be
of resource productivity
illustrate
grazing
alternative
easily
can
measures
of
to
measurement.
the expression of study area
escapement
and
potentials
production
resource
potentials
resource
terms
in
productivity.°
of
Table
5.16 presents the average annual cattle grazing potentials
reported in Table
AUMs
of
5.15
livestock
expressed in terms of average annual
grazing.
Table
5.17
presents
the
periodic average annual deer grazing potentials recorded in
Tables
5.111
annual
5.15
and
deer
harvest
measured
in
potentials.
terms periodic average
Tables
5.18
and
5.19
present the periodic average annual and average annual elk
grazing
potentials
reported
in
Tables
and
5.111
5.15
expressed in terms of periodic average annual and average
annual days of recreational elk hunting.
5.21
present
recorded in Table
species
average
the
annual
Tables
salmonid
5.20
and
escapement
5.15 measured in terms of annual average
escapement
and
average
annual
angler
days
of
steelhead trout fishing.
10The TREES Model provides summary reports for harvest and
inventory volumes in both Scribner board feet and cubic
feet.
in
TABLE 5.16
ANNUAL AVERAGE AUM OF CATTLE GRAZING PER RUN
AT VARYING CATTLE GRAZING LEVELS'
RUN
LEVEL OF
CATTLE GRAZING
NONE
LIGHT
MODERATE
HEAVY
1
2
3
0
0
0
216.0
270.0
Z131.1I
6)47.14
5
6
7
0
0
0
0
250.8
252.6
255.6
26L0
251.
539.11
502.2
5011.6
510.6
527.11
508.8
809.11
753.0
757.2
766.2
791.14
763.2
' based on usuage rate of 6 AUM per head per year.
TABLE 5.17
AVERAGE ANNUAL DEER
HARVEST POTENTIALS PER ROTATION DECADE-PERIOD
1991
2001
2011
109.11
88.8
111.0
133.2
85.3
106.6
127.9
121.6
1118.0
90.8
113.5
136.2
151.3
1981
RUN'
20$
25%
30%
73.0
91.2
33 1/3$
20Lø.3
25%
30%
33 1/3%
IO9[
t09.
105.$
136.7
126.11
1110.5
1611.0
136.7
158.6
176.2
182.3
loLo
1 oA .3
3
5
25%
30%
105.11
126.11
33 1/3%
201
1I0.5
25%
30%
105.11
126.11
1110.5
135.8
162.9
181.0
JL3
10L2
105.11
126.11
132.7
159.3
177.0
33 1/3%
201
25%
30%
6
!110.5
U.3
10L2
25%
30%
105.11
126.11
1110.5
132.7
159.3
177.0
107.2
25%
30%
33 1/3%
L3
105.11
126.11
1110.5
'Percentage
1311.0
160.8
178.6
.
20111
2061
69.5
86.9
72.9
91.2
l'l.3
1111.11
109.11
111.11
127.1
i05J99.
132.2
121.5
123.8
71.2
89.0
106.8
118.7
1211.5
1111.8
137.7
153.0
133.9
111.6
131.6
109.0
130.9
101.2
128.6
1118.8
1116.3
1115.11
1112.9
A2.2
1112.1
A5.3
106.6
128.0
157.9
1112.2
79.0
98.8
118.6
131.7
75.7
9I.6
113.5
126.1
77.7
97.1
116.6
129.5
p1.9
72.5
90.7
108.8
120.9
73.1
92.0
102.11
101.2
121.11
1112.1
1119.3
165.9
9L
91.1
U.5
131.0
157.2
119.7
1113.6
108.2
129.8
1711.7
159.6
11111.2
1110.0
92.1
115.1
138.1
15.11
92.2
115.2
138.2
153.6
AL9
L2
106.1
127.3
105.3
126.3
2.9
103.6
1111.11
111O.
118.5
92.9
19.-
h.9
101.2
121.11
1311.9
A3.1
1211.3
138.1
139.3
122.8
136.5
115.9
105.2
126.3
103.2
123.9
1110.3
IF.?
2071
611.5
81.0
97.2
108.0
12.1
1311.9
103.2
123.9
137.7
9.0
86.3
103.5
115.0
70.1
87.6
105.2
116.9
77.2
96.6
115.9
128.7
79.0
98.8
118.5
131.7
72.7
90.8
109.0
121.1
110.11
122.6
o.g
U.2
U.7
10&.II
105.9
127.1
1011.2
127.7
1111.9
1111.2
91.2
U.j
1111.0
110.11
1116.6
93.0
116.3
139.6
132.5
162.9
155.1
136.9
152.1
108.2
129.9
1117.2
11111.3
or grazing potential harvested
1011.3
7.2154
1011.5
125.11
5T1
97.1
122.2
2051
95.11
76.3
95.1
.riO.1iOL1
33 1/3%
203
33 1/3%
203
7
162.5
180.6
2031
102.7
123.2
136.9
111.o
105.0
126.0
130.0
156.0
173.3
135.11
2021
125.1
139.0
2.i
103.7
1211.11
138.2
TABLE 5.18
AVERAGE ANNUAL ELE HUNTING DAYS PER ROTATION
DECADE-PERIOD AT
VARYING CATTLE GRAZING LEVEL5
RUN/LEVEL OF
CATTLE CRAZING
I
NONE
LIGHT
HOPER-ATE!
2
3
HEAVY
NONE
LIGHT
MODERATE!
HEAVY
HONE
LIGHT
HODEIIATE/
II
5
6
7
HEAVY
NONE
LIGHT
MODERATE!
HEAVY
NONE
LIGHT
HODERATE/
HEAVY
NONE
LIGHT
MODERATE!
HEAVY
NONE
LIGHT
MODERATE/
HEAVY
U
1981
1991
2001
2011
2021
956
669
5$4
532
5-LU
1178
1239
867
620
12118
12111
B7I
1183
828
592
11118
8011
6214
869
620
1173
821
566
1107
831
1189
1155
832
1078
755
5911
5914
808
518
1039
727
520
1191
1183
1202
1206
11111
1051
8311
828
592
8111
81111
601
603
799
570
736
526
11149
8014
1331
1203
1191
1127
8112
8311
789
5711
932
666
602
596
5614
1210
11511
1191
1207
12112
8117
8311
8115
6011
869
605
808
511
1281
897
1200
12111
1208
1131
600
869
620
8116
6110
850
607
1228
860
12111
8110
192
566
1365
956
682
1258
881
629
1217
852
608
1382
967
691
1359
951
680
1225
858
6*2
1156
809
578
13141
1329
930
6614
596
1156
809
578
11428
12311
111111
1000
8614
7111
617
801
572
1156
809
578
11192
1290
903
6l5
1156
809
578
11112
1156
809
578
1319
965
690
1156
809
578
808
939
610
101111
7116
908
706
2071
1020
111
5-'*O
---577
2061
7116
598 ----5-56
1'48
531t
2051
1065
1081
157
11511
20111
1108
776
1112
178
1068
2031
1196
837
1095
166
511-8-----
596
6111
539
5711
1030
721
515
1112
778
556
621
6014
1087
761
51114
Based on an average of 50 hunting days per harvested elk and a harvest rate of 20% of grazing potential
114
TABLE 5.19
AEEAGE ANNUAL ELK HUNTING DAYS PER RUN
AT VARYING CATTLE GRAZING LEVELS'
RUN
LEVEL OF
CATTLE GRAZING
NONE
LIGHT
MODERATE
HEAVY
1
2
6
5
3
7
1086
1243
119Z
1183
1208
123
1216
760
870
836
828
846
870
851
543
622
597
592
6O4
622
608
5143
622
597
592
60k
622
608
'based on an average of 50 hunting days per
harvested elk and a harvest rate of 20% of
grazing potential
TABLE 5.20
AVERAGE ANNUAL ESCAPEMENT PER ANADHOHOUS FISH SPECIES AT VARYING LEVELS OF GRAZING'
COnG
CHINOOK
RUN
STEELHEAD
Heavy Cattle Grazing
Moderate Cattle Grazing
None/Light Cattle Grazing
SEA-RUN
CUTTHROAT
CONG
CHINOOK
STEELHEAD
-
SEA-RUN
CUTTHROAT
-
COHO
CHINOOK
TEELHEAD
-
SEA-RUN
CUTTHROAT
-
1
256.7
201.7
229.2
229.2
2112.3
190.11
216.11
216.11
215.11
169.3
192.11
2
311.14
21111.6
278.0
278.0
280.2
220.2
250.2
250.2
2119.1
195.7
222.11
222.11
3
312.8
2115.8
279.3
279.3
281.5
221.2
251.Il
251.11
250.3
196.6
233.11
233.11
11
313.1
2116.0
279.6
279.6
281.8
221.11
251.6
251.6
250.5
196.8
223.6
223.6
5
313.1
2116.0
279.6
279.6
281.8
221.11
251.6
251.6
250.5
196.8
223.6
223.6
6
313.0
2146.0
279.5
279.5
281.8
221.11
251.6
251.6
250.5
196.8
223.6
223.6
7
312.6
2115.7
279.2
279.2
281.11
221.1
251.2
251.2
250.1
196.5
223.3
223.3
'Based on an escapement distribution
:
Coho 28%
Chinook 22%, Steelhead 25%, and sea-run Cutthroat 25%
192.11
116
TABLE 5.21
ANNUAL AVERAGE ANGLER-DAYS FOR STEELHED TROUT AT
VARYING LEVELS OF CATTLE GRAZING*
RUN
LEVEL OF
CATTLE GRAZING
1
2
3
NONE/LIGHT
Z58.0
556.0
558.6
MODERATE
432.8
5OO.4
3814.8
141414.8
HEAVY
5
6
7
559.2
559.2
559.0
558.2
502.8
503.2
503.2
503.2
502.14
1466.8
14147.2
14147.2
14147.2
14146.6
*Based on a catch-to-escapement of' 0.5 and
14
angler-days/fiSh
117
The resource productivity values presented in Tables
5.114
use
identify the multiple
5.15 and Tables 5.16-5.21
and
resource
management
policies
production
programs,
on
management
timber,
the
impacts
deer,
habitat
alternative
of
intensities,
elk
cattle,
harvest
and
salmonid
and
The
resources of the Upper Middle Drift Creek Watershed.
information presented in Tables 5.114-5.21 provide data on
the physical consequences
resource
allocation
nature of
study
the
area
over
of selecting
another
or
one
and
others
use
For
resources.
withdrawal of regular acreage for
the
on
technical relationships between and
multiple
use
multiple
among
example,
the
fisheries and wildlife
for protection purposes from lands representative of actual
wildlife and fisheries habitat location (Run 3) rather than
on a proportional basis (Run 2)
reduces output levels for
all resources except salmonids (Tables 5.15 and 5.20).
increase in
the level of cattle grazing intensity has no
affect upon deer grazing potentials.
cattle
An
grazing
from
the
no
level
However,
of
increasing
cattle
grazing
intensity to the light level of grazing intensity reduces
average annual elk production potentials (Tables 5.114, 5.15
and 5.18).
Tables
5.22
annual resourc
resource
Watershed.
and
present
the
relative
average
output differences between the multiple use
allocations
The
5.23
of
relative
the
Upper
Middle
Drift
Creek
resource, production differences
between an unchanged study area acreage inventory and an
TABLE 5.22
AVERAGE ANNUAL OUTPUT EFFECTS OF ALLOCATION CHANGES
CHANGE FROM RUN
RUN
OUTPUTS
1
RUN 2
CHANGE FROM RUN 2
1
RUN 3
RUN 2
liON 3
PHYSICAL UNITS (Average
annual output)
TINDER
ou. ft.
m. bd. ft.
NO
CATTLE
GRAZING
LIGHT
LEVEL
OF
CATTLE
GRAZING
MODERATE
LEVEL
OF
CATTLE
GRAZING
HEAVY
LEVEL
OF
CATTLE
GRAZING
Grazing
Harvest
ELK
Grazing
Harvest
'496
0
1211
1196
-1211.
2650
-16
-670
2630
-650.
potential
potential'
383.11
78.11
1111.2
1161.8
127 7
26.1
111.7
153.8
314.2
11.11
potential
potential'
108 6
21 7
15.7
3.1
10 8
2.2
1214
961 7
150.3
155 5
36.0
216.0
9.0
511.0
76.0
9.0
7.6
87.0
15.2
1.8
1.5
17.14
-3.6
-0.7
961.7
150.3
155.5
1112.0
5.2
71.9
17.9
108.0
11.8
70.6
89.9
1431.11
539.11
-6.2
-37.2
511.3
7.9
5.14
62.2
10.9
1.6
1.1
12.11
-2.5
-0.5
865.5
135.3
1140.0
1000.8
II.?
107.9
27.0
162.0
17.6
105.6
134.9
-9.4
6147.11
809.14
-56.14
511.3
7.9
5.11
62.2
10.9
1.6
1.1
12.11
-2.5
-0.5
769.11
120.2
1214.14
889.6
11.2
3
-14.9
2l 9
1.0
1112.0
5.2
5.8
t5.0
311.8
270.0
-3.2
-19.2
SALNOISIDS
Escapement potential
CATTLE
Grazing potential
A.U.N.
ELK
Grazing potential
Harvest potential'
SALKONIDS
Esoapement potential
CATTLE
Grazing potential
A.U.N.
ELK
Grazing potential
Harvest potential'
SALMONIDS
Escapement potential
CATTLE
Grazing potential
A.U.M.
ELK
Grazing potential
Harvest potential'
SALNONIDS
Escapement. potential
'Based on a harvest rate of 33.3 percent of deer
of elk grazing potential.
grazing potential and 20 percent
TABLE 5.23
AVERAGE ANNUAL OUTPUT EFFECTS OF ALLOCATION CHANGES
CHANGE FROM RUN 3
OUTPUTS
RUN 3
PHYSICAL UNITS (Average
annual output)
TIMBER
m-u ft.
NO
CATTLE
GRAZING
LIGHT
LEVEL
OF
CATTLE
GRAZING
MODERATE
LEVEL
OF
CATTLE
GRAZING
HEAVY
LEVEL
OF
CATTLE
GRAZING
m. bd. ft.
DEER
Grazing totential
Harvest iotentlal'
ELK
Grazing iotential
Harvest potential'
SALMONIDS
Escapement potential
CATTLE
Grazing potential
A.U.M.
ELK
Grazing potential
Harvest potential'
SALMONIDS
Escapement potential
CATTLE
Grazing potential
A.U.M.
RUN 4
CHANGE FROM RUN
RUN 4
RUN 5
37-2-31-B
300
1980
RUN 5
II
CHANGE FROM RUN 5
RUN 5
RUN 6
--53-
30
2170
190
110
2280.0
RUN 7
-20
-370
427.6
5.8
1.11
1133.4
142.4
0.5
144.3
-I.4
-1.4
429.0
142.9
10.3
1.9
3.11
12.6
4.2
119.11
-.9
-.2
1.11
0.3
118.3
23.7
2.5
23.9
0.5
120.8
24.2
3.5
0.7
0.8
0.2
1117.2
1.0
1.0
1118.2
0.0
1118.2
-.2
-1.6
41.8
250.8
0.11
0.8
112.1
11.8
252.6
0.5
3.0
42.6
255.6
1.4
1.8
8.4
-.2
-1.2
83.6
1.0
811.6
2.11
0.5
0.2
82.8
16.6
1.8
16.7
-.8
-.2
0.11
16.9
0.5
0.1
1117.2
1.0
1.0
1118.2
0.0
1118.2
-.2
-1.6
83.7
502.2
0.4
1.6
811.1
1.0
85.1
2.11
8.4
504.6
6.0
510.6
2.8
16.8
-2.11
59.7
11.9
-.5
0.7
0.2
59.2
1.2
60.11
1.8
0.11
-.1
11.8
0.3
12.1
0.11
0.08
1005.5
0.9
0.9
1006.11
0.0
1006.11
0.0
_.5
125.5
753.0
0.7
4.2
2.2
13.2
126.2
757.2
1.5
127.7
11.2
.5
9.0
766.2
25.2
-3.6
59.7
-.5
0.7
59.2
1.2
0.1$
-.1
0.3
11.8
0.2
60.4
12.8
1.8
11.9
0.4
893.8
1.2
1.2
8911.6
0.0
894.6
0.0
-
-.3
ELK
Grazing potential
Harvest potential'
SALNONIDS
Escapement potential
CATTLE
Grazing potential
A.U.M.
ELK
Grazing potential
Harvest potential'
SALMONIDS
Escapement potential
'based on a harvest rate of 33.3 percent of deer
grazing potential and 20 percent of elk grazing potential
0.08
-1.3
120
inventory adjusted
for acreage acquistiions and riparian
and wildlife habitat acreage withdrawals at low levels of
management inteisification are reported under the headings
The relative
"Change from Run 1" and "Change from Run 2".
resource
output
differences
between
riparian and nan-spotted owl habitat acreage
intensively managed riparian and
acreage
(Run
from Run
3".
the moderate
3)
(Run
and
non-spotted owl habitat
are presented under
)
managed
extensively
the
heading "Change
The relative production differences between
level of management intensification (Run
14)
and the high 1eel of management intensification (Run 5)
is
reported
under
heading
the
"Change
from
Run
14".
The
relative resource production level differences between
shortened rotation (Run 6)
5)
a
and an unchanged rotation (Run
and the relative resource output differences between a
non-sustained yield harvest policy (Run 7) and a sustained
yield harvest policy (Run 5) are compared under the heading
"Change from Run 5".
Interpretation
In
f Results
general,
management
rotations
programs,
and
impacts
the
management
harvest
of
alternative
intensities,
habitat
length
of
upon
the
production of study area resources are significant.
The
withdrawal
of
regular
scheduling
acres
for
policies
fisheries
habitat protection purposes on other than
and
wildlife
a proportional
withdrawal bases reduces average annual timber harvests by
121
11.7 to 25 percent, average annual deer grazing potentials
by
to
14.3
7.14
percent,
average
9.3
percent,
and average annual elk
to
percent.
potentials by 2.2
grazing
to
potentials
by
0
'1.8
cattle
annual
While
grazing
average
annual salmonid escapements are observed to increase, the
increases do not exceed
1
percent.
The intensified management of riparian and non-spotted
owl wildlife habitat acreage for timber production purposes
increases
percent
average
and
potentials by
escapement
average
average annual timber harvest volume
the
annual
percent.
1
potential
annual
elk
is
deer
cattle
and
by
8
grazing
While the average annual salmonid
observed
grazing
to
increase
potential
and
observed
is
the
to
decrease,- the resource production potential changes do not
exceed
1
percent.
Comparison of Run 2 and Runs
interesting observations.
3
and
14
reveal several
First, the multiple use resource
allocation associated with a wildlife and fisheries habitat
acreage
total
significantly
withdrawn
different
on
a
proportional
from
a
multiple
bases
use
can
be
resource
allocation based on a habitat acreage total withdrawn from
actual
habitat
area
locations.
Secondly,
the
expected
average harvest volume loss associated with the withdrawal
of 340
older growth acres for bald-eagle and spotted owl
habitat protection purposes is 65 percent greater than the
average
harvest
volume
lost
when
the
3140
acres
are
withdrawn from actual bald-eagle and spotted owl nesting
122
site
stands.
Thirdly,
growth acreage
sustained-yield calculations cannot
to
overemphasized.
importance of existing older
the
Upper
The
Drift
Middle
contains 2,293 acres of timber under
Creek
be
Watershed
15 years of age, has
2,207 acres of timber greater than 50 years of age but only
787 acres of conifer stands greater than 65 years of age.
While plantation and younger aged acreage is forecasted by
the TREES Allowable Cut File to provide significant volumes
of
harvestable
timber,
none
is
harvested
during
any
simulation run.
The change of the management intensity from the Beuter
et al. Target A levels to the Beuter et al. Target B levels
increases
percent.
the
The
average annual timber harvest volume
average annual
elk grazing
increases
by
6
by
2
percent. The average annual salmonid escapement potential
remains unchanged
while
potential is reduced by
the
percent.
1
Collectively Runs 3,
which
timber
average annual deer grazing
4
management
and S demonstrate the extent to
intensification
programs
can
compensate for harvest volume losses resulting from regular
acreage
withdawals
protection purposes.
and
increased
riparian
for
and
wildlife
habitat
Intensified habitat timber management
levels
of
management
intensification
are
shown to be capable of reducing annual timber volume losses
by 53 percent, from 12
ft. per year.
in.
Cu.
ft.
per year to 66
in.
Cu.
123
shortening
The
of
100-year
the
management
forest
planning horizon to an 80-year planning horizon increases
the average annual timber harvest volume and average annual
deer grazing
potential
percent.
2
by
Also,
the
average
annual cattle and elk grazing potentials are increased by
percent,
and
the
average
is
left
unchanged.
potential
escapement
salmonid
annual
deviation
The
3
from
a
sustained-yield harvest policy increases the average annual
timber harvest volume for the first three periods of the
ten-decade planning horizon by 25 percent over the average
annual timber harvest volume for the first three periods of
Run
5.
The annual deer grazing potential is observed to
increase by
3
potentials
are
While the elk and cattle grazing
percent.
observed
to
increase
salmonid
the
and
escapement potential is observed to decrease, the change in
resource productivities do not exceed
percent.
1
5.11_5.23
The information presented in Tables
that
within
the
range
of
resources
indicate
allocation
and
alternatives considered, the multiple use resources of the
Upper
Middle
Drift
supplementary
product
Creek
(independent)
relationships.
relationships
Watershed
between
The
study
and
have
competitive
nature
area
complementary,
of
technical
the
resources
product-
range
from
strongly complementary as in the case of timber production
and deer harvest potential to mutually exclusive as in the
case
of
timber
preservation.
production
and
spotted
owl
habitat
124
In general, the technical relationships between timber
harvest and
deer,
complementary
between
while
timber
relationship
product-product
the
and
independent.1
and cattle grazing potentials are
elk,
salmonids
competative
weakly
is
or
The greater the number of acres harvested
and the higher the level of' management intensification, the
greater the volume of timber harvested and the greater the
grazing potentials for deer, cattle and elk.
the
number
protection
salmonid
acres
of
harvested
activities,
escapement
relationships
cattle are
timber
than
between tiniber and elk.
indifferently
activities,
and
relationship
riparian
the
reduction
The
complementary
deer,
and
habitat
and
timber
of
and
complementary relationships
the
Unlike deer and cattle which react
timber harvest and/or timber management
to
elk exhibit harassment or avoidance responses
Skovlin
of
1974; Penderson,
1973; Lemos and Hines,
(Gibbons and Salo,
Adams,
greater
potentials.
between
stronger
the
without
The greater
1979).
The
and
timber
deer
competitive
observed
when
the
level
of
management intensity is changed from the moderate level of
intensification
intensification
fewer
acres
(Run
(Run
rather
14)
the
to
5)
results
than
from
from
an
high
the
level
harvesting
operative
of
of
competitive
11The measurement of deer, elk and cattle productivities in
terms of grazing potentials restricts deer, elk and cattle
production levels which are not competive with timber or
forage resources.
125
product-product relationship between timber production and
deer.
The technical relationships between salmonids and elk,
salmonids and deer, deer and cattle and deer and elk are
generally
found
product-product
to
be
independent.
relationships
While
competitive
between
observed
are
salmonids and elk and salmonids and deer, the relationships
are statistically insignificant at
confidence.
a
99 percent degree of
Observed statistically significant competitive
and complementary relationships between deer and elk and
deer
and
cattle
typically
reflect
significance
the
of
timber harvest and silvicultural activities over the range
of
allocation
alternatives
considered
rather
than
underlying technical relationships. Research indicates that
in
the
absence
of
forage
constraints
the
relationships
between deer and cattle and deer and elk are independent
(Hines,
1973; Mackie, 1978;
Table
5.2t
summarizes
Skovlin et al.,
the
average
1968).
annual
resource
production effects of alternative levels of cattle grazing
intensities upon study area resources.
