Becky Parker
September 6, 2004
The primary study question, for which the following analyses are used to answer, is “Does conifer success (quality of conifer growth) depend on the presence (or absence) of CEVE?” The quality of conifer growth can be measured by several different quantities. The total number of conifers per plot, crop tree diameter, height, leader, and whorl sum are all reasonable measures of the quality of conifer growth. The significance level of 0.10 (10%) was used throughout the analyses.
An analysis was performed to determine if the average total number of conifers per plot is significantly related to the height of CEVE and if it significantly differs among the CEVE cover classes. The natural log (LN) of the total number of conifers was used as the response (dependent) variable and CEVE height and cover were the explanatory (independent) variables of interest. The assumption of the residuals being normally distributed was violated when the untransformed total number of conifers data was used. The LN transformation was used to adequately resolve the violation of the normally distributed residuals assumption. CEVE height is a continuous variable measured in feet and CEVE cover is a categorical variable measured in the percent cover classes of 0-9%, 10-24%, 25-50%, 51-80%, and 81-100%. Stand, transect within a stand, slope, aspect, and shrub cover were also considered as potential explanatory variables in the model to help reduce the error variability, which in turn allows for an easier detection of a significant dependence on CEVE height or cover. All explanatory variables in the model (except CEVE height) are categorical. Please note only the explanatory variables that contributed to reducing the error variability were retained in the model, the others were discarded.
General
Linear Model: LN Total Conifers versus Stand, Slope, Aspect, CEVE Height,
CEVE Cover, and Shrub Cover
Factor Type Levels Values
Stand fixed 9 610-014 640-024 640-036 640-124 645-129 650-190 655-002
655-007 660-003
Slope fixed 4 < 10% 10% -
19% 20% - 29% > 30%
Aspect fixed 8 N NE E SE S
SW W NW
CEVE
Cover fixed 5 1 2 3 4 5
Shrub
Cover fixed 5 1 2 3 4 5
Analysis
of Variance for LN Total Conifers, using Adjusted SS for Tests
Source DF
Seq SS Adj SS Adj MS F P
Stand 8 51.637 30.963 3.870
3.48 0.001
Slope 3 7.925 5.375 1.792
1.61 0.190
Aspect 7
10.979 10.185 1.455
1.31 0.252
CEVE
Height 1 0.159 0.569 0.569
0.51 0.476
CEVE
Cover 4 3.284 4.268
1.067 0.96 0.432
Shrub
Cover 4 8.537 8.537 2.134
1.92 0.112
Error 117
130.086 130.086 1.112
Total 144
212.608
Term Coef SE Coef T P
Constant 2.1163 0.5050 4.19
0.000
CEVE
Height 0.1149 0.1606
0.72 0.476
Conclusion regarding CEVE Height:
Based
on the p-value (p=0.476) for CEVE height, we can conclude that the average
total number of conifers per plot is not significantly related to CEVE height.
The estimated slope for the linear relationship between LN total number
of conifers per plot and CEVE height was 0.1149.
Based on this estimate, we do not have enough evidence to conclude
that there is a significant linear relationship between total number of conifers
per plot and CEVE height. See Figure
1 to view the relationship between the total number of conifers per plot and
CEVE height.
Figure 1: This graph shows the relationship between CEVE height and the total conifers per plot. As found in the statistical analysis, this graph illustrates the conclusion that there is no significant linear relationship between CEVE height and total conifers per plot.
Conclusion regarding CEVE Cover:
Based on the p-value (p=0.432) for CEVE cover, we can conclude that the average total number of conifers per plot does not significantly depend on CEVE cover either. In other words, the average total number of conifer per plot does not significantly differ among the cover classes. Please note since the LN transformation was used, regular averages cannot be calculated by back-transforming means on the natural log scale.
Two trees (called ‘crop trees’) were selected from each plot (where available) and were treated as replicates of the most vigorous conifers per plot for the purpose of analyses.
An analysis was performed to determine if the average crop tree diameter is different in the presence versus absence of CEVE. The crop tree diameter was used as the response (dependent) variable and CEVE and Location were the two explanatory (independent) variables of interest where CEVE has two categories (present and absent) and Location has three categories (within, edge, and outside). Stand, transect within a stand, slope, aspect, CEVE height, CEVE cover, shrub cover and relevant interactions were also included in the model as potential explanatory variables to help reduce the error variability, which in turn allows for an easier detection of a significant CEVE or Location effect. All explanatory variables considered in the model are categorical, except CEVE height. Please note only the explanatory variables that contributed to reducing the error variability were retained in the model, the others were discarded.
