This file was created by scanning the printed publication.
Errors identified by the software have been corrected;
however, some errors may remain.
Stream Channel Characteristics under Natural and Grazed
Conditions (continued)
STREAM CHANNEL PROPERTIES
The following is a listing of stream channel properties associated
with this riparian type. Analysis employed follows methods outlined
in Chapter 5 (ECODATA Data Bases and ECOPAC Analysis Software) of the_ Ecosystem Classification Handbook, U.S. Forest Service, Northern Region.
Property
Stream Channel Characteristics under Natural and Grazed
Conditions
Property
Natural
Conditions
Under
Prolonged
Season Long
Grazing
2-4
Unchanged
Valley Bottom Gradient (%)
<3
Unchanged
Rosgen Classification
C6
C6 to C3 or C4
Bankful Width (ft)
5 - 15
5 - >15
Depositional Features
None
Point Bars
1.5 - 2.0
1.3-1.8
Width/Depth Ratio
2.5
>3.0
Pool
Embeddedness %
Dominant Particle Size
70
50
S
30-60
FS
Glide
Embeddedness %
Dominant Particle Size
27
40
S
75 - 80
20-50
FS
Stream Order
Sinuosity
3
Under
Prolonged
Season Long
Grazing
Riffle
Em bedded ness %
Dominant Particle Size
30
S
4 -10
10 - 30
SG
Percent Undercut
80
40-80
Width Undercut (ft.)
1.1
.5
Stream Overhanging Plant
Cover
Trees
Shrubs
Herbs
.5
.5
.5
0
.5
.5 - 10
.5
.5
100
0
.5
70 - 80
1-3
0
0
60
1-3
10
10
.5
.5
50
1-3
30
10
80-90
60-80
Streambank Plant Cover
Trees
Shrubs
Herbs
Streambank Ground Cover
Bare Soil
Gravel
Rock
Litter
Wood
Moss
Basal Vegetation
10 - 20
Natural
Conditions
Percent Stable Banks
30
A METHOD FOR PHOTOSYNTHETIC CALIBRATION OF
PROCESS MODELS FOR CONIFER ECOSYSTEMS
A. Koehn and G. I. McDonald
light compensation point, and the Michaelis-Menton constant for light. The Michaelis-Menton constant we refer
to in this paper is not exactly the same as the MichaelisMenton constant of enzyme kinetics; rather it is the calculated value from nonlinear regression analysis.
This poster synopsis describes procedures to estimate
calibration parameters for the assimilation portion of a
process-based forest ecology model known as Forest-BGC
(Running and Coughlan 1988). Calibration will facilitate
site-specific simulation of key system processes involving
carbon, water, and nitrogen cycles. We describe a procedure using a Clark-type oxygen electrode system to make
laboratory estimates of maximum mesophyll conductance,
MATERIALS AND METHODS
Data collected from two trees in February 1990 were
used to illustrate calibration procedures. Tree 123 was
a control tree, shaded only by the greenhouse structure
(35 percent full sun), and tree 144 was from the shade
treatment which received 20 percent of the light of the
control treatment.
A. Koehn is Ph.D. candidate at the University ofldaho, Moscow, ID.
G. I. McDonald is Research Pathologist, U.S. Department of Agriculture,
Forest Service, Intermountain Research Station, Moscow, ID.
244
was covered by the electrolyte, a 2 cm2 piece of cigarette
paper, and a teflon membrane of the same size.
The system was calibrated by injecting 1 cm3 of air into
the chamber and recording the change in voltage (the capillary matting already in the chamber). The system calibration calculations were:
Photosynthetic oxygen evolution rates were measured
using the leaf-disc electrode system designed by Delieu
and Walker (1981, 1983) and manufactured by Hansatech
Instruments Ltd., England. The system consisted of a
Clark-type electrode that measures oxygen polargraphically. Light was supplied by the Hansatech LS-2 unit
consisting of a 100-watt photo lamp, a heat-reflecting
mirror to reduce the infrared content of the emitted light,
a system oflenses to produce a beam of light with low
variation of intensity across the beam and little divergence from parallel, and three slots that accept 50-mm2
neutral density filters to give precise control of the desired
light intensity. The lamp housing was cooled by a highoutput 12-v d.c. fan, which blows filtered air across the
bulb and heat-reflecting mirror. Photon flux density of
each light level was measured using an Omnidata Model
ES-240 quantum sensor.
