Ecology and regeneration of forest communities on the alluvial fan ...

-Materials <strong>and</strong> Methodsagglomerative
cluster analysis was applied to the transformed abundance data to
classify the vegetation. For distance measurement the square root <strong>of</strong> the Bray-Curtis
coefficient, that has metric properties, was used.
Table 3.1 Transformed abundance data <strong>of</strong> the North Carolina Index (NCI)
NCI 0 1 2 3 4 5 6 7 8 9 10
transformed values 0 0.1 0.5 1.5 3.5 7.5 17.5 37.5 62.5 85 97.5
As linking procedure the ward’s minimum variance method (Ward 1963) was chosen to
minimize the squared error for each clustering step. Species occurring in less than three
plots were not included in this procedure. The socio-ecological species groups were
arranged manually <strong>and</strong> the plant <strong>communities</strong> were arranged roughly along a moisture
gradient. The vegetation <strong>communities</strong> were named after two highly frequent species
present within the community.
To reveal the correlations with the site parameters, a Detrended Correspondence
Analysis (DCA) was run with the program PCOrd (version 5.10.) without down
weighting rare species <strong>and</strong> rescaling axes with 26 segments. All species, occurring less
than three times in the whole dataset as well as species, that could only be determined to
genus level were dropped. In order to test if the <strong>forest</strong> types could be distinguished only
by means <strong>of</strong> their structure, this was repeatedly done using the importance values <strong>of</strong> the
tree species <strong>and</strong> the same site parameters.
To reveal successional trends within the <strong>communities</strong> a non-metric multidimensional
scaling (NMDS) was made. For this purpose from each <strong>of</strong> the 59 sampling plots with
complete information about canopy structure (PCQ) <strong>and</strong> rejuvenation we created two
corresponding “sub-plots”. To avoid distortions in the ordination scatter we restricted
the analysis to 19 tree species that potentially can grow into the tree layers (Table 3.2).
One sub-plot contained the importance values <strong>of</strong> the PCQ data <strong>and</strong> the second sub-plot
contained the importance values <strong>of</strong> the respective rejuvenation. To generate importance
values for the rejuvenation, the numbers <strong>of</strong> individuals within each <strong>of</strong> the six different
rejuvenation classes were multiplied with a factor (seedling x 0.05 /