Cattle and timber
and cattle and deer are observed to be independent for all
levels of cattle grazing intensities.
Cattle and salmonids
are observed to be independent at the light level of cattle
grazing intensity and competitive at the moderate and heavy
levels of cattle grazing intensities.
Cattles and elk are
observed to be competitive at the light and moderate levels
TABLE 5.2I
AVERAGE ANNUAL EFFECTS OF INCREASE CATTLE
GRAZING FROM THE NO CATTLE GRAZING INTENSITY LEVEL
DEER2 CATTLE2
ELK2
CATTLE GRAZING
SALMON3
TIMBER1 DEER2
CATTLE2
ELK2 SALMON3
SALMON3
TIMBER1
-32.6
0
0
0
71.9
_51$.3
-96.2
0
0
107.9
0
-192.3
45.0
-31.3
0
0
0
89.9
-62.1
-111.2
0
0
134.9
0
-222.4
0
111.8
-35.8
0
0
0
83.7
-59.7
-111.1
0
0
125.5
0
-223.4
0
0
42.1
-35.5
0
0
0
811.1
-59.2
-111.8
0
0
126.2
0
-223.6
5
0
0
42.6
-36.2
0
0
0
85.1
-60.11
-111.8
0
0
127.7
0
-223.6
6
0
0
1111.0
-37.3
0
0
0
87.9
-62.2
-111.6
0
0
131.9
0
-223.2
7
0
0
42.4
-36.5
0
0
0
84.8
-60.8
-110.7
0
0
129.2
0
-221.3
DEER2
CATTLE2
HEAVY
MODERATE
CATTLE GRAZING
LIGHT
CATTLE GRAZING
RUN
TIMBER1
1
0
0
36.0
2
0
0
3
0
II
ELK2
1MM Cu. Ft.
2Grazlng Potential
3Eaoapement Potential
-
127
of cattle grazing intensities and independent at the heavy
level of cattle grazing intensity.
Thus
far,
allocations
has
consequen.ces
of
multiple
use
consideration
the
been
restricted
alternative
resources.
resource
simulated
of
physical
the
to
allocations
of
Discussions
have
area
study
focused
on
projected physical impacts of alternative forest management
programs,
management intensities and harvest policies on
the timber, range, wildlife and salmonid fishery resources
of
Upper
the
resource
Middle
Drift
have been
impacts
Projected
Watershed.
Creek
measured
terms
in
of
timber
harvest volumes (cu. ft. and bd. ft.), deer, cattle and elk
grazing
These
potentials
impacts
have
been
periodic
basis
basis.
Examples have
and
salmonid
and
been
potentials.
an
average
annual
horizon
average
annual
reported
planning
on
escapement
on
presented
demonstrating
the
quantification of non-timber resource impacts in terms of
alternative
measurement
criteria.
grazing
Cattle
potentials were expressed in terms of average annual Animal
Unit Months (AUMs)
of livestock grazing. Big game grazing
potentials were reported in terms average periodic big game
harvest
potentials
and
recreational
activity
data.
Salmonid escapement potentials were expressed in terms of
average annual escapements of Coho, Chinook, steelhead and
sea-run
cutthroat
steelhead trout.
and
annual
average
angler
days
for
While physical production numbers supply
data on the nature of the technical relationships between
128
study
area
trade-off
resources
provide
and
information
useful
resource
and
product-product
information
supply
required by Secion 219.9 and 219.10 (NFMA, 1976). Physical
production numbers alone provide little information on the
relative
worth
of
alternative
multiple
resource
use
allocations or the economic consequences of selecting one
management
strategy
or
multiple
use
resource
allocation
over another or others.
Economic Implications
The Multiple Use-Sustained Yield Act (1960) authorizes
and directs the Forest Service to manage all the various
renewable resources of National Forests
so
that they are
utilized in the combination which best meets the needs of
the American people.
to
Forests contribute in numerous ways
human satisfaction.
livestock
grazing,
They
may
wildlife
provide
and
fishery
recreational opportunities, wilderness or
of these.
timber,
habitats,
any combination
However, any given forest area can only provide
one multiple use resource allocation at a time.
one
water,
particular
combination
of
multiple
use
Choice of
resources
requires giving up other multiple use resource allocations.
The
economic
problem
in
allocating
multiple
use
resources is a classic case of allocating scarce resources
among
competing
uses.
The
economic
criteria
for
determining the most efficient allocation of resources are
well defined
if acceptable market values exist
for
each
129
In such cases, resources
product or use of the resource.
are allocated in such a way that marginal value products in
each use are equal.
absence
The
market
of
values
for
forest
all
land
renewable surface resources precludes the determination of
use resource allocation which maximizes the
the multiple
net
benefit
to
society.
that
fact
The
markets
are
imperfect, and indeed do not exist at all for major classes
of forest outputs, provides an important raison d'etre for
The public management of natural
government intervention.
resources
justified
is
system
market
largely
unable
is
make
to
the
on
grounds
provision
that
the
Pareto-
for
relevant externatlities and for extra-market goods such as
fishery
wildlife
and
preservation
lands
of
(Convery,
wilderness
1977;
watershed
resources,
areas
Haigh
grazing
and
and
protection,
on
Krutilla,
public
1979;
and
Musgrave, 1969).
The
existence
of
extra-market
effects
compels
analyst to adopt one of two valuation approaches.
an
Either
resource values may be assumed to be zero or pseudo-prices
If a zero resource value is assumed, the
may be defined.
resource marginal value product is also assumed to be zero;
and according to
the rules or marginal analysis,
none of
that particular resource should be provided if there is any
cost
involved
variety
of
in
making
it
pseudo-pricing
(provison
available
alternatives
value non-marketed goods and servies.
cost).
are available
A
to
For a given resource
130
in a given situation there is more than one implicit value.
The correct derivation of a substitute market value depends
on the use to which the value will be employed.
management
land
planning,
decisions
where
In forest
will
made
be
about whether to change the quantity or quality of forest
multiple
value
use
has
resources,
been
willingness
determined
consumers
of
outputs. (Brown,
appropriate
the
to
derivation
estimates
of
1977;
goods
the
for
1976).
"willingness
and
services
reflects one of two basic valuation approaches.
first
approach,
service
'valued
value
derived from
is
good
or
of
an
the
survey
Under the
good
or
the observed value of a market-
service.
Under
second
the
from
an
market
observed
valuation
produced
value
first
methodology
(the
of
the
valuation
contingent
second
approach
indirect
method)
auctions,
are
(the
experiments and substitution games.
the
method)
are
The most common
direct
iterative
open-ended
by
Foremost examples
formulations of the "travel cost method."
examples
typically
extra-market
establishment of a hypothetical market.
of
pay"
to
the value of a non-marketed good or service is
approach,
derived
the
the
Dwyer, Kelly and Bowes,
consumers'
non-marketed
for
of
land
Martin, Tinney and Gum 1978, Mishan,
The
estimate
an
forest
pay
to
1982, 1981;
be
market
implicit
value
method
bidding
or
games,
questions
and
131
Numerous willingness to pay studies have been directed
at
the valuation of non-marketed multiple use resources.
no universally accepted values have been derived
To date,
for
non-marketed
any
timber multiple
only
utilized
in
in
land
resource.
resources, considered
use
salmonids
identified
forest
have
an
Forest
economic
Service
specifically
value
documents
Planning
resource allocation analyses.
values considered
this
in
study
for
study,
this
n
non-
the
Of
economic
The
area
research
and
non-
timber multiple use resources are presented in Table 5.25.
Reflecting an absence of Forest Service identification and
the lack of universal agreement regarding the appropriate
value of non-marketed resources, a range of economic values
are provided forharvested deer and elk and AtJMs
of cattle
grazing.
Willingness to pay estimates provide resource economic
values for current resource products or uses only.
current
non-marketed
accurately
determined,
future
economic
values
values
economic
are
reniain
For the purpose of this analysis, it was assumed
unknown.
that
resource
Even if
the
relative
relationships
value
of'
study
area
multiple use resources would not change over time.
While
range,
forest
wildlife
land
and
simultaneously
fishery
provides
resources,
the
timber,
realized
production of particular forest land resources occurs at
different points
in
time.
Range, wildlife and
fishery
resources provide annual flows of resource product values;
132
TABLE 5.25
ECONOMIC VALUES OF STUDY AREA
NON-TIMBER MULTIPLE USE RESOURCES
VALUE
REFERENCE,
DEER
I8.69
Brown, Nawas, Stevens (1973)
DEER
160.00
Brown, Nawas, Stevens (1973)
DEER
19U.75
W.R.0 (1973)
DEER
253.00
Shalloff (1981)
RESOURCE
2
CATTLE (AUM)
1.60
USDA (1976)
CATTLE (AUM)
5.30
Statistiai. Report Service (1977)
CATTLE (AUM)
6.50
(Brown, 1976)
CATTLE (AUM)
16.00
ELK
151LO
ELK
259.66
(Gardner, 1959)
Brown, Naves, Stevens (1973)1
Brown, tiawas, Stevens (1973)2
ELK
336.00
W.R.0 (1973)
Shalloff (1981)
ELK
SALZIONIDS
106.98
Kunicel and .Ianik (1976)
1Westerri Oregon harvested aninal adjusted to 1975 price level.
21975 price level and Hobo hunter days per aninal harvested.
3Hebo hunter days per aniaal harvested and average daily net benefit.
133
timber resources provide product values which are realized
incrementally upon
thinning
harvesting.
and
values which occur at different points
compare
To
in time,
standard
analytical procedure is to discount all resource values to
their present values.
In
discount
evaluating
rate
determining
the
forestry
used
can
level
outputs (Josephson,
be
and
mix
resource
of
allocations,
extreme
importance
multiple
of
the
resource
use
1976 and Klemperer, 1976).
in
The higher
the discount rate, the lower the value given future product
values as
compared with present ones.
For example,
the
present value of $1,000 of benefits 30 years in the future
is
$1412
discounted
at
3
percent,
$1714
discounted
percent but only $57 discounted at 10 percent.
at
6
The present
value of $1,000 received annually over a 30-year period is
$19,600 discounted at
3
percent, $13,765 discounted at
percent and $9,427 discounted
at
10
percent.
Thus,
6
the
present value of benefits realized 30 years in the future
can be changed by more than a factor of 7 depending on the
discount rate used; and
the present value of a stream of
benefits realized over 30 years can be changed by more than
a factor of 2 depending upon the discount rate used.
Much has been written about the appropriate rate
discount for natural resource decision making.
of
the
appropriate
discount
rate
has
of
Selection
emerged
as
an
important issue in public forest planning (Row, Kaiser and
Sessions,
1981).
The Renewable Resources Planning Act of
134
197k and the National Forest Management Act of 1976 (NFMA)
direct the USDA Forest Service to use economic efficiency
as
one
of
major
the
decision-making.
develop
economic
for
chosen
below current
rates of
specified
the
for
is
only
is
interest or
Office
percent
1
discount
study
this
federal agencies (Stockfish,
rate
and
of
6
the
1969).
a
rate.
The
percent,
well
percent rate
10
Management
less
including
analysis,
appropriate
an
for
discount rate
by
planning
resource
in
The NFMA requires the Forest Service to
guidelines
recommendation
criteria
and
Budget
for
The 6 percent discount
than
the
discount
rate
recommended by the U.S. Water Resource Council but is well
above the
2
or
percent rate traditionally employed
3
in
forestry decision-making and planning.
The present net worth of the study area average annual
non-timber resource production potentials (livestock AUM's,
harvestable deer and elk, and salmonid escapements) valued
at aLternative willingness to pay estimates are presented
in Tables
5.26-5.29.
The present net worth of study area
resource allocations based on specific resource values are
5.30.
presented in Table
Resource values used were $160
for each harvested deer, $336 for each harvested elk,
for
each
AUM of
uncaught salmonid.
livestock grazing
and
$106.98
for
$6.50
each
TABLE 5.26
GRAZING POTENTIALS
PRESENT NET WORTH OF THE AVERAGE ANNUAL CATTLE
AT ALTERNATIVE AUM VALUATIONS AND LEVELS OF CATTLE GRAZING INTENSITIES
1.60/AUM1
Level of cattle
grazing intenaity
5.30/AU142
of
cattle
grazing intensity
Level
6.50/AuH3
Level of cattle
16/AUM4
Level of cattle
grazing intensity
grazing intensity
MODERATE
HEAVY
LIGHT
46,597
69,929
29,165
58,263
66,322
27,087
44,366
66,688
22,517
44,968
20,900
23,096
20,291
22,401
LIGHT
MODERATE
1
5,750
11,1166
17,216
19,028
2
7,179
111,3111
21,520
3
6,664
13,3114
II
6,714
5
HEAVY
MODERATE
HEAVY
57,432
1111,697
172,129
87,1127
71,790
1113,1113
215,203
511,241
81,328
66,688
133,526
200,214
27,287
5I1,507
81,794
67,170
1311,1711
201,327
67,486-
27,602
55,155
82,758
67,968
135,769
203,720
146,143
69,239
28,329
56,593
84,922
69,734
139,303
209,037
1111,819
67,220
27,1186
511,956
82,442
67,635
135,287
202,922
HEAVY
LIGHT
37,989
57,016
23,332
23,780
47,511
71,291
20,025
22,085
44,237
13,1111
20,1211
22,252
6,797
13,577
20,3711
6
6,967
13,934
7
6,764
13,527
LIGHT
MODERATE
RUN
1USDA, 1976
2Statistical Reporting Service, 1977
3Brown, 1976
11Gardner, 1959
TABLE 5.27
PRESENT NET WORTH OF THE AVERAOE ANNUAL DEER PRODUCTION AT AI.TP.RNATIVE
HARVESTED ANIHAL. VALUATIONS AND ALTERNATIVE OJIAZINO POTENTIAL HARVEST RATES
$118.69/deer1
$160.00/deer2
$19I .75/deer3
$253/deer'4
203,866
2'18,157
322,389
RU N / H AR VEST
62,052
77,556
93.061
20%
25%
30%
33 1/3%
20
2
3
93,410
112,105
33 1/3%
12IIll36
9,197
86,1197
1183,5811
306,960
366,355
'4°°L066
373,639
11118,370
11971692
1185,395
562,1178
3115,970
1115,167
11602834
598663
350,656
420,784
1155,5119
21i5,5
227,3I1
33 1/3%
115_t212
3782608
81,660
105,209
116775
288,090
345,70'l
25%
30%
9,1130
33 1/3%
20J
22,t32
1151595
3192838
232,I
70,2
88,2111
105,938
33 1/3%
11125911
71,1157
69,322
101,186
33 1/3%
383743
285,165
342,198
25%
30%
25%
30%
230,1115
66,779
1011,128
1j,985
290,096
3l8,109
386,l10
21i,29
293,5110
21,773
20,52
61165110
359,51
11119,1150
539,331
31,132
546,6119
60619O
3117,100
416,5111
1150,913
5111,099
227,7
3o,7
1162329
60062'l
353,0911
1123,720
'458,119
Il10325
25,30
357,287
3,91
550,1160
6111015
371.329
'4611,157
352,225
1128,7411
556,985
32.QL988
11152923
6188511
2Brown, Nawa., and Stevens applied to Rebo suoceserates and adjusted to 1975
'4Shalloff (1981)
536118
1167O82
1l3rown, Nawas, and Stevens northwest Oregon adjusted to 1915
3w.n.c. and Ilebo suooeseratea
1102,987
339,1173
103.796
7O,l
310,208
372,2211
1113L190
2811,2311
3111,0811
20
7
305,621
25%
30%
33 1/3%
6
711,731
25%
30%
2O
25%
30%
5
lO3297
2511,8511
TABLE 5.28
PRESENT NET WORTH OF THE AVERAGE ANNUAL ELR PRODUCTION AT ALTERNATIVE
GRAZING POTENTIAL HARVEST RATES AND LEVELS OF CATTLE GRAZING INTENSITIES
154.40/elk1
NONE
RUN
20%
1
25%
30%
55,670
69,796
83,638
33.3$ 92,878
2 25%
30%
58,1195
611 910
111,628
1110,671
46111117
156209
65,591
81,993
98,379
10916Il
55,936
66,971
110,033
117,976
134,190
911,0711
160,9115
112,620
33.3$1O2118
75,9711
91,083
53,626
30,527
38,238
103,131
128,590
611,395
115,932
hlL32'I
51O67
53,111
63,630
31,972
45,666
__.HOl.8L7O,o9 59,552
2,O5 !3,35F31,o11
20J
))
ii.q9u 'I,391 3*1,737
30%
92,878
33.3%103,1118
65,176
72,355
116,11117
19,276
30%
95,075
33.3$105,526
20J
2,351
7 25%
78,005
30%
93,659
33.3%lOj,912
55,569
66,531
73,927
113,22
511,657
65,'125
HOD ER A T El
NONE
LIGHT
HEAVY
121,162
151,872
'17.028
58,678
70,327
182,0311
781O5
2O2125
67,320
80,697
139,O2
173,658
208,273
O'l,868
60,855
106,089
127,310
75,9411
121,727
91,017
101,071
9,231
87,112
1111,270
97,7J19
160,613
201,327
HODERATE/
HEAVY
80,680
100,672
2111,293
267,9119
112,504
140,638
168,756
187,268
11i,10
*2,79O
91,71
161,360
115,462
193,1811
21'1,655
138,1111
1115,7110
104,1*11
6
161,926
115578
230,193
276,091
306,435
120,6117
133,974
153,218
,1139
17,99
123,O5
611,312
77,2110
166,396
199,898
*16,692
83,190
15'I,'18O
1'IO,156
99,9111
111,730
ll9965
220,571
264,990
154,697
185,789
110,2911
132,1195
651865
50,91
22212311
155,229
111,108
92,95
5,9O
2911,587
175,1120
205,7611
147,302
132,329
165,283
198,220
122,73
87,31111
115,570
82,6111
219,092
138,1*78
1511,115
9J1,357
99,392
109,995
262,7611
153,218
183,562
109,5'16
131,7118
1115,823
118,370
8'I,320
11*1,818
157,1155
101,071
1121238
U,77
_1!O019
1O1i,112
130,318
156,209
39,770
133,310
159,890
l77'172
116,697
LIGHT
93,2115
51,566
5j,763
31,30
39,002
NONE
133,11lIj-
173,1159
117,661
HODERATE/
HEAVY
II 115 .4 l/e lk'1
51,350
127,726
153,185
,
336/elk3
12,05
90,186
108,300
-r-n ,11iTi11 ,WTT ,nr'i,
6 25%
LIGHT
93,625
117,373
76,1159
91,8611
25%
30%
NONE
27,968
34,898
112,111
30%
HODERATE/
HEAVY
39,002
48,757
1,32O
20J
3 25%
II
79,800
95,703
LIGHT
259.66/elk2
j11
89,322
107,020
1191101
72,920
63,83
91,1182
65,159
78,105
86 729
109,596
l21677
76,608
85,001
219989
1J,12l
2,2T11
168,623
202,125
.2211,1159
T,T1-----9,512
93,1157
111,881
ioI,o
1211,313
131,162
157,505
91,9111
111,773
133,9711
11181781
91,179
1111,705
103,726
11111820
301111126
213,2117
,117
179,57
125,32
811,068
225,008
270,159
2991772
157,655
11111,784
229,6110
160,8611
65,591
78,537
169,736
203,803
118,935
1112,383
101,619
1121786
158,021
297,5115
156,924
187,999
208,739
160,302
191,917
86,5110
_.h'3
125,O11,11
127,9115
120,928
7j_j_17111755i221jo9 87jjj_
20111286
13,1O1
172,519
206,907
135,11,922
291,629
179,125
223,529
267,949
228,683
274,281
66,878
80,168
88,736
73,352
110,028
7,59
137,503
1521213
90,302
188,7117
112,5011
1311,706
209,470
149,512
'Brown, Nawae, and Stevena northwest Oregon adjueted to 1975
2Brown, Nawas, and Stevens applied to Hobo £uooeearates and adjusted to 1975
3v.r*.c.
and Hobo
'1Shallofr (1981)
uooeaeratea
H
-4
138
TABLE
5.29
NET PRESENT WORTH OF SALMONID ESCAPEME1NTS
AT VARYING LEVELS OF CATTLE GRAZING
106.98/Escapement fish
NONE/LIGHT
MODERATE
HEAVY
RUN
1
1,709,710
1,538,694
1,367,828
2
1,976,911
1,779,223
1,581,518
3
1,986,150
1,787,565
1,588,997
it
1,987,928
1,789,177
1,590,1109
5
1,987,928
1,789,177
1,590,1109
6
1,974,526
1,777,1142
1,579,977
7
1,985,O87
1,786,502
1,588,099
1Kunkel
and Janik, 1976
TABLE 5.30
NET PRESENT WORTH OF STUD! AREA MULTIPLE USE RESOURCE ALLOCATIONS AT
ALTERNATIVE LEVELS OF CATTLE GRAZING INTENSITIES
33.3 (h)
160/DEER
Deer
Timber
ELK
Cattle ($6.50/AUM)
LIGHT MODERATE
CATTLE
GRAZING
HEAVY
20S (b)
($336/ELK)
MODERATE/
LT CATTLE
HEAVY
GRAZING
NONE-LIGHT
CATTLE CRAZING
SALMONIDS
($106.96/FISH)
MODERATE
CATTLE GRAZING
HEAVY CATTLE
GRAZING
RUN
2,O01,241I
339,4473
23,332
46,59?
69,929
124,162
814,868
60,685
1,709,710
1,538,6914
1,367,828
1
1,998,157
1408,686
29,165
58,263
87,42?
439,026
97,4449
69,231
1,976,914
1,779,223
1,581,518
2
1,473,060
376,608
27,087
514,2441
81,328
133,443
93,2445
66,4439
1,986,150
1,187,565
1,588,991
3
1,595,813
383,743
27,287
54,507
81,794
132,329
92,695
65,890
1,987,928
1,789,177
1,590,409
14
5
1,639,499
379,838
27,602
55,155
82,758
135,424
94,357
67,569
1,987,928
1,789,177
1,590,1409
6
1,9145,470
386,410
28,329
56,593
811,922
138,114
96,512
68,776
1,974,526
1,177,4442
1,579,997
7
2,015,971
390,988
27,486
514,956
82,442
135,686
94,922
68,147
1,985,087
1,786,502
1,588,099
h
percentage of grazing potential harvested
140
Interpretation of Results
The multiple use resource allocation values presented
in
5.26
Tables
5.29
-
non-timber
alternative
identify
resource values for the Upper Middle Drift Creek Watershed
associated
with
alternative
management intensities,
summarizes the
management
forest
and harvest policies.
Table
5.30
allocation values associated with specific
5.28 - 5.29
resource output evaluations.
Tables
5.30
lacking
provide
programs,
heretofore
the
and Table
information
on
the
relative worth of alternative resource allocations and the
economic consequences of selecting one management strategy
or multiple use resource allocation over another or others.
A
noticeable
inclusion of
three
cattle,
and
values
elk,
for
intensity
characteristic
possible production
salmonids.
cattle,
level
quantification
relationships
elk,
of cattle
of
and
the
level values
for
salmonids
grazing
cattle
is
identified
and
the
joint
elk
production
based
reflects
competitive
the
between
The
5.30
Table
of
on
the
economic
production
and
cattle
the
present net
and
salmonid resources.