Oxygen evolution was measured at 20 ± 1 °C and saturating CO2 (5 percent CO2), The CO2 concentration was
controlled by a sodium carbonatelbicarbonatelborate
buffer solution, which wets a capillary matting in the
bottom of the chamber. Temperature control was provided by a controlled-temperature water circulator. Oxygen
evolution was measured at eight different photon flux
densities (PFD's): 30, 50, 95, 170, 230, 430, 820, and
1,500 J.1moleslm 2/s (full sun for the summer averages
approximately 1,600 J.1moleslm 2/s). Dark respiration
was measured with the lights off at the beginning of the
sampling session. Five voltage readings were recorded
with a Polycorder 700 data recorder in 300-microsecond
intervals every 15 seconds for 3 minutes at each PFD
and for dark respiration (fig. 1). The five voltage readings
from each 15-second interval were averaged to provide one
reading. Twelve readings were obtained over a 3-minute
period at one PFD.
The electrolyte used for the electrode was one part saturated KCL solution, one part 0.4 M borate buffer at pH
9.0, and two parts 1.0 M sodium bicarbonate adjusted to
pH 9.0 with 1 M sodium carbonate solution. The electrode
1. correction for standard temperature and pressure:
X = J.1moles Oil cm 3 of air at 20 °C.
=9.37 (PlPo) (2731T); PlPo =exp (-A/8,500),
(A = altitude in meters)
= 9.37 (0.91) (273/293)
= 7.94 J.1moles 0il cm 3 of air at 20 °C.
2. J.1moles 0lmv = 7.94 J.1moles O/mv during
calibration.
Oxygen evolution rates were calculated using linear
regression on the data points for the 3-minute readings
for each photon flux density (fig. 2). Electrode sensitivity
to temperature changes that occur with increasing light
intensity was compensated for by completing a blank
(tissue absent) run over all PFD's. Difference between
the slopes of the regression lines (fig. 2) was the rate of
02 evolved (or in the case of dark respiration, 02 uptake).
Needle area was measured using a high-resolution monochrome TV camera, a PCVISIONplus Frame-grabber, and
Java video analysis software.
Micromoles of 0/m2/s for the needle sample was calculated as follows:
1. J.1moleslmv (value from calibration) * mv outputlleaf
area
=J.1moleslleaf area
2. corrected slope from regression of J.1moleslleaf area
vs. time
= J.1moles 0fleaf area/second
3. (J.1moles of 0fleaf area (mm 2)/sec) * 1,000,000 mm2/m2
= J.1moles of 02 evolvedlm2/s.
At low photon flux densities (up to 95 J.1moleslm2/s), the
rate of photosynthesis is directly proportional to PFD and
quantum yield (photon yield) is constant and maximal
(Bjorkman and Demmig 1987). Quantum yield is a measure of the efficiency with which light is converted to stable
photosynthetic products. On the assumption that plants
use the same photosynthetic pathways and are equally
efficient in converting photons into chemically bound
energy, one would expect them to have identical quantum
yields as long as the functional integrity remains intact
(Bjorkman and Demmig 1987). We mention quantum
yield because it is a potential quantitative indicator of the
effect of stress on the photosynthetic system. Quantum
yield is equal to the slope of the photosynthetic rate vs.
PFD at low light levels. The light compensation point
and dark respiration are also derived from the same linear regression analysis (figs. 3 and 4).
The method used to extract values of calibration parameters P and K from 02 evolution data was a nonlinear
regressi;n analy~is. Enzfitter (Leatherbarrow 1987) is a
nonlinear regression program designed to analyze enzyme
kinetics. The model for the anaylsis was the MichaelisMenton enzyme kinetics equation and fit of actual to
model was adequate (fig. 5). Photosynthesis values used
in this analysis are net photosynthesis + dark respiration.
17.36
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17.26
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17.24
17.22
0
300
600
900
1200
TIME IN MICROSECONDS
Figure 1-Five voltage readings shown in this graph
illustrate the variation in the Polycorder 700 signal.
245
3000
2500
C
W
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NEEDLES
2000
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O~~~--~--r-~--~--~~---r--'---'--'~
o
15
30
45
60
75
90 105 120 135 150 165
TIME IN SECONDS
Figure 2-02evolution rate for a 3-minute period at one PFD is
calculated from the difference in slope (J.unoles O.jm2/s vs. time)
between needle and blank. Each data point is composed of the
mean of five readings (fig. 1). These calculations are made for
all nine PFD's (including dark respiration).
-
~
(I)
20
18
'1
E 18
UJ
W
DARK RESPIRATION • 1.104 mlcroMOLES 02"'-1 S-1
O QUANTUM YIELD • .071 ..loroMOLEaIPHOTON
2
14
Y • .071X - 1.104
..... 12
0
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8
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ON
COMPENaATION POINT. 15.48 mlcroMOlEa O2 m- 2 a- 1
0
-4
0
10
20
30
40
60
80
70
80
PHOTON FLUX (mlcroMOLES m-2s-1 )
Figure 3-Linear regression on the PFD's up to 95 J.UTl0les/m2/s
calculates the light compensation point, quantum yield, and dark
respiration. This graph shows the results for tree 123.
