abuocc: Abundance/Occurrence Graphical Analysis

abuoccR Documentation

Abundance/Occurrence Graphical Analysis

Description

Calculates and plots summary statistics about species occurrences in a data frame

Usage

abuocc(comm,minabu=0,panel='all')

Arguments

comm

a community data.frame with samples as rows and species as columns

minabu

a minimum abundance threshold species must exceed to be included in the calculations (default=0)

panel

controls which of four graphs is drawn, and can be 'all' or integers 1-4

Details

This functions calculates and plots four data summaries about the occurrence of species:

Plots:

1) the number of samples each species occurs in on a log scale, sorted from maximum to minimum

2) the number of species in each sample plot (species richness) from highest to lowest

3) the mean abundance of non-zero values (on a log scale) as a function of the number of plots a species occurs in

4) the total abundance/sample as a function of the plot-level species richness

The third plot allows you to identify individual species with the mouse; the fourth plot allows you to identify individual sample units with the mouse.

Value

Returns an (invisible) list composed of:

spc.plt

number of species/sample

plt.spc

number of samples each species occurs in

mean

mean abundance of each species when present (excluding values smaller than minabu)

Note

It's common in niche theory analyses to calculate the rank abundances of taxa in a sample. This function is similar, but works on multiple samples simultaneously. The spc.plt vector in the returned list can be used anywhere species richness is desired. The plt.spc vector in the returned list can be used to mask out rare species in calculations of sample similarity using dsvdis among other purposes.

Author(s)

David W. Roberts droberts@montana.edu

See Also

fisherfit, prestonfit, radfit

Examples

data(bryceveg) # produces a data.frame called bryceveg
abuocc(bryceveg)

labdsv documentation built on April 10, 2023, 5:08 p.m.

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