The data analysis's were either run on R or in analyzed in Excel.
Analyzing sizes from 10mx10m up to 40mx40m determined the optimal size for the new subplots was to be 30mx30m. Subplots that were smaller then the optimal size did not capture the clustering that was occurring and subplots that were larger then the optimal size captured greater portions of the surrounding area which data was not available for.
The values calculated by the Morisita's Index can be viewed in the
Cluster Data Table.
The minimum frequency constraint was lifted when calculating a clustering value for species which had high frequency
in 2 of the three stands, since in all cases the clustering value was calculated in the low frequency stand equaled 1,
indicating the species was located randomly within that stand or 0, indicating the species were located uniformly within
the stand. If the frequency of the species in the stand was 1 or 0 a
clustering value of 1 was also assigned to the species in that stand.
Concern arised when using the Morisita's Index since the number of subplots in each of the stands was not equal.
Since the Old Growth stand is almost 3 times the size of the Young and Mid Growth stands there are significantly more
subplots in the Old Growth stand then the other research stands. This can be a problem since the Morisita's Index
accounts for the number of subplots being sampled and as a result clustering values in the Old Growth stand would be
larger since they are being multiplied by a larger n (number of subplots) value. While the number of subplots is larger
in the Old Growth stand values of clustering are not compared between stands, but rather within stands. Although
the number of subplots differs within a stand the relationship of clustering amongst a species remains constant,
therefore the number of subplots within a stand is irrelevant in this analysis.
The slopes of the dbh distributions for early and late succession species in each stand follow the outlined criteria well, but
the variation in the calculated slopes for mid succession species was greater in the 3 stands. Overlapping in
regeneration times and variation in growth characteristics can account for this discrepancy.
Select the stand title for graphic examples of species
within the stand and how the slopes were calculated.
PLOTA
-Young Growth Stand
PLOTB
-Mid Growth Stand
PLOTC
-Late Growth Stand The slope values calculated by the analysis of the
dbh distributions can be viewed in the
Slope Data Table.
From previous research 5 early, 8 mid and 9 late successional species were classified using seed size, flower size and
other traditional variables.
The resulting comparison mean table is:
The mean slope for the dbh distribution for the early successional in the Mid Growth stand was unable to be calculated
because the frequency of the 4 species in the Mid Growth stand was less then 5 individuals.
Based on the means, the variables that describe both early and late successional species fit the hypothesized conditions
and therefore those variables were included in the multivariate analyses. The variables that describe the mid
successional species fit the hypothesized conditions except for the dbh slope in the Mid Growth stand (PLOTB).
therefore the slope of the dbh distribution in the Mid Growth stand (PLOTB) was dropped from the data set. Comparing the
correlations amongst the variables also resulted in the same conclusion. By dropping this variable 10 additional species
were added to the test data bringing the total number of species for the multivariate analyses to 35 species which
included 5 early, 4 mid and 5 late species whose succession classification was all ready known. Each of the 35
species had a complete data set therefore the multivariate analyses could be completed.
Slecet the
Data Table
link to view the final complete data set that was used in the multivariate analyses.
HOME
Data Preparation Results & Discussion: Determining Slope of the
dbh Distribution of Each Species in Each Stand
Data Results & Discussion: Determining Significant
Variables for Multivariate Analyses
FreqA
ClustA
dbhA
FreqB
ClustB
dbhB
Freqc
ClustC
dbhC
Early
42.25
2.70358
-0.93201325
8.75
0.7261905
N/A
32.75
4.396491
0.18637075
Mid
17
3.802896875
-0.20248825
47.125
1.472673375
-0.0723725
52.75
2.104919475
-0.482347
Late
11.66666667
1.250560222
-0.013661333
14.22222222
0.3076081
-0.392445
64.11111111
1.736597767
-0.080582889
INTRODUCTION
DATA DETAILS
MULTIVARIATE METHODS
MULTIVARIATE RESULTS & DISCUSSION
CONCLUSION
APPENDICES
REFERENCES & ACKNOWLEDGEMENTS
DATA PREPARATION METHODS
DATA PREPARATION RESULTS & DISCUSSION
PRELIMINARY ANALYSIS