Mimics traditional manual ordering of vegetation data table by (i) clustering rows
and columns (hclust), (ii) rearranging the resulting groups according to the first AOC axis (aocc),
(iii) rearranging rows and columns inside groups based on CA (cca), (iv) Putting high
resolving species on top of the table (aoc). Also offers variants for ordering.
This is a vegetation data frame, releves are rows, species columns
method
The method used for ordering: "raw", "sort", "ca", "clust", "aoc" or "mulva"
y.r
Transformation of species scores when clustering releves (rows): x'= x exp(y.r)
y.s
Transformation of species scores when clustering species (columns): x'= x exp(y.s)
k.r
The number of releve groups
k.s
The number of species groups
ndiffs
The number of (high resolving) species used for top portion of the table
...
Use method="normal" for conventional display, "compressed" for very large tables
rorder
The order of releves (rows) for printing
sorder
The order of species (columns) for printing
grr
The group labels of releves (rows) for printing
grs
The group labels of species (columns) for printing
x
An object of class "Mtabs"
object
An object of class "Mtabs"
range
A subset of species to be displayed in summary table, e.g., c(1,10) for the first 10.
vec
A vector of group labels, analyzed similar to function table(), but without sorting
y
Transformation of species scores: x'= x exp(y)
Details
Function plottab() and plottabl() are for internal use only
Value
An object of class "Mtabs" with at least the following items:
method
The method used for ordering
transf.r
Argument y.r
transf.s
Argument y.s
order.rel
The resulting order of rows
order.sp
The resulting order of columns
order.relgr
The resulting order of releve groups
order.spgr
The resulting order of species groups
MSCC
Mean square contingency coefficient
CAeig.rel
Eigenvalues of correspondence analysis
AOCeig.rel
Eigenvalues of analysis of concentration
veg
The input vegetation data frame
centroids
The matrix of groups centroids (see summary.Mtabs
Note
This extremely complex procedure accords with conventions used in vegetation ecology.
It assumes that the vegetation data frame has many zero entries (plots in which species
are not found). The summary method displays a frequency table (relative frequency of
all species within the releve groups, centroid).
Author(s)
Otto Wildi
References
Wildi, O. 1989. A new numerical solution to traditional phytosociological tabular
classification. Vegetatio 81: 95–106.
Wildi, O. 2013. Data Analysis in Vegetation Ecology. 2nd ed. Wiley-Blackwell,
Chichester.
Examples
y.r<- 0.5 ; y.s<- 0.2 # defining transformations used
k.r <- 3 ; k.s <- 4 # row- and column numbers
ndiffs <- 18 # no. of columns used to show pattern
o.Mt<-Mtabs(nveg,"mulva" ,y.r,y.s,k.r,k.s,ndiffs)
plot(o.Mt,method="normal")
# to see the original order simply replace "mulva" by "raw"