General
Linear Model: Crop Tree Diameter versus Stand, Transect within Stand,
Aspect, CEVE, Location
Factor Type Levels Values
Stand fixed 9 610-014 640-024 640-036 640-124 645-129 650-190
655-002 655-007
660-003
Transect(Stand) fixed
19 A A B C A A B C A B C A B C D E A A A
Aspect fixed 8 N NE E SE S
SW W NW
CEVE fixed 2 absent present
Location fixed 3 Within Edge Outside
Analysis
of Variance for Crop Tree Diameter, using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F P
Stand 8 18.4386 14.3988 1.7998
7.66 0.000
Transect(Stand) 10
6.6631 8.1745 0.8175 3.48 0.000
Aspect 7 5.4898 4.5522 0.6503
2.77 0.009
CEVE 1 0.9358 1.0919 1.0919
4.65 0.032
Location 2 2.8516 2.8516 1.4258
6.07 0.003
Error 178 41.8069 41.8069 0.2349
Total 206 76.1859
Tukey
Simultaneous Tests
Response
Variable Crop Tree Diameter
All
Pairwise Comparisons among Levels of CEVE
CEVE
= absent subtracted from:
Level Difference SE of
Adjusted
CEVE of Means Difference T-Value P-Value
present 0.2451 0.1137 2.156 0.0324
Tukey
Simultaneous Tests
Response
Variable Crop Tree Diameter
All
Pairwise Comparisons among Levels of Location
Location
= Within subtracted from:
Level Difference SE of
Adjusted
Location of Means Difference T-Value P-Value
Edge 0.2923 0.08415 3.4738 0.0019
Outside 0.1828 0.52700 0.3469 0.9358
Location
= Edge subtracted from:
Level Difference SE of
Adjusted
Location of Means Difference T-Value P-Value
Outside -0.1095 0.5188 -0.2110 0.9758
Conclusion regarding CEVE:
Based on the p-value (p=0.0324) for CEVE and Tukey’s simultaneous test, we can conclude that the average crop tree diameter is significantly greater where CEVE is present compared to where CEVE is absent. The average crop tree diameter where CEVE is present is 1.546 inches, whereas the average crop tree diameter where CEVE is absent is 1.301 inches, a difference of 0.245 inches.
Conclusion regarding Location:
Based on the p-value (p=0.0019) for Location and Tukey’s simultaneous test, we can conclude that the average crop tree diameter is significantly greater for crop trees located on the edge compared to crop trees located within. The average diameter of crop trees located on the edge was 1.557 inches and the average diameter of crop trees located within was 1.265, a difference 0.292 inches. The average crop tree diameter does not significantly differ for crop trees located outside versus edge or for crop trees located outside versus within.
|
Crop Tree Location |
Within |
Edge |
Outside |
|
Crop Tree Diameter Mean (in.) |
1.265 |
1.557 |
1.448 |
An analysis was performed to determine if the average crop tree height is different in the presence versus absence of CEVE. The crop tree height was used as the response (dependent) variable and CEVE and Location were the explanatory (independent) variables of interest where CEVE has two categories (present and absent) and Location has three categories (within, edge, and outside). Stand, transect within a stand, slope, aspect, CEVE height, CEVE cover, shrub cover, and relevant interactions were also included in the model as explanatory variables to help reduce the error variability, which in turn allows for an easier detection of a CEVE significant difference. All explanatory variables considered in the model are categorical, except CEVE height. Please note only the explanatory variables that contributed to reducing the error variability were retained in the model, the others were discarded.
General Linear Model: Crop Tree Height versus Stand, Transect within Stand,
Aspect, CEVE, Location
Factor Type Levels Values
Stand fixed 9 610-014 640-024 640-036 640-124 645-129 650-190
655-002 655-007 660-003
Transect(Stand) fixed
19 A A B C A A B C A B C A B C D E A A A
Aspect fixed 8 N NE E SE S
SW W NW
CEVE fixed 2 absent present
Location fixed 3 Within Edge Outside
Analysis
of Variance for Crop Tree Height, using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F P
Stand 8 73.313 43.423 5.428
3.37 0.001
Transect(Stand) 10
53.450 50.395 5.039
3.13 0.001
Aspect 7 32.775 28.987 4.141
2.57 0.015
CEVE 1 6.868 7.194 7.194
4.46 0.036
Location 2 3.804 3.804 1.902
1.18 0.310
Error 180 290.170 290.170 1.612
Total 208 460.380
Tukey
Simultaneous Tests
Response
Variable Crop Tree Height
All
Pairwise Comparisons among Levels of CEVE
CEVE
= absent subtracted from:
Level Difference SE of
Adjusted
CEVE of Means Difference T-Value P-Value
present 0.6158 0.2915 2.113 0.0360
Conclusion regarding CEVE:
Based on the p-value (p=0.036) for CEVE and Tukey’s simultaneous test, we can conclude that the mean crop tree height is significantly greater where CEVE is present compared to where CEVE is absent. The average crop tree height where CEVE is present is 4.499 feet, whereas the average crop tree height where CEVE is absent is 3.883 inches, a difference of 0.6158 inches.
