abuocc | R Documentation |
Calculates and plots summary statistics about species occurrences in a data frame
abuocc(comm,minabu=0,panel='all')
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 |
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.
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) |
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.
David W. Roberts droberts@montana.edu
fisherfit
,
prestonfit
,
radfit
data(bryceveg) # produces a data.frame called bryceveg
abuocc(bryceveg)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.