246
90
100
-cr
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20
18
-2 -1
DARK RESPIRATION • 2.471 microMOLES 02m I
16
O 2 QUANTUM YIELD • .164 mlcroMOLES/PHOTON
14
Y • .164X - 2.471
12
0
:i
10
~
8
..
.
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z
COMPENSATION POINT· 15.07mlcroMOLES 02m-2.-1
8
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C'II
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-4~--~--~--~----~--~--~--~----~--~--~
o
10
20
40
30
50
60
70
90
80
100
quantum yield, and dark respiration. This graph
shows the results for tree 144.
PHOTON FLUX (microMOLES m-2s-1 )
40
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V MAX • SUBSTRATE
K M
+ SUBSTRATE
15
10
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a.
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a::-
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Figure 4-Linear regression on the PFD's up to 95
J.l1Tloles/m 2/s calculates the light compensation point,
'~""*'*"""""''''*''''''''''''''''''''''''''''''*'''''''' ..............................................
*
-6
0
200
400
600
800
1000
1200
1400
1600
=
SUBSTRATE PHOTON FLUX
(microMOLES m-2s-1)
The anaylsis provides estimates of V (= P in the
assimilation model) and K (= Micha~ns-Me~ton constant
for light, the light intensity at 1/2 P mil:.)'
Parameters derived from the laboratory measurement
of 02 evolution-maximum photosynthesis (PMAX), the
Michaelis-Menton constant for light (Km), dark respiration, and the light compensation point (fig. G)-were used
to calibrate the photosynthesis assimilation model used
in Forest-BGC. To calibrate the Forest-BGC assimilation
equation, modifications were made as described elsewhere
(McDonald these proceedings). The equation we used was:
where: ICC
Figure 5-Results of nonlinear regression
used to calculate V max and ~ for the MichaelisMenton enzyme kinetics model. Values used here
represent net photosynthesis + dark respiration.
= internal CO2 concentration =59,259
°
ubars = 5 percent CO2 in 2 measurement cells
MCC = maximum stomatal conductance
0.008 mls (Lohammer and others 1980)
MMC = maximum mesophyll conductance
PMAXlICC (Landsberg 1986)
LMCS = Light-dependent mesophyll conductance
scaler
= (current light-light compensation point)/
(current light + Michaelis-Menton
constant).
Jlmoles CO/m 2/s = (ICC*MCC*MMC*LMCS)/
(MCC + MMC*LMCS); Jlmoles
CO2 = 0.75 02 evolved
247
RESULTS AND DISCUSSION
Since Forest-BGC assimilation is computed from this
equation, the procedure described has the potential to
calibrate the process model for specific species growing
on specific sites with a specific growth history. These
parameters taken singly or in combination may also
provide useful quantitative indicators of system stress.
Results of calibrating the assimilation model with data
from the two different Douglas-fir seedlings are shown
in figure 7. The calibrated model was then inserted into
Forest-BGC.- Output from Forest-BGC after calibration
for some assumed situations is shown elsewhere (fig. 6
in McDonald these proceedings). Photosynthesis values
in this figure are net photosynthetic rates.
Our calibration procedure, using the Hansatech 02
evolution cells, seems to be capable of providing the
necessary parameters for the assimilation portion of
Forest-BGC. Lohammer and others' (1980) equation
appears to represent the actual data points (fig. 7).
-
ACKNOWLEDGMENTS
This research is funded by Stillinger Funds from the
University of Idaho and the Intermountain Research
Station.
40
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MICHAELIS-MENTEN. CONSTANT
£
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0
MAXIMUM RATE OF PHOTOSYNTHESIS
5
SLOPE. QUANTUM YIELD
LIGHT COMPENSATION POINT
0
DARK RESPIRATION
N
1200
400
800
800
1000
1200
1400
1600
PHOTON FLUX (mlcroMOLES m-2s-1)
-
...
'(I)
Figure 6-Photosynthetic parameters calculated from the 02 evolution data using linear
and nonlinear regression techniques.
40 ~------------------------------------~-------------,40
-
OF 144 MODEL
o
144 ACTUAL
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en
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25
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20
20
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--_. OF 123 MODEL
30
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35
123 ACTUAL
30
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6
0
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-6 L---~~--~----~----~----~----~----~----~-5
800
800
200
400
1000
1200
0
1400
1800
PHOTON FLUX (mlcroMOLES m-2s-1)
248
Figure 7-02 evolution for trees 123 and
144 plotted on calibrated assimilation model
output. Values represent net photosynthesis.