Table
5.31
presents
the changes
in
worth of simulation resource allocations associated with
varying intensities of cattle grazing.
For all runs, elk
harvest value losses exceed cattle AUM gains when cattle
are
introduced at
the
light
level
of grazing
intensity.
For cattle AUM gains to exceed elk harvest value losses,
TABLE
5.31
RESOURCE PRESENT NET WORTH CHANGES AT VARYING LEVELS OF CATTLE GRAZING
CATTLE GRAZING
(6.50)
ELK $(336)
LIGHT MODERATE HEAVY
CATTLE CATTLE CATTLE CATTLE
GRAZING GRAZING GRAZING GRAZING
NO
$160
TIMBER
DEER
LIGHT MODERATE HEAVY
SALMONIDS $106.98
LIGHT MODERATE HEAVY
NO
CATTLE
CATTLE CATTLE CATTLE
GRAZING GRAZING GRAZING GRAZING
RUN
1
23,332 23,265 23,332
2
29,165 29,098 29,1611
3
27,087 27,1511 27,087
-'10,198 -26,806
-39,634 -26,805
5
27,287 27,220 27,087
27,602 27,553 27,603
-110,764 -26,788
-171,016 -170,866
-197,688 -197,705
-198,585 -198,568
-198,751 -198,768
-198,751 -198,768
6
28,329 28,2611 28,329
-'11,602 -27,736
197,0811 -197,1165
7
27,1186 27,'lTO 27,1186
-'l0,76'i -26,805
-198,585 -198,'103
II
--,
-36,29H -23,983
-111,877 -27,918
142
cattle grazing must
be
increased
the
to
heavy
level
of
However when cattle grazing is increased
cattle grazing.
from the light to the moderate level of grazing intensity,
joint-production
the
salmonids changes
from an
and
cattle
independent relationship
to
a
For cattle AUM gains to exceed elk and
competitive one.
salmonid
between
relationship
losses
when
elk
and
salmonid
values
left
are
unchanged, ATJM values must be increased by a factor of 5 at
the moderate level of grazing intensity and by a factor of
6
at
the
heavy
of grazing
level
For
intensity.
cattle
grazing gains to exceed elk and salmonid losses when cattle
AUM's are valued at the Forest Service recommend rate of
1976), harvested elk are valued at $336
$1.60 (U.S.D.A.,
and salmonids are -valued $106.98 (salmonid escapement value
derived
from
Forest
Service
study cited in Hebo FEIS,
increased
by
factor
a
of
fishery
resource
valuation
1978 p.26), AUM values must be
20
at
the
moderate
level
of'
grazing intensity and by a factor of 24 at the heavy level
of grazing intensity.
The information presented in Table 5.31 indicates that
in
the
absence
of
significant
changes
in
resource
valuations, an efficient allocation of study area multiple
use
resources
will
exclude
cattle
grazing
activities
entirely or include cattle grazing limited to a low level
of grazing intensity.
Such a conclusion is consistent with
the current absence of cattle grazing on study area acreage
and absence of any Forest Service plans to expand cattle
143
grazing beyond existing locations or above existing trivial
1978,
grazing intensity levels (Hebo FEIS,
present
The
net
impacts
value
13).
P.
riparian
which
and
wildlife habitat acreage withdrawals have upon study area
resource allocations when timber and wildlife and fisheries
habitats are
5.32.
extensively managed
presented
are
in
Table
The withdrawal of study area acreage on other than a
proportional bases reduces the present net worth of timber
by 25 percent, the present net worth of deer harvest values
by 7.24
percent and
values
by
the present net worth of elk harvest
percent.
24
While
present
the
net
worth
of
salmonids is observed to increase, the magnitude of change
does not exceed one-half of
1
percent.
The present net worth impacts resulting from changes
in selected management practices on multiple use resource
allocations of the Upper Middle Drift Creek Watershed can
readily
be
management
determined
by
practices
included
examining
habitat management practices,
rotation
length,
differences
between
(Run
habitat acreage
are
"Change from Run #3".
moderate (Run
24)
24)
These
fisheries
and
management intensification,
extensively
wildlife habitat acreage
(Run
wildlife
harvest
and
5.33.
Table
3)
policy.
The
managed
relative
riparian
and
and intensively managed
compared
under
the
heading
The relative differences between the
and the high (Run 5) ranges of management
intensities are compared under the heading "Change from Run
#24".
The relative differences between a shortened rotation
TABLE 5.32
AVIRAGE OUTPUT EPEECTS OF ALLOCATION CHANGES
cHANGE IRON RUN 12
CHANGE IRON RUN #1
OUTPUTS
PHYSICAL UNITS
(average annual
output)
Tiuber(a ou.ft.)
Deer(harveetl)
Cattle(AUN)
Elk(harveetl)
Salmonida(eeoapement
RUN1
RUN2
0
96
127.7
RUN5
-12k
96
1.7
26.1
-
R0N5
_1211
11.
153.8
-
-
2.9
2.2
155.5
3.2
150.3
21.7
961.7
RUN2
-1.0
5.2
961.7
nui.bera)
DOLLAR VALUES
(Present net worth)
Timber
Deer
Cattle
Elk
Salmonids
2,O11,2
339,73
-
121,162
1,709,710
-13,007
538,1811
1,998,157
69,13
39,135
'108,886
-
17,86'1
267,201
-
12,281
276,201
-
139,026
1,976,911
-525,097
-30,278
-
-5,583
9,239
TABLE 5.33
AVERAGE OUTPUT EFFECT OF ALLOCATION CHANGES
CHANGE FROM RUN #3
OUTPUTS
RU" 3
RU"
CHANGE FROM RUN #1
5
flJ't
CHANGE FROM RUN #5
RU" 11
RU" 5
1103
27
I3O
8
1OI.3
-1.11
1112.9
3.11
I.2
211.2
.7
1,118.2
-.2
-.9
-1.6
RU" 5
RU"
7
PHYSICAL U" TS
(average annual output)
Timber (in ou.tt.)
372
Deer (harvest 0)
Cattle (AUM)
Elk (harvest 0)
Salmonids
(Escapement numbers)
1112.11
Dollars Values
(Present Net Worth)
Timber
Deer
Cattle
Elk
Salmonids
31
1.9
-
-
23.9
1117.2
1,1173,060
378,608
-
58
10.5
-
-.2
.3
1.0
1.0
122,753
5,135
-
133,11113
-1,1111
1,986,150
1,778
-
23.7
1,118.2
-
.5
0
-53
-
166,1139
1,595,813
'13,686
1,639,1199
1,230
383,7'13
-3,905
379,838
305,971
6,572
135,121
1,987,928
2,993
565
-13,I102
2,8111
-
1,678
1,778
-
132,329
1,987,928
376,1172
11,150
-
2,792
0
146
(Run 6) and an unchanged rotation (Run 5) and the relative
differences between
non-sustained yield
a
harvest policy
(Run 7) and a sustained yield harvest policy (Run 5)
compared under the heading "Change
general,
In
habitat
the
management,
policies are
wildlife
significant.
and
production
between
intensified
intensities,
harvest
and
The intensified management of
fisheries
increases
from Run #5".
differences
management
are
habitat
present
the
acreage
worth
net
timber
for
of
timber
harvests by 8.3 percent and the present net worth of deer
harvest values by 1.I
of salmonjds
worth
magnitudes
Overall,
harvest
of
the
While the present net value
observed to increase and
is
elk
'of
percent.
value
observed
is
change
intensified
do
not
management
the present net
to
decrease,
exceed
of
1
the
percent.
wildlife
and
fisheries habitat acreage increases allocation total value
by 3.2 percent (or $128,552).
The change of management intensity from the Beuter et
al. Target A levels
the Beuter et al. Target B levels
to
increases the present net worth of timber harvests by 2.7
percent.
The
increased by
present
2.1
percent.
harvests is reduced by
salmonids is
net
1
value of the multiple
of
deer
harvests
is
The present net value of elk
percent. The present net value of
left unchanged.
management of study area
$12,573)
worth
Overall, the intensified
acreage increases the present net
resource allocation by
1
percent (or
147
3,
Collectively, Runs
to
which
management
timber
compensate
harvest
for
and
14
demonstrate the extent
5
programs
intensification
value
producing acreage withdrawals
habitat protection purposes.
resulting
reductions
for wildlife and
can
from
fisheries
Intensified habitat timber
management and increased management intensification reduce
the
net worth
present
$525,097
percent, from
The
planning
shortening
horizon
increases
of timber harvest
(Run 3)
of
to
$358,658
ten-decade
the
net
values
present net
percent.
value of deer harvests
percent.
increased
by
the present net value of elk harvests
And
increased by
The present net
18.6
is
horizon
allocation
all
resources with the exception of salmonids.
worth of timber harvests is increased by
31.7
management
planning
of
by
(Run 5).
forest
eight-decade
an
present
the
to
losses
2.2
The
1.7
is
The reduction of the present net
percent.
worth of salmonid escapement does not exceed
1
percent.
Overall, the shortening of a ten-decade rotation length to
an eight-decade rotation length increases the present net
worth of the multiple use allocation by
7.9
percent
(or
$302 , 1 314).
The deviation
for
the
from
three
first
a
sustained-yield harvest policy
decades
of
a
ten-decade
planning
horizon increases the present net worth of timber harvests
by
23
percent. The present net value of deer harvests
increased
by
2.9
percent.
The present net
value
is
of elk
harvests is increased by less than one percent, while the
148
present net worth of salmonjd
less
than
one
percent.
Overall,
sustained yield harvest policy
worth
of
multiple
the
is decreased by
escapemerits
use
deviation
the
from
a
increases the net present
resource
allocation
by
9.3
percent (or $385,3146).
Employment and Income
Forest Service administrators have traditionally been
concerned
with
communities
the
and
economic
welfare
individuals
Such statements
near
the
.
(USDA,
opportunities
Forest
concerns.
requires
Service,
The
that
for
.
.
describe
National
Forest
evaluations
of
income,
jobs
development,"
Forest
Management
alternative
resource allocations must include
Forests.
., and identify
community
19714)
of
seek opportunities for
.,
.
development of forest based enterprises
promote
National
as "provide public services,
and amenities in rural areas
and
stability
and
Act
Service
of
multiple
1976
use
forecasts of changes in
payments to local governments and estimates of employment
and income impacts upon local and regional economies.
Local and regional employment and income is influenced
by many factors.
be
caused
exports,
inputs,
by
by
or by
a
Change in area employment and income can
change
change
a
a
in
in
the
final
demand
availability
for
an
area's
of production
change in the area's infrastructure.
the major factors influencing employment and income,
timber
supply
is
subject
to
direct
manipulation
by
Of
only
the
149
Forest Service.
Because of
its
control over commercial
timber sales and harvests,
the Forest Service can have
profound
rate
affect
upon
the
quantity
and
a
timber
of
available to local timber and wood products industries.
Whether
change
a
signifiqaritly
volume
harvest
in
affects local and regional employment and income depends
First, does a harvest volume
upon a number of criteria.
change actually change the harvest level or only the limits
on the harvest level.
harvest supplied by
And
finally,
income
single agency or firm substantial.
a
percentage
the
is
provided
is the proportion of total
Second,
the
by
of
local
employment
industry
products
forest
and
significant.
The economy of the oregon Coast is, as a whole, quite
dependent on the forest industry and upon timber supplied
by the U.S. Forest Service (Hebo FEIS,
1978, Owen,
1981).
Consequently, harvest volume changes may have potentially
major repercussions
Tables
5.314
regional
in
5.35
and
employment
local and regional economies.
the
present
income
and
the
estimated
impacts
of'
local
and
alternative
allocation harvest volumes.
Table
industry
simulation.
employment
per
the
average
simulation
annual
period
and
forest
per
Table 5.35 presents the present net value of
monies returned
employment
identifies
5.314
to
levels
industries and
the
local governments,
the average annual
for
the
and
trade
net
present value of business
income
forest,
service
TABLE 5.31j
AERA0E ANNUAL FOREST INDUSTRY EHPLOYMENT
Simulation
RUN
1981
1991
2001
2011
2021
2031
20111
2051
2061
2071
1
18.6
19.1
19.6
20.7
19.0
18.6
18.6
20.0
22.3
22.3
19.9
2
18.6
20.0
20.1
19.8
18.6
18.6
18.6
18.7
22.3
22.3
19.7
3
13.9
111.7
111.8
15.6
9.3
13.9
13.9
9.0
16.7
16.7
111.9
II
15.1
15.8
16.0
16.9
15.9
15.1
15.1
16.8
18.1
18.1
16.3
5
11.8
15.6
18.7
17.8
17.7
16.1
17.9
18.2
18.5
19.1
17.1
6
11.8
15.8
19.0
18.1
18.1
16.2
18.2
18.11
-
7
17.1
19.5
21.3
16.2
111.7
13.0
12.5
12.0
9.8
'Based on 7.5 Joba (baaio industry) per HNBF (Hebo, FEIS, 1978,
p.57)
Averae
17.0
7.1
1II.3
TABLE 5.35
TIMBER EMPLOYMENT AND INCOME IMPACTS
RUN (Allocation Alternative)
Description
2
3
II
5
6
7
Average Annual Jobs
Supported:
1
Forest Industry
Service and Trade
19.9
39.8
19.7
11$ .8
39.1$
29.6
16.3
32.6
17. 1
17.0
111.3
3'I.2
311.2
28.6
Monies Returned
To Counties2
Business Inoo.e
Genera ted3
1L90'l.L.30
1t890,256
j.1123082
l5596111
l63OT0l
1613612
2±01112.990
33028,275
32777OO5
21$,677730
2j0II5±795
281116780
27982,755
3I1919777
'Based on 7.5 jobs (basic induety)
job. (Hebo FEIS, 1978, p.67)
per NMBF and 2.0 Service and Trade jobs per basic
2Based on a .onies returned to counties rate of 25 percent of gross stumpage values
(Ilebo FEIS, 1978, p. 67) and a discount rate of 6 percent.
3Business Income Generated is 3 times the average manufactured product value of $250/MBF
of logs consumed per 1972 data.
152
generated
alternative
by
study
area
timber
resource
production levels.
No attempt has been made
and
income
impacts
particular
for
differentiate between counties
economic
impacts
However,
because
dependencies
of
forest
Service supplied timber,
employment
and
income
volumes will differ.
communities
or
to
relative magnitude of
the
alternative
different
upon
identify the employment
to
harvest
communities
industry
volume
different
have
activity
levels.
Forest
and
the severity of local community
impacts
alternative
of
harvest
Given that the value of total output
by the wood products sector in Lincoln County is less than
that in Tillamook County,
the severity of Lincoln County
employment and income impacts of varying harvest levels can
be expected
Similarly,
to
be
given
possess only
3
less significant (Owens,
that
Lincoln
1981,
Tillamook
and
p.. 57).
counties
percent of the regional work force,
local
employment and income effects can be expected to be greater
than regional
employment
and
income
effects
(Hebo
FEIS,
1978, p. 171).
An
important
source
of
coastal
income
is
income
generated by recreational activities.
Forest lands of the
Coast
largest
Range
steelhead and
annually
salmon
fisheries (Daily,
contribute
to
the
the
states
sport and
numbers
of
commercial
1975) and provide important habitat for
deer and elk populations.
Consequently, changes in fishery
and big game populations can significantly affect local and
153
regional income derived from recreational fishing and big
game hunting activities.
Table 5.36 presents the estimated
local and regional income impacts of alternative study area
allocations of deer, elk and salmonids.
interretatjon of Results
The results reported in Tables 5.311 and 5.35 indicate
that
changes
forest
in
intensification
management
programs,
harvest policies
and
management
have
can
important
effects upon monies returned to counties and upon local and
regional employment and income.
The withdrawal of forest
acreage for wildlife and fishery habitat purposes on other
than
a
proportional bases
(Runs
and
1
significantly
2)
reduces monies returned to counties for all Runs except Run
7,
decreases local and regional timber related employment
for all Runs, and reduces local and regional timber related
income for all runs except Run 7.
returned to counties ranges
from
The reduction in monies
13
to
percent.
25
The
decrease in timber related average annual employment ranges
from 13 to 28 percent.
income ranges from 13
And the reduction in timber related
to 25 percent.
Run 7's accelerated
harvest of timber volumes during initials planning periods
increases the present net worth of timber monies returned
to counties and timber related income by 5.8
6.6 (Run 2) percent.
from
increases
decreases
of
of
414
(Run
and
1)
Deer related income differences range
11.5
to
7
to
15.2
percent
percent
from
Run
from
2.
Run
Elk
1
to
related
TABLE
5.36
NON-TIHBKR RESOURCE INCOME IHPACTS
RUN (Allocation Alternative)
Buatneas Income
Generated'
1
2
3
Deer
67551
B136B3
Elk
2tlrj!12
276L662
753.3O
265552
Salmonida
3,O2323 393IIOS3
5
6
763L619
75587B
768956
718O66
26133Il
2689O
27'IL8117
27OO15
35jL'I3B 355971 3955911 39293O1 395323
'Business
Inoome Oenerated Ia 1.99 tImes the present net worth of
average annual deer and elk harvest and salmonid escapements.
155
income
differences
percent from Run
to
from
increases
from
Run
Salmonid
2.
differences range from increases of 15.5
from Run
of
9.2
to reductions of 7 tenths of
1
percent
£1.8
range
114
1
percent
related
income
16.7 percent
to
and from a reduction or one-tenth of
1
to
percent
1
from Run 2.
Comparison of monies returned
counties and
to
and regional employment and income impacts of Runs
local
and
3
14
identify the local and regional economic impacts associated
with
the
increased
habitat
acreage
moderate
level
management
purposes
for
of
of
related
employment
percent.
Deer
1
timber
of
riparian
production
management
withdrawn
increases
percent.
management
and
returned
timber
harvest
timber
for
at
income
a
Intensified
production
counties,
to
related
related
wildlife
purposes
intensity.
acreage
monies
and
income
timber
by
increases
9.6
by
1
Elk harvest income is 'reduced by eight-tenths of
percent.
Salmonid
related
income
is
increased
by
less
than one-tenth of 1 percent.
The
effects
which
change
a
in
intensification can have upon monies returned
and
local
and
regional
employment
determined by comparing Runs
14
and 5.
and
management
to counties
income
can
be
Increasing the level
of management intensification from the Beuter et al. Target
A
levels
timber
to
monies
the Beuter et.
returned
to
al
Target
counties
employment and income by 5 percent.
B
and
levels increase
timber
related
Elk related income is
156
increased by 2 percent.
by
less
Salmonid related income increaes
than one-tenth of
generated business
income
while deer harvest
percent,
1
reduced
is
by
percent.
1
The
reduction of deer harvest related income is consistent with
empirical
findings
that
clearcuts
support
greater
deer
populations than do thinned stands.
An
indication
of
the
which
effects
a
change
of
rotation length can have upon monies returned to counties
and
local
determined
and
regional
comparing
by
income
Runs
5
employment
and
and
can
be
Shortening
6.
the
rotation length from 100 years to 80 years reduces monies
returned to counties and timber related income by less than
1.6
percent,
percent,
percent.
timber
and
related
salmonid
employment
related
Conversely,
less
by
income
less
by
shortening of rotation
the
than
1
than
1
length
increases deer and elk generated business incomes by
1.7
and 2.2 percent respectively.
The effects which a change in harvesting policies can
have upon monies returned to counties and upon local and
regional
employment
and
income
can
be
determined
comparing Runs 7 and 5 and Run 7 and Runs 3,
7
and
5
inventory,
comparisons
rotation
intensification.
Run
indicate
length
7
and
impacts
and
Runs
of
level
3,
indicate income and employment impacts
4
and
and 6.
by
Run
an
unchanged
of
management
6
comparisons
for differing levels
of management intensification, a shortened rotation length,
and an unchanged inventory.
The specification of target
157
harvest volumes 25 percent
greater than the even-flow of
volume values of' Run 5 for the first three planning periods
of Run 7 increases monies returned to counties and timber
generated business income by 23 percent over Run 5 levels.
While the average annual timber related employment
7
of Run
is 16.2 percent less than the average annual employment
value of Run 5, the average annual employment for the first
three
periods
of
Run
is
7
percent greater
25
than
the
average annual employment of the initial three periods of
Run 5.
The accelerated harvest of timber volumes during
initial
planning
horizon periods
increases
deer harvest
business generated income by 3 percent, elk harvest related
income by
four-tenths of
generated business
percent and
1
income
by
less
reduces salmonid
two-tenths of
than
1
percent.
The specification of target harvest volumes 25 percent
greater than the even-flow of volume values of Run
the
initial planning periods
of
Run
increases
7
5
for
monies
returned to counties and timber related income over Run 3,
4
and
levels
6
respectively.
by
While
29.2,
ZI1.6,
the
average
and
annual
2LI.9
percent
timber
related
employment of Run 7 is 3.7 percent less than Run 3,
percent less than Run
14
and
13.6
18.14 percent less than Run 6,
the average annual level of timber related employment for
the initial three periods of' Run
than
Run
3,
23.6
7
percent greater
percent greater than Run 6.
Run 7
is 33.5 percent greater
than
Run
LI,
and
19.14
deer harvest business
158
generated
income
is
3.2
percent greater than Run
Run
7
percent
and
14
1.6 percent greater
is
2.5 percent more than Run
3,
1.8
1.2 percent more than Run 6.
elk harvest related income
than Run
3,
Run
than
more
1.8 percent
and
24
less than Run 6.
Salmonid income difference between Runs 7
and Runs 3,
6
and
II
are less than one percent.
The economic impacts presented in Tables 5.324 - 5.36
identify
likely
the
affects
area
study
alternative
of
forest management programs, management intensification and
harvest policies upon monies returned to counties and local
and regional employment and income.
The extent to which an
area or region's economy is adversely affected by changes
in harvest.volumes or non-timber resource production levels
is
dependent
many
upon
Although
variables.
timber
resources may provide the primary source of employment and
income
of
an
area
comparable
or
of
vitality of
would be
an
lost
and
secondary
production levels.
importance
to
may
the
be
reduced timber and
The
manner
in
of
economic
not all such employment and
area,
by
resource
non-timber
income
non-timber resource
which
the
timber
and
recreation sectors adapt to future output levels will have
a tremendous impact on
the local economy.
Additionally,
the vitality of the other basic sectors of the economy will
play an important role in formulating future changes in the
economy.
For
the
purposes
of
the
analysis,
the
local
and
regional impact of dollar of business income generated by
159
big game hunting and fishing activities was equated to
dollar generated
by
timber industry.
the
a
the extent
To
that timber and non-timber business generated dollar values
are
not
equal,
the
significance
local
of
alternative
multiple use resource allocations are incorrectly estimated
(Ridd,
196)4).
Thus
far,
multiple
discussion
the
resource
use
of
simulated
allocations
study
area
considered
has
the
economic
impacts of alternative management strategies or
resource
allocations
While
estimated
valuations,
separately
allocation
monies
resource
returned
to
physical
from
impacts.
production,
counties,
output
employment
and
income impacts occur at different points in time, physical
and economic impacts are assummed to occur concurrently for
analytical purposes.
Table
summarizes
5.37
estimated
the
physical
and
economic impacts presented in Tables 5.11 - 5.2k and Tables
5.26
-
for
5.36
resource
simulated
the
allocations.
study
Comparison
area
of
the
multiple
use
alternative
multiple use resource allocations presented in Table 5.37
identifies
the
selecting one
physical
and
economic
consequences
of
study area management strategy or multiple
use resource allocation which excludes study area cattle
grazing
grazing.