Conclusion regarding Location:
Based on the p-value (p=0.310) for Location, we can conclude that the mean crop tree height does not significantly differ among the locations (within, edge, outside).
An analysis was performed to determine if the mean crop tree leader is different in the presence versus absence of CEVE. The square root (SQRT) of the crop tree leader was used as the response (dependent) variable and CEVE and Location were the explanatory (independent) variables of interest where CEVE has two categories (present and absent) and Location has three categories (within, edge, and outside). The assumption of the residuals being normally distributed was violated when the untransformed crop tree leader data was used. The SQRT transformation was used to adequately resolve the violation of the normally distributed residuals assumption. Stand, transect within a stand, slope, aspect, CEVE height, CEVE cover, shrub cover and relevant interactions were also included in the model as explanatory variables to help reduce the error variability, which in turn allows for an easier detection of a CEVE significant difference. All explanatory variables in the model are categorical. Please note only the explanatory variables that contributed to reducing the error variability were retained in the model, the others were discarded.
General
Linear Model: SQRT Crop Tree Leader versus Stand, Transect within Stand,
Slope, Aspect, CEVE, Location, Slope*CEVE,
Aspect*CEVE
Factor Type Levels Values
Stand fixed 9 610-014 640-024 640-036 640-124 645-129 650-190
655-002 655-007
660-003
Transect(Stand) fixed
19 A A B C A A B C A B C A B C D E A A A
Slope fixed 4 < 10% 10% -
19% 20% - 29% > 30%
Aspect fixed 8 N NE E SE S
SW W NW
CEVE fixed 2 absent present
Location fixed 3 Within Edge Outside
Analysis
of Variance for SQRT Crop Tree Leader, using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F P
Stand 8 13.9844 5.7649 0.7206
2.16 0.033
Transect(Stand) 10
4.6377 4.3323 0.4332
1.30 0.234
Slope 3 1.0303 0.6088 0.2029
0.61 0.610
Aspect 7 5.5040 1.9581 0.2797
0.84 0.556
CEVE 1 0.5707 1.4280 1.4280
4.29 0.040
Location 2 1.2820 1.7260 0.8630
2.59 0.078
Slope*CEVE 3
2.3287 2.5664 0.8555
2.57 0.056
Aspect*CEVE 7
4.0908 4.0908 0.5844
1.75 0.100
Error 166 55.2967 55.2967 0.3331
Total 207 88.7252
Tukey
Simultaneous Tests
Response
Variable SQRT Crop Tree Leader
All
Pairwise Comparisons among Levels of CEVE
CEVE
= absent subtracted from:
Level Difference SE of
Adjusted
CEVE of Means Difference T-Value P-Value
present 0.4457 0.2153 2.070 0.0400
Tukey
Simultaneous Tests
Response
Variable SQRT Crop Tree Leader
All
Pairwise Comparisons among Levels of Location
Location
= Within subtracted from:
Level Difference SE of
Adjusted
Location of Means Difference T-Value P-Value
Edge 0.2186 0.1012 2.1610 0.0811
Outside -0.2215 0.6666 -0.3322 0.9410
Location
= Edge subtracted from:
Level Difference SE of
Adjusted
Location of Means Difference T-Value P-Value
Outside -0.4401 0.6568 -0.6700 0.7812
Conclusion regarding CEVE:
Based on the p-value (p=0.040) for CEVE and Tukey’s simultaneous test, we can conclude that the mean crop tree leader is significantly greater where CEVE is present compared to where CEVE is absent. Unfortunately, estimates of the average crop tree leader cannot be generated due to the fact that back-transforming from the square root scale will not give a recognizable measure on the original scale.
Conclusion regarding Location:
Based
on the p-value (p=0.078) for Location and Tukey’s simultaneous tests, we can
conclude that the mean crop tree leader is significantly greater for crop trees
located on the edge compared to crop trees located within. The mean crop tree leader does not
significantly differ for crop trees located outside versus edge or for crop
trees located outside versus within.
Again, the average crop tree leader estimates cannot be calculated.

