Measurements of Quantum Yields in Forest Canopy in Mixed-Species
Natural Forest
Liang Wei
Department of Forest Resources
STAT 507 Class Project, Instructor: Zaid Abdo . Fall, 2008
Introduction:
•The quantum yield of plant is a measure of photosynthetic efficiency
expressed in mole of CO2 assimilated per mole of photons absorbed. The
quantum yield is influenced by environmental factors, including temperature,
water condition, solar radiation, etc.
• The purposes of this project are to test
1) if the quantum yields differed from site to site due to different species
composition, temperature, water availability and solar radiation.
2) if there are differences in quantum yields between needles form top and
bottom of canopy.
3) if the quantum yields differed by tree species.
Methods:
• In summer 2008, quantum yields of 4 tree species were measured in 5
different sites in Mica Creek Experimental Watershed (MCEW), Idaho.
• Five sites in MCEW which are natural regrowth from clear-cut in 1930s
varied in species composition(Table 1). Two are pure grand fir (Abies grandis
Donn ex D.Don) stands ( > 80% by basal area) and the other three are mixedspecies formed with grand fir, Douglas-fir (Pseudotsuga menziesii var. glauce
(Beissn.) Franco), western red cedar ( thuja plicata Donn ex D. Don) and
western larch (Larix occidentalis Nutt.).
• The methods of measuring quantum yield followed Nippert and Marshall
(2003). One year old sun and shade foliage (2 level) was collected by treeclimbing from 3 trees. per species per site, which were randomly selected. A
LiCor LI-6400 portable photosynthesis system was used to measure net CO2
assimilation (A) of foliage at decreasing levels of photosynthetically active
radiation (PAR).
• Data were fitted using non-linear regression and the slope at A = 0 were
used to estimate the quantum yield. A non-rectangular hyperbolic model
(Hanson et.al, 1987) was used to estimate quantum yield.
• Quantum yields larger than the theoretical largest value ( 0.125 mol C/mol
photon) were removed from analysis.
Figure 2: Q-Q plot, which shows that data are
normal distributed.
Figure 3: Residual plot, which
shows nonconstant variance.
Results:
• There is no difference for the quantum yields amongst sites or between two canopy
levels(Table 2).
• The effect of species and site*species interactions are significant (Table 2).
• Only the quantum yield of western red cedar is significantly larger than those of other
three species.
Source
site
nu(site)
species
site*species
canopy(site*species)
DF
SS
MS
F
P
4
0.000724
0.000181
0.57
0.6864
0
0
.
.
.
3
0.004093
0.001364
4.29
0.0101
5
0.00433
0.000866
2.73
0.0324
13
0.003239
0.000249
0.78
0.6719
Table 2: ANOVA Table .
(a)
(b)
Species
N
Mean
SD
ab gr
29
0.0572
0.0177
la oc
11
0.0606
0.0147
ps me
17
0.0604
0.0169
th pl
10
0.0803
0.0254
site
MC150
N
6
Mean
0.0653
SD
0.0216
MC200
MC300
MC350
MC000
17
19
7
18
0.0570
0.0624
0.0615
0.0656
0.0108
0.0257
0.0126
0.0213
Table 3: Average quantum yields for each (a)species and (b) sites (unit: mol carbon/mol
photon).
Site
MC200
MC150
MC350
MC300
MC000
Partial cut or Uncut
Partial cut
Uncut
Uncut
Uncut
Uncut
Discussion:
Species
3
1
1
3
4
Number of samples
17
6
7
18
18
• The variance of the data is nonconstant (Figure 3). Log-transferring did not change the
variance. Several outliers may account for the nonconstant variance but there is no
solid reason to reject those data points from the data set.
• The degree of freedom of WPE is zero, so SPE is used as the denominator to calculate
the F value of S. Doing this increased the chance of type I error, because SPE has smaller
variance than that of WPE,
Table 1: Stand properties and number of samples. Data for sites and species
are unbalanced.
• Model:
where a is the effect of sites (S) ; h is the whole plot level random error
(WPE); b is the effect of different species (P) ; ab is the effect of interaction
of sites and species(SP); g is the effect of canopy positions (C); and e is splitplot level random error (SPE).
• I used a split-plot design for this experiment. The differences among sites,
species and canopy position are all included in the model. The effect of
canopy levels is nested in the SP interaction.
• The Hasse diagram is shown below:
Figure 4: Box plot of the quantum yields of four species averaged for all sites. Only
the quantum yield of western red cedar (thpl) is significantly higher than other
three species. (abgr: grand fir; psme: Douglas-fir; thpl: western red cedar; thpl:
western larch)
Conclusion:
Figure 1: Hasse diagram of the experiment.
• Quantum yields averaged for 5 sites in MCEW ranged from 0.056 to 0.072 mol CO2
per mol incident photon.
• However, there were no significant differences between canopy positions or among
sites.
• There were no differences among the quantum yields of grand fir, Douglas-fir and
western larch, which are significantly lower than that of western red cedar.
• The results suggest that these conifer species maintain relatively consistent quantum
yield in MCEW.
• This consistency simplifies the use of a process-based model to accurately predict
forest productivity in these areas.