5.37
over
another
or
others
which
exclude
cattle
The absence of cattle grazing figures in Table
reflects
the
restriction
of
resource
allocation
presentations to only those alternatives with the greatest
TRIILE 5.31
PHYSICAL AND ECONOMIC IMPACTS OP AI.TERN&TIVE STUDY AREA
MULTIPLE USE RESOURCE AI.I.00ATIONS
MULTIPLE USE RF..SOURCE AllOCATION
DESCRIPTION
2
I
1*
3
6
5
7
Ti MO ER
Production (average annual)
MOrE
HCUFT
2,650
2,650
1196
i .900
312
7,170
1196
1103
1130
'*38
Present Net Ih,rth'
1.910
311
2,011,21111
1.998, 157
1,595,813
Return to Counties (INN)
Jobs supported''
Forest Industry
Servioe & Trade'''
Business Income Generated (PNW)
1.473,060
1,639,1199
1,9115,1170
1,9011,630
1,890 256
2,015,971
1,1123,082
1,551,61*1
1,618,701
1,613,672
2,0111,990
19.9
39.8
33.020,275.0
111.8
19.7
39.11
32,779,005
2.200
16.3
32.6
2,260
17.1
17.0
111.3
29.6
311.2
211,677.730.027,0115,795.020,1116,780.0
311.0
27,982,755.0
20.6
311,919,777.0
1139.3
11111.6
11*6 .3
386 , 11 10
1117.1
390. 9 88
760,956
778,066
DEER
Production
Gralng Potential (0.1.)
Harvest Potential (33.3$ UP)
Present Net WorthllC
Business Income Generated (INN)
383.11
1161.0
1127 .6
127.7
153.8
*112.11
339,1173
1108.686
370,600
675,551
813,683
753, 11 30
1133.11
11111.3
1129.0
1112.9
383,7113
763,6119
379,838
755,870
133,1111 3
110.3
23.1
132,329
211.2
135, 121
138,1111
135 .686
265,552
261,3311
260,890
2111,8117
210,015
1,118.2
1,987.928
3.955.917
1,118.2
1,981,928
3,955,977
CATTLE
Production
Present Net Worth
Business income Generated (PRy)
ELK
Production
Grazing Potential (0.1.)
Harveat Potential (20$ 0.P.)
Present Net Worth'''
Buaineee Incoae Generated (INN)
SALNONIDS
Production
Eseepeaent Potential
Present Net North
Business Income Generated (PNW)'''
SPOTTED OWL
Habitat average
Number of paLr,
DALD EAGLE
Habitat average
Number of paIrs
''
'00.6
21.1
121,162
2111,112
1211.3
211.9
139,026
276,662
119.11
23.9
1,112.0
961.7
1,709,710
1,976,911
1,117.2
1,986,150
3.1102,323
3,9311,053
3,952,1138
0
300
300
0
0
0
0
110
300
120.8
121.6
1211.3
24.9
1,110.0
9711,526
3,929.307
24 . 3
116.6
1,985,087
3,950,323
300
300
300
110
110
110
I
110
40
I
0
based on a monies returned to counties rate of 25 percent of gross st.Iapel'.e
values, stuiepage valued a 81*73/liD? (limbo PEIS, 1*978, p.67) end a dineoupit ,at
01
1
6 percent.
based on 7.5 fobs (basic industry) per MHDF and 2.0 service
sod trade jobs per basic job (111.11*0 1.1.13, 1978, p.61)
Tiaber buines income genera Led iv 3 times the average sanu fac Lured prodact. vs lue of 5250/MOP of logs consumed per 1972
data
discounted at 6 percent. Deer, elk, and ealmonid business incomC Cencratod is 1.99 t!n,es the preseol net worth of
harvested big gnm.
animals and salmo,,Ids (Rvhdy sod l.ovegrove, 1970).
161
present net worth.
At current grazing rates, present net
worth gains associated with alternative levels of cattle
grazing intensities are greatly outweighed by present net
worth
losses
associated
with
reduced
salmonid escapements (Table 5.31).
elk
harvests
and
162
Summary and Conclusions
VI.
Introduction
Forested
excellent
watersheds
examples
of
Oregon
the
multiple
of
Range
Coast
resources.
natural
use
are
Coastal forest lands simultaneously supply resource outputs
such
as
recreation,
wildlife
which
independent
timber,
interrelated
are
complementary
and
relationships.
Forest
through
physical
multiple
fisheries
range,
water,
use
and
competitive,
biological
and
while
resources,
abundant by many standards are indeed limited. As a result
choices
have
to
combinations
of
be
regarding
made
forest
multiple
use
the
levels
resources
to
and
be
provided. The economic criterion for maximizing the returns
from
f6rest
that
marginal
land
outputs
value
well-known prescription
the
is
products
should
be
equal
for
all
resource outputs. However, serious problems are encountered
in allocating
forest
multiple
use
resources because
the
dynamic and complex biological and physical relationships
between and among forest land renewable surface resources
are
little
understood
and
the
extra
market
nature
of
various multiple use resources produces an absence of data
regarding resource values and provision costs.
Research Summary
The stated objectives of this research were:
(1)
to
define an analytical framework which facilitates allocation
163
decision-making regarding multiple use resources and (2) to
test
the methodology
for operationality,
analyze results
and evaluate model performance. Criteria were the need to
specify little understood complex and dynamic multiple use
resource
production
simultaneously
relationships
and
consider
to
large number of management alternatives
a
for alternative planning horizons using a heterogeneous set
of
resources.
provided
by
Joint
production
forest
a
theory
simulation
information
and
system
was
used
to
construct the analytical framework.
The analytical approach was tested on the upper middle
portion
of
the
Drift
Creek Watershed
located within
the
Hebo Ranger District of the Siuslaw National Forest on th
Oregon
Coast
Range.
Managed
accordance
in
with
the
provisions of the Multiple Use-Sustained Yield Act of 1960,
the
Resources
administered
Planning
Act
provide
to
including timber,
range,
1976,
of
numerous
water,
the
multiple
watershed
use
recreation,
is
resources
wildlife
and
fisheries. For the purposes of the study, the consideration
of study area multiple use resources was limited to timber,
deer,
elk, cattle grazing, salmonids,
bald
eagle
pairs.
Area
timber
and spotted owl and
yield
information
was
obtained from Forest Service personnel and planning unit
documents.
Data
describing
the
non-timber
multiple
use
resource joint production relationships were obtained from
Forest
Service
documents
and
personnel,
from
other
Forest
Service
published
planning
sources.
unit
Non-timber
164
multiple use resources joint production relationships for
deer,
cattle
elk,
grazing
salmonid
and
were
fisheries
expressed as annual production coefficients per acre and as
functions
forest
of
coefficients
for
stand
cattle
deer,
production
Resource
age.
identified
elk
and
the
maximal stocking rate allowable without causing damage to
forage and
timber resources;
identified
salmoriids
production coefficients
escapement
annual
numbers
for
fish.
of
Non-timber resource productivity parameters were combined
harvest volume
TREES
with
inventory
timber
and
data
to
project study area multiple use resource allocations for
seven forest management strategies.
The study area resource production estimates, resource
value projections and employment and income impacts of' the
simulated resource allocations were compared with estimates
reported
Forest
in
presented
production
in
Service
various
Planning
for
documents
studies.
empirical
projections
Unit
timber,
area
Study
cattle,
or
elk
and
salmonids were found to be comparable with results reported
in
Hebo
alternative
Planning
Unit
empirical
documents
studies.
harvest potential projections
and
Study
for
area
deer were
presented
grazing
found
to
in
and
be
significantly different from U.S. Forest Service estimates,
but were found
Hines
to
(1973, 1975)
be consistent with finding reported by
and Sturgis
(1977) for forest areas with
comparable physiographic characteristics.
165
Study area multiple use resource production values for
timber,
salmonids
consistent
with
found
reported
valuations
resource
were
grazing
cattle
and
be
to
Forest
in
Service documents and presented in published multiple use
resource
valuation
studies
Gibbs, Queirolo, Lomnick,
(Brown,
1979;
1982;
1978; Mathews
Flebo, FEIS,
1977;
1973; Statistical Reporting Service,
and Brown,
1975;
Everest,
and
USDA, 1976). Study area resource allocation values for deer
and elk were found to be significantly different from the
gross expenditure values derivable from area Planning Unit
documents
1978, p.161) but were
(Hebo FEIS,
consistent with big game
valuation
game
studies
Nawas
be
1973;
Stevens,
and
1981).
Gibbs, Queirolo, Lomnicki, 1979; Shallof,
to
in various big
values reported
(Brown,
found
Study area
allocation resource production value projections were found
to
significantly
be
different
Service
Forest
from
estimates.
Resource production values were projected
all
area
study
resources
and
reported
in
terms
of
for
the
present net worth of the average annual net resource values
discounted at
percent; Forest Service documents provide
6
resource
production
expressed
in
terms
timber
only
average annual current
gross
estimates
value
of
the
for
values.
Study
area
timber
related
extension
returned
projections
income
values
to
of
and
utilized
counties,
monies
returned
employment
to
timber
derive
to
utilized
Hebo
production
counties,
same
the
FEIS
monies
employment,
and
166
generated business
income
figures.
Study area allocation
economic impact projections include forecasts of deer, elk,
and
salmonid
business
Planning Unit
incomes
documents.
absent
Forest
in
multiplier used
The
to
Service
project
non-timber multiple use resource business income was found
to be consistent with multiplier values reported by Rohdy
and Lovegrove (1970), Rompa (1979), and Youmans, Rompa, and
Ives
(1977).
production
monies
As was
values,
returned
the case with multiple use resource
study
to
area
counties,
allocation projections
elk
deer,
timber,
of
and
salmonid business income impacts were reported in terms of
net present values while identified planning unit economic
impacts were reported for timber only in terms of average
annual current dollar values.
Research Conclusions
Study area multiple use resource output figures, production
values and economic impact estimates were found to provide
several advantages over Forest Service projections.
resource production estimates are reported
for all
First,
study
area multiple use resources and are presented on both an
average annual bases for allocation planning horizons and
on an average annual bases for allocation planning horizon
decade-periods.
projections are
Secondly,
presented
allocation
for
all
resource
considered
study
value
area
multiple use resources, are reported on an average annual
bases
for
planning horizons and planning horizon decade-
167
periods, and are reported in terms of net present values.
Thirdly,
study
area
business income
economic
forecasts
projections
impact
area
study
considered
all
for
include
multiple use resources and all income and monies returned
to counties values are expressed in terms of net present
values.
An Appraisal of the Research
The
purpose
of
this
analytical framework useful
research
to
was
to
develop
managers of multiple
an
use
A model may be considered useful or successful
resources.
on the bases of several'criteria.
First, the formulation
shuld be consistent with available information.
Secondly,
it should provide greater insight and understanding of the
phenomona being investigated than do alternative models.
And
thirdly,
future
the
model
occurrences,
should
be
particularly
capable
of projecting
ocnditions
under
that
differ from the past.
The analytical framework employed
in
this study was
developed after an extensive examination and evaluation of
available information. Study area resource joint production
potentials
were
production
levels
found
to
presented
be
in
with
resource
Service
planning
consistent
Forest
documents or reported in comparable area studies.
traditional
forest
management
models
which
Unlike
restrict
consideration to impacts upon timber yields, the developed
framework simultaneously considers the
impacts
of forest
168
management
programs,
management
intensities
harvest
and
polices upon an array of multiple use resources.
The model
transforms several sets of complex resource relationships
which form a forest ecosystem into a few sets of allocation
alternatives
which
evaluation.
The
output
levels
themselves
lend
to
examination
and
analytical framework forecasts resource
throughout any
specified planning horizon.
Timber and non-timber resource production coefficients can
easily be adjusted to reflect new of differing information.
And
the
inherent
of TREES
flexibility
provides
for
the
projection of multiple use resource allocations for a wide
variety of forest management strategies.
Management
information
certainly should
planning process.
to
forest
be
the
beneficial
managers
framework such
use
the
to
as
and
this
obtaining results from the model.
multiple
type
above
presented
forest management
One of the benefits expected to accrue
resource
analytical
of
resource
data
to
planners,
one,
is
using
incidental
an
to
The methodology requires
be
assembled.
simple
The
process of data assembly may reorientate thinking away from
the more tradtional forest management emphasis upon timber
production and towards the management of a forest area for
multiple
use
compilation
resource
of
purposes.
multiple
use
The
collection
resource
and
information
contributes to the determination of the real but unspeci-
fled multiple use and sustained-yield relationships among
forest renewable resources as required by Section
.
(5)(A)
169
of the National Forest Management Act, 1976. The analytical
framework
identifies
dynamic
resource
changes
supply
associated with alternative forest management strategies,
providing
forest
resource
supply
mandated
by
managers
resource
resource product-product
and
Sec.
planners
and
information
National Forest Management
the
of
2(1)
with
Act, 1976.
The applicaiton
of
analytical
the
framework
the
to
Upper Middle Drift Creek Watershed appears
to
successful.
physical and
methodology projected
The
the
have been
economic consequences of seven alternative allocations of
study area
eagle
timber,
and
spotted
owl
salmonid
cattle,
deer,
resources.
Other
fishery,
results
bald
can
be
derived by utilizing different sets of production data and
forest management strategies.
Several
framework
disadvantages
stem
from
of
data
its
using
analytical
the
requirements.
First,
the
complex and dynamic relationships between and among forest
land renewable surface resources are lj.ttle understood and
have
received
1976;
Teeguarden,
product
quantitiative consideration
1977).
Ecosystem
data
or
(Davis,
resource
data, if available at all, are generally of poor
quality.
to
little
Secondly, large quantities of data were required
simulate
Watershed
fisheries.
conditions
for
timber,
on
the
deer,
Upper
elk,
Middle
cattle,
Drift
and
Creek
salmonid
To derive non-timber resource output figures
for each of the considered allocation alternatives required
170
the multipication of a 336 element matrix by a 2140 element
matrix.
expansion
The
of
framework
analytical
the
to
consider all possible multiple use resources of the study
area would necessitate the collection of gargantuan amounts
of
data
and
manipulation
the
matrices
of
tremendous
of
proportions.
Third,
project
joint production coefficients utilized
the
allocation
output
identified
figures
resource annual production averages
in
the
analysis
to
expected
rotation decade-
for
periods and were presummed to be deterministic.
was made
to
No attempt
consider important risk and
uncertainty issues associated with the long-term nature of
the forestry production process.
not
address
policy
Moreover, this thesis did
implications
resource
average
output
marginal
resource
productivity
associated
figures
as
substitute
a
values.
using
with
for
marginal
Without
values, however, there can be no guarantee that resources
will not be allocated inefficiently.
In
addition,
the
problem
identifying
of
the
appropriate social values and costs for nonpecuniary forest
land
outputs
framework
is
difficult
indicates
the
allocation alternatives,
of
multiple
use
at
The
best.
consequences
of
analytical
selecting
among
it does not indicate what levels
resources
society
prefers
or
whether
society's willingness to pay for a particular multiple use
resource is as large as the opportunity cost of providing
the resource.
Resource and
discount rate
values used
in
171
this analysis were
a representative sample of valuations
utilized in non-marketed forest land resource studies.
No attempt was made to evaluate one resource valuation
In the case of
figure as superior to another or others.
the interest rate employed in the analysis, no attempt was
made
differentiate between real
to
and
nominal rates
of
interest or between individual and social time preferences.
Consideration of disadvantages and problems associated with
this
other
and
approaches
deferred
is
subsequent
to
research.
positive
the
On
obtained
from
this
side,
quality
the
justifies
applicaiton
trial
information
of
a
considerable amount of optimism regarding the expansion of
the analytical framework to include additional multiple use
resources and
the application of the model to additional
study areas.
Multiple use resources of the Upper Middle
Drift
Creek
Watershed
have
been
placed
in
economic
perspective and economic values and impacts associated with
some multiple use resource trade-offs have been identified
in
the
course
resource
of
investigating alternative multiple
allocations.
constructed
which
An
provides
informational
forest
base
resource
has
managers
use
been
and
planners with an opportunity to estimate the physical and
economic consequences of forest management strategies and
to
revise
manner.
those
estimates
in
a
relatively
inexpensive
172
BIBLIOGRAPHY
Adams, D. M. t97L1.
Forest Products Prices and National
Forest Timber Supply in the Douglas-fir Region.
Forest Science 20:2113259.
Adams, D. M.
1977. Effects of National Forest Timber
Harvest on Softwood Stumpage, Lumber, and Plywood
Oregon State
Markets:
An Econometric Analysis.
University, Corvallis. Forest Research
Laboratory.
Research Bulletin 15. 50 p.
Adams, D. M. and A. R. Ek. 19711.
Optimizing the Management
of Uneven-aged Forest Stands. Canadian Journal
Forest Research. 11.:27k_287.
Adams, D. M. and R. W. Haynes. 1980. The 1980 Softwood
Timber Assessment Market Model: Structure,
Projections, and Policy Simulations. Forest
Science Monograph 22. 62 p.
Alderdice, D. F., W. P. Wickett and J. R. Brett. 1958. Some
Effects of Temporary Exposure to Low Dissolved
Journal of
Oxygen Levels on Pacific Salmon Eggs.
Fishery Research Canada. 15(2):229-250.
Alston, R.
1972.
Goals and Decision-Making in the Forest
Intermountain Forest and Range
Experiment Station, Ogden.
Service.
Amidon, E. L. and E. M. Gould, Jr. 1962.
The Possible
Impact of Recreation Development on Timber
Production in Three California National Forests.
Pacific Southwest Forest and
USDA Forest Service.
Technical Paper 68.
Range Experiment Station.
Armour, C. L. 1977.
Effects of Deteridrated Range Streams
on Trout.
U.S. Dept. of Interior, Bureau of Land
Management.
Idaho State Office, Boise, Idaho.
p.
7
Armstrong, F. H. 1969. Forest Management by Parametric
Linear Programming. Ph.D. Thesis. Duke
University.
Arrow, K. J. and R. C. Lind. 1970.
Uncertainty and the
Evaluation of Public Investment Decisions.
American Economic Review 6O:364-378.
Arrow, K. J. and T. Scitovsky.
1969. Readings in Welfare
Economics.
Vol. 12, Homewood.
173
Baily. A. W. 1966. Forest Associations and Secondary Plant
Succession in the Southern Oregon Coast Range.
Ph. D. Thesis.
Oregon State University,
Corvallis.
Bare, B. B. 1971. Applications of' Operations Research in
Forest Management:
A survey.
University of'
Washington, Seattle.
Center for Quantitative
Science in Forestry, Fisheries and Wildlife.
Quantitative Science Paper 26. 51 p.
Basile, J. V. and T. N. Lonner. 1979.
Vehicle Restrictions
Influence Elk and Hunter Distribution in Montana.
Journal of Forestry 77:155-159.
Bator, F. N. 1958. The Anatomy of Market Failure.
Quarterly Journal of Economics. Vol. 72. August
pp. 365-371.
Baumol, W. J. 1975.
The Theory of Environmental Polic;
Externalities, Public Outlays and Quality of Life.
Englewood Cliffs, Tew Jersey. Prentice-Hall.
272 P.
Behnke, R. J. and M. Zarn.
Biology and Management of
1976.
Threatened and Endangered Western Trouts.
USDA
Forest Service.
General Technical Report RM-28
p. 15
Rocky Mountain Forest and Range Experiment
Station.
Fort Collins, Colorado.
Bell, E. F. 1975.
Problems with Goal Programming on a
National Forest Planning Unit.
pp. 119-126 in
Systems Analysis and Forest Resource Management.
Proceedings of a Workshop sponsored by Systems
Analysis Working Group, S.A.F. USDA Forest
Service, Southeast Forest and Experiment Station
and School for Resource, University of Georgia,
Athens. Aug. 11-13.
Bell, E. F.
1976.
Goal Programming for Land Use Planning.
USDA, Forest Service. General Technical Report
PNW 53:14_5.
Bell, E. F. 1977. Mathematical Programming in Forestry.
Journal of Forestry 75:317-319.
Bellman, R. E. Dynamic Programming.
Press.
Princeton University
174
Beschta, R. L. 1978. Long-term Patterns of Sediment
Production Following Road Construction and Logging
Water Resource
in the Oregon Coast Range.
Research 1I (6):1O11-1016.
Beuter, J. H., K. N. Johnson and H. L Scheurman.
1976.
Timber for Oregon's Tomorrow: An Analysis of
Reasonably Possible Occurences. Forest Research
Oregon State
Laboratory.
School of Forestry.
University.
Research Bulletin 19.
Bishop, R.
C. 1978.
Endangered Species and Uncertainty: the
American
Economics of a Safe Minimum Standard.
Journal of Agricultural Economics. 60 (February):
10-18.
Black,
Fl.
Wildlife and Reforestation in the
(ed.) 1969.
Oregon
Pacific Northwest.
School of Forestry.
State University, Corvallis. 92 p.
C.
Black, H. C. (ed.) 1971.
Wildlife and Forest Management in
the Pacific Northwest. School of Forestry.
Oregon State University, Corvallis. 236 p.
Black, P. E. 19614. Timber and Water Resource Management.
Forest Science 9(2):137.-1I5.
Forest Diversity--New
Boyce, S. G. and N. D. Cost. 1978.
Concepts and Applications.
USDA Forest Service.
Research
Southeast Forest Experimental Station.
Asheville, N. D. 36 p.
Paper SE-1914.
Braizier, 3. R. and G. W. Brown. 1972.
Buffer Strips for
Stream Control.
Oregon State University,
Corvallis.
Research Paper No. 15. 12 p.
Brewer, M. F. 1961.
Pricing Publicly Owned Range and Water
Resources.
Water and Range Resources and Economic
Report No. 9, University
Development of the West.
of Arizona, Tucson.
Analysis of
Brodie, J. D., D. M. Adams, and C. Kao.
1978.
Economic Impacts on Thinning and Rotation for
Douglas-fir Using Dynamic Programming. Forest
Science 214:513_522.
Oregon's
Brodie, 3., R. McMahon, and W. Gravelis.
1978.
Forest Resources: Their Contribution in the
State's Economy. Forest Research Laboratory.
Research
Oregon State University, Corvallis.
Bulletin 23, 80 p.
175
Bromley, D. W. 1969.
Economic Importance of Federal
Grazing:
An Interindustry Analysis. Journal of
Range Management 22 (i):9-124.
Bromley, D. W., G. E. Blanch, and H. H. Stoevener.
1968.
Effects of Selected Changes in Federal Land Use in
a Rural Economy. Agricultural Experimental
Station Bulletin No. 6o4.
OregonState
University, Corvallis.
Brookshire, D. S., L. S. Eubank, and A. Randall. 1978.
An Experiment.
Valuing Wildlife Resources:
Forty-Third North American Wildlife Conference.
pp.
302-310.
Brookshire, D. S. and A. Randall. 1978.
Contingent
Valuation Methods for Nonmarket Goods. Presented
to annual meeting of Western Economic Association,
Honolulu, June.
Brookshire, D. S., A. Randall, and J. R. Stoll. 1980.
Valuing Increments and Decrements in Natural
Resource Service Flows. American Journal of
Agricultural Economics 62:2478-2488.
Brown, E.
R. 1961.
The Black-tailed Deer of Western
Washington.
Biological Bulletin 13. Washington
State Game Department.