Figure 2: This plot shows the interaction between CEVE and Slope. Based on this data, the combination that maximizes the crop tree leader is CEVE present and <10% slope.
Figure 3: This plot shows the interaction between CEVE and Aspect. Based on this data, the combination that maximizes the crop tree leader is CEVE present and southeast aspect.
An analysis was performed to determine if the mean crop tree whorl sum is different in the presence versus absence of CEVE. The natural log (LN) of the crop tree whorl sum was used as the response (dependent) variable and CEVE and Location were the explanatory (independent) variables of interest where CEVE has two categories (present and absent) and Location has three categories (within, edge, and outside). The assumption of the residuals being normally distributed was violated when the untransformed crop whorl sum data was used. The LN transformation was used to adequately resolve the violation of the normally distributed residuals assumption. Stand, transect within a stand, slope, aspect, CEVE height, CEVE cover, shrub cover and relevant interactions were also included in the model as explanatory variables to help reduce the error variability, which in turn allows for an easier detection of a CEVE significant difference. All explanatory variables in the model are categorical. Please note only the explanatory variables that contributed to reducing the error variability were retained in the model, the others were discarded.
General
Linear Model: LN Crop Tree Whorl Sum versus Stand, Transect within
Stand, Aspect, CEVE, Location
Factor Type Levels Values
Stand fixed 9 610-014 640-024 640-036 640-124 645-129 650-190
655-002 655-007
660-003
Transect(Stand) fixed
18 A A B C A A C A B C A B C D E A A A
Aspect fixed 8 N NE E SE S
SW W NW
CEVE fixed 2 absent present
Location fixed 3 Within Edge Outside
Analysis
of Variance for LN Crop Tree Whorl Sum, using Adjusted SS for Tests
Source DF Seq SS Adj SS Adj MS F P
Stand 8 2.9972 2.8403 0.3550 2.82 0.006
Transect(Stand) 9
3.1452 3.5920 0.3991
3.17 0.001
Aspect 7 2.8418 2.3845 0.3406
2.71 0.011
CEVE 1 0.5471 0.5972 0.5972
4.75 0.031
Location 2 0.0719 0.0719 0.0360
0.29 0.752
Error 173 21.7642 21.7642 0.1258
Total 200 31.3675
Tukey
Simultaneous Tests
Response
Variable LN Crop Tree Whorl Sum
All
Pairwise Comparisons among Levels of CEVE
CEVE
= absent subtracted from:
Level Difference SE of
Adjusted
CEVE of Means Difference T-Value P-Value
present 0.1835 0.08422 2.179 0.0307
Conclusion regarding CEVE:
Based on the p-value (p=0.0307) for CEVE and Tukey’s simultaneous tests, we can conclude that the average crop tree whorl sum is significantly higher where CEVE is present compared to where CEVE is absent. Again, regular averages cannot be calculated since the test was performed on the natural log scale.
Conclusion regarding
Location:
Based on the p-value (p=0.752) for Location, we can conclude that the mean crop tree whorl sum does not significantly differ among the locations (within, edge, and outside).
A chi-square test was conducted to determine if
the likelihood of a crop tree being considered dominant depended on whether or
not CEVE was present. The sub-dominant
(SD) category was ignored because there were not enough occurrences to include
it in the analysis.
Chi-Square
Test: Crop Tree Dominance vs. CEVE
Expected
counts are printed below observed counts
absent present Total
D
22 113 135
21.14 113.86
CD
9 54 63
9.86 53.14
Total 31
167 198
Chi-Sq
= 0.035 + 0.007 +
0.076 + 0.014 = 0.131
DF
= 1, P-Value = 0.717
Conclusion:
Based on the data, the proportion of conifers that were considered dominant is similar in the presence and absence of CEVE.
A chi-square test was conducted to determine if
the likelihood of a crop tree being considered dominant depended on its
location relative to the CEVE. The
sub-dominant (SD) category was ignored because there were not enough
occurrences to include it in the analysis.
Chi-Square
Test: Chi-Square Test: Crop Tree Dominance vs. Location
Expected
counts are printed below observed counts
Within Edge Outside Total
D
56 78 77
211
71.58 75.30 64.12
CD
40 23 9 72
24.42 25.70 21.88
Total 96
101 86 283
Chi-Sq
= 3.390 + 0.097 + 2.587 +
9.933 + 0.283 + 7.582 = 23.871
DF
= 2, P-Value = 0.000
Conclusion:
Based on the data, the proportion of conifers that were considered dominant depends on the crop tree’s location relative to the CEVE, where the conifers are more likely to be dominant on the outside and less likely to be dominant within.