goeveg (version 0.4.2)

syntable: Synoptic tables and calculation of fidelity and differential species character

Description

This function calculates an unordered synoptic table for vegetation unit analysis from a species-sample dataframe and a numeric vector of cluster identity input. Synoptic table options for displaying species in clusters is absolute or percentage frequency, mean/median cover values, differential character (positive, negative, positive-negative, according to Tsiripidis et al. 2009) or fidelity phi (Bruelheide 2000). Created unordered synoptic table can be sorted automatically with synsort function in this package.

Usage

syntable(spec, cluster, abund = "perc", type = "percfreq")

Arguments

spec

Species matrix or dataframe with species in columns and samples in rows. Values must be numeric ("." as decimal character) or integer. Missing values, NA or NaN are not allowed. Species and sample names must be defined as column- and rownames.

cluster

Integer vector with classification cluster identity. Ensure matching order of cluster identity and samples in dataframe for correct allocation of cluster numbers to samples.

abund

Data input type. Define whether input species matrix or dataframe is presence/absence data (abund = "freq") or percentage cover (abund = "perc", default).

type

Type of synoptic table output, type = c("percfreq", "totalfreq", "mean", "median", "diffspec", "phi"). See Details for description of options.

Value

The function returns a list of result components.

abund

abundance of each species (in decreasing order)

$syntable

unordered synoptic table for given species and clusters

$others

names vector of species that are not included in synoptic table due to failing treshold values for min1 and/or min2

$samplesize

total samples in clusters

Additionally for differential taxa calculation:

$onlydiff

synoptic table only with differentiating taxa

$differentials

lists diagnostic taxa for each cluster

Details

For synoptic table calculation, six types are available.

• type = "totalfreq" Creates an absolute frequency table

• type = "mean" Calculates mean of species values per cluster

• type = "median" Calculates median of species values per cluster

• type = "diffspec" Calculates differential character of species according to Tsiripidis et al. 2009. Synoptic table gives specification of positive (p), negative (n), positive-negative (pn) or no differential character (-). Consider that differential character is always restricted to some and not necessarily all of the other units, so regarding percentage frequency is essential for correct interpretation of diagnostic character of species.

• type = "phi" Calculates fidelity measure phi (algorithm basing on Sokal & Rohlf 1995, Bruelheide 2000). Values are ranging between -1 and 1 with high values near 1 indicating high fidelity.

For sorting synoptic tables, use synsort function. See also syntab function from vegdata package for creating ordered synoptic tables from turboveg inputs.

References

Bruelheide, H. (2000): A new measure of fidelity and its application to defining species groups. - Journal of Vegetation Science 11: 167-178.

Chytry, M., Tichy, L., Holt, J., Botta-Dukat, Z. (2002): Determination of diagnostic species with statistical fidelity measures. Journal of Vegetation Science 13: 79-90.

Sokal, R.R. & Rohlf, F.J. (1995): Biometry. 3rd edition Freemann, New York.

Tsiripidis, I., Bergmeier, E., Fotiadis, G. & Dimopoulos, P. (2009): A new algorithm for the determination of differential taxa. - Journal of Vegetation Science 20: 233-240.

See Also

synsort

Examples

# NOT RUN {
## Synoptic table of Scheden vegetation data
library(cluster)
pam1 <- pam(schedenveg, 4)  # PAM clustering with 4 clusters output

## 1) unordered synoptic percentage frequency table
unordered <- syntable(schedenveg, pam1$clustering, abund = "perc",
                      type = "percfreq")
unordered                   # view results

## 2) differential species analysis
differential <- syntable(schedenveg, pam1$clustering, abund = "perc",
                         type = "diffspec")
# show complete table with differential character of species
differential$syntable
# list differential species for second cluster
differential$differentials$group2

## 3) Synoptic table with phi fidelity
phitable <- syntable(schedenveg, pam1$clustering, abund = "perc",
                     type = "phi")
phitable
# }