Brown, G. Jr. 1977.
Promising Research Topics Regarding
Non-Timber Products From Forest Related Lands.
Clawson (ed.), Research in Forest Economics and
Forest P+olicy.
Resources for the Future,
Washington, D.C.
pp. 191-212.
Brown, G.
W.
1969.
Streams.
M.
Predicting Temperatures of Small
Water Resources Research 5(1):68-75.
Brown, G. W. and J. T. Krygier, 1970. Effects of ClearWater Resources
Cutting on Stream Temperature.
Research 6(14):1133-1139.
Brown, T. C. 1976. Alternative Analysis for Multiple Use
Management:
USDA Forest Service.
A Case Study.
Rocky Mountain Forest and Range Experiment
Station. 16 p.
-
Brown, T.
C. 1981.
Tradeoff Analysis in Local Land
Rocky
USDA, Forest Service.
Management Planning.
Mountain Forest and Range Experiment Station.
General Technical Report RM-95.
176
Brown, W. G., F. H. Nawas, and J. B. Stevens. 1973. The
Oregon Big Game Resources:
An Economic
Evaluation.
Oregon State Agricultural Experiment
Station Special Report No. 379. Corvallis.
Brown, W. G., A. Singh, and E. N. Castle. 19614.
An Economic
Evaluation of the Oregon Salmon and Steelhead
Sport Fishery.
Oregon State Agricultural
Experiment Station.
Technical Bulletin 78.
Corvallis.
Buchanan, D. U., P. 5. Tate, and J. R. Morning. 1976. Acute
Toxicities, of Spruce and Hemlock Extracts to Some
Estuarine Organisms in Souteastern Alaska.
Journal of Fishery Research.
Canada 33(5):
1188-1192.
Buchanan, J.
M.
1968.
Goods.
The Demand and Supply of Public
Rand McNally, Chicago.
Buffington, C. D. and T. H. Ripley. 19714.
Trade-offs in
Multiple Use.
University of Kentucky, Lexington.
Mimco. pp. 117-120.
Burt, 0.
R.
Burt, 0.
R. and D. Brewer, 1971.
Estimation of Net Social
Benefits from Outdoor Recreation. Econometrica
19614.
Optimal Resource Use Over Time with an
Application to Ground Water.
Management Science
(Series A)
11:80-93.
39(5) :813-27.
Bury, R. B., H. W. Campell, and N. J. Scott. Jr. 1980.
Role
and Importance of Nongame Wildlife. Transactions
of North American Wildlife and Natural Resource
Conference 145: 197-203
Campbell, D. L. and J. Evans. 1980.
Improving Wildlife
Habitat in Young Douglas-fir Plantations.
Proceedings Forty-fifth North American Wildlife
Conference 145:58-69.
Carlson, S. 1956.
A Study on the Pure Theory of Production.
Kelley and Millman, New York. 128 p.
Castle, E.
1965. The Market Mechanism, Externalities,
and Land Economics.
Journal of Farm Economics 117:
N.
5142-556.
177
Castle, E. N. 1966.
Multiple Use Relationships-Timber
Production and Fishery Resources.
Paper Prepared
for the Society of American Foresters at Seattle,
Washington. Sept. 114.
Cesario, F. J. and J. L. Knetsch. 1970. Time Bias in
Recreation Benefit Estimates.
Water Resources
Research 6: 700-704.
Chappelle, D. E. 1966.
A Computer Program for Scheduling
Allowable Cut Using Either Area or Volume
Regulation During Sequential Planning Periods.
USDA Forest Service.
Pacific Northwest Forest and
Range Experiment Station.
Research Paper PNW-33.
p. 9.
Chappelle,
0. E. 1977. Linear Programming for Forestry
Planning.
F. J. Convery and G. W. Ralston (eds.)
Forestry and Long Range Planning. School of
Forestry and Environmental Studies. Duke
University Durham.
Cicchetti, C. J., A. C. Fisher, and K. V. Smith.
1973.
Economic Models and Planning Outdoor Recreation.
Operations Research.
Vol. 21. Sept/Oct.
pp.
11O4-1113.
Ciechetti, C. J. and K. V. Smith.
1973. Congestion,
Quality Deterioration, and Optimal Use. Social
Science Research 2 (1).
Ciriacy-Wantrup, S. V. 1938.
Multiple and Optimum Use of
Wildiand Under Different Economic Conditions.
Journal of Forestry 36:665-714.
Ciriacy-Wantrup, S. V. 1968.
Resource Conservation:
Economics and Policies.
University of California
Division of Agriculture Sciences, Berkeley and Los
Angeles.
Clawson, M.
1959. Methods for Measuring the Demand For and
Value of Outdoor Recreation.
Reprint No. 10.
Resources for the Future, Inc., Washington, D.C.
Clawson, M. 19714. Forests for Whom and For What?
Resources
for the Future, Inc.
The John Hopkins University
Press. p. 119.
178
Conflict, Strategies, and Possibilities
Clawson, M. 1975.
For Consensus in Forest Land Use and Management
In:
Forest Policfor the Future.
M. Clawsori
Resources for the
RFF Working Paper LW-i.
(ed.).
Future, Inc., Washington, D.C. pp. 105-192.
The Economics of National Forest
Clawson, M. 1976.
Resources For the Future, Washington,
Management.
D. C. June.
Decision Making in Timber Production,
Clawson, M. 1977.
Resources for the Future,
Harvest and Marketing.
Washington, D. C.
Clawson, M. and J. L. Knetsch.
1966. Economics of' Outdoor
Recreation.
John Hopkins Press.
Cohen, J.
1978.
Multiobjective Programming and Planning.
Academic Press, New York. 370 p.
A Review and Evaluation of
Marks. 1975.
Cohen, J. and D.
Multiobjective Programming Techniques. Water
Resource Research 11 (2):208-220.
I-I.
Connaughton, K. P. and W. McKillop.
1977. Impact of
Changing Levels of Timber Output on Local
Employment and Income in Selected Northern
Report to USDA, For. Serv,
California Counties.
Pac. Southwest Exp. Stn, Dept. For. and Conserv.,
University of California, Berkeley. p. 71.
Connaughton, K. P. and W. McKillop.
1979. Estimation of
Small Area Multipliers for the Wood Processing
Sector--an Econometric Approach. Forest Science
25 (i):7-20.
Convery, F. J. 1973.
Unit Planning and Local Economic
Impacts of Alternative Forest Management
School of
Technical Paper No. 1.
Practices.
Forestry.
Duke University, Durham.
Research
Convery, F. J. 1977.
Land and Multiple Use. In
in Forest Economics and Forest Policy. M. Clawson
(ed.) Resources for the Future, Washington, D. C.
:
Convery, F. J. and C. W. Rader.
1976. The Valuation of
Water Flowing from Federal Watersheds in the
Minerals and Watershed
South:
An Inquiry.
Regional Office, U. S. Forest Service,
Division.
Atlanta.
179
Convery, F. J. and C. W. Ralston (eds). 1977.
Forestry and
Long Range Planning.
School of Forestry and
Environmental Studies.
Duke University, Durham.
Copeland, J. 1933.
Copeland Report. A National Plan for
American Forestry.
U.S. Forest Service. U.S.
Government Printing Office, Washington, D. C.
Cowan, T.
M.
Daily, N.
Oregon Salmon and Steelhead Catch Data,
Oregon Department of Fish and Wildlife.
Fishery Division.
Portland, Oregon.
19145.
The Ecological Relationships of the Food
of the Columbian Black-Tailed Deer, Odocoileus
hemionus Columbianus (Richardson), in the Coast
Forest Region of Southern Vancouver Island,
British Columbia.
Ecology Monograph 15:109-139.
1975.
1965_714.
Dana, S. T. 19143.
Multiple Use Biology and Economics.
Journal of Forestry (editorial) 141:625-626.
Dana, S.
T.
Forest and Range Policy.
1956.
McGraw-Hill,
New York.
Dane, C. W., N. C. Meador, and J. B. White.
Programming in Land-Use Planning.
Forestry 75: 325-329.
1977.
Goal
Journal of
Daniel, T. C., E. H. Zube and B. L. Driver. (Tech. Coords).
1979.
Assessing Amenity Resource Values.
USDA
Forest Service.
Rocky Mountain Forest and Range
Experiment State.
General Technical Report RM-68.
70 p.
Dantzig, C. 3. 1960.
Linear Programming and Extensions.
University Press, Princeton, New Jersey.
Darr, D. and R. D. Fight.
19714.
Douglas County:
Potential
Economic Effects of a Changing Timber Resource
Base.
USDA Forest Service.
Pacific Northwest
Forest and Range Experiment Station. PNW-179.
141
p.
Davis, G. E.,
J. Foster, C. E. Warren, and P. Doudoroff.
The Influence of Oxygen Concentration on
the Swimming Performance of Juvenile Pacific
Salmon at Various Temperatures. Transactions
American Fisheries Society 92(2):111_1211.
1963.
Davis, K.
P.
What Multiple Forest Land Use and For
Journal of Forestry. Oct. pp. 718-721.
1969.
Whom?
180
Davis, L. S. 19711. A Model for System Assessment and Data
Gaps in the 1975 Assessment.
Seminar Report from
Utah State University on Resources Planning Act of
19714.
Mimeo. Logan.
pp. 13-23.
Davis, R. K. 196.
Value of Big Game Hunting in a Private
Forest.
Transactions 29th North American Wildlife
and Natural Resources Conference.
Las Vegas,
Nevada.
March 9-11.
James B. Trefethen, Ed.
Wildlife Management Institiute, Washington, D. C.
pp. 393-1403.
Dillion, J. L.
The Analysis of Response in Crop &
1968.
Livestock Production.
Pergamon Press, Oxford, New
York. p. 135.
Dorfman, R, and N. S. Dorfman.
Economics of the
1972.
Environment; Selected Readings. W. W. Norton, New
York.
Duerr, W. A. 1960.
Fundamental of Forestry Economics.
McGraw-Hill, New York.
579 p.
Duerr, W. A., D. E. Teeguarden, S. Guttenberg, and N. B.
Christiansen.
Forest Resource Management:
1975.
Decision-Making Principles and Cases.
Oregon
State University Book Stores, Inc., Corvallis.
Duerr, W. A., D. E. Teeguarden, S. Guttenberg and N. B.
Christiansen. 1979. Forest Resource Management:
Decision-Making Principles and Cases.
Oregon
State University Book Stores, Inc., Corvallis.
Duff, D. A. 1977.
Livestock Grazing Impacts on Acquatic
Habitat in Big Creek, Utah.
In. Symposium on
Livestock Interactions with Wildlife, Fisheries,
and their Environment. USDA, Forest Service,
Reno, Nevada.
Dwyer, J. F., J. H. Kelley, and M. D. Bowes.
1977.
Improved Procedures for Valuation of the
Contribution of Recreation to National Economic
Development.
Water Resources Center Research
Report No. 128.
University of Illinois, UrbanaChampaign.
Dyer, A. A., J. G. Hoff, J. W. Kelley, S. A. Crim, and G. S.
Alward. 1979.
Implications of Goal Programming in
Forest Resource Allocation.
Forest Science 25(11):
5355143
181
Eckstein, 0. 1958.
Water-Resource Development. Harvard
University Press, Cambridge.
Everest, F. H. 1975.
A Method of Estimating the Value of
Streamside Reserve Trees.
Siskiyous National
Forest, Grants Pass, Oregon.
p. 12.
Everest, F. H. 1978.
Flow to Persuade Interdisciplinary Team
Members and Resource Managers that Fishery
Proceedings Western
Considerations are Important.
Division Fish and Game Conservation Commission
Annual Meeting.
Sun Valley, Idaho.
Everest, F. H., and W. R. Meehan.
1981. Forest Management
and Anadromous Fish Habitat Productivity.
Transactions North American Wildlife and Natural
Resources Conference.
46:52153O.
Fairfax, S. K. 1977.
the
Politics and Bureaucracy:
Multiple Use Sustained-Yield Act, A Cas'e Study.
In. Forestry and Long-Range Planning. F. J.
Convery and C. W. Rader (eds.). School of Forestry
and Environmental Studies.
Duke University,
Durham.
Ferguson, C. E.
1971. The Neoclassical Theory of
Cambridge University
Production and Distribution.
Press.
383 p.
Ferguson, C. E. and J. P. Gould. 1975.
1975. Microeconomic
Theory.
Richard D. Irwin, Inc., Homewood.
Feldstein, M. S. 1964. The Social Time Preference Discount
Rate in Cost-Benefit Analysis.
Economic Journal
7)4 :360-379.
Field, D. B. 1973.
Goal Programming for Forest Managment.
Forest Science 19(2):125-135.
Field, D. B. 1976.
Applications of Operations Research to
Quantitiative Decision Problems in Forestry and
the Forest Products Industries--A Bibliography.
Fight, R. D. and D. Darr.
Potential
197)4. Douglass County:
Economic Effects of a Changing Timber Resource
Base.
USDA, Forest Service Research Paper PNW-
179. p. 41.
Fight, R. D., K. N. Johnson, K. P. Connaughton, and R. W.
Sussaman.
Can Intensive Management Make up the
Harvest Lost when Roadless Areas are Left
Undeveloped? Journal of Forestry 77(3): 1)48-151.
182
Fisher, A. C. and J. V. Krutilla. 1975. Resource
Conservation, Environmental Preservation and the
Rate of Discount. Quarterly Journal of Economics
Volume LXXXIX, August.
Flacco, P. R. 1978.
Projected Income and Employment Impacts
of a Decline in the Timber Resurce Base of a
M. S. Thesis.
Highly Timber Dependent Economy.
Oregon State University, Corvallis.
Flick, W. A. 1972.
Resource Valuation and Multiple Use
Planning:
U. S.
An Input-Output Approach.
Department of Interior, Bureau of Land Management.
Portland,
Guides to Land Management Report 15.
Oregon.
Flick, W. A.
Resource Flows and Values. Technical
1975.
Note.
U. S. Department of Interior, Bureau of
Land Management.
Freeman, 0. L.
Grazing Fees.
1969.
314(9): 5O245O5.
Frisch, R.
1965.
Chicago.
Federal Register
Theory of Production.
p.
Rand and McNally,
370.
Gallizioli, S. 1977.
Statement of Steve Gallizioli, Chief
of Research, Arizona Game and Fish Department.
Proceedings of a Seminar on Improving
pp. 90-96.
Fish and Wildlife Benefits in Range Management.
U. S. Department of Interior, Fish and Wildlife.
FWS/OB5-77/1. Washington, D. C.
Gangmark, H. A. and R. D. Broad. 1956. Further Observations
on Stream Survival of King Salmon Spawn.
California Fish and Game 142:37_149.
Gardner, B. D. 1959.
Misallocation of Livestock Grazing
Permits.
Journal of Farm Economics.
145(1):
109-120.
Gibbons, D. R. and E. 0. Salo. 1973.
Annotated Bibliography
of the Effects of Logging on Fish of the Western
United States and Canada.
USDA, Forest Service.
Pacific Northwest Forest and Range Experiment
Station. General Technical Report PNW-1O. 1145 p.
The
Gibbs, K., L. Queirolo, and C. Lomnicki: 1979.
Valuation of Outdoor Recreation in a Multiple Use
Forest. Oregon State University Forest Research
Laboratory,
Corvallis. Research Bulletin 28.
p.
18.
183
Giger, R.
1972. Ecology and Management of Coastal
Cutthroat Trout in Oregon.
Oregon State Game
Commission.
Fish Research Report No. 6. p. 61.
D.
Grace, J. and N. Easterbee. 1979.
The Natural Shelter for
Red Deer in a Scottish Glen.
Journal of Applied
Ecology 16(1):37_148.
Graybeal, W. J. and U. W. Pooch. 1980.
Simulation:
Principles and Methods. Winthorp Publishers,
Inc., Cambridge. p. 2!9.
Gregory, G. R.
1955. An Economic Approach to Multiple Use.
Forest Science. 1(1):6-13.
Gregory, G. R. 1972. Forest Resource Economics.
and Sons, New York.
John Wiley
Gunderson, D. R. 1968. Floodplain Use Related to Stream
Morphology and Fish Populations. Journal of
Wildlife Management 32(3):507-5114.
Gustafson, R. D. 1975.
Regional Employment Impacts of
Timber Harvest Changes in Oregon. M. S. Thesis.
Oregon State University, Corvallis.
Haigh, J. A. and J. V. Krutilla.
1979. Analysis of
Fundamental Policy Directions:
National Forest
Management as an Illustrative Case. Resources for
the Future, Washington, D. C. 51 p.
Hall, J. D. and R. L. Lantz. 1969.
Effects of Logging on
the Habitat of Coho Salmon and Cutthroat Trout in
Coastal Streams. Symposium on Salmon and Trout in
Streams.
University of British Columbia,
Vancouver.
pp. 365-375.
1968. Recreational and
Esthetic Values of Wildlife in Relation to Forest
Management.
H. C. Black (ed.) Wildlife and
Reforestation in the Pacific Northwest.
Proceedings of a Symposium held Sept. 12-13, 1968.
School of Forestry.
Oregon State University,
Corvallis.
Hall, J. D. and T. G. Scott.
Halvorson, C., J. Linduska, and A. Stebler.
1972. Economic
Values of Wildlife Production in Forestry Areas in
North America. U. S. Department of the Interior,
Bureau of Sport Fisheries and Wildlife.
Washington,
D.
C.
Mimeo.
18 p.
184
Hann, D. W. and K. Butters. 1982. A Key to the Literature
on Forest Growth and Yield in the Pacific
Northwest: 1910-1981. Forest Research Laboratory.
School of Forestry. Oregon State University,
Corvallis.
Research Bulletin 39.
Diet Overlap of Deer,
Hansen, R. M. and L. D. Reid.
1975.
Elk, and Cattle in Southern Colorado. Journal of
Range Management 28(1):L3_147.
Foods of Elk and Other
Hansen, B. M. and R. C. Clark, 1977.
Ungulates at Low Elevations in Northwestern
Colorado.
Journal of Wildlife Management 28(1):
L3_i7.
Harestead, A. S. 1979.
Understory Vegetation:
Succession.
Unpublished Manuscript.
Wildlife Group, Faculty of Forestry.
of British Columbia, Vancouver.
Patterns in
Forestry
University
Oregon
Harper, J. A. (1971)
Ecology of Roosevelt Elk.
State Game Commission. P-B Project W-59-R.
p.
Harr, R. D. 1976.
Forest Practices and Streamfiow in
Pacific
Western Oregon.
USDA, Forest Service
General
Northwest Range Experiment Station.
Technical Report PNW_149.
.
Harr, R. D., R. L. Fredriksen, and J. Rothacher.
1979
Changes in Streamfiow. USDA, Forest Service.
Pacific Northwest Range Experiment Station.
Research Paper PNW-29.
21
p.
Classification and Analysis of
Harshman, E. P. 1971.
Vegetation for Coordinating Forest Cover Removal
USDA, Forest Service.
with Wildlife Needs.
Willamette National Forest.
Unemployment,
Haveman, R. H. and J. V. Krutilla.
1968.
Idle Capacity, and the Evaluation of Public
Expenditures:
National and Regional Analysis.
Johns Hopkins Press, Baltimore.
Hazard, J. W. 1968.
Convex Programming for Sampling on
Successive Occassions with Multiple Objectives.
Paper read at the Annual Meeting of the Society of
American Foresters. Philadelphia, PA.
Hazard, J. W. and L. C. Promnitz. 1974. Design of
Optimization by
Successive Forest Inventories:
Convex Mathematical Programming. Forest Science
20:117-127.
185
Heady, E. 0. 1952.
Economics of Agricultural Production and
Resource Use.
Prentice-Hall, Englewood Cliffs.
Heady, H. F. 1975.
York.
1459
Rangeland Management. McGraw-Hill, New
p
Hebo Draft Environmental Impact Statement.
USDA,
1976.
Forest Service.
Pacific Northwest Region.
Siuslaw National Forest.
Hebo Final Environmental Impact Statement.
USDA,
1978.
Forest Service.
Pacific Northwest Region.
Siuslaw National Forest.
roeconomi_:
Henderson, J. M. and E. Quandt. 1980.
A Mathematical Approach.
McGraw-Hill, New York.
1420
p.
Her Majesty's Treasury. 1972. Forestry in Great Britain:
An Interdepartmental Cost/Benefit Study.
Her
Majesty's Stationary Office, London.
Herrmann, R. B., C. E. Warren and P. Doudoroff. 1962.
Influence of Oxygon Concentrtions on the Growth of
Juvenile Coho Salmon. Transactions American
Fishery Society. 91(2):155-167.
Hill, M.
1973.
Planning for Multiple Objective An Approach
to the Evaluation of Transportation Plans.
Monograph Series No. Five.
Regional Science
Research Institute.
Philadeiphis, PA.
Hillier, F. S., and G. J. Lieberman.
Research, Second Edition.
Francisco, CA.
800 p.
Operations
19714.
Holden-Day Inc., San
Hills, G. A. 1966. The Classification and Evaluation of
Land for Multiple Use. Forestry Chronicle Vol.
142, No. 2.
Hines, W. W. 1973.
Black-Tailed Deer Populations and
Douglas-fir Reforestation in the Tillamook Burn,
Oregon.
Oregon State Game Commission.
Game
Research Report No. 3.
Project W-51-R.
55 p.
Hines, W. W. 1975. Black-Tailed Deer Behavior and Population Dynamics in the Tillamock Burn, Oregon.
Oregon State Game Commission. Wildlife Research
Report No. 5. 31 p.
Holterman, S. E. 1972. Externalities and Public Goods.
Econometrica 39 (153):78-87.
186
House, V. W. 1971. An Economic Model for Allocation of
Multiple Use Natural Resources. Ph.D. Thesis.
Washington State University, Pullman.
26 p.
Intriligator, M. D. 1978. Econometric Models, Techniques,
and Applications.
Prentice-Ball, Englewood
Cliffs.
Irland, L. C. 1979.
Wilderness Economics and Policy.
Lexington Books, D.C. Heath and Company,
Lexington.
226 p.
Ives, E. E. 1977. Input-Output Models Estimates From Data:
Sampling Considerations and Parameter Variability.
Ph.D. Thesis.
Oregon State University, Corvallis.
Janz, D. W. 1980.
Preliminary Observations on Seasonal
Movements and Habitat Use by Vancouver Island
Roosevelt Elk.
Proceedings of the Western States
Elk Workshop.
W. Macgregor (ed.). British
Columbia Fish and Wildlife Branch, Victoria,
British Columbia.
Jenkins, K. J. 1980.
Home Range and Habitat Use by
Roosevelt Elk in Olympic National Park Washington.
M.S. Thesis.
Oregon State University, Corvallis.
Johnson, K. N. and D. B. Jones. 1980. A User's Guide to
Multiple Use - Sustained Yield Resource Scheduling
Calculations (MUSYC). Timber Management, USDA,
Forest Service. Ft.Collins, Colorado.
22 p.
Johnson, K. N. and H. L. Scheurman.
197L.. Techniques for
Prescribing Optimal Timber Harvest and Investment
Schedules Under Different Objectives--Discussion,
Evaluation and Synthesis.
Mimeo. Utah.
Johnson, K. N. and H. L. Scheurman. 1977. Techniques for
Prescribing Optimal Timber Harvest and Investment
Under Different Objectives--Discussion and
Synthesis.
Forest Science Monograph 18.
31 p.
Josephson, H. P. 1976. Economics and National Forest Timber
Harvests.
