rad.fit: Rank Abundance Distribution Fit (RAD)

In patauchi/unsaacBEA: Biodivresity and Ecological Analysis at UNSAAC

Description

RAD is used to show structure community of species using different approaches to fited our date like Abundance, Relative Abundance and Log2.

These methods are the most used on ecology.

Usage

rad.fit(Vdata, name = FALSE, plot = F, method = "Log10",
  mixing = FALSE, ...)

Arguments

Vdata	data.frame. Abundance dataset e.g. the first column is species name then communities
name	logial. used just plot is TRUE. Default = FALSE
plot	logical. used to plot RAD. Default = FALSE
method	different methods to RAD plot. e.g. 'Abundance', 'Log2', 'Log10', 'Rel.Abun'.
mixing	Combining all abundance dataset in a plot
...	optional

Details

The function rad.fit uses three different methods for fitting a curve. Abundance is a bit used.

Value

If plot = FALSE. The function creates a list of all communities. Another way, plot RAD.

Examples

sps <- c('sp1','sp2','sp3','sp4','sp5','sp6','sp7','sp8','sp9','sp10','sp11','sp12','sp13',
        'sp14','sp15')
comm1 <- c(5,4,3,5,6,1,4,5,65,87,12,45,67,89,23)
comm2 <- c(1,2,6,0,0,5,7,2,7,9,3,2,1,6,5)
comm3 <- c(335,123,57,3,4,0,0,0,0,12,34,54,11,3,0)
ec_data <- data.frame(sps,comm1, comm2, comm3)

# Plot 
outcomes <- rad.fit(ec_data)
str(outcomes)

# Plot
outcomes <