mefa (version 1.0-4)

mefa: Makes Object of Class 'mefa'

Description

Makes and object of class 'mefa' from az 'xcont' and sample and species attribute 'xorder' objects. Incomplete 'mea' object can becreated, when one out of samples or species attributes is missing.

Usage

mefa(xc, xorder.samples, xorder.species)

## S3 method for class 'mefa':
print(x, \dots)

## S3 method for class 'mefa':
plot(x, sample.var = NULL, species.var = NULL, \dots)

Arguments

xc

object of class 'xcount'.

xorder.samples

object of class 'xorder' for sample attributes, or NULL.

xorder.species

object of class 'xorder' for species attributes, or NULL.

x

an object of class 'mefa'.

sample.var

column index (numeric or character) of the sample attribute table to plot as independent variable.

species.var

column index (numeric or character) of the species attribute table to plot as independent variable.

...

other arguments.

Value

• A result is an object of class 'mefa'.
• data
  count data from the 'xcount' object.
• sample.attr
  data frame containing data of 'xorder' object containing sample attributes.
• species.attr
  data frame containing data of 'xorder' object containing species attributes.
• call
  returns the call.
• segment
  segment of the 'xcount' object.
• digits
  digits of the 'xcount' object.
• nsamples
  number of rows (samples) in data.
• nspecies
  number of columns (species) in data.
• totalcount
  sum of count or measurement in data.
• presences
  sum of presences in data.
• ninds
  a vector, containing number of individuals (or sum of measurement values) within samples.
• srichn
  a vector, containing number of species (based on occurences) within samples.
• specabund
  a vector, containing number of individuals (or sum of measurement values) within species.
• specoccur
  a vector, containing number of occurences within species.
• attributes
  character, indicating the presence of "both" or only one ("samples.only" or "species.only") attribute tables.
• attrib.matrix
  a matrix with 2 rows and 3 columns. Columns contain check.setrel, number of variables and na from 'xcount' objects for samples (first row) and species (second row). If one 'xorder' object is missing, respective row contains NAs.

Details

The plot method works as for 'xcount' objects if only a 'mefa' object is specified. If sample and species attributes (one or both) are also specified, scatterplots or box-and-whiskers diagrams are drawn, based on the type of the independent variable. Species richness, number of individuals, abundance and number of species occurrences are plotted as response variable. If the crosstable is binary, only richness and occurences are used.

See Also

check.attrib, marmat, sscount, xcount, xorder

Examples

### Example 1: simple atrificial data

ss <- data.frame(
cbind(
c("sample1","sample1","sample2","sample2","sample3","sample4"),
c("species1","species1","species1","species2","species3","zero.count"),
c("male","female","male","female","male","male")
),
c(1, 2, 10, 3, 4, 1)
)
colnames(ss) <- c("sample.id", "species.id", "gender", "catch")

spectab <- as.data.frame(rbind(
	c("species3", "family1", "1"),
	c("species2", "family2", "5"),
	c("species1", "family1", "2"),
	c("species5", "family2", "1"),
	c("species4", "family1", "10")
))
colnames(spectab) <- c("species", "taxonomy", "size")

sampletab <- as.data.frame(rbind(
	c("sample3", "bad"),
	c("sample1", "good"),
	c("sample2", "good"),
	c("sample4", "bad")))
colnames(sampletab) <- c("sample", "quality")

xct <- xcount(sscount(ss, zc="zero.count"))
xo1 <- xorder(xct, "samples", sampletab, 1)
xo2 <- xorder(xct, "species", spectab, 1)

mf1 <- mefa (xct, xo1, xo2)
mf1

mf2 <- mefa(xcount(sscount(ss, zc="zero.count"), 2), xo1, xo2)
mf2

### Example 2: field data of Villany Hills

data(landsnail, vsample, vtable)

vt <- as.xcount(vtable, FALSE)
spec <- xorder(vt, which="species", landsnail, 2)
sampl <- xorder(vt, which="samples", vsample, 1)

vmf <- mefa(vt, sampl, spec)
vmf

plot(vmf)
plot(vmf,type="rank")
plot(vmf, 3)
plot(vmf, NULL, 5)
plot(vmf, "site.descr", "shell.dimension")

### Example 3: field data of the dolina

data(dol.count, dol.sample, landsnail)

dmf <- mefa(
dxc <- xcount(sscount(fill.count(dol.count), zc="zero.count")),
xorder(dxc, which="samples", dol.sample, 1),
xorder(dxc, which="species", landsnail, 2)
)

dmf

plot(dmf, "microhabitat", "shell.dimension")