Journal of Forestry 74:605-608.
Julander, 0. 1958.
Techniques in Studying Competition
Between Big Game and Livestock. Journal of Range
Management.
11(1):18-21.
Kahn, A. E. 1970.
The Economics of Regulation:
Principles
and Institutions Volume I.
John Wiley and Sons,
mc, New York.
187
Kalbacher, J. Z. 1979. Shift-Share Analysis A Modified
Approach.
Agricultural Economics Research 31(1):
12-25.
Kao, C. and J. D. Brodie.
1979. Determination of Optimal
Thinning Entry Interval Using Dynamic Programming.
Forest Science 25:672-67k.
1980. Linear Programming in Land-Management
Planning on National Forests. Journal of Forestry.
Kent, B. H.
pp. k69-k71.
Kiefling, J. W. 1972. An Analysis of Stock Densities and
Harvest of the Cutthroat Trout of the Snake River,
Teton County, Wyoming. M. S. Thesis. University
of Wyoming, Laramie.
Kirby, M.
1975. Land Use Planning, Transportation Planning
and Integar Programming. Systems Analysis and
Forest Resource Management. J. Meadows, et al.
(eds.) Society of American Foresters. Bethesda,
Maryland.
1981.
Klemperer, W. D.
Return.
617.
Interpreting the Realizable Rate of
Journal of Forestry.
September. pp. 616-
Krutilla, J. V. and A. C. Fisher.
1975. The Economics of
Natural Environments:
Studies in the Valuation of
Commodity and Amenity Resources. Johns Hopkins
Press, Baltimore.
Kunkel, C. and P. Janick.
1976. An Economic Evaluation of
Salmonid Fisheries Attributable to Siuslaw
National Forest. pp. 12, illus., Appendix.
Siuslaw National Forest, Corvallis, Oregon.
Lantz, R. L. 1970.
Effects of Logging on Aquatic Resources.
Progress in Game and Sport Fishery Research 196k79. H. J. Campbell and W. C. Lightfoot (eds.).
Oregon State Game Commission. Research Division:
13-16.
Lantz, R. L. 1971.
Guidlines for Stream Protection in
Logging Operations.
Oregon State Game Commission,
Research Division.
29 p.
Larson, B. W. and M. H. Goforth.
1970. TRAS-A Computer
Program for the Projection of Timber Volume.
USDA, Forest Service. Agriculture Handbook No.
377..
24 p.
188
Lawrence, W. H. 1969.
The Impact of Intensive Forest
Management on Wildlife Populations. Wildlife and
Reforestation in the Pacific Northwest. H. C.
Orgeon State
Black (ed.).
School of Forestry.
University, Corvallis. pp. 72711..
Ledeboer, M. V. 1982. A Structural Description of Oregon
M.S. Thesis. Oregon State
Counties, 1973-1978.
University, Corvallis.
Lemos, J. C. and W. W. Hines. 19711..
Guidelines for
Enhancing Big Game Values on Forest Lands.
Oregon
Wildlife Research Western Oregon Big Game Habitat
Studies.
Oregon Wildlife Commission. Portland.
Leopold, A. 5. 1950.
Deer in Relation
Deer Edge Dwellers:
to Plant Succession.
Fifteenth American Wildlife
Conference Transactions.
pp. 571-578.
Leuschner, W. A., J. R. Porter, M. R. Reynolds, and H. E.
Burkhart. 1975. A Linear Programming Model for
Multiple Use Planning.
Canadian Journal of Forest
Research 5:851491.
Leven, C. L. 1966.
The Economic Base and Regional Growth.
Research and Education for Regional and Area
Development.
M. R. Maki and B. L. Berry (eds.).
pp. 79914.
Iowa State University Press, Ames.
Levno, A. and J. Rothacher. 1967.
Increases in Maximum
Stream Temperatures After Logging in Old-Growth
USDA, Forest Service.
Douglas-fir Watersheds.
Pacific Northwest Range Experiment Station.
Research Note PNW-65.
12 p.
Lloyd, A. and J. Rothacher.
1967. Increases in Maximum
Stream Temperatures After Logging in Old-Growth
USDA, Forest Service.
Douglas-fir Watersheds.
Pacific Northwest Range Experiment Station.
Research Note PNW-65.
12 p.
Lorz, H. W. 19711.
Ecology and Management of Brown Trout in
Little Deschutes River. Oregon Department of Fish
and Wildlife.
Fishery Research Report No. 8.
149
Lowry, G.
p.
Net Production, Movement and Food of
19614.
Cutthroat Trout (Salmo clarki clarki Richardson)
in three Oregon Coastal Streams. M. S. Thesis.
Oregon State University, Corvallis. 72 p.
R.
189
Lowry, G.
R. 1965.
Movement of Cutthroat Trout, (Salmo
clarki clarki Richardson) in three Oregon Coastal
Streams.
Transactions American Fishery Society
9)4(k) :33)4-338.
Lowry, G. H. 1966.
Production and Food of Cutthraot Trout
in Three Oregon Coastal Streams.
Journal of
Wi:Ldlife Management.
3O(14):75k767.
Lynne, G.
197k.
Multiple Ogjective Planning Procuedures
in Water Resource Development:
The Trade Off
Ratio. Ph. D. Thesis Oregon State University,
Corvallis.
D.
Lyon, L. J. 1975.
Coordinating Forestry and Elk Management
in Montana:
Initial Recommendations.
Transactions North American Wildlife and Natural
Resource Conference kO:193-201.
Lyon, L. J. 1976. Elk Use as Related to Characteristics of
Clearcuts in Western Montana. Proceedings:
ElkLogging-Roads Symposium.
University of Idaho,
Moscow.
pp. 69-72.
Lyon, L. J. 1979a. Habitat Effectiveness for Elk as
Inf:Luenced by Roads and Cover. Journal of
Forestry 77:658-660.
Lyon, L. J. 1r979b.
Influences of Logging and Weather on Elk
Distribution in Western Montana.
USDA, Forest
Service.
Intermountain Forest and Range
Experiment Station.
Research Paper INT-236.
11
p.
Lyon, L. J. 1980.
Coordinating Forestry and Elk Management.
Transactions North American Wildlife Conference
:278-287.
Mackie, H. J. 1976.
Interspecific Competition between Mule
Deer, Other Game Animals and Livestock.
Mule Deer
DecJLine in the West:
A Symposium.
Utah State
University, Logan.
pp. k9-5k.
Mackie, H. J. 1978.
Impact of Livestock Grazing on Wild
Ungulates.
Transactions North American Wildlife
and Natural Resource Conference 143:k62.1476.
Maki, W. H. and D. L. Schweitzer. 1973. Importance of
Timber-Based Employment to the Douglas-fir Region,
USDA, Forest Service. Pacific
1959-1971.
Northwest Range Experiment Station.
Research Note
PNW.
196.
190
Maloney, J. E.
1972. Development and Application of' A
Linear Model of' the California Division of
Forestry Airtanker Fire Retardant Delivery
System.
Ph.D. Thesis.
University of California,
Berkely.
Maloney, J. E.
1973. A Summary of the Development and
Application of an Optimizing Airtanker Allocation
Model.
Canadian Forestry Service Publication
13214.
29 p.
Marcuson, P. E.
1977. The effect of Cattle Grazing on
Brown Trout in Rock Creek Montana. Symposium on
Livestock Interactions with wildlife, fisheries,
and their environments. USDA, Forest Service.
Reno, Nevada.
Marglin, S. A.
1963. The Social Rate of Discount and the
Optimal Rate of Investment. Quarterly Journal of
Economics. February. pp. 93-111.
Marousek, G.
1976. Shift-Share Analysis of Employment
Changes in Northern Idaho. 1960-1970. Idaho
Agriculture Experiment Station Research Bulletin
No. 90. February.
Martin, A. J. and P. E. Sendak.
1973. Operations Research
in Forestry: A Bibliography. USDA Forest Service.
Northeast Forest Experiment Station. General
Techical Report NE-8.
Martin, W. E. and G. L. Jefferies.
1965. Value of Public
Grazing Permits. Progressive Agriculture in
Arizona 17(2):4-5.
Martin, W. E., R. L. Gum, and A. H. Smith.
19714. The
Demand For and Value of Hunting, Fishing, and
General Rural Outdoor Recreation. University of
Arizona Agriculture Experiment Station, Tucson.
Technical Bulletin No. 211.
Martin, W. E., J. C. Tinney, and R. L. Gum.
1978. A
Welfare Economic Analysis of the Potential
Competition Between Hunting and Cattle Ranching.
Western Journal Agricultural Economics.
60(12) :87-97.
Maass, A., and M. Hufschmidt. 1959.
In Search of New
Methods for River System Planning.
Journal
Boston Society of Civil Engineers 146:99-117.
191
Martyr, R.
1978. The Benefits of Nongame. Western
Proceedings: Fifty-eight Annual Conference of the
Western Association of Fish and Wildlife
Agencies. San Diego, California. July 17-20. pp.
172-184.
McArdle, R. E.
1953. Multiple Use-Multiple Benefits.
Journal of Forestry 51:323-325.
McArdle, R. E., W. Meyer, and D. Bruce.
1961. The Yield of
Douglas-fir in the Pacific Northwest. USDA
Technical Bulletin No. 201. 714 p.
MoGreer, D. J.
1975. Stream Protection and Three Timber
FaLLing Techniques. A Comparison of Costs and
Benefits. M.S. Thesis. Oregon State Univerity,
Corvallis. 92 p.
Mdllarg, I. L.
1969. Design with Nature. Doubleday, New
Yo r k.
McKean, R. N. 1958. Efficiency in Government Through
Systems Analysis. John Wiley and Sons, Inc., New
York.
McKean, R. N.
1968. Public Spending. McGraw-Hill, New
York. 179 p.
MeKillop, W.
19714. Economic Impacts of an Intersified
Timber Management Program. USDA Forest Service
Research Paper WO-23. Washington, D.C. 16 p.
McKillop, W. 1978. Economic Cost of Withdrawing Timber and
Timberland From Commercial Production. Journal of
Forestry. July. pp.14114-1417.
Mead, W. J.
1977. Pricing Policy for Timber Products form
Forest Lands -- Resource Allocation and Income
Distribution Effects. M. Clawson (ed.). Research
in Forest Economics and Forest Policy. Resources
for the Future, Washington, D.C. July. pp. 161188.
Meadows, J. and A. Schuler.
1976. Nonlinear Programming
and Decreasing Marginal Utility Problem
A Goal
Programming Framework For Decision-making.
Proceedings 12th Annual Meeting Southwest Chapter
Instructional Management Science. Atlanta,
Georgia. Oct. 21-22. pp. 307-3114.
:
192
Meehan, W.
R. and W. S. Platts.
1978. Livestock Grazing
and the Aquatic Environment. Journal of Soil and
Water Conservation. 33(6):2714-278.
Meslow, E. C, C. Maser, and J. Verner.
1981. Old-Growth
Forest as Wildlife Habitat. Transactions North
American Wildlife and Natural Resource Conference
146 :329-336.
Miller, R. F.
19714. Spring, Summer and Fall Use by Cattle
and Big Game on Foothill Rangelands. M.S. Thesis.
Oregon State University, Corvallis.
126 p.
Miller, R. L.
1969. Progress in Developing Multiple-Use
Forest Watershed Production Models. Annuals of
Regional Science Science. June. pp. 135-1142.
Mishan, E. J.
1976. Cost-Benefit Analyses. Praeger
Publishers, New York.
19714. Immediate Effects of
Moring, J. R. and R. L. Lantz.
Logging on the Fresh Water Environment of
Sa:Lmonids. Final Report Project AFS-58. Oregon
Wi:Ldlife Commission Research Division, Corvallis.
101 p.
Moring, J. R. and R. L. Lantz.
1975. The Alsea Watershed
Study: Effects of Logging on the Aquatic
Resources of Three Headwater Streams of the Alsea
River, Oregon. Oregon Department of Fish and
wi:Ldlife. Fishery Research Report 9. 66 p.
Morris, W.
G,,
1970. Effects of Slash Burning in Overmature
Stands of the Douglas-fir Region. Forest Science
16::3) :258-270.
Mulhlenberg, N.
19614.
A Method for Approximating Forest
Multiple-Use Optima. Forest Science 10(2):2092 1 2.
Musgrave, R. A.
1959. The Theory of Public Finance.
McGraw-Hill, Inc., New York.
Musgrave, R. A. 1969. Fiscal Systems. Yale University
Press, New Haven.
Narver, D. W.
1971. Effects of Logging Derbis on Fish
Production. J. T. Krygier and J. D. Hall (eds.),
Proceedings of a Symposium on Forest Land Uses
and Stream Environment. Oregon State University,
Corvallis.
193
Navon, D. T.
1967. Computer-Oriented Systems for Wildlife
Management. Journal of Forestry 65(7):1173-179.
Navon, D.
I. 1969. Activity Analysis in Wildland
Management. Annuals of Regional Science.
December.
Navon, D. I.
1971. Timber RAM-A Long Range Planning Method
for Commercial Timber Londs Under Multiple Use
Management. USDA Forest Service. Pacific
Southwest Forest Experiment Station. Research
Paper PSW-70.
Navon, D. I. arid R. J. McCorinen.
1967. Evaluating Forest
Management Policies by Parametric Linear
Programming. USDA, Forest Service. Pacific
Southwest Forest Experiment Station. Research
Paper PSW-12.
Naylor, T. H. and J. M. Vernon.
1969. Microeconomic and
Decision Models of the Firm. Harcourt, Brace and
World, Inc., New York.
Nemhauser, G. L. 1966. Introduction to Dynamic Progamming.
John Wiley, and Sons, New York. p. 256.
Nobe, K. C. and H. W. Steinhoff.
1973. Values of Wildlife.
E. Decker and G.A. Swanson (eds.). Wildlife and
the Environment, Proceedings of Governor's
Conference.
Environmental Resource Center.
Colorado State University. Information Series
No.
7.
pp.
33-37.
O'Connell, P. F.
1972. Valuation of Timber, Forage, and
Water from National Forest Lands. Annuals of
Regional Science 6(2):1-1'l..
O'Connell, P. F. and R. S. Boster.
19711. Demands on
National Forests Require Coordinated Planning.
Arizona Review 23(2):1-7.
O'Connell, P. F. and H. E. Brown.
1972. Use of Production
Functions to Evaluate Multiple Use Treatment on
Forested Watersheds. Water Resources Research 8
(5) :1188-1199.
Oliveira,
R. A.
1981. Outdoor Recreation and Public
Interest
Benefits and Costs in Federal and
State. Resource Planning. Paper Presented at
Meeting held in Tuson, Arizona. February 19-20.
:
194
Oliveira, R. A. and 0. Rausser.
1977. Daily Fluctuations
in Campground Use
An Econometric Analysis.
Journal of' Agricultural Economics 59(2):283-293.
:
Owen, L. P.
1979. Migration and Economic Change in TimberReliant Counties
An Econometric Analysis. M.S.
Thesis. Oregon State University, Corvallis.
:
Paqoulatos, A. and L.A. Walker. 1976. On the Proper
Discount Rate for Public Investment Projects in
Natural Resources. College of Agriculture.
University of Kentucky, Lexington. Research
Re:port
25.
Pavelis, G. A., P. Johnson, and W.D. Shrader.
1961.
Methodology of Programming Small Watershed
Development. Agricultural Experiment Station.
Iowa State University, Ames. Bulletin 93.
Pearse, P. H.
1969. Principals For Allocating Wildiand
Among Alternative Uses. Canadian Journal of
Agricultural Economics 17(1):121-131.
19114. Multiple Use in Forestry. Journal of'
Pearson, G. A.
Forestry
2:23-29.
Pederson, R. J., A. W. Adams
Management in Blue
Department o' Fish
Robertson Project.
and 3. Skovlin.
1979. Elk
Mountain Habitats. Oregon
and Wildlife. Pittman-
W-70-R.
27. p.
Pederson, R. J., A. W. Adams and J. M. Skovlin.
1980. Elk
Habitat Use in an Unlogged and Logged Forest
Environment. Oregon State Game Commission.
Pittman-Roberts Project. W-70.-R. 814 p.
Pickford, G. D. and E. H. Reid. 19143. Competition of Elk
and Domestic Livestock for Summer Range Forage.
Journal of Wildlife Management. 7(3):328-332.
Pinchot, G. 19147.
Breaking New Ground.
and World, New York.
Harcourt, Brace
Platts, W. S. 1978. Livestock Interactions With Fish and
Aquatic Environments:
Problems in Evaluation.
Transactions North American Wildlife and Natural
Resources Conference 143:1498-5014.
Platts, W. S. 1979.
Livestock Grazing and Riparian/Stream
Ecosystems--An Overview.
Grazing and
Riparian/Stream Ecosystems Forum Proceedings.
Trout Unlimited, Vienna.
pp. 39-145.
195
Platts, W. S. 1980. Streamside Management to Protect Bank
- Channel Stability and Acquatic Life. Interior
Spokane,
West Watershed Symposium Proceedings.
Washington. April.
Ponce, S. L. and G. W. Brown.
Demand for Dissolved
1973.
Oxygen Exerted by Finely Divided Logging Debris
Oregon
in Streams.
Forest Research Laboratory.
State University, Corvallis. Research Paper
No.
19.
Randall, A. 1977.
Evaluating Non-Market Goods and
Services.
Department of Agriucitural Economics.
Staff Paper
University of Kentucky, Lexington.
51.
Randall, A. and D. Brookshjre.
Public Policy,
1978.
Public Goods and Contingent Value Mechanisms.
Department of Agricultural Economics. University
of Kentucky, Lexington.
Staff Paper 68.
Reiser, B. W. and T. C. Bjornn.
Habitat
1979.
Requirements and Anadromous Salmonids. W. R.
Influence of Forest and
Meehan (tech. ed).
Rangeland Management on Anadromous Fish Habitat
USDA Forest Service.
in Western North-America.
Pacific Northwest Experiment Station. Technical
Report.
PNW-96. 514 p.
Beneficial Aspects for
Resler, R. A. 1972.
Clearcutting:
Wildlife Resources. Journal of Soil and Water
Conservation 27 (6):250-2514.
Rice, R. M., J. S. Rothacher, and W. F. Mehahan.
Erosional
Consequences of Timber Harvest: An Appraisal.
Symposium Proceedings on Watersheds in
Transition.
American Water Resources
Association, Urbana.
pp. 321-329.
Rich, L. and J. R. Thompson.
Watershed Management
19714.
The Status
in Arizona's Mixed Conifer Forests:
of Our Knowledge. USDA Forest Service.
Rocky
Mountain Forest and Range Experiment Station.
Research Paper RM-130. 15 p.
Ridd, M. K. 19614.
An Area-Oriented Approach to Multiple
Land Use Research. Econ.omic Research in the Use
and Development of Range Resources. University
of Nevada, Reno. Report No. 6.
76 p.
196
Riitters, K., J. D. Brodie, and D. W. Hann.
1982. Dynamic
Programming for Optimization of Timber Production
and Grazing in Ponderosa Pine. Forest Science
28(3) :517-526.
Ripley, T. H. and C. D. Buffington.
197k. Trade-offs in
Multiple Use.
University of Kentucky, Lexington.
Mimeo.
pp. 117-120.
Roberts, K. 1973.
Economic and Environmental Trade-offs in
an Estuarine Based Economy: A Modified InputOutput Model of Clatsop County, Oregon. Ph. D.
Thesis.
Oregon State University, Corvallis.
Roberts, K. and R. B. Rettig.
1975. Linkages Between the
Economy and the Environment: An Analysis of
Economic Growth in Clatsop County, Oregon.
Agricultural Experiment Station. Oregon State
University, Corvallis. Bulletin 618.
Roberts, N. K. 1963.
Economic Foundations For Grazing Use
Fees on Public Lands. Journal of Farm Economics.
145(14) :721-731.
Rochelle, J. A. 1980. Mature Forests, Litterfall and
Patterns of Forage Quality as Factors in the
Nutrition of Black-Tailed Deer on Northern
Vancouver Island. Ph.D.
Thesis.
University of
British Columbia, Vancouver. 296 p.
Rhody, D. D. and R. E. Lovegrove.
1970. Economic Impact
of Hunting and Fishing Expenditiures in Grand
County, Colorado. Department of Economics.
Colorado State University, Ft. Collins.
Rompa, W. J.
1979. A Working Model of the Clatsop County
Economy. Agricultural Experiment Station.
Oregon State University, Corvallis. Special
Report
No.
Row, C.
1977.
5111.
Balancing Supplies and Demands.
M. Clawson
(ed.).
Research in Forest Economics and Forest
Policy.
Resources for the Future, Wahington,
D.C.
pp. 83-158.
Row, C., H. F. Kaiser and J. Sessions.
1981. Discount
Rate for Long-Term Forest Service Investments.
Journal of Forestry.
79(6):367-369.
197
Ruderman, F. K. 1979,
Production, Prices, Employment, and
Trade in Northwest Forest Industries. USDA,
Forest Service.
Pacific Northwest Forest and
Range Experiment Station.
60 p.
Saltzman, W. 0. 1976.
Impact of Stream-side Use of
Fisheries.
Columbia River Salmon and Steelhead.
American Fishery Society.
Bethesda.
Special
Publication 10.
pp. 160-163.
Sandrey, R. A. 1983. Economic Considerations in Managing
Oregon Rocky Mountain Elk. Ph. D. Thesis.
Oregon State University, Corvallis.
118 p.
Sassarnan, R. W., E. Bolt, and K. Bergsvick.
1972. User's
Manual For a Computer Program For Simulating
Intensively Managed Allowable Cut. USDA, Forest
Service.
Pacific Northwest Forest and Range
Experiment Station.
General Technical Report
PNW-1. 50 p.
Schallau, C. H. 1980.
Stages of Growth Theory and Money
Flows From Commercial Banks in Timber Dependent
Communities.
USDA, Forest Service. Research
Paper PNW-279. 16 p.
Schallau, C. H. and W. R. Maki.
1983. Int&rindustry Model
for Analyzing the Regional Impacts of Forest
Resource and Related Supply Constraints.
Forest
Science 29 (2):38'-3gJ4.
Scheurman, H. L. and K. N. Johnson.
1975. Computational
Experience With a Renewable Resource (Timber)
Harvest Model.
Oregon State University,
Corvallis.
Utah State University, Logan.
Mimeo.
35 p.
Schmisseur, W. E.
1977. Maiheur Nation Wildlife Refuge
Grazing Fee Survey:
Survey Results and
Recommendations Grazing and Haying Fee Base
Rates.
Oregon State University Extension Service
and Malheur National Wildlife Refuge.
Schmidt, J. S. and P. L. Tedder.
1981. A Comprehensive
Examination of Economic Harvest Optimization
Simulation Mehtods.
Forest Science 27(3):
523-536.
Schoen, J. W., 0. C. Walimo, and M. D. Kirchhoff. 1981.
Wildlife-Forest Relationships: is a Reevaluation
of Old-Growth Necessary?
North American Wildlife
Natural Resource Conference.
Vol.
6.
198
Schuler, A. T. and J. C. Meadows.
1975. Planning Resource
Use on National Forests to Achieve Multiple
Objectives.
Journal of Environmental Management
3(4) :351-366.
Schuler, A. T., H. H. Webster and J. C. Meadows.
Goal Programming in Forest Management.
of Forestry.
75:320-324.
1977.
Journal
Schuize, W. :D., R. C. d'Arge, and D. S. Brookshire.
1981.
Valuing Environmental Commodities:
Some Recent
Experiments.
Land Economics 57:151-172.
Schweitzer, R. L., R. W. Sassaman, and C. H. Schallau.
1972. Allowable Cut Effect--Some Physical and
Economic Implicaitons. Journal of Forestry.
70(7):
141 5 -4 18.
Shalloff, F. M. 1981.
Estimation of Net Economic Benefits
of the Oregon Big Game Resource To Hunters.
M.S.
Thesis.
Oregon State University, Corvallis.
146 p.
Shannon, R. E. 1975. System Simulation:
the Art and the
Science.
Prentice-Hall, Inc., Englewood Cliffs.
387 p.
Shih, K. S. 1981.
An Econometric Analysis of Timber Demand
and Supply Relationships on the Siuslaw National
Forest.
M.S. Thesis, Oregon State University,
Corvallis.
126 p.
Shorus, C.
1980. Estimated Expenditures by Sport Anglers
and Net Economic Values of' Salmon and Steelhead
for Specified Fisheries in the Pacific Northwest.
Ph.D. Thesis. Oregon State University, Corvallis.
142 p.
Shumway, D.L., C. E. Warren, and P. Doudoroff.
1964.
Influence of Oxygen Concentrations and Water
Movement on the Growth of Steelhead Trout and
Coho Salmon Embryos. Transactions American
Fishery Society 93(14):342-.356.
Silver, S. J., C. E. Warren, and P. Doudoroff.
1963.
Dissolved Oxygen Requirements of Developing
Steelhead Trout and Chinook Salmon Embroys at
Different Water Velocities.
Transactions
American Fishery Society 92(4):327-3143.
199
Sinden, J. A. 19714.. A Utility Approach to the Valuation of
Recreational and Aesthetic Experiences. American
Journal of Agricultural Economics 65(1): 61-72.
Siuslaw National Forest.
Final Environmental
1979.
Statement:
Ten-Year Timber Resource Plan.
Forest Service. Pacific Northwest Region.
USDA,
Skovlin, J. M., P. J. Edgerton, and R. W.. Harris.
1968.
The Influence of Cattle Management on Deer and
Elk..
Transactions North American Wildlife and
Natural Resources Conference 33: 169-181.
Skovlin, J. M. and R. W. Harris.
Management of
1970.
Conifer Woodland Grazing Resources For Cattle,
Deer and Elk.
Proceedings International
Grassland Congress 11:75-78.
Smith, R. J. 1977.
Conclusions.
Proceedings of a Seminar
on :Emproving Fish and Wildlife Benefits in Range
Management.
Fish
U.S. Department of Interior.
and Wildlife Service. Washington, D.C.
pp. 117-118.
Snedecor, G. W. 1961.
Statistical Methods Applied to
5th Ed.
Experiments in Agriculture and Biolbgy.
Iowa State University Press, Ames. 5311 p.
-
Society of American Foresters.
Multiple Use Forest
1973.
Lands.
Journal of Forestry. 71:606-607.
Statistical Reporting Service.
U. S. Department of
1963.
Agr:Lculture.
Farm Real Estate Market
Developments.
ERS, CD-63, Washington, D.C.
April.
Steinblums, I. J. 1978.
Streamside Buffer Strips:
Survival, Effectiveness, and Design. M.S.
Thesis.
Oregon State University, Corvallis.
193
p.
Stelfox, J. 0,, 0. M. Lynch, and J. R. McGillis.
1976.
Effects of Clearcut Logging on Wild Ungulates in
the Central Albertan Foothills.
Forest
Chronicle.
52(2): 65-70.
Steuer, H.
An Interactive Multiobjective Linear
1978.
Programming Approach to Problems in Forest
Management.
Operations Research 26(2):25'4-269.
200
Stockfish, J. A.
Measuring the Opportunity Cost of
1969.
Government Investment.
Institute for Defense
Ana]Lysis. Research Paper 9O. 28 p. Arlington,
Va.
Stoddard, C. H. 1978. Essentials of Forestry Practices 3rd Edition. John Wiley and Sons, New York.
387 p.
Stoddard, L., A. Smith, and T. Box.
Range
1975.
Management 3rd Edition.
McGraw-Hill, Mew York.
532 p.
Stuart, R.
Y. 1933.
Report of the Forester to the
Honorable Henry W. Wallace, Secretary of
Agriculture, for the Fiscal Year Ended June 30,
Washington, D. C.
1933.
U.S. Government
Printing Office. 146 p.
Sturgis, H.
1977.
20 Years at McDonald Forest.
Wildlife.
July.
pp. 3-6.
Oregon
Swanson, F. J. and G. W. Lienkaemper.
The History
1975.
and Physical Effects and Large Organic Debris in
Western Streams.
In:
Logging Debris in Streams
Workshop.
Oregon State University, Corvallis.
18 p.
Swanston, D. N. 1980. Influence of Forest and Rangeland
Management on Anadromous Fish Habitat in Western
North America:
Impacts of Natural Events.
USDA
Forest Service.
Pacific Northwest Forest and
Range Experiment Station.
General Technical
Report PNW-10LI..
27 p.
Swanston, D. N. and F. J. Swanson.
Timber
1976.
Harvesting, Mass Erosion, and Steepland Forest
Geomorphology in the Pacific Northwest. D. R.
Goates (ed.).
Geomorophology and Engineering.
Dowden, Hutchinson and Ross, Stroudsburg.
pp. 199-221.
Taber, R. D.
Deer and elk in Managed Forests in
1979.
Western Washington--Report for the Biennium.
July 1, 1977-June 30, 1977. College of Forest
Resources.
University of Washington, Seattle.
Taber, R. B. and K. J. Raedeke.
Roosevelt elk of
1980.
the Olympic National Forest.
Final Report to
USDA.
Olympic National Forest, Port Angeles.
201
Tedder, P. L. 1979.
Oregon's Future Timber Harvest: the
Size of Things to Come. Journal of Forestry.
November pp. 711_716.
Tedder, P. L., J. S. Schmidt and J. Gourley.
TREES,
1980.
Timber Resource Economic Estimation System.
Vo:Lume I:
A User's Guide For Forest Management
and Harvest Scheduling.
Forest Research
Laboratory.
Oregon State University, Corvallis.
Research Bulletin 31a. 81 p.
Tedder, P. L., J. S. Schmidt and J. Gourley.
TREES,
1980.
Timber Resource Economic Estimation System.
Vo:Lume III:
Example Problem Guide.
Forest
Research Laboratory.
Oregon State University,
Corvallis.
Research Bulletin 31c. 87 p.
Tedder, P. L., J'. S. Schmidt, and J. Gourley.
1981.
TREES, Timber Resource Economic Estimation
System.
Volume II:
Mathematical Analysis and
Policy Guide.
Forest Research Laboratory.
Oregon State University, Corvallis. Research
Bulletin 31b.
Teeguarden, I). E. 1975. Multiple Services.
In.
Forest
Resource Mana&ement:
Decision-makinprinciples
and Cases.
Duerr et al. (eds.)
Oregon State
University Bookstore, Corvallis.
Teeguarden, I). E. 1977.
Information Resources for Research
in Forest Economics and Policy.
In.
Research in
Forest Economics and Forest Policy. M. Clawson
(ed.).
Resources for the Future, Washington,
D.C.
pp. 383-k32.
Theil, H., J. C. Boot and T. Kloek.
Operations
1965.
Research and Quantitative Economics: An
Elementary Introduction.
McGraw-Hill, New York.
258 p.
Thompson, K. 1972.
Determining Stream Flows for Fish Life
Proceedings, Instream Flow Requirement Workshop.
Pacific Northwest River Basin Commission.
Vancouver, Washington. pp. 31-50.
Trierweiler, J. (Chairman). 1976. Review of Public Land
Grazing Fees.
Report Prepared by a Technical
Committee From: ERS, FS and SRS, USDA and BLM,
USD1.
November 15, 1976.
Federal Register
k2:2Z (February 1977), Washington, D.C.
202
19711.
Turner, J. M.
Allocation of Forest Management
Practices on Public Lands. Annuals of Regional
Sc:Lence
8(2):72-88.
U. S. Congress.
1960. Multiple Use-Sustained Yield Act.
Public Law 86-517.
U. S. Congress.
1969.
National Environmental Policy Act.
U. S. Congress.
1973.
Threatened and Endangered Species
Ac t.
U. S. Congress.
197l. The Forest and Rangeland Renewable
Resources Planning Act.
Public Law 93-378.
U. S. Congress.
1976. National Forest Management Act.
Public Law 911588.
U. S. Department of Agriculture.
1973. Resource
Capability System--A User's Guide.
Parts 1-VI.
Division of Watershed Management.
USDA, Forest
Service.
Washington, D.C. p. 665
U. S. Department of Agriculture.
1976. Agricultural
Statistics.
United States Government Printing
Office, Washington, D.C.
USDA, Forest Service.
1969. Douglas-fir Supply Study
Alternative Programs for Increasing Timber
Supplies from National Forest Lands.
Government
Printing Office, Washington, D.C.
USDA, Forest Service.
1973. Forest Service Manual, Title
8200. Land Use Planning. Washington, D.C.
USDA, Forest Service.
1976. The Nation's Renewable
Resources - Programs, '1975 and Supplemental
Appendix (Published separately).
Government
Printing Office, Washington, D.C.
USDA, Forest Service. 1979. A Report to Congress on the
Nation's Renewable Resources:
RPA Assessment and
Alternaive Program Directives.
209 p.
USDA, Forest Service. Pacific Northwest Forest and Range
Experiment Station.
Research Paper PNW-189. 149
p.
U.S.
Government
Manual.
1982.
Washington, D.C.
Government Printing Office,
203
U.S.
Water Resources Council.
Water and Related
1973.
Land Resources:
Establishment of Principles and
Standards for Planning. Federal Register.
38(1711): 211778_21869, Part III.
Wall, B.
Employment Implications of Projected
1973.
Timber Output in the Douglas-fir Region, 19702000.
USDA, Forest Service. Pacific Northwest
Forest and Range Experiment Statioz.
Research
Note PNW-211. 11 p.
H.
Wall, B. R. and D. D. Oswald.
A Technique and
1975.
Relationship for Projections of Employment in the
Pacific Coast Forest Products Industries.
19711.
Waits, F. J.
Design of Culvert Fishways.
Idaho
Water Resource Fesearch Institute Reprot.
Project A-027-IDA.
Moscow.
62 p.
Ware, G. 0. and J. L. Clutler.
A Mathematical
1971.
Programming System for Management of Industrial
Forests.
Forest Science 17:L128_1115.
Warren, C.
1978.
Our Economics is too Small:
Wildlife and
the Human Concept of Value.
Western Proceedings
Fifty-eight Annual Conference of the Western
Association of Fish and Wildlife Agencies. San
Diego, CA.
July 17-20.
pp. 8-13.
Whaley, R. S. 1968.
Multiple Use Decision-Making:
Where
Do We Go From Here? A Report to The Rocky
Mountain Forest and Range Experiment Station.
USFS Contract 12-11-204-3.
Natural Resource
valuation--The Conceptual and Operational Basis
for Economic Analysis in a Multiple Use Context.
Economic Research Institute and Department of
Forest Science.
Utah State University, Logan.
Whitmore, C. M., C. E. Warren and P. Doudoroff.
1960.
Avoidance Reactions of Salmonid and Centrarchid
Fish to Low Oxygen Concentrations.
Transactions
American Fisheries Society 89(1):17-26.
Witmer, G.
W. 1981.
Roosevelt Elk Habitat Use in the
Oregon Coast Range.
Ph.D. Thesis.
Oregon State
University, Corvallis. 100 p.
Worley, D. P. 1965.
The Beaver Creek Pilot Watershed for
Evaluating Multiple-Use Effects of Watershed
Treatments.
USDA, Forest Service. Rocky
Mountain Forest and Range Experiment Station.
Research Paper RM-13.
APPENDICES
205
APPENDIX A
Management intensification information used
in the analysis and TREES simulation runs.
206
The
purpose
of
appendix
this
is
identify
to
the
management intensification assumptions used in Chapters IV
and V.
The assumptions of the three levels of management
intensification
(Current,
Beuter
et
Target
al.,
A
and
Target B levels) considered during the course of analysis
are defined below.
Percentage Distribution of A1res
in the Regular Acreage Class by
Management Intensity, Currently
and for Two Projections*
Upper Middle Drift Creek Watershed
Management2
Intensity
current3
Target A
1975-2005 2005+
Target B5
1975-2005 2005+
2
19
3
'H
-
13
13
18
-
5
5
16
16
61
33
5
33
5
22
2
2
98
98
6
7
-
1Management
intensity
is assumed for all acres in
the special land class.
When managed for timber, outside
acres are brought into the producing acreage class in the
same manner as that class.
1
2Management intensities are defined as follows:
MI-i is softwood species type with no management
intensification.
The basic yield function for
the appropriate softwood species applies for this
207
except
that
yields
are
reduced
for
environmental
reasons.
Reductions
are
accomplished by the imposition of more sever
ending conditions for the projection than are
used
for
which
implies
longer
much
MI-3,
rotations for MI-i.
MI,
MI-2 is softwood species type with no management
intensification.
The
basic
hardwood
yield
function applies.
MI-3 is softwood species type with no management
intensification.
The basic yield function for
the appropriate softwood species type applies for
this MI.
Growth is adjusted to take into account
the present stocking of the stand relative to the
basic (standard) yield function.
is
softwood
species
type,
including
commercial thinning.
The thinning rules for this
analysis are:
(A) Only acres that are greater
MI_14
than or equal to 70 percent stocked compared to
the basic yield function (MI-3) are eligible for
thinning, provided the timber is between ages 35
and 95, inclusive for the low and very low site
classes (see footnote, No. 3, Table Al for site
class definitions); (B) Volume to be .removed in
thinning is determined such that the stand after
thinning is 60 percent stocked compared to the
basic
after
yield function, or such
thinning has 67 percent
that the stand
of the before-
thinning volume per acre, using whichever leaves
the greatest volume per acre in the stand after
thinning; (C) If the thinning volume calculated
as above is less than 800 cubic feet per acre, no
thinning
occurs.
Growth
after
thinning
is
calculated as 90 percent of gross growth (the
basic
yield
function
mortality).
plus
(MI-3)
When no thinning occurs, growth is calculated as
for MI-.3.
MI-5 is softwood species type, including stocking
controL (precommercial thinning) and commercial
thinning.
Stocking control is assumed to occur
at age 15 for the high and medium site classes,
and age 25 for the low and very low site classes
(see
footnote
Table
Al
for
site
class
3,
definitions).
At the time of stocking control,
the basic yield function is shifted such that
yields occur earlier as follows:
For high and
medium site classes, shift basic yield function
such that comparable yields occur 5 years earlier
208
than for the basic yield function (MI-3); for low
very low site classes, shift basic yield
function such that comparable yields occur 10
years earlier than for the basic yield function.
After stocking control occurs, the thinning rules
for MI-Il apply, except that the inclusive ages
are 25 to 95 for the high and medium site classes
and 35 to 105
for the low and very low site
classes.
Growth after thinning is calculated as
percent of gross MI-5 growth (MI-5 yield
90
function,
plus mortality).
When no thinning
occurs growth is calculated as for MI-3.
and
MI-6 is softwood species type, including stocking
commercial thinning and fertilization.
This management intensity is basically the same
as MI-5, except that fertilization is assumed to
control,
occur
the
raised
by
yields
are
For the high site
following specified amounts:
class, MI-6 yields
1.10 x MI-5 yields; For the
medium site class, MI-6 yields
1.15 x MI-5
yields; for the low and very low site classes,
MI-6 yields
1.20 x MI-5 yields.
For this
analysis, fertilization is allowed only between
the following ages:
For the high and medium site
classes, ages 15 to 75, inclusive; for the low
and very
low site
classes, ages 25 and 85,
inclusive.
Thinning rules and growth is assumed
for MI-7 compared to MI-6, higher yields can be
expected because M1-7 is accompanied by more
optimistic regeneration assumptions. That is, it
is
assumed that regeneration lag is less, the
failure rate for regeneration is less, higher
stocking levels are attained, and fewer acres
revert to hardwoods for MI-7.
that
such
3The
current distribution of acres by management
intensity reflects the starting inventory as of 1976.
Target A distribution was intended to be a moderate,
attained movement from current management
likely-to-beintensities.
5Target
B
distribution
is
represents an extensive movement
a
high
distribution
and
from current management
intensities.
*Adapted from Timber for Oregon's Tomorrow (Beuter et
al.,
1976).
209
APPENDIX B
Research studies considering the
impacts of forest management activities upon
deer, elk and anadromous fishersy resources.
210'
This appendix contains a summary of research regarding
the
impacts
of
forest
management
activities
production of non-timber resources.
impacts
the
of
forest
the
on
Studies considering
management
activities
the
on
population levels of deer, elk and anadromous fisheries are
reviewed in the following pages.
Deer and Elk
Forest land
is
the principal source of deer and elk
1968).
habitat (Hall and Scott,
and
with
elk
three
Forest stands provide deer
essential habitat
requirements:
1)
security from predation and harassment (hiding cover);
modified
more
and
favorable
cover); and 3) forage.
weather
regimes
2)
(thermal
No one forest stand must supply all
three habitat requirements.
However, the array of forest
stands within the respective home ranges of the ungulates
must
provide
otherwise
Lynch,
forage,
deer
and
and
McGills,
hiding
elk
cover,
will
1976)
abandon
modify
or
and
the
thermal
area
their
distributional pattern (Grace and Easterbee,
cover,
(Stelfox
home
range
1979).
Deer and elk populations are directly related to the
condition of their habitat.
range,
with
necessary
to
sufficient
maintain
Adequate
conifers
herd
to
size.
summer and winter
provide
Forest
cover,
are
management
activities and their timing directly influence the quantity
and quality of big game forage, hiding and thermal cover.
211
Of
forest management activities,
harvesting
have
been
those related
identified
to
having
as
timber
most
the
significant influence on deer and elk habitats (Lemos and
Hines, 197k; Lyon, 1979a).
method
The
of
timber
removal
and
treatment
slash
influences the subsequent quality and quantity of deer and
elk
habitat
comparison
(Hines,
of
big
1973;
game
Lemos
use
of
Hines,
197').
A
selectively
logged
and
and
clearcut areas in the Coast Redwood Forest and Douglas Fir
regions of Oregon revealed
clearcuts--where
(Campbell
and
forage
Evans,
that game
occurred
1980;
Harvesting methods such as
in
Lemos
use was greater in
greater
and
abundance
Hines,
197LI).
skyline operations limit soil
disturbance and reduce understory vegetation removal.
High
lead and tractor logging operations usually create a wide
range of soil disturbances of varying degrees of severity.
The more varied the soil disturbance, the mor
subsequent vegetation responses.
varied the
The more severe the soil
disturbance, the greater the delay in the establishment of
woody species.
Morris (1970) observed that slash burning
delayed brush development
for several years and promoted
muah vegetation variety.
New and brushy clearcuts are important forage areas
for deer and elk (Gibbons and Salo, 1973; Lemos and Hines,
19711).
1966;
Clearcuts provide more preferred forage
Cowan,
19115)
(Bailey,
and assuming they remain uncovered by
snow, higher quality forage during all seasons (Rochelle,
212
1980).
Preferred forage production usually peaks between
and
years after harvesting
30
1979;
Lemos
and
preference
(Bailey,
1966;
Harestead,
1979;
Taber
Hines,
19724;
Taber,
While
deer
demonstrate
1980).
Rae deke,
between
new
and
special
no
elearcuts,
brushy
or
24
brushy
clearcuts are the foraging areas most commonly utilized by
elk
1971; Janz,
(Harper,
1980; Jenkins,
1980 and Wilmer,
1981).
Clearcuts
temporal
The
and
spatial
distribution
of
affects the quality of deer and elk habitat.
olearcuts
Consecutive
cuts produce sub-optimal big game habitat unless earlier
adjacent
clearcuts
have
developed
sufficient
create an edge bordering the newer clearcut.
Hines
(19724
p.13)
report
that
the
cover
Lemos and
optimal clearcuts
deer populations are rectangular designs no more than
50
acres
size.
in
For maximum utilization
to
the
for
240
-
authors
suggest that the width of the c].earcut should not exceed
1,200
-
1,500 feet.
Long and narrow cutting designs were
observed to provide a greater edge and benefit more deer
than were designs having a circular or square configuration
(Lemos
and
(1981,
p.148)
Roosevelt elk more heavily utilized
forage
Hines,
observed that
19724
p.
areas where cover was nearby.
elk
have
demonstrated
124).
Witmer
Studies of Rocky Mountain
increased
elk
sensitivity
to
disturbance and harassment when less than two-thirds of an
213
area was
in
1975; 1979a,
forest cover
(Basile
and
Loriner,
1979b; Lyon and Jensen, 1980).
1979;
Lyon
Harper (1971)
found that Roosevelt elk use was reduced 55 percent when
timber adjacent
to
(1981,
recommends
p.
28)
areas was
forage
that
harvested.
clearcuts
optimal Roosevelt elk utilization should be
acres
or
of
a
shape which maximizes
Witmer
designed
for
less than
edge habitat
18
(i.e.
cover is within 960 feet of any point of the clearcut)
Logging activities, road construction and road traffic
While deer respond rather indifferently to the timing
and intensity of logging and road construction activities
and
to road traffic, elk exhibit harassment and avoidance
responses (Gibbons and Salo,
1973; Lemos and Hines,
197k).
Lyons (1979a) reported that second to weather, the timing
and intensity of logging activities is the most important
determinate of elk distributions.
identified
manipulating
Pederson,
as
:Logging
Roosevelt
et al.
(1980)
most
the
elk
Lemos and Hines (1975)
habitat
found:
(1)
important
in
western
activity
Oregon.
no summer elk use of
newly logged areas during the summer of logging activity or
the following year,
after logging, and
logging.
Lyon
(2)
limited elk use the second summer
(3) preferred use the third year after
(1975,
1979a,
1979b),
Marcum (1975),
and
Ream (1973) observed that elk avoid logging areas from one
month to two years after the cessation of logging activity,
relocating one to five miles from active logging sites with
214
greatest disp:Lacement associated with highly visible ridge
line
logging
operations
stands
or
having
thirds of the area in forest cover.
elk moving back to
Beau
logged winter range site within two
a
In sale area
activity
minor
prolonged,
not
avoidance were
two
(19714) reported
days after the logging ended.
was
than
less
recorded by
recoveries
(1979)
Lyons
where logging
as
an
from
elk
immediate
response to the removal of men and equipment (Hyde-Lupine,
1975; EdsCreek, 1976; Lion Creek, 1977).
The
directly
construction of roads affects
removing
by
elk
in
habitat
productive
possible
two ways:
and
1975;
indirectly by creating a disturbance factor (Compton,
19714).
Perry and Overly; Rost and Bailey,
road bed width, roads remove
production for
2.7
Depending upon
to 14.1 acres of land fom
1979).
each mile of road (Pederson, et al,
(1977) stated that roads permanently remove
Sidhu and Case
5-10 percent of the productive cutover area from production
at
the
time of first harvest and that subsequent harvest
could increase this loss.
that
during
adjacent
to
road
the
Pederson et al.,
construction elk
disturbance area
avoided
for
a
(1979)
found
using habitat
distance
of
820
feet.
The
extent
to
which
roads
may
reduce
elk
use
of
adjacent habitat varies by season and according to the size
and the location of the road, traffic intensity, and cover
availability.
