AN ABSTRACT OF THE THESIS OF
Donald Sachs for the degree of Master of Science in Forest Science
presented on May 25, 1983.
Title: Management Effects on Nitrogen Nutrition and Long-term
Productivity of Western Hemlock Stands:
An Exercise in Simulation
with FORCYTE
Abstract approved:
Signature redacted for privacy.
Phillip Sollins
Regression equations applicable to biomass components of stands
of western hemlock [Tsuga heterophylla (Raf.) Sarg.} were developed
by destructive sampling of a thinned and an unthinned stand of
western hemlock near Seaside, Oregon.
Equations predicted more live-
branch biomass and less dead-branch biomass per tree for the thinned
stand, but equations for biomass of foliage, twigs, stern wood and
stem bark did not differ significantly between stands.
Concentra-
tions of N, F, K, S, Ca, Mg, and Mn in tree components were deternir.ed and aboveground tree biomass and nutrient content were esti-
mated for both stands.
The biomass data was used in conjunction with published data to
modify an existing computer model in order to simulate growth and
nutrient cycling of western hemlock stands.
The FORCYTE computer
model, originally developed for Douglas-fir forests in British
Columbia by J. P. Kitnmins and K. Scoullar, was used.
Calibration
runs indicated that yield in FORCYTE was extremely sensitive to the
parameter defining the rate of mineralization of soil organic matter,
a process which supplied the majority of N available for tree uptake.
The mineralization rate was set initially so that yield remained
constant in three succesive 90 year rotations, which resulted in a
4.1% loss of soil organic matter over the 270 year period.
Simula-
tions of 6 different 270 year management scenarios of varying intensity indicated that more intensive management (e.g., whole-tree har-
vesting and commercial thinning) caused faster depletion of soil
organic matter and site N capital, resulting in an eventual decline
in site productivity in later rotations.
Simulations suggested that
hemlock forests may not begin to accumulate soil organic matter until
they approach old-growth status.
Predicted declines in soil organic
matter caused by intensive management were compared to documented
losses of organic matter in agricultural systems.
FORCYTE predicted
soil organic matter would eventually equilibrate in about 1500 years
when inputs to the soil organic matter pool balanced decomposition,
resulting in an equilibrium yield level well below that of the first
rotation, but sustainable in perpetuity.
nesses of the FORCYTE model are discussed.
The strengths and weakThe predicted trends are
based on currently available information, but it must be realized
that as more information becomes available, predictions will inevitably change.
Management Effects on Nitrogen Nutrition
and Long-term Productivity of Western Hemlock Stands:
An Exercise in Simulation with FORCYTE
by
Donald Sachs
A THESIS
submitted to
Oregon State University
in partial fulfillment of
the requirements for the
degree of
Master of Science
Completed
Commencement
May 25, 1983
June 1984
APPROVED:
Signature redacted for privacy.
Research'Ass4jate professor of Forest Science in charge of major
Signature redacted for privacy.
Read of Department of Forest Science
Signature redacted for privacy.
Dean of Gra(ate School
Date thesis is presented
May 25, 1983
Typed by Kathy Faubel for
Donald Sachs
Acknowledgements
I gratefully acknowledge the assistance of Crown Zellerbach
Corporation, which provided the study Site and the great majority of
the funding for this project.
Walt Shields and Bob Walkup at C-Z
Forestry Research Division were extremely helpful.
Larry French at
C-Z in Seaside felled the sample trees and probably saved me from
getting hurt doing it myself.
I am also grateful to the OSU Computer
Center for providing additional funding for computer time.
Paul
Buckley helped with many hours of field work, Chris Geanious ground
many of the samples, and Carol Glassman did her usual flawless job
with the sample digestions.
Many persons, both faculty and students, have gone out of their
way to assist me with this project and have made my stay at OSU most
enjoyable.
Greg Koerper and Paul Alaback of the Forest Science Data
Bank provided valuable assistance with field data sheet design, data
handling, and storage.
Rod Slagle answered all my SPSS questions.
All the members of my committee have been quite helpful and supportive.
I also wish to thank Dr. Susan Stafford for her help with sta-
tistical design and analysis.
questions.
She was always available to answer my
I thank all who have reviewed these papers.
I have learned the most from one person during my two years
here.
Dr. Phillip Sollins, my major professor, and my friend, has
helped in every phase of this project.
He tolerated my rather erra-
tic schedule, kept me on course, and allowed me to do this project in
my own way without constantly looking over my shoulder.
Phil has
undoubtedly influenced the direction of my career in a most positive
way.
I wish to thank, him for putting up with me for two years.
TABLE OF CONTENTS
Page
INTRODUCTION
DISTRIBUTION OF BIOMASS, NUTRIENTS, AND AVAILABLE
NITROGEN IN A THINNED AND AN UNTHINNED STAND OF
WESTERN HEMLOCK
Introduction
Study site
Methods
Results and discussion
III
MANAGEMENT EFFECTS ON NITROGEN NUTRITION AND LONGTERM PRODUCTIVITY OF WESTERN HEMLOCK STANDS:
AN
EXERCISE IN SIMULATION WITH FORCYTE
Introduction
Description of FORCYTE
Calibration for western hemlock
Results and discussion
Conclusions
1
2
2
3
4
7
19
19
20
21
27
39
BIBLIOGRAPHY
42
APPENDIX
49
LIST OF FIGURES
Figure
Page
Distribution of N, P, and K in the aboveground
tree biomass of an unthinried stand of western
hemlock near Seaside, Oregon.
16
Predicted levels of available N, stored N, and
leaching of NO3 during a 90-year rotation.
28
Predicted annual net primary production, biomass harvested, and biomass of forest floor
plus soil organic matter during a 27O-year
simulation under six different management
scenarios.
31
Predicted yields over 40 rotations under management scenario D as described in Figure 3.
38
LIST OF TABLES
Table
Page
Biomass components of a 30-cm tree as predicted
with equations developed from data for trees at
Haney British Columbia (Krumlik 1974) and at
Seaside, Oregon.
9
Biomass equations for coastal western hemlock.
10
Nutrient concentrations (%) in tree components.
12
Component biomass and nutrient content of thinned
and unthinned stands of coastal western hemlock.
14
Nitrogen status of the forest floor and mineral
soil of a thinned and an unthinned stand of
coastal western hemlock.
15
Predicted biomass of forest floor components in
a 90 year-old stand.
24
Effects of alternate assumptions about the rate
of N mineralization after clearcutting upon soil
organic matter levels and yields.
35
MANAGEMENT EFFECTS ON NITROGEN NUTRITION AND LONG-TERM PRODUCTIVITY
OF WESTERN HEMLOCK STANDS: AN EXERCISE IN SIMULATION WITH FORCYTE
INTRODUCT ION
The major objective of this research was to investigate the
long-term effects of intensive management on site productivity of
Oregon coastal western hemlock forests.
This was done with the aid
of FORCYTE, a mangement-oriented simulation model of forest growth
and nutrient cycling.
FORCYTE was originally developed for Douglas-
fir forests in British Columbia and required modification to simulate
western hemlock forests.
The first paper in this thesis describes
the collection of data necessary for the modification of FORCYTE,
including:
development of biomass equations for western hemlock on
the Oregon coast, determination of nutrient content of the various
tree components, and measurement of mineralizable N, an index of N
availability, in the soil and forest floor of the hemlock stands.
The second paper details the modification of FORCYTE and the results
of the simulation.
2
DISTRIBUTION OF BIOMASS, NUTRIENTS, AND AVAILABLE NITROGEN
IN A THINNED AND AN UNTHINNED STAND OF WESTERN HEMLOCK
Introduction
As forest management intensifies and rotation lengths shorten,
the concern is that removal of large amounts of nutrients from
forests may adversely affect site productivity (e.g., Leaf 1979).
Methods for quantifying the biomass and nutrient content of forest
stands are needed for estimating the amounts removed by various harvest operations.
Commonly, regression equations relating the biomass
of tree components to diameter at breast height (dbh) are used to
estimate forest biomass.
Gholz etal. (1979) developed equations for some Pacific
Northwestern species of trees, shrubs, and herbs growing mainly in
natural, unmanaged, old-growth forest stands.
The equations for
western hemlock [Tsuga heterophylla (Raf.) Sarg.} combined data from
three unmanaged stands--a young coastal stand near Otis, Oregon
(Fujimori 1971), an old-growth stand near Haney, B.C.
(Krumlik
1974), and an old-growth stand in the Oregon Cascades (Grier and
Logan 1977).
But because management practices such as thinning are
known to affect stem form and crown development (Larson 1963; Assman
1970), thereby changing the partitioning of biomass within the tree,
biomass equations developed for unmanaged stands may be inaccurate
for thinned stands.
The objectives in this study were to develop biomass regression
equations applicable to both thinned and unthinned stands of Coast
3
Range western hemlock, then to measure nutrient concentrations in
tree components and use the data with the bioinass equations for
calculating amounts of biomass and nutrients removed during harvest.
Available N in the soil and forest floor was measured in order to
learn whether the stands were N limited and in order to assess the
potential long-term effects of harvest practices on nutrient availability.
Study site
The two study sites were adjacent 52-year-old stands of western
hemlock located on a gentle (0-10°) southwest slope at 250-m elevation in Crown Zellerbach's Clatsop Managed Forest near Seaside,
Oregon (T.6 N., R.9 W., Sect. 16).
Average minimum and maximum tem-
peratures in this area are 0°C and 8.9°C in January, 11.1°C and 20°C
in July.
Annual precipitation averages 190 cm, 20 cm falling between
May and September (National Oceanographic and Atmospheric
Administration records for Seaside, Oregon).
The soil is of the
Hembre series (fine-loamy, mixed, isomesic, Typic Haplumbrept).
The present stands were established by natural regeneration
after logging in the l92Ots.
One stand was thinned five times bet-
ween 1960 and 1970 to maintain a basal area of 41 m2/ha; the other
remains unthinned.
In 1980, the thinned stand had 700 trees/ha and
66.8 m2/ha basal area, the unthinned stand 1,110 trees/ha and 81.8
ni2/ha basal area.
The understory, dominated by western hemlock
seedlings, also includes Oxalis oregana Nutt., Vaccinium parvifolium
Smith, V. ovalifolium Smith, Viola sempervirens Greene, Thelypteris
4
phegopteris (L.) Slosson, Montia sibirica (L.) Howell, and
Eurhynchium oreganum (Sull.) Jaeg.
Methods
Tree sampling
A diameter-frequency distribution of 5-cm-diameter classes was
constructed for each stand from inventory data.
The 11 trees
selected for sampling in each stand spanned the diameter range and
were allocated according to the diameter distribution.
Random num-
bers were used to choose a pair of coordinates on a grid system
established at each site, and the tree of the desired diameter class
closest to the coordinate intersection was sampled.
In the field, diameter at breast height (1.3 m) of each sample
tree was measured before and total height after a tree was felled.
The main stem was marked at four points:
at breast height, midway
between breast height and the first live branch, at 5 cm below the
first live branch, and midway in the live crown.
The crown was
divided into three strata of equal length and all branches were
removed from the main stem.
After dead branches, dead portions of
live branches, and foliage-bearing twigs were separated from live
branches, all components were weighed in the field.
In preparation for establishing dry-to-green-weight ratios,
a
sample branch selected randomly from each stratum was bagged,
weighed, and returned to the laboratory for oven drying.
Also, the
main stem of each tree was cut at the marked points, and a disk
removed from the base of each section was weighed and returned to the
5
laboratory for oven drying.
Stem sections from each of the smaller
trees were further cut into sections approximately 1 in long before
weighing in the field.
The sub-neiloid formula (Dilworth 1973) was
used to calculate volume of stem wood and bark from section length
and minimum and maximum diameters of larger stems measured inside and
outside the bark at each cut.
In the laboratory, bark and wood from the disks were separated
and dried with sample branch components for 1 week at 60°C.
Density
of wood and bark of the larger stem sections was determined by
dividing ovendry weight by green volume, which was measured by water
displacement (Forest Products Laboratory 1952).
We used the calcu-
lated wood and bark densities to convert volumes of large stem sections to ovendry weights.
After foliage was separated from foliage-
bearing twigs, the ratios of foliage dry weight and twig dry weight
to green weight of twigs-plus-foliage were calculated.
Dry-to-green
weight ratios were calculated for live and dead branches and for wood
and bark from smaller stem sections.
Green weights of all branch
components from each stratum and of bark and wood from small stein
sections were converted to dry weights by multiplying by the
appropriate dry-to-green-weight ratios.
Ovendry stem wood, stem bark, and sample branch components were
ground in a Wiley mill to pass through a 40-mesh screen (0.419 mm
opening).
The diameter range was divided into three equal size
classes and sample material was composited by class.
Foliage was
separated by sites and diameter classes (2 x 3 = 6 samples) and stem
wood by stem sections and diameter classes (4 x 3 = 12 samples).
6
N and P were determined with an Autoanalyzer, Technicon method
334-74 A/A, after a standard Kjeidahl digest with a copper-selenium
catalyst.
Total S was determined by a turbidometric method after dry
ashing (Tabatabi and Bremner 1970) and cations by standard methods of
atomic absorption spectroscopy after a perchioric acid digest.
Soil and litter sampling
Soil and litter were sampled at six locations at 7-m intervals
along a transect through each stand.
At each location, all litter
was removed from a 25- x 25-cm area and two soil cores were taken
from the top 7.5 cm of the mineral soil.
cooler during transport to the laboratory.
All samples were kept in a
Litter samples were
weighed fresh, and a lO-g subsample of each was oven dried at 60°C
for at least 4 days for determination of moisture content.
One soil
core from each location was oven dried similarly for bulk-density
determination.
Exchangeable N}i+4 was determined by extracting
triplicate 5-g subsamples of the remaining litter samples and soil
cores with 1 N KC1, and N availability by measuring net
produc-
tion during a 7-day anaerobic incubation at 40°C (Keeney and Bremner
1966).
All NW4-N measurements were made with an ion-selective HNU
Systems ammonium electrode.
Regression procedure
Regression equations were of the form in Y = a + b in X, where
Y = component biomass and X = dbh.
Tree height was not included in
the model as it did not significantly decrease the mean square residual for any tree component equation.
Regression equations developed
7
for each stand were compared by fitting a full model that included a
separate slope and intercept for each stand.
The hypothesis that the
slopes did not differ significantly was tested by fitting a reduced
model with a separate intercept but common slope for each stand and
by testing for a significant reduction in the regression sum of
squares (Cunia 1973).
A similar approach was used to test for a com-
mon intercept and to compare regressions from this study with those
developed from data taken by Krumlik (1974).
All equations were
checked for logarithmic bias with a computer program (developed by
Bruce Ludwig, Department of Forest Management, Oregon State
University) that calculates five correction factors according to
methods reviewed by Flewelling and Pienaar (1981).
All correction
factors applied to the coefficients decreased the accuracy of
prediction; therefore uncorrected coefficients are reported here.
Results and discussion
Regression equations
To test whether the development of local regression equations
was justified, those from this study were compared with those developed from data taken in British Columbia by Krumlik (1974).
Statistically significant differences between sites of the two studies were found in equations for stem wood, stem bark, and foliage
biomass.
For a tree of a given diameter, the equations from
Krumlik's data predicted less biomass for stem wood and more for stem
bark and foliage than did those from this study (Table 1).
8
The local equations for stem wood, stem bark, foliage, and twigs
(Table 2) applied equally to both thinned and unthinned stands, with
the exception that intercepts for live and dead branches differed
significantly (thinned, a = 0.1; unthinned, a = 0.01).
The
equations predicted more live-branch and less dead-branch biomass for
a given size tree in a thinned than in an unthinned stand.
For
example, a tree 30 cm in diameter in a thinned stand would have 23.4
kg of live-branch biomass and 7.3 kg of dead-branch biomass, but 17.4
kg and 11.7 kg in an unthinned stand.
nable.
Such differences are reaso-
A tree in a thinned stand, with more growing space and less
self-pruning, should support more live lower branches than a tree in
an unthinned stand.
Such a tree should also support more foliage
biomass; however, thinning did not affect the foliage biomass
equations.
Nor did the measured ratio of foliar to live-branch
biomass per tree differ between the stands (which would have
accounted for the lack of difference in the equations).
Possibly no
difference appeared because the sample size was limited and foliage
biomass per tree was highly variable, as evidenced by the foliage
biomass equation, which had the highest mean square residual (S2.),
thus the greatest uncertainty.
Tissue concentrations
The values for foliar N, P and K (Table 3) were similar to those
reported by Radwan and DeBell (1980) and Gill and Lavender (l983a)
for Coast Range western hemlock.
However, the values for foliar Ca,
Mg, and Mn were about twice those reported by Gill and Lavender, who
9
TABLE 1.
Biomass components of a 30-cm tree as predicted with
equations developed from data for trees at Haney, British
Columbia (Kruinlik 1974) and at Seaside, Oregon.
Tree
component
Haney
Seaside
Stem wood
221.85
281.95
Stem bark
48.08
27.45
Foliage
29.13
12.43
Biomass, kg
10
TABLE 2.
Biomass equations for coastal western hemlock
Coefficients
Component
B1
B2
Number of
trees sampled
r2
S2y.x
Equations of the form in Y = B0 + B2 (in X), where X is diameter at
breast height (cm) and Y is component biomass (kg).
Stemwood
-2.681
Stem bark
-4.371
Foliage
-6.524
Twigs
-6.611
-
-
2.447
19
0.98
0.032
2.259
19
0.97
0.035
2.659
21
0.91
0.157
2.431
21
0.91
0.123
Equations of the form in Y = B0 + B1(X1) + B2(ln X) where X =
diameter at breast height, X1 = 1 if site is thinned, X1 = 0 if site
is unthinned, and Y = component biomass (kg).
Live
branches
-4.876
0.306
2.271
21
0.89
0.139
Dead
branches
-7.085
-0.474
2.805
21
0.93
0.134
11
used direct-reading spark-emission spectroscopy after dry ashing
(Chaplin etal. 1974), a technique that often yields lower values for
cation concentrations than the technique used in this study CD.
Hanson, Department of Soil Science, Oregon State University, personal
communication).
Our data for concentrations of N, P, K, Ca, and Mg
in most tree components agreed well with data for samples from a
stand in the west-central Oregon Cascade Range analyzed with the same
techniques (C. C. Crier, unpublished data).
Discrepancies were in
the concentrations of N, P, and Ca in dead branches, which were about
twice as high at the coast sites as at the Cascade site.
Concentrations of N, S, and Mg were higher in dead than in live
branches; P, Ca, and Mn concentrations were slightly lower; and K was
much lower.
Apparently, K was translocated before death, or was
leached afterwards,
There was no evidence of translocation or
leaching of other elements.
Possibly the dead branches on the tree
suffered a net carbon loss due to microbial respiration during decomposition, which would increase concentrations of the remaining
nutrients.
Estimation of nutrient removal by harvest operations
The biomass equations and nutrient data made it possible to
estimate biomass and nutrient pools in the Coast Range western
hemlock stands from existing forest inventory data (Table 4).
Data
on total N concentrations in the surface mineral soil (0-20 cm) and
forest floor at nearby sites on the Clatsop Managed Forest (J. R.
Boyle, unpublished data) were used to calculate total N in the sur-
TABLE 3.
Nutrient concentrations (%) in tree components.
Component
Numbers of
samples*
N
P
Standard errors are in parentheses.
K
S
Ca
Mg
Mn
Foliage
6
1.16(0.007)
0.162(0.013)
0.565(0.036)
0.113(0.007)
0.497(0.047)
0.168(0.015)
0.152(0.017)
Twigs
3
0.827(0.044)
0.116(0.006)
0.437(0.032)
0.084(0.003)
0.120(0.006)
0.120(0.006)
0.074(0.009)
Live branches
3
0.330(0.020)
0.045(0.002)
0.223(0.009)
0.027(0.001)
0.053(0.003)
0.053(0.003)
0.047(0.002)
Dead branches
3
0.373(0.020)
0.035(0.005)
0.030(0.012)
0.048(0.001)
0.063(0.003)
0.063(0.003)
0.044(0009)
iod
12
0.080(0.003)
0.021(0.001)
0.075(0.005)
0.010(0.001)
0.018(0.002)
0.018(0.002)
0.013(0.001)
Stem bark
3
0.320(0.021)
0.055(0.005)
0.257(0.023)
0.036(0.003)
0.053(0.009)
0.053(0.009)
0.045(0.008)
Stem
*Compoeite samples, see text.
13
face soil and the forest floor of both thinned and unthinned stands
(Table 5).
We based mineral-soil bulk density, 0.5 g/cm3 for the top
20 cm, on data for other coastal Oregon sites (Grier 1976; J. Boyle
and K. Baker, personal communications).
Table 5 shows that the
unthinned stand had accumulated significantly more litter (z = 0.01)
than the thinned stand.
Repeated thinnings probably incorporated
litter into the soil, temporarily increased the rate of litter decomposition, and undoubtedly removed most of the trees that would have
died and subsequently added wood and foliage to the forest floor.
Data on biomass and nutrient content of stands can be used to
estimate amounts of nutrients removed in various harvest operations.
For example, a standard-stems-only clearcut would remove 379.8 (275.2
+ 104.6) kg N/ha from the site, accounting for 51.2% (37.1 + 14.1) of
the total N in the aboveground portions of the trees (Fig. 1).
(Not
all of this amount would be lost if some slash were left behind.)
Whole-tree harvesting would remove nearly twice as much, 740.9 N
kg/ha.
Delaying removal of felled trees until most of the foliage
had fallen could reduce the loss by as much as 181.2 kg/ha, though
the reduction would probably be smaller due to some translocation of
N back into the twigs before abscission.
Consequences of N and P removal
The N removed by clearcutting constitutes 5.0% of the total N in
the aboveground tree biomass, forest floor, and top 20 cm of the
mineral soil.
tal.
A whole-tree harvest would remove 9.7% of the N capi-
Though it seems unlikely that such removals would greatly
14
TABLE 4.
Component biomass and nutrient content of thinned and
unthinned stands of coastal western hemlock.
Component
Dry weight,
Mg/ha
N
P
-- kg/ha
K
Unthinned stand
Stem wood
Stem bark
Foliage
Twigs
Live branches
Dead branches
Total
344.0
6.4
28.0
9.3
436.0
275.2
104.6
181.2
52.8
92.2
34.8
740.8
72.6
17.8
25.3
7.4
12.6
3.3
139.0
258.0
84.0
88.3
27.9
62.3
300.6
27.8
14.1
5.6
23.8
8.6
380.4
240.5
88.9
163.4
46.0
78.5
32.1
649.4
63.1
15.3
22.8
225.4
71.4
79.6
24.3
53.0
2.6
456.3
32.7
15.6
2.8
523.3
Thinned stand
Stem wood
Stem bark
Foliage
Twigs
Live branches
Dead branches
Total
6.5
10.7
3.0
121.4
15
TABLE 5.
Nitrogen status of the forest floor and mineral soil of a
thinned and an unthinned stand of coastal western hemlock.
Standard errors are in parentheses.
Unit
Unthinned
stand
Forest floor mass
Mg/ha
62.9**(13.2) 17.8**(2.3)
Soil bulk density
(0-7.5 cm)
g / cm3
Exchangeable NH1.-N
pg /g
Parameter
Thinned
stand
71.4 (7.0)
20.5 (4.9)
pg /g
Forest floor
Soil (0-7.5 cm)
Total N (see text)
Forest floor
Soil (0-20 cm)
stands *
0.440 (0.43)
Forest floor
Soil (0-7.5 cm)
Net mineralizable
NHL + -N
Combined
363 (28)
151 (24)
kg/ha
614**
173**
7,000
* Combined values are reported where means for thinned and unthinned
stands did not differ significantly.
** Difference is significant at a = 0.01.
16
p
Figure 1.
Distribution of N, P, and K in the aboveground tree
hiomass of an unthinned stand of western hemlock near
Seaside, Oregon.
17
affect site productivity during the first several rotations, continued removals of organic matter might pose a long-term problem.
However, the consequences of nutrient removal from coastal western
hemlock sites depend on which element limits growth.
There is
substantial circumstantial evidence that P, not N, is limiting over
much of the area.
The amount of exchangeable NH+4N in the forest
floor (Table 5) is about twice the 31 ig/g reported by Vitousek et
al.
(1982) for a 120-year-old coastal stand of western henilock-sitka
spruce [Picea sitchensis (Bong.) Carr.} on the central Oregon coast,
but agrees well with the 85 pg/g reported by Sidle and Shaw (in
press) for a recently clearcut spruce-hemlock site in southeast
Alaska and with values for 10 other sites near our study area (J.
Boyle, personal communication).
The value for exchangeable NH+4_N in
the top 7.5 cm of the mineral soil (Table 5) is similar to those
reported for the top 0-15 cm of the soil at other coastal sites
(Vitousek etal. 1982; Sidle and Shaw in press; J. Boyle, personal
communication).
Mineralizable N is also plentiful.
Net NH+4 production
(anaerobic incubation) averaged 363 iig N/g for the forest floor and
151 pg N/g for the surface soil (Table 5), and differences between
the thinned and unthinned stands were not significant (c = 0.05).
Boyle (1982) reported similar values for 10 nearby stands.
Net NH+4
production from surface soil (0-15 cm) ranged from 6 to 139 pg N/g
for 16 stands of western hemlock in Washington--the average value for
coastal sites significantly higher than that for the Cascade Range
sites (Radwan and Shumway in press).
18
At both of our study sites and at 16 of the 18 sites in the studies just mentioned, levels of mineralizable N in the surface soil
far exceeded the fertilization-response thresholds reported for
Douglas-fir, 45 jig mineralizable N/g (Shumway and Atkinson 1978), and
for true fir and ponderosa pine, 16 jig N/g (Powers 1980).
These data
suggest that western hemlock may not generally be N limited at
coastal Sites, and they may explain in part the lower and more highly
variable response to N fertilization at coast sites than at Cascade
sites (Olson etal. 1979).
P availability may limit growth of coastal western hemlock
stands.
In their study of 16 such stands, which included fertilizer
test plots set up as part of the Regional Forest Nutrition Research
Project (Olson etal.
1979), Radwan and Shumway (in press) examined
correlations between the growth response to application of 224 kg/ha
of N fertilizer and the levels of total and available N, total
sulfate, mineralizable S, and extractable P.
Extractable P in the
forest floor correlated most significantly (r = 0.77, a = 0.001).
The mineral soil parameter that correlated best was the ratio of
extractable P to mineralizable N (r = 0.67, a = 0.005).
Extractable
P levels in both forest floor and surface mineral soil were signif i-
cantly higher in Cascade than in coastal sites.
In a greenhouse
study by ileilman and Ekuan (1980), hemlock seedlings grown in
Washington coastal soil responded significantly to P fertilization.
Because of this evidence and the results of our study, we believe
that P availability and dynamics should be emphasized in future
research on western hemlock nutrition at Coast Range sites.
19
MANAGEMENT EFFECTS ON NITROGEN NUTRITION AND
LONG-TERM PRODUCTIVITY OF WESTERN HEMLOCK STANDS:
AN EXERCISE IN SIMULATION WITH FDRCYTE
Introduction
It is difficult to estimate the long-term effects of forest
management practices without actually monitoring yield over several
rotations, which could, of course, take centuries.
What is needed is
a method of integrating current information from a wide variety of
studies to predict long-term trends.
simulation modeling.
This can be accomplished using
A management-oriented simulation model can be
of value to land managers because it allows the prediciton of the
long-term consequences of various silvicultural practices (Sollins et
al. (in press)).
Such models can also be useful to researchers by
providing a mechanism for integrating and testing ideas and to direct
and prioritize research (Van Veen et al. 1981).
Through sensitivity
analysis critical processes can be identified and research directed
where the need is greatest.
In this study we worked with FORCYTE, a management-oriented
simulation model of growth and nutrient cycling (Kiminins and Scoullar
1979, 1981, 1982).
FORCYTE was originally developed for Douglas-fir
forests in British Columbia, but can be adapted for any even-aged
forest species.
Our first objective was to adapt FORCYTE for use with
western hemlock based in part on data we collected for two stands in
Coastal northwest Oregon (Sachs and Sollins (in review)).
We then
20
used FORCYTE to gain insight into the consequences of silvicultural
practices on long-term productivity of western hemlock stands at
those sites.
Nitrogen availability has often been cited as a growth-
limiting factor although recent research has indicated that
phosphorus may be limiting on some Sites (Radwan and Shumway (in
press), Sachs and Sollins (in review)).
Proceeding under the assump-
tion that N was limiting, we attempted to use FORCYTE to investigate
the factors which regulate N availability.
Description of FORCYTE
FORCYTE is as management-oriented simulation model of forest
growth and decomposition which includes nutrient cycling, nutrient
limitation on growth and management intervention (Kimmins and
Scoullar 1979, 1981, 1982).
The model is designed to be adaptable to
any even-aged forest with rotation lengths of less than 150 years.
A
major design criterion of FORCYTE is that it can be driven by inven-
tory type data, collectable in one or two field seasons or available
in the literature and that it not require detailed process inf or-
mation which could take years of research to gather.
Growth of stemwood in FORCYTE is driven by volume/age equations
of the Chapman-Richards type (Pienaar and Turnbull, 1973) for each of
five different site qualities, which can be developed from local
yield tables.
Growth of other tree components is calculated using a
set of age-specific ratios of foliage, branch, stembark and root
biomass to stemwood bioniass.
The model also requires information on
the nutrient content of the various tree components.
21
Nutrient demand each year is calculated as the product of the
predicted growth of each component and the nutrient content of that
component.
lity.
Predicted growth is then modified by nutrient availabi-
If nutrient demand exceeds availability in any year, growth in
that year is reduced to a level at which all the available nutrient
supply is utilized.
Nutrients in excess of this level cause an
increase in growth, although the increase is limited so that trees
cannot respond unrealistically to a sudden increase in nutrient
availability.
Throughout the simulation, site quality can vary
depending on the size of the available nutrient pool in relation to
tree demand.
When available nutrients are not sufficient to satisfy
demand, site quality is reduced, resulting in less predicted growth
and lower nutrient demand the following year.
Conversely, an excess
of available nutrients causes an increase in site quality resulting
in increased predicted growth and nutrient demand the following year.
FORCYTE can model the effects of any single nutrient on growth.
The
current version simulates nitrogen cycling because N is most often
limiting and most research has focused on nitrogen.
For a detailed
description of FORCYTE see Kimmins and Scoullar (1979, 1981, 1982).
Calibration for Western Hemlock
Calibration of FDRCYTE for western hemlock required collection
of field data as well as a thorough search of the literature.
Information on the growth of stemwood was taken from western hemlock
yield tables by Wiley (1979) and Barnes (1962).
This information was
used to construct Chapman-Richards growth equations for each of five
different site classes (I-V) for input to FORCYTE.
Age-specific
22
ratios of foliage, branch, stembark and root biomass to stemwood
biomass were estimated using data from three Oregon coastal hemlock
forests:
a 26-year-old hemlock stand on the central Oregon coast
(Fujimori 1971), a nearby 121-year-old stand (Grier 1976), a
52-year-old stand near Seaside, Oregon (Sachs and Sollins (in
review)).
All three studies provided information on biomass of stem-
wood, stembark, foliage, and branches.
measured coarse root biomass.
Grier and Fujimori also
Additional data on root biomass came
from a review by Santantonio et al. (1977).
Information on the nitrogen content of the various tree components was taken primarily from the site II stand of pure western
hemlock that we studied (Sachs and Sollins (in review)).
requires this information for all site classes.
FORCYTE
Some data for
western hemlock on lower site classes in the Cascades was available
(C.C. Grier, unpublished data).
Data on foliar N concentrations in
western hemlock stands on sites I-V were taken from a study by Radwan
and DeBell (1980).
Values for nitrogen concentrations of other tree
components on poorer sites were estimated using the data from Sachs
and Sollins and Grier (unpublished data).
Forest floor biomass data was taken from the studies of the
three Oregon coastal hemlock forests.
Additional information on the
amounts of coarse woody debris in northwest forests was found in
papers by Sollins (1982) and Graham and Cromack (1982).
Estimates of
total soil nitrogen and soil organic matter content were based on the
studies by Grier (1976), Sachs and Sollins and unpublished data provided by J. R. Boyle.
23
Initial model calibration was accomplished by running FORCYTE
with the nutrient feedback system turned off,
Under this condition
FORCYTE simulates the growth of a hemlock forest as described by the
yield table without regard to nutrient limitations.
to simulate a site II stand and ran it for 90 years.
We set the model
At the end of
this period FORCYTES's predictions of the biomasss of various components of the forest floor were compared to the available data on
the forest floor of hemlock stands.
Decomposition rates for the
various forest floor components were adjusted and the model run
again.
Through trial and error we were able to simulate a forest
floor which was comparable to the data we had.
The model's predictions of the forest floor biomass under a 90
year-old stand are shown in Table 6.
FORCYTE predicts 222 Mg/ha of
decomposing logs which agrees well with the 212 Mg/ha reported by
Grier (1976) for a 121 year-old stand.
based upon a decay rate of 0.03 year
The FORCYTE prediction is
Grier calculated a decay
rate of 0.012 year' from the change in density of decaying logs over
time.
Sollins (1982) reported a decay rate of 0.028 year' for an
old-growth Douglas-fir stand in Washington, calculated by assuming a
steady state and dividing bole mortality by the amount present.
He
stated that rates calculated by this method are often 3-5 times those
calculated directly from change in density alone which fail to
include the large amount of material lost in fragmentation.
FORCYTE
predicts litterfall (including branches, but not boles) to average
approximately 7.0 Mg/ha/yr which is similar to values reported by
Grier (1976) and Fujimori (1971).
24
TABLE 6.
Predicted biomass of forest floor components in a 90 yearold stand.
Component
Biomass (Mg/ha)
Logs
222
Bark
64
Foliage
11
Branches
37
Roots
53
25
We made one major design modification in the FORCYTE program.
parameter defining the rate of fine root turnover was added.
A
In the
original version of FORCYTE no more than 90% of the fine root
biomass could die and be replaced in any given year.
Our modifica-
tion allows the user to set fine root turnover to much higher levels.
Santantonio (1982) reported fine roots turned over 2.8, 2.0, and 1.7
times/year on dry, medium and wet examples of mature Douglas-fir
forest in the Oregon Cascades.
Lacking data for western hemlcok, we
set fine root turnover at 2.0 times/year initially in FORCYTE.
Initial calibration runs of FORCYTE indicated that yield in the
model was extremely sensitive to the parameter defining the rate of
mineralization of soil organic matter.
In FORCYTE there is one soil
organic matter pool, which includes all soil o.m. plus the forest
floor h layer.
The nitrogen released during its mineralization pro-
vides the majority of the N available for uptake by trees each year
and therefore regulates tree growth.
Unfortunately, little is known
about mineralization of soil organic matter and therefore we had only
a vague idea as to what mineralization rate to use in FORCYTE.
We
first set the rate so that the starting level of soil o.m. would be
maintained over a 270 year period under a management scenario of
three 90 year rotations, with no thinnings and a clearcut at rotation
age removing only stem wood and bark.
We assumed this would simulate
minimum management of the site; a situation in which soil o.m. levels
might be expected to remain constant.
Under these conditions FORCYTE
predicted a 4% drop in yield in the second rotation and a 6% drop in
the third.
We then increased the mineralization rate until yield
26
remained relatively constant over three rotations.
This resulted in
about a 4% drop in soil o.m. over the 270 year period.
It was
decided to leave the mineralization rate at this level to give a good
base to which the effects of other, more intensive management scenarios could be compared.
One problem we encountered involved leaching of soil NO3- and
NH4
The ratio of NO3:NH4
is user defined.
At the end of each
year, any NH4+ not taken up by vegetation or immobilized during
decomposition is stored as soil N, and any leftover NO3
out of the soil.
is leached
Therefore leaching is extremely sensitive to the
parameter defining the ratio of NO3:NH4
in the soil, which had to
be set to about 0.04 to keep leaching losses to a reasonable level
(< 50 kg hayr) during the first 10 years of the rotation.
proportion seems low.
This
Crier (1976) measured about 25% of the extrac-
table N in the top 15 cm of the soil at his hemlock site to be in the
NO3
form.
The amounts of available soil N and stored soil N followed the
same general pattern in all rotations (Figure 2).
The initial pulse
in soil N is due mainly to the input from mineralization of soil
humus, which is assumed to occur at a constant rate.
There is some
uptake by herbs and shrubs, but little or none by trees.
Simulated
leaching losses during this stage are about 15-30 kg/ha/yr.
As trees
occupy the site, uptake by trees increases and both available and
stored soil N decrease.
years.
Tree uptake is at maximum from about 10-30
During this time available soil N drops to about 100 kg/ha
27
and all stored soil N is depleted.
Leaching losses during this
period are minimal, averaging less than 1 kg/ha/yr.
N uptake by
trees decreases after age 30, available soil N begins to increase
again, and excess soil N is stored every year after about age 50.
Rotation lengths of less than 50 years never allow the stand to reach
this soil N building stage.
Leaching losses begin to increase again
after about age 70, reaching 3-4 kg/ha/yr by the rotation age of 90
years.
This trend is in agreement with measurements made by Vitousek
and Reiners (1975) who reported higher NO3
levels in stream runoff
from mature spruce-fir forests in New Hampshire than from nearby
30-40 year old stands.
Results and Discussion
We simulated a number of different forest management scenarios
with the revised FORCYTE model in order to gauge their long-term
effects on site productivity.
periods.
All simulations were for 270-year
These included management for sawlogs on both 90- and 45-year
rotations with precommercial and commercial thinnings, and management
for biomass with whole tree utilization on 30- and 45-year rotations
with thinning.
As expected under the assumptions we used, the more
intensive management scenarios caused marked depletion of the soil
o.m. pool over the 270-year period.
Depletion of the soil o.m.
eventually decreased N mineralization which reduced the amount of N
available for tree growth and caused a decline in site productivity
and yield after 150-200 years (Figures 3A and B).
The most intensive
management scenarios generally caused the greatest long-term decline
1000
800
>1
.0
I',
600
3O
x
z
20w0
400
I
4w
IOj
-J
0
U)
I-)
200
I)
0
0
10
20
30
40
50
60
70
80
90
0
10
YEAR OF ROTATION
Figure 2.
Predicted levels of available N, stored N, and leaching of NO3during a 90-year rotation.
29
in productivity as indicated by predicted annual rates of production
per rotation.
Predicted yields for the different regimes are shown in Figure
3B.
Stemwood yield was maximum under 90-year rotation with thinning.
Biomass yields from whole-tree harvesting were greatest under 45-year
rotations.
Apparently 30-year rotations are too short, harvesting
the stand before culmination of mean annual increment.
Intensive
management caused initial increases in yield followed by rapid declines in later rotations due to depletion of soil o.m. and thus N capital.
The soil o.m. pool became depleted because the inputs to soil
o.m. decreased.
The only inputs to soil humus are through decom-
position of forest floor materials and root death.
Shorter rota-
tions, commercial thinnings, and increased utilization remove more
biomass from the site which would eventually have entered the forest
floor through litterfall.
The effects can be seen clearly in Figure
3C which depicts the predicted change in total forest floor biomass
and soil o.m. over the 270-year simulation under the different management regimes.
Notice that the additional removal caused by the
commercial thinning of the stands during 90-year rotations increased
loss of forest floor biomass and soil o.m. by about 24% over three
rotations.
When utilization was increased from stems-only to whole-
tree under 45-year rotations, forest floor biomass and soil o.m. loss
increased considerably; shortening the rotation to 30 years had the
same effect.
30
Available soil N often increased temporarily for periods of
150-200 years under simulated intensive management, after which it
decreased, often to levels well below those of the first rotation.
This effect was due, in the model, to an interaction of two mechanisms.
The initial increase in available N was due to increased
removals of biomass, which resulted in a decreased forest floor
biomass, which in turn initially decreased the amount of N immobilized each year by the forest floor and left more N available for
uptake by plants.
However, the increased biomass removals eventually
decreased the input to the soil o.m. pool.
As the soil o.m. pool
decreased in size, the amount of N mineralized each year dropped and
available N decreased in later rotations.
The initial increase in soil available N levels caused yield to
increase for the first 150 - 200 years under short rotations (Fig.
3B).
Later, yield dropped as soil N decreased in subsequent rota-
tions due to depletion of the soil o.m. pool.
FORCYTE predicted this
initial yield increase because N availability is the only factor
assumed to limit tree growth.
If another factor such as P availabi-
lity were to become limiting during this flush of N mineralization,
then such increases in growth would be diminished or not occur at
all.
Future versions of the FORCYTE will be able to model the
effects of two nutrients on tree growth (J.P. Kimmins, personal
communication).
Fertilization briefly increased growth and therefore litterfall
and root death and decreased the loss of soil o.m., but this effect
only lasted one or two years.
FORCYTE predicts a positive response
31
Figure 3.
Predicted annual net primary production, biomass har-
vested, and biomass of forest floor plus soil organic
matter during a 270-year simulation under six different
management scenarios.
All rotations start with a com-
bination of planted and naturally established seedlings
totaling 2400 per hectare.
clearcuts.
All final harvests are
All scenarios except A include a pre-
commercial thinning at age 15 years.
Scenario F inclu-
des a fertilization at age 17 years.
Rotation
Scenario
No. Commercial
Utilization
Length
Thinnings
Standard
A
90
0
Stems-only
B
90
2
Stems-only
C
45
2
Stems-only
D
45
2
Whole-tree
E
30
0
Whole-tree
F
30
0
Whole-tree
32
36
0
I
I
I
I
I 11 1
1111111
111TTII
I
I
I
I IT
I
I T1
lilT I I III
34
U0
A
32
. 'I,
30
28
I.-w
z*-.
26
z
24
0
200
I
I LII
III I
1[I I 1.1I
1111111
LIII
I IT1I 1
11 TI 111111
I
11111
111111111
111111111
00
(000
U
!
900
600
-
7777
(3227)
177
(WHOLETREE)
(2858)
500
(26101 (S EMS)
400
(2789) (WHOLE-TREE)
300
I2
ttIIItItI
(3070)( WHOLE-TREE)
(24 32) (STEMS)
(STE MS
200
0
II
I
UT] I
111I Ii-
LI-
11 I I1 1 1I II
-
tilliliti
I Ill I
I
I
II
400
&&.o
0
o>
1200
0
000
800
0
ROTATION
23
23
MANAGEMENT
SCENARIO
A
B
23456
C
(23456
D
Figure 3.
(23456789
E
2 3456789
F
33
to fertilization whenever N is limiting.
This may not be reasonable.
The data on growth response of western hemlock to N fertilization are
inconclusive with some stands showing negative response (Olson et al.
1979).
This variable response has been attributed to several factors
including possible P deficiency (Radwan and Shumway, in press) and
fertilizer induced increases in mortality of mycorrhizae or changes
in relative populations of tnycorrhizal types associated with hemlock
roots (Gill and Lavender, 1983b).
However, FORCYTE is not presently
capable of modeling these mechanisms.
In any case, the response to
fertilizer is short-lived, because simulated fertilization at typical
levels only adds one or two years' supply of N.
One would have to
fertilize constantly at a rate comparable to uptake as is done in
agriculture to produce a long-term effect.
The effects of alternate assumptions about the mineralization
rate of soil o.m. must be considered.
The predicted yields (Fig. 3B)
are based on the soil o.rn. mineralization rate we chose which kept
yield constant over three 90 year rotations.
If we had chosen a
lower mineralization rate to maintain a constant soil o.m. pool under
our minimum management plan, then yield would have decreased even
more under the more intensive management scenarios.
All of the mana-
gement runs were made with the mineralization rate held constant,
which may not be a valid assumption.
The mineralization rate could
increase after clearcutting due to more favorable temperature and
moisture conditions (Binkley, in press).
It could also decrease when
there are no trees if fine roots are responsible for most or part of
the mineralization of soil organic matter (Reid et al. 1982).
34
FORCYTE can simulate such changes.
There is a parameter in the model
which changes the mineralization rate by a certain percentage when
there is little or no foliage on the site.
As an experiment, we set
the model to increase the mineralization rate by 50% under these circumstances and found that depletion of the soil o.m. pool under three
90-year rotations increased greatly.
Yield increased in the second
rotation and then dropped back to the first rotation level in the
third as the soil o.m. pool was depleted.
have shown decreased yield.
A fourth rotation would
We then set FORCYTE to decrease the
mineralization rate by 50% when there was no foliage present.
The
soil o.m. pool decreased more slowly, but still decreased, and yield
decreased considerably in the second and third rotations (Table 7).
FORCYTE predicts that soil o.m. levels observed in second growth
stands cannot be maintained, even using rotations as long as 90
years.
Production decreases consequently (Fig. 3A).
tion is not all that surprising.
Such a predic-
The unmanaged coastal hemlock
forests were subject to fire regimes characterized by crown fires at
very long return intervals, quite possibly over 300 years (Kilgore,
1981).
It is quite possible that large soil o.m. reserves only begin
to accumulate after stands reach ages of several hundred years.
In
FORCYTE, soil o.m. never increased, even under 90-year rotations,
unless the mineralization rate of soil o.m. was set so low as to
severely limit tree growth, even during the first rotation.
We
suspect that soil o.m. will begin to accumulate in older stands, but
we couldn't use FORCYTE to test this assumption because the model
does not simulate old-growth forests accurately.
This is because of
35
Table 7.
Effects of alternate assumptions about the rate of N
mineralization after clearcutting upon soil o.m. levels
and yield.
All runs were made using management scenario
D as detailed in Fig. 3.
Change in
mineralization rate
Loss of
Yield (Mg/ha)
soil o.ii.(%)
Rotation
1
2
Constant
543.14
545.32
541.00
4.1
Increased 50% when
no foliage present
588.08
599.35
589.00
9.0
Decreased 50% when
no foliage present
522.81
500.29
492.28
0.2
36
a lack of data on stocking, growth, mortality, and yield of old
growth western hemlock stands across a range of site qualities, which
causes tree mortality to cease in the model after about 110 years.
That shorter disturbance intervals caused by management may mine
the soil o.m. pool is quite consistent with agricultural experience.
Voroney et al. (1981) measured losses of organic C resulting from 70
years of cultivation of the native Saskatchewan prairie.
They
reported an average of 38% of the organic C was lost from the soil
profile with losses from the A horizon averaging 52%.
Van Veen and
Paul (1981) modelled organic C dynamics in grassland soils.
The
model showed sharp decreases in soil C as a result of cultivation of
native grassland with C levels eventually stabilizing after 3-400
years.
Losses are even more rapid under isomesic and warmer con-
ditions (Fox 1980).
Therefore, it is not unreasonable that FORCYTE
should indicate a similar trend in soil organic matter levels for a
hemlock forest ecosystem subjected to intensive management.
Soil o.in. levels in FORCYTE eventually approached a steady
state, but this took about 1500 years.
FORCYTE will only simulate
500-year periods, but the final output from one run can be used as
input for another simulation.
Using this technique we simulated suc-
cessive 45-year rotations with commercial thinnings and whole-tree
removal until soil o.m. levels stabilized as inputs to soil o.m.
balanced annual decomposition.
After about 1500 years, yield
remained relatively constant due to a repeating pattern of N availability in successive rotations resulting from a stable soil o.m. pool
(fig. 4).
37
FORCYTE predicts that first rotation yields cannot be maintained
indefinitely except, perhaps, under extremely high levels of fertilization.
Yields eventually stabilize however, and equilibrium
yield levels can probably be increased with increasing inputs of
energy.
These predictions suggest that non-declining even flow
(NDEF) may not be a biologically reasonable management strategy.
NDEF is based upon the assumption that yield of forest stands can be
maintained at or near present levels in perpetuity.
FORCYTE suggests
this assumption may be unreasonable for hemlock stands in coastal
Oregon, but that a lower yield than the original second growth
rotation may be readily sustainable in perpetuity.
If true, then a
major rethinking of management objectives and plans may be called
for.
For example, the optimum rotation length should perhaps be that
which maximizes the energy benefit:cost ratio rather than short-term
yield.
If declines are inevitable, but lower yield can be maintained in
perpetuity, it could be argued that one should opt for short rotations and intensive utilization which would maximize short-term yield
and cause soil o.m. and yield to equilibrate at lower but sustainable
levels in the shortest time.
uncertainty.
However, our predictions are subject to
It would seem more prudent to protect soil o.m. levels
by using longer rotations and less intensive harvest methods until
further research can refine our ability to predict future yields more
quantitatively.
It is much easier to lose soil o.m. than to build it.
600
a
a,
5OO
t400
(I)
0300
0
200
Cl)
Lii
>
I
100
1500 yr
0
I
5
10
20
IS
25
I
I
30
35
40
ROTATION
Figure 4.
Predicted yields over 40 rotations under mangement scenario D
as described in Figure 3.
39
Conclusions
Our work with FORCYTE has pointed out the model's strong points
and a few weaknesses.
FORCYTE is relatively easy to modify to model
forest types other than the British Columbia Douglas-fir it was ori-
ginally designed for, provided the necessary data is available.
The
model accurately tabulates the N cycle each year and regulates tree
growth based on N availability.
It produces output graphs of all
ecosystem processes, which aid in checking the reality of its predictions.
It should be emphasized that FORCYTE is very complex and
several weeks can be required to decipher the reasons for its
behavior.
The majority of the difficulties we encountered while working
with FORCYTE did not involve problems associated with model struc-
ture, but rather a lack of data about the system being modelled.
Examples include information about N mineralization rates, soil NO3
levels and leaching rates, and fine root turnover.
FORCYTE is
capable of simulating all of these processes, but data on them in
hemlock forests is sketchy or non-existent.
We discovered two major weaknesses in the design of the model.
The soil o.m. and forest floor humus are combined into a single pool,
which is too simple an approach.
There should be several soil orga-
nic pools including a forest floor humus pool and several soil layers
with transfers between them.
There should also be some modeling of
physical protection of soil organic matter (Tisdall and Oades 1982,
Van Veen and Paul 1981).
large woody debris.
The other problem involves decomposition of
Respiration losses need to be separated from
40
fragmentation losses (Lambert et al. 1980, Sollins 1982).
These
problems are being addressed in the next version of FORCYTE to be
released in the summer of 1983 (JP. Kiinmins, personal
communication).
A major value of a model such as FORCYTE lies in its ability to
pinpoint key processes and test hypotheses concerning them thereby
increasing our understanding of the system and prioritizing research.
Work with FORCYTE has indicated a need for further research into the
factors which regulate soil N availability, most notably the mineralization of soil organic matter.
More information on soil NO3
levels
and leaching rates in western hemlock stands is also required.
FORCYTE is the acronym for Forest Cycling Trend Evaluator.
model's major purpose is to predict trends.
The
Its predictions of
future yields are not to be taken as quantitative.
They are only as
accurate as the yield table information and other data used in the
calibration of the model.
FORCYTE's method of regulating tree growth
by changing site quality may not be completely realistic, but no
better method has been proposed.
The model's predictions are based
upon the most current available knowledge.
Further research will
undoubtedly modify these predicitons, but to ignore them now could
prove costly.
Our results indicate that soil organic matter is as precious a
resource in hemlock forests as in agricultural soils and subject to
the same losses during intensive management.
Yield can be maintained
in agricutlure by yearly fertilization, but this is generally not
feasible in forest ecosystems.
It is quite possible that initial
41
second rotation yields will not be sustainable in perpetuity under
current management practices, but that yield could be readily sustainable at a lower level.
42
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The principles of forest yield study.
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BINKLEY, D.
Does forest removal increase rates of decom-
1983.
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44
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1979.
a computer
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S. P. Gessel, R. M. Kenady,
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45
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46
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Distribution of biomass,
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47
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48
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APPENDIX
49
APPENDIX
The following are the input files for FORCETUP and FORCYCLE, the
end-of-run state file used as the starting of the ecosystem for all
management simulations, and copies of the code modifications to
FORCETUP and FORCYCLE.
One major modification was made to both the FORCETUP and
FORCYCLE programs involving the addition of a parameter defining fine
root turnover.
This parameter is named TURN in the FDRCETUP input
file and FINE ROOT TURNOVER in the FORCYCLE input file.
-O.O30I60.
lolbO
3.00.3130
10(12
651(05
211(03
1(111 1,1451.14, ...
01*0 10011
SHOUS *0001*9
Vfl*1 10011 ...
In
.0(44* .605 .0490 .919 SIlfl591I...NSIFIISI
.002 0(15 .330 .059 .073 .0.
9199.3)06.4PbP.30*40.2372.27.I4O0.I260.01l0.30.
51(14551 I...8S111450
00,8*.
(IS
.002 .00.0 .330 .1109 .073 .61.9 .4*011 .0)5 .1*91 .909 OA&I40411...6RbIl*S I
.300 .223 .102 .096 .092 .090 .007 .086 .080 .059 8*.LRIS(0...6013I480
16101
(0
.002
.0240 .330 .909 .573 .669 .0*0 .2450 .092 .929 *IAIO*.40...NIlF0L)
.272 .220 .202 .055 .011(1 032 .023 .022 .009 .013 80(1
olol...p*oFo1p
66*80
10
.0202
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I. ..0l*BkNl
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6680!
00
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1.30 .380 .360 .350 .305 .340 .330 .325 .320 .3(5 801s0140...O.88012
CISSAP
(80508
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.0007 .0007 .5030 .0030
CNI080 16000*6
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.006 .035 .025 .337 .630 .874 .895 .950 .999
2.502 .75 1.1150 .150 .350 .258 .200 .208 .200
.835 .063 .025 .337 .604 .790 .095 .958
5.70 2.50 1.70 1.000 .700 .508 .435 .480 .390
.0000
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500.00
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9(011 8050 SiTE
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TREE 1*061 8001 00080
THEE 010000 8001 141DM
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.8008
60*004 II
GRAPH 83
GOOD SIlL
TREE 5*7*000 INCR(100T
CNH008
GRAPH 82
... LAIELS FOR P0181(0 PLOTS
TOtE 1*801 ROOT 18(00
tREE MEDIUM 0001 18CR
TREE 58*11 (4000 14(00
TOTAL 18(1 P800UCTION
0008(8 OF SILOS 07080
P18(181 STEMS 0710*
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GRAPH 84
TREE 1*001 0001 LICk
TREE IIEUIUM 8001 COCI.
1011 SMALL 8001 CYCI
10001 TREE 0*190 MOOT
TOT6L 0008008 IN MOOT
14(414) 0000 08(0(104140
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18(1 8*801 000(0 CIII
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1811 001.1*61 *4*1 CIII
TREE LIV 80*6(0 0(8111
TREE FOLIAGE LITTER
TREE 501*1 0001 1011(8
TOTAL TREE LI(ItO
TOTAL 1000(8 000000(4
S14PUB 08*6 8101US$
SH808 FOLIAGE 1101US$
SHRUB 0001 8008*5%
44(80 FOLIAGE ('00805$
*4(00 8001 RIOMASS
SHOU0 11*16 INCREMENt
5440U14 FOLIAGE INCREMI
S4'RUO ROOT INCRIMINT
44(04) P01.1*01 10(61880
(8*48044
10(1 88*8(14 11(6(0(80
18(1 FOLIAGI. *8(0(007
18(1 01*0 8*80 LITTER
1000 SITE
P181100
TREE 04*88 IO4CMIi4ENI
I IEA8S ACCUM UPTOKE
TREE oCcUo UPTAKE
CPO4IRNP
68*011 85
TOTAL 0011 INTER CTCL
TOTAL TREE 0400 0(0*80
101*1 TREE NIT UPT*44E
GOOD Silt
001*1 SHRUb 100018
514808 1.11110 NIT008EN
101*1 *418(0 1.101(8
111044 1111(8 8*1805(0
TOTAL SHRU* 181 COCI
10081 4410* 1008 CIII
TOTAL S,,NU6 N 0(4*80
000*1. 44180 NIT 01(8*80
10101. 51,8*14, N OCTANE
101*1 44(01* NIT UPT*441
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GRAPH II
10(1 7014*61 OIOPIOSS
10(1 18061 8001 0200*
70(0 IILORUM 0097 82044
18(0 58011 0001 0200*
NU0060 OF 10(1 ST(MS
44(00 704.2*1,6 0200*05
11(18 0000 BI000SS
SHRUB 7*28 IPICR(M(441
588278 702. 1*61 20(7701
SHRUB 8001 INCOININI
HERO 7011*61 26(0(7221
47(044 ROOT IN(0t4'(NT
(#0 07 DATA
GRAPH 02
LABELS FOR POiNTER PLOTS
#20044(11 07 SlIMS DYING
P60(6221 SILOS DyilaG
9(01 6000 SlIt
GRAPH 04
1011 SlIM 00418 C7C1.
0016 0*047 222110 CIII
10(6 18*0(47 2918 11(1
1016 0010*61 291 17(4.
TOtE 4.8061 11001 CIII.
10(6 LIV RI1ANCH 01*744
TOLL 704.2*66 1211(0
2016 50*4. ROOT 1210(0
100*1 18(6 4.201(0
TOTAL 121110 PIIT0061PI
000*4. TOtE 901210 #001
SHRUR 11126 010005$
SH0218 FOLIOOC 44300*55
5470278 0001 0100*55
1(81 GOOD Sill
£98000
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000747 03
11*05 81CU8 UPhIll
10(0 00*0 0*06 1211(0
10161 6210009 29 9000
TREE ACCUPI UPTAkE
9(81 GOOD Silt
COHONO
1811 0(0209 0001 18CR
1R(( 50*4.1 0007 19(80
TOTAL 10(( 0208*55
VERY GOOD Silt
CNHROF
IOU 5*711094) INCRE8221
1011 44*022 19(018(91
TIlt ORAOICH INCREMENT
10(1 704.2601 282.0(091
70(1 1*01,4. 0001 222(449
10(1 0*00 0IONASS
TREE 00*8(8 0200055
707*4. 1016 22200014122
(647047
7(04708
HIRB GROWTH ... VERY GOOD
GRAPH *5
10(1 0(00218 ROOT dcl
TRIO SNAIL 0001 CIII
101*4. 2016 081(0 CII
TOTAL 10(1 4417 0(01122
101*1. TOIl $11 LIPIAKC
7(05 6004) SIlt
TOTAL 58000 1110CR
5472200 LItTER #11006(22
101*1 44(00 117110
8(040 1.011(8 #211406(9
101*1 SlilUd 1222 dcl
101*1 47(08 181* (Id
101*1 SI'OUH N 41(9080
100*4. 41(448 NIl 4)122*220
lOYAL 52102044 N 071*441
101*1. 47106 NIl 071*81
GRAPH 86
.*.
IN'UT OAT)
TITI.[ OF J-kOj(CT
NAMI
OF (JPLPATOH
ILL U(i) FORETELl-RD
tTUP NUN
lNLOcK VERSION
NUN 0 5
1
SACHS
I
NUTRIENT SIMULATED
NITROGEN
TREE SPECIES SIMULATED ESTtIN HEMLOCK
NORTI,IRP. OREGON COAS
GEOGRAPHICAL REGION
COASTAL WESTERN HEPILOCIA
ECOLOGICAL ZONE
RUN PARAMETERS AND MANAGEMENT SCENARIO
450
NuMBER OF YEARS TO liE SIMULATED
28
SIRE QUALITY AT RIsC TIART OF THE RUN
90
ROTATION LINOTH (VIAlS)
NUMbER OF TREES PLANTED AFTER HARVEST 2400
(0:NATUISAL REGIN)
PERCENTAGE OF DIFFERENT TREE COMPONENTS REMOVED AT FINAL HARVEST:
STEMOOU .95 SIEMBARK .95 bRANCHES .00 FOLIAGE .G0 ROOTS .00
999
999
499
9999
9999
TEAkS OF THINNING
0.00
0.00
0.00
0.00
PROPORTION STEMS Cut 0.00
750
300
0000
450
0 OF STEMS REMAINING
0000
4
2
4
3
3
THINNING CODE;
1.SPACING BY A STEMS CUR;
2rSPACING TO GIVEN STEMS/HA
4:COMM(RCIAL THINNING TO STEMS/HA
3COMRERCIAI. THINNING BY A
PERCENTAGE OF DIFFERENT TREE COMPONENTS REMOVED AT THIMNINGI
STLMOOU .95 STEMLiAISA .95 LIRANCHES .00 FOLIAGE .00 ROOTS .00
YEAR OF FERTILIZATION 999 999 949 999 999 099 999 999 999 999
AMOUNT OF FERTILIZER 100 100 100 000 000 000 000 000 000 000
PARAMETERS DEFINING NUMBER OF AGE CLASSES OF NIOMASS COMPONENTS
SAPW000
8
50
LIVE BARK 20
DEAD DARK
DEAD BRANCHES RETAINED ON ThE TREE
10
POOR SITE 2
FOLIAGE GOOD SITE
3
2.0
FIN( ROOT TURNOVER
PARAMETERS CONTROLLING HERD AND SHRUB LITTERFALL
.250
.300
PROPORTION OF SHRUB ROOTS AND TWIGS WHICH DIE EACH YEAR
PROPORTION OF HERB ROOTS WHICH 011 EACH TEAR
PARAMETERS CONTROLLING SHADING EFFECTS ON SHRUBS AND HERBS
1.250
1.000
0.800
I OF MAXIMUM TREE FOLIAGE TO FULLY SHADE OUT SHRUBS
A OF MAXIMUM TREE FOLIAGE TO FULLY SHADE OUT HERDS
A OF MAXIMUM SHRUB FOLIAGE TO FULLY SHADE OUT HERBS
PARAMETERS CONTROLLING GEOCHEMICAL INPUTS
5.0
0.0
1.0
BIOLOGICAL FIXATION OF NITROGEN (CONSTANT)
1.0
BIOLOGICAL FIXATION OF NITROGEN BY TREES
0.001
SHRUbS
0.020
ANNUAL INPUTS OF NITROGEN IN PRECIPITATION
WEATHERING
SEEPACE
HERBS
PROPORTION OF POPULATION FIXING NITROGEN
ECONOMIC PARAMETERS
0.050
0.01
0.00
0.05
KG/HA
KG/HA
KG/HA
KG/HA
KG/KG FOLIAGE/YR
KG/KG FOLIAGE/YR
KG/KG FOLIAGE/YR
TREES
SHRUBS
HERBS
Cl VALUE AT START OF SIMULATION)
000000.00
3.0
3.0
5.0
250.
250.
ROB.
100.
2500.
ASSETS AT START OF PuN
INTEREST CHARGED ON LOANS
CI)
EARNED ON REVENUE
CX)
DISCOUNT RATE
CX)
COST OF PLANTING
(A/HA)
SPACING
CA/HA)
U/HA)
THINNING
FERTILIZATION CA/HA)
FINAL HARVEST (s/HA)
VALUE OF TREE DIOMASS COMPONENTS EXTRACTED AT IHINNINGS CA PER I)
50 STEMNANK
0
STEMWOOD
0
ROOTS
BRANCHES
FOLIAGE
0
0
VALUE OF TREE BIOMASS COMPONENTS EXTRACTED AT FINAL HARVEST (SIT)
ST(MW000 10
STEMOARK
0
(IRANCHES
0
FOLIAGE
U
ROOTS
0
thtl(.Y P*000ITjkS
LN[R)1 (EIFITS .It.iIOi CALORIES 6CR TON)
J1M.00
41100
[OA1,C, OS
.u00
4000
6()LIAL
4000
4000
ENERGY COSTS u,liLlo:. CALORIES PLO HA)
PLA1TIN6
630
56ACI.t,
210
20000
9460
000000
PI1ROGCN CONcENTRATIONS iN TREE 0100*15
THINNING
FERTIL. IZAT100
HARVESTING
0.0008 0.0000 0.000? 0.0007
0.0032 0.0032 0.0032 0.0032
0.0033 0.0033 0.002 0.0012
0.0)16 0.0116 0.008
0.0312 0.0112 0.005
0.001 0.001 0.0009 0.0008
0.0015 0.0015 0.0010 0.0010
0.0065 0.0060 0.0032 0.0025
0.005
0.020
0.005
0.015
0.008
CR0100 CNI-Lblc CN000 CRP(thK
0.000
0.005
C000IP
C000LP CNOFLP
CR0011 COPRIL CNG[IRL CNPUIIL
CNORTM CNPRTM CNG000 COPORM
COGNIS CNPRTS CNGDRS COPORS
0.006
0.004
NITROGEN CONCENTRATIONS IN HERO 010)1*55
0.005
0.000
0.007
0.004
TREE GROWTH ..*
CKGLHN CNPLBR CNG000 COPEJON
C600LE.
CROFLG
CNOFLG
NITROGEN CONCENTRATIONS IN SHRUB BIOMASS
0.005
0.000
0.005
C065AP CNPSAP CNGHRT COPIIPI
0.007
0.004
CP.GSHT COPOHI
CNGSNF CNPSNF ENGSDF CNPSOF
CJIIGSNR COPSOR CNGSDR CP.PS&H
0.. SHRuB GROWTH 0*
CNGHNF CNPHNF CIIGHOF Ct.P0$DF
.0. KERO GROWTH 0**
CNGHNR CP4PHNR COGHOR COPHUR
PARAMETERS CONTROLLING DECOMPOSITION
A.
NWIBER OF AGE CLASSES OF EACH DECOMPOSING PLANT 010NASS COMPONENT
70
70
20
10
000510 NOKIORK NOA800
2
50
00
10
NORRIS NOIIRTM 000RTL
5
00
3
2
000SHF NOI(SHR 000HRF
B. IINC-OEPENOENT DECAY RAILS FOR GOOD AND POOR SITES, BY COMPONENTS
-
1
-
NOGSTP)
1. 30. 66, 120. 050.
035 .035 .035 .035 .035
5
1. 30. 66. 120. 050.
OGSIMII(I...NOGSTN)
0
0
.
.033 .033 .033 .033 .0133 .
I.4 10. 50. 100.
1.
10.
50. 000.
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2. 10. 20.
.2303.2303.2303.2303.
4
1.
2. 10. 20.
.2250.2250.2250.2250.
4
1.
3. 10. 20.
.
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5. 15. 20.
1.
.0805.0805.060500005.
4
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4
1.
1783.1705.1783.I763.
4
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.17 .07 .1? .17 .
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1. 10. 20. 30.
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PARAMETERS CONTROLLING THE DECOY RATE OF HUMUS
.0079
0.00
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MISCELLANEOUS PARAMETERS
-0.5
-1.0
-0.5
1.0
0.0
1.0
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0.010
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1
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1.0
LAaELS FOR GRAPHICAl. OUTPUT
GRAPH RI
.. VARIABLE PI.OITED
TREE STEM0000 BIOMASS
TREE BARK BIOMASS
TREE BRANCH BIOMASS
TREE FOLIAGE BIOMASS
TREE ROOT BIOMASS
SHRUB TWIG BIOMASS
SHRUB FOLIAGE PIOMISS
SHRUB ROOT BIOKASS
HERB FOLIAGE BIOMASS
HERO ROOT BIOMASS
VARIABLE PLOTI(O
GRAPH 03
TREE STIMW000 N CONTENT
TREE STIMOARK N CONTENT
TREE OBANCH
N CONTENT
TREE ROOT
SHRUB TWIG
N CONTENT
TREE FOLIAGE
N CONTINT
N CONTINT
SHRUB FOLIAGE N CONTENT
SHRUB ROOT
HERB FOLIAGE
HERB ROOT
N CONTENT
N CONTENT
N CONTENT
GRAPH IS
. VARIABLE PLOTTED
TREE STIM INTRNL CYCLING
TREE BANK IPiTPNL CYCLING
TREE BRANCH INTL CYCLING
TREE FOLIAGE INT CYCLING
TREE ROOT INTNNL CYCLING
IRrE TOTAl
INTRN Pvc! IN(
1.25
DGHUN
OPHUM
DKHCXP
CNGHUN
CNPHUM
T000ND
OSPSTM DSPITRK USPITRN DSPFOL DSPRTS OSPRYM
OSPRIL OSPSHT DSPSHF DSPSHR OSPHRF DSPHRR
DEC00
RSPCTR
AVLGYR
PNO3G
RSPCU
ISPCSH
AVLPTR
FNO3P
DSPCO
RSPCHR
*VLT4RB
MAXIMUM S.. 5* VARIABLE PLOTTED
GRAPH 02
TREE STLMW000 INCREMENT
TREE BARK INCREMENT
TREE BRANCH INCREMENT
TREE FOLIAGE INCREMENT
TREE ROOT INCREMENT
SHRUB TWIG INCREMENT
SHRUB ANNUL FOI. PRODUCIN
SHRUB ROOT INCREMENT
HERB ANNUL FOL PRODUCIN
HERO ROOT INCREMENT
GRAPH 14
MAXIMUM ... .. VARIABLE PLOTTED
O(COMPOSING SIEMW000 PlO
DECOMPOSING BARK BIOMA.S
.. NITROGEN FEEDBACK ...
MAXIMUM ..
MAXIMUM ...
DECOMPOSING BRANCH BIOMS
DECOMPOSING FOLIAGE SlUM
DECOMPOSING ROOT HIOMASS
DECOMP SHRUB TWIG 0101105
OCCOMP SHRUB FOLIAGE 010
UtCUMP SHRUB ROOT SIOMAS
DECOMP HERB FOLIAGE BIOM
DECOMP HERB ROOT BIOMASS
GRAPH $6
MAXIMUM ... 5. VARIABLE PLOTTED
HUMUS IJIOMASS
HUMUS NITROGEN CONTENT
HUMUS ANNU ITIOMASS INCITH
HUMUS ANNU NITKUGN INPUT
TOTAl. FUllEST FLOOR BIOMA
FnNrcT FlOOR NTIR rtNINI
MAXIMUM ...
(.11
.. VAkIALLI ILOTTtfl
lvi TvEI STIMWOO( tIrMA
(kAPH VT
MAXIMUM ..*
*vr TKEE ITARK t,IOM4
AVE THEE LRAICH IJIUHASS
lvi TREE FOLIAGE HIOlAS$
lvi TREE LRG ROOT PILMIS
AVE INtl SHE ROOT UIMAS
TREE OESITT (STEMS/hA)
GRAPH A9
VARIABLE P1.017(0
TOTAL AVAILAILE NITRGGLN
SHIUt 1IG LITTERFALL
SHRUII FOLIAGE LI ITIRFALL
ShtUO POOl LITTEKFALL
HINt FOLIAGE LITTEFFALL
HERb ROOT LITTENFALL
MAXIMUM .'.
TREMOD OF PERCENT No.
HRPMOO OF PERCENT P03
TOTAL AVAILALLE P03
TOTAL AVAILAD1.( NH
POFENIIAL SHRUB tAH4
POTENTIAL TREE P114
POTINTIAL HERB P03
POTENTIAL SHRUB P03
POTENTIAL THEE P03
END OF DATA
VARIAbLE PLOTTED
HERb DEHANT, NiTROGEN
SHRUB OLMAPU NITROGEN
TREE DEhANI) NITROGEN
TOTAL POTEN 1111111 NITHO
GRAPH NiB
MAXIMUM
TOTAL PORN SPIKUB NIIRO
TOTAL PUTEN TREE P111(0
HERB UPTAKE NITROGEN
SHNUU UPTAKE NITROGEN
TREE UPTAKE NITROGEN
GRAPH Iii
VARIABLE PLOTTED
OECOMP AND INPUTS NITROG
TOTAL SOIL NITROGEN
STORED SOIL NITROGEN
SOIL LEACHING NITROGEN
OECOMPOSITIOP NITROGEN
TOTAL NITROGEN FIXATION
FIXATION BY TREES
FIXATION BY SHRUBS
FIXATION BY HERDS
I LIVE BRANCH CLASSES
MAXIMUM **
71111 HOOT LITIEPEALL
AVE TRUE MED ROOT DIMAS
TRIE DENSITY CHANGE
X TREE DENSITY CHANGE
GRAPH Pb
VARIAIiLI PLOITEL
TREE SIlMOUU LITTIHEALL
TREE DARK LITIEI4FALL
TREE fMAPCI LIITCRFALL
TRIE FOLIAGE LITTIHEALL
SITE QUALITY
MAXIMUM
VARIABLE PLOTTED
GRAPH 112
TREE STLHW000 LITTER NIT
THEE BARK 1111Ev NITROGN
TREE BRANCH UTTER NITRO
TREE FOLIAGE LITTER PITH
TREE ROOT LITTER NITYROG
SHRUB TwIG LITTER NITROG
SHRUB FOLIAGE LITTER NIT
SHRUB ROOT LITTER NITROG
HERD FOLIAGE LiTTER PITH
HERB ROOT LITTER NITROGN
MAXIMUM **.
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62
Modifications to FORCETUP program (underlined).
00451 C:
00482 C:
0048:3
004E:5
451
00437
SMAL.L ROOTS
SMALL ROOT DEATH LIKE FOLIASE LITTERFALL
RATE=PERRT3*FOLL IT! (TOTFCIL±FOLL IT)
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RTSLTNRTSLIT*r:NE;RTS
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63
Modification to FORCYCLE program (underlined).
01:364 C:
0i.36
C
01 :3,
01:367
01368 C:
01:369
01:370
(>1:371
ShALL ROOTS
SMALL ROOT DEATH LIKE FOLIAGE LITTERFALL
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RTSLTN=RTSLIT*CNDRTS
IF(RTSLTN. OT, TRANSN ) RTSLTN=TRANSN