Rost and Bailey
(1979) demonstrated that elk
more actively avoid paved and gravel roadside habitat than
215
primitive road habitat.
that
present
Pederson et al.,
research
effectiveness is
data
reduced by
indicates
69
(1980)
that
reported
habitat
elk
percent where one mile of
primary road and one mile of secondary road per square mile
of habitat
is open to traffic.
found
elk avoid
that
Hershey and Leege (1976)
primary and
distance of 1,320 feet.
secondary
Perry and Overly
roads
(1977)
for
a
observed
that elk use up to one-half mile from a road edge increased
15
percent
paved
for
roads,
108
percent
secondary
for
roads, and 33 percent for primitive roads.
Compton
(1975)
recorded that elk observed in the open respond to vehicles
up to one-half mile away.
Beall
(197L) reported that elk
avoided primitive spur roads and
jeep trails with little
traffic
found
only
that
during
hunting
the
elk were more
Marcum
seasons.
tolerant of roads
July, increasingly intolerant from August to
more tolerant again in November.
Roby
Marcum
(1975)
June
in
and
October, and
(1975),
Gruell and
(1976) and Schoen (1977) concluded that elk do not
avoid primitive roads,
they avoid human activity on road
ways.
Management Intensification
The management of public forest land
characterized
by
management
utilization
practices
regenerations,
eugenics).
the
The
stocking
ultimate
(shorter
control,
influence
is increasingly.
intensive
of
rotations,
fertilization
of
intensive
forest
rapid
and
timber
216
management is yet unknown; to date, no stand of intensively
managed Douglas fir has completed a rotation (Campbell and
Evans,
The length of the growth cycle,
1980).
the speed
with which cutover lands are reforested, stocking control,
fertilization, and eugenic activities will all have effects
1973).
on future big game numbers (Hines,
Shortening the
rotation period
increase annual
will
harvest acreage and the proportion of forest area in the
earlier stages of forest succession (younger age classes).
Theoretically, increases in annual harvest acreage should
provide
increased
Lawrence
(1969) estimated that shortening the rotation of
Douglas fir from
forage
80
capacity for deer.
and
to
14Q
potential
deer
for
elk.
and
years may double the carrying
In practice, however, shorter cycles
silvicultural activities designed
accelerate tree
to
growth early in the rotation period reduces the number of
years a cutover is in maximum forage production and reduces
the maximum carrying capacity that can be attained (Hines,
1973; Lemos and Hines, 19714).
Stocking control activities designed
density
promote
and
conditions for
commercial
optimal
timber
to
reduce
production
improve
the production of big game forage.
thinning
increases
forage
tree
Pre-
potential
during
earlier age classes; commercial thinning stimulates forage
production
influence
in
the
later
age
ultimate
Factors
classes.
impacts
of
that
stocking
will
control
activities upon big game forage production and utilization
217
include
tree
composition
stern density,
size,
of
the
forage
location,
stand
vegetation
stocking control activities (Hines
and
species
timing
the
of
1973, Gibbons and Salo,
1973; Witmer, 1981).
The application of fertilizers and the utilization of
superior planting stocks are management practices designed
to
accelerate
acceleration of
forage
growth
stand
and
forest canopy
productivity
development.
reduces
closure
potential.
Any
The
area's
an
beneficial
initial
responses of big game forage to fertilization may very well
be
overshadowed
by
a
more
rapid
decline
forage
in
production caused by the accelerated closure of the forest
canopy.
The actual and ultimate effects of fertilization
and eugenics on big game carrying capacities are yet to be
fully investigated (Hines,
1973
p.
41; Campbell and Evans,
1980, 59).
Fisheries
Timber management activities which physically modify
the aquatic environment directly influence the hydrological
and
biological
components
of
a
stream
Forest
system.
management activities are highly compatible with increased
water yield but not compatible with water quality (Goodell,
1971; Lynch and Sopper, 1970).
the
simultaneous
totally
production of
compatible
activities,
mutually exclusive (Everest,
It is well documented that
timber
but
and
fish
neither
are
are
not
they
1981; Gibbons and Salo, 1973;
218
1976; Lantz, 1971).
Harr,
forest
management
a review of the effects of
In
activities
(1973)
production, Gibbons and Salo
derived inconclusive results,
resource
fishery
on
found that 63 articles
95 discussed adverse logging
practices or the mitigation of adverse logging practices,
10
were
indeterminate
harvesting
upon
as
fishery
effects
the
to
resources,
timber
of
seven
presented
quantitative evidence of the detrimental impacts of timber
harvesting
evidence
upon
fisheries
supportive
of
production,
and
proposition
the
advanced
five
timber
that
harvesting is beneficial to fisheries production.
Habitat
requirements
of
populations
fishery
are
species specific, vary.ing with the season of the year and
the
stage
of
life
the
cycle,
and
are
related
stream
to
sediment, stream flow, debris, stream temperature, surface
and
intragravel
b ioma ss
and
dissolved
size
of
streamside
oxygen,
aquatic
cover,
invertebrates,
and
structure and biomass of fish populations (Everest,
1979).
Reiser and Bjornn,
1966).
and Moring and Lantz
certain
parameters
populations
while
are
anadromous
Hall and Lantz
(19714)
by
salmonids
1972; Kiefling,
(1969),
Lantz
1972;
(1970)
have demonstrated that within
cutthroat
altered
1981;
to aquatic changes than are
anadromous salmonid species (Giger,
1965;
the
Research has shown that trout
species are more susceptible
Lowry,
the
trout
forest
species
(Salmo
harvesting
are
not.
clarki)
activities
Because
cutthroat trout and other salmonidae species are separated
219
by narrow environmental tolerance limits, Moring and Lantz
(19714)
recommend
cutthroat
that
can
trout
be
useful
a
indicator species, "change in cutthroat populations can be
an
indication
imminent
of
changes
salmonids."
other
in
19714, p. 214).
(Moring and Lantz,
Sediment
Of all
fishery populations,
factors influencing
the
bedload sediments are the most detrimental:
fill gravel restricting
and
reducing
dissolved
and
oxygen
intragravel waterfiows
quantities
incubating
to
(2) deposited sediment can physically prevent
fishery ova;
(3) sediment reduces food resources by
fry emergence, and
filling
inter
(1) sediments
gravel
substrates
intensities
aquatic,
for
communities (Anon,
instable
promoting
and
invertabrate,
perphyton
and
1970, Brown and Krygier, 1970.
Gibbons and Salo (1973) reviewed over 25 articles on
the impacts of forest operations (timber harvesting, timber
yarding,
disposal
slash
environments
activities
the
sedimentation.
road
concluded
and
are
and
primary
Swanston
and
building)
source
construction
road
that
stream
increased
of
Swanson
stream
on
(1976)
found
that
stream sedimentation associated with roads was 25-314 times
greater
than
areas.
Yee
stream
and
sedimentation
Roelofs
(1980)
in
unroaded
observed
that
forested
while
the
incremental sediment contribution per unit area from roads
is often many times that from all other forest management
220
activities, both roads and harvesting operations appear to
contribute
sediment
based on total area.
material
debris
and
1972 found that stream
Rice et al.,
sediment is generally proportional
equally
nearly
the amount of base
to
soil exposed in a watershed.
Streamf low
management
Forest
quality and
alter
activities
quantity,
the
timing of streamfiow from a watershed.
magnitude of change in streamflow varies with the
and the
1978; Douglas Fir Supply Study, 1969; Gibbons and
1973;
less than
skid
season
intensity and type of forest management activity
(Beschta,
Salo,
The
Barr,
1976).
(1976) reported that,
Barr
"If
10% of a watershed is in haul roads or tractor
decreases
roads,
summer
in
slows
increases
or
in
1976 p.
damaging winter flood flows will not occur." (Barr,
10).
Streamflow
regulates
velocities of a stream.
migration
create
(Thompson,
water
abilities
spawning
streamflow
area
1972);
1973;
Watts,
1973).
quality of spawning,
(Gangmark and Broad,
too
that
available
(Fry,
depth
and
water
Too little streamflow can inhibit
velocities
(Bell,
water
the
is
great
may
exceed
19724).
fish
The
controlled
by
Fry,
can
swimming
quantity
of
amount
of
the
Stream velocities regulate
incubating and
1956;
streamfloj
a
the
rearing environments
1973; Thompson, 1972).
221
Debris
The accumulation of debris material in streams can be
either
beneficial
or
detrimental
populations
fishery
to
depending upon the stream size, the size, quantity and rate
of debris accumulation and the species of fish (Everest and
1981).
Meehan,
Large debris accumulations in medium sized
streams (thi:rd and fourth order streams) provide cover for
1971; Hall and
resident trout and anadromous fish (Narver,
1975),
Baker,
create
habitats
(Swanson
1975; Swanson
1978).
Lienkaemper,
can
inhibit
or
Massive
prohibit
the
flooding
bank
erosion
(Helmers,
channel
and
1966).
197k)
instability
debris
Dislodged
debris
migration
anadromous fish (Homiman and Evans, 1964; Meehan,
intensify
for
1975; 1978) and stabilize stream beds and
and Lienkaemper,
accumulations
rearing
and
1979; Bustard and Narver,
salmonids (Baker,
banks
spawning
of
and
during
can
scour
streambeds thereby removing cover and gravel and altering
stream
morphology
(Everest,
1981).
Increases
in
concentration of small debris in streams can enhance food
supplies
(Cummins,
however,
if
19714; Swanson
excessive,
small
and
debris
accumulations
potentially
toxic
estuaries (]3uchanan, et al.,
lachates,
can
1969)
and
particularly
in
reduce dissolved oxygen levels (Hall and Lantz,
produce
1975)
Lienkaemper,
1976).
Natural accumulation of debris in streams is slow and
fairly constant
in
mature
forests,
and
eventually
moves
222
towards an equilibrium between the rate of increase and the
rate of biological and physical processing
stands
(Sedell
Triska,
and
in old growth
management
Forest
1977).
activities change the rate and size of debris accumulations
in
streams.
The
magnitude
depends
change
of
upon
the
timing, extensiveness and the type of forest activity and
the
topography
pre-existing
and
1981,
(Everest and Meehan,
Harr,
conditions
1976).
the
of
area
1esearch indicates
that the rates and magnitudes approximately equal to the
natural
rates
quantities
and
magnitudes
and
1976; Moring and Lantz,
hundreds of times greater (Harr,
19711; Swanston,
rates
to
1980; Swanston and Swanson, 1976).
Temperature
Stream
temperature
environmental
Unusual
factors
temperatures
patterns (Bell,
Brown,
1973;
Moring
incubation success
(Brett,
vegetation
is
one
influencing
influence
the
of
most
populations.
fishery
residency
important
and
migratory
1973), dissolved oxygen levels (Braizer and
(Reiser and Bjornn,
survival
is
and
Lantz,
197!)
disease
incidence
1979), spawning activity (Bell, 1973),
Reiser and Bjornn,
1952;
removed,
McAfee,
exposing
1976) and juvenile
1966).
the
If
stream
streamside
to
direct
sunlight, water temperatures generally increase during all
seasons
1974).
(Chapman,
Research
1962;
Greene,
indicates
that
1950;
Moring
and
Lantz,
the
effect
of
forest
management activities on stream temperature varies with the
223
amount of cutting (Brown and Krygier,
1970; Meehan et al.,
1969), the size of the impacted stream (Brown, 1971;
and Krygier,
1970) and the aspect of the watershed (Levino
1967).
and Bothacher,
are
left
Brown
along
Where buffer strips of vegetation
streambanks,
the
changes
in
temperatures have been found to be minimal (Braizer,
Braizer and Brown,
water
1973;
1972; 1973).
Dissolved 0xyen
Reduced dissolved oxygen levels can adversely affect
the
population
densities
and
distributions
of
resident
trout and salznonid species (Moring and Lantz, 19714,
1975).
Low dissolved oxygen concentrations can adversely affect
the swimming performance of resident and salmonid fishery
species (Davis, Foster, Warren and Doudoroff,
19149)
can
and
(Whitmore
cause
and
a
cessation
Doudoroff,
of
1963; Graham,
migration
salmorlid
1960).
oxygen
Reduced
concentrations lengthen incubation periods (Shumway, Warren
and
Doudoroff,
19614)
stimulate
(Alderdice, Wickett and Brett,
vitality
(Silver,
al., 19611).
1958), reduce fry size and
Warren and Doudoroff,
1963;
Shumway et
Low concentration of dissolved oxygen decrease
the growth rate,
food consumption rate, and efficiency of
food utilization of juvenile fishery species
Herrxnann, Warren and Doudoroff,
Forest
hatching
premature
management
(Fry,
1957;
1962).
activities
influence
dissolved oxygen levels in three principal ways.
stream
Increases
224
in
stream sedimentation resulting from timber harvesting
operations
streambed
fill
reducing
gravel
gravel
the
intensities available for the retention of dissolved oxygen
(Koski, Moring and Lantz, 197; Phillips,
in
stream
temperatures
arising
1971).
from
Increases
removal
the
of
streamside vegetation decrease the capacity of stream water
1973; Moring
to retain dissolved oxygen (Brazier and Brown,
1975).
1974,
Lantz,
and
populations
resulting
debris
increase
can
Increases
from
the
the
demand
microorganism
in
of
decomposition
for
dissolved
oxygen
fishery populations beyond the
microorganism and
logging
by
streams
197'4,
ability to supply dissolved oxygen (Moring and Lantz,
1975).
Cover
Overhanging
submerged
streamside
vegetation
and
undercut
vegetation,
rocks,
banks,
water
debris,
floating
depth and turbulence provide cover for fishery populations
1972).
(Giger,
Cover
is perhaps most important
to
fish
species survival during rearing than at any other time, as
it
is
when
increased
they
water
are
most
temperatures
susceptible
(Reiser
predation
to
and
Bjornn,
and
1979).
The role of cover becomes less important as stream width
and streamfiow increase (Gibbons and Salo,
1973).
Forest management activities which remove
streamside cover,
supplies,
increase
or
damage
increase water temperature, reduce food
sediment
and
debris
and
increase
the
225
likelihood of disturbance and predation (Gibbons and Salo,
1973;
Reiser
Bjornn,
and
1978).
Steinblums,
1979;
The
retention and protection of vegetative buffer strips during
the
execution
stream
of
temperature
Ponce and Brown,
forest
increases
Meehan,
food
1978)
buffer
and
debris
(Moring and
1979).
indicates that
and
1973;
Brown,
Research
the
1973;
1973; Gibbons and Salo,
accumulations
1981; Moring and Lantz,
supplies
Bjornn,
(Brazier
reduces
1973), physical disturbances of streambeds
and channel banks (Brazier,
Steinbluxns,
activities
management
1971;
by
Ponce
1975;
a
Reiser and
Brown
and
maximum effectiveness
strip was reached within
and
1975). and increases
197k;
Lantz,
(Everest
of
the
width of 80
(1973)
average
feet;
90
percent of that maximumwas attained within 55 feet (Ponce
and Brown,
1973; p.
8).
226
APPENDIX C
Discussion of the development of production
coefficients used in the analysis.
227
purpose
The
appendix
this
of'
to
is
describe
the
development of non-timber production coefficients presented
The procedure adopted
in Chapter IV and used in Chapter V.
to
develop
study
area
resource
non-timber
production
coefficients was to relate deer, elk, cattle, and salmonid
populations to the number of years that have elapsed since
logging
management
forest
and
grazing
cattle
and
Research studies considered and
intensification levels.
production assumptions adopted in the analysis are reviewed
in the following pages.
For the purposes of this study, the elapse times
since
harvesting
stand
used
production
potentials
are
Production
potentials
for
predicting
for
model
age
classes.
cattle
and
elk
TREES
deer,
resource
are
expressed as area grazing capacities (resource pr.oduction
levels
which
resources).
fishery
do
potentials
production
The
species
(numbers
in
the
impact
of
timber
as
anadromous
or
forage
for
anadromous
salznonid
escapement
potentials
expressed
are
spawning purposes).
used
adversely
not
fish
available
for
The resource production coefficients
analysis
are
described
in
the
following
paragraphs,
Deer
Research by
(1973)
and House
Black
(1971)
(1969,
197'4),
indicate
Brown
that
the
(1961),
Hines
deer carrying
228
capacity of an area increases immediately after logging.
Area
deer
animals
carrying
per
decrease
by
potentials
square
mile
20-30
percent
reach
years
10-30
every
two
a
peak
after
decades
of
10Oi10
logging
and
thereafter
until 100 years have elapsed since harvesting.. The carrying
capacity
of
stands
in
relatively constant at
excess
of
100
years
remains
25 animals per square mile.
thinning is performed, deer
If
potentials are observed
to increase by7 to 10 percent (Brown, 1961; Hines, 1973).
For
the
purposes of this
study,
the average annual
deer grazing potential of timber 0-10 years of' age
is
30
animals per square mile (area grazing capacity is assumed
to be 60 percent of area carrying capacity).
The average
annual deer grazing capacity of timber 10-30 years of age
is assumed to be 75 animals per square mile. The average
annual deer grazing potential of timber 30-50 years of age
is assumed to be 52 animals per square mile.
The average
annual deer grazing capacity of timber 50-70 years old is
presumed to be 35 animals per square mile.
90 years of age,
For timber 70-
the average annual grazing potential of
deer is assumed to be 28 deer per square mile.
90-100 years age,
deer
is
presumed
For timber
the average annual grazing capacity of
to
be 20 animals per square mile.
The
average annual deer grazing capacity of timber in excess of
110 years of age is assumed to be 15 deer per square mile.
Precommercial thinning activities are assumed
area
deer
grazing capacities
by
7
percent.
to increase
Commercial
229
thinning
grazing
activities
are
potentials
by
assumed
percent.
10
increase
to
area
densities
Deer
deer
and
distributions are presumed to be independent of elk, cattle
and salmoriid densities and distributions.
Cattle
Research by Gibbons and Salo (1973), Harshman (1971)
and Young, Hendrick and Keniston (1967) indicate that the
cattle carrying potential of an area increases immediately
after logging and reaches a peak of 50 animals per square
mile within 5-20 years of harvesting. Area cattle
potentials
decrease
logging.
by
Area cattle
80-90
percent
20-40
carrying
years
after
potentials remain relatively stable
at 9 animals per square mile 140_80 years after cutting. At
80-90
years
after
harvesting,
cattle
area
carrying
capacities increase by 20-30 percent and remain relatively
constant thereafter at approximately
mile.
stands
If
stands
capacities
precominercially
thinned,
cattle
are observed to increase by 10 percent.
potentials
If
are
cattle per square
7
are
are
commercially
observed
increase
to
cattle
thinned,
by
30_10
carrying
percent
(Harshman, 1971; Young et al., 1967).
For
the
purposes
of
analysis,
the
annual
cattle
grazing capacity of timber 0-20 years of age is assumed to
be 30 animals per square mile.
The average annual cattle
grazing potential of timber 20140 years of age is presumed
to be 5.6 animals per square mile.
For timber 40-8O years
230
of age,
the average annual grazing capacity of cattle is
assumed
to
annual
be
cattle
older
is
animals per
3
grazing
assumed
to
potential
be
mile.
square
of
timber
animals
24
average
The
years
90
square
per
and
mile.
Precominercial thinning is presumed to increase area cattle
grazing
potentials
activities
assumed
are
potentials by
by
33
10
to
percent.
percent.
increase
Commercial
area
cattle
thinning
grazing
Cattle grazing capacities are
assumed to be independent of natural deer, elk and salmonid
densities and distributions.
Elk
Research by Gibbons and Salo (1973), Lemos and Hines
(1974) and Mackie (1978) indicate that elk usage of an area
decreases immediately after
logging.
Area
elk carrying
capacity reaches a peak of 33 animals per square mile 10-20
years after logging and declines gradually by 10-20 percent
every
decades
two
elapsed
thereafter
since harvesting.
timber in
stable at
excess of
11
The
until
90-100
years
have
elk carrying capacity of
100 years of age remains relatively
animals per square mile.
For the purposes of analysis, the average annual elk
grazing capacity of timber 0-10 years of age is assumed to
be
2
animals
per
square
mile.
The
average
annual
elk
grazing capacity of timber 10-20 years of age is presumed
to be 20 elk per square mile.
For timber 20-240 years of
age, the average annual elk grazing potential is assumed to
231
be 15 animals per square mile.
age,
average
the
annual
For timber Lt060 years of
grazing
potential
presumed to be 12.5 animals per square mile.
of
elk
is
The average
annual elk grazing capacity of timber 60-80 years of age is
assumed to be
animals per square mile.
11
100 years of age,
For timber 80-
the average annual grazing potential of
elk is assumed to be
elk per square mile.
8
The average
annual grazing potential of timber in excess of 100 years
of age is assumed to be 6.5 elk per square mile.
No elk
grazing capacity increases are identified for precommercial
and commercial thinning activities.
capacity
assumed
increases
to
be
arising
forage
from
counterbalanced
Potential elk grazing
by
increases
reduced
area
are
usage
associated with increased human activity.
While deer are indifferent to the presence of grazing
cattle, studies have shown a strong negative relationship
between area elk populations and cattle grazing intensities
(Mackie,
1976,
1978,
Slovlin
et
al.,
1968).
For
the
purposes of analysis, light cattle grazing (cattle grazing
density
50
percent
less
than
the
area's
cattle
grazing
capacity) is assumed to reduce area elk grazing capacity by
30 percent.
Moderate cattle grazing (area's cattle grazing
capacity) and heavy cattle grazing (cattle grazing density
50 percent greater than the area's cattle grazing capacity)
are assumed to reduce elk grazing potentials by 50 percent.
232
Salmonids
(1969),
Research by Hall and Lantz
(1973),
Moring
and
Lantz
(197k)
and
Gibbons and Salo
(1980)
Swariston
indicate that the two most important variables influencing
the fisheries production capacity of an area are
Logging impacts typically occur during
and natural events.
the
course
immediately
of
logging
cutting
activities
within
or
Natural event
following harvesting.
occur throughout forest stand rotations.
years
the
impacts
Adverse impacts
resulting from logging activities and natural events are
projected by the Forest Service to reduce the study area's
overall fisheries production capacity by 10 percent.
For the purposes of analysis, logging activities are
assumed to reduce area salmonid escapement potentials by 30
percent for
the first decade following harvesting and
Major natural events were
percent for the second decade.
assumed
to
occur
the
at
15
rotation
Salmonid
mid-point.
escapement reductions associated with major natural events
are assumed to be identical to logging activity reductions.
Per unit
salmonid escapement numbers were
area,
using the methodology employed by Kunkel and Janik
derived
(1976).
Reflecting the observed negative relationship between
cattle
grazing
and
(Behnke and Zarn,
19711;
1976;
are
reduced
1978)
by
and
distributions
1977; Gunderson, 1968;
Duff,
Meehan and Platts,
potentials
densities
sairnonid
10
area
salmonid
percent
when
Lorz,
escapement
cattle
area
233
grazed at a moderate level of grazing intensity and by 20
percent
when
intensity.
cattle
are
grazed
at
a
heavy
level
of
234
APPENDIX D
Stumpage value and regeneration and cultural
treatment costs used in TREES simulation runs.
235
This
section
regeneration
analysis.
and
identifies
cultural
the
treatment
stumpage
costs
value
used
in
and
the
Revenue and silvicultural costs used in Chapter
V are presented below.
Stumpage Value and
Regeneration and Cultural
Treatment Costs
Stumpage market value 173/MBF
Cost/Acre
Regeneration per cutover acre
1401
Regeneration per unstocked acre
501
Precommercial Thinning
201
Fertilization
Cultural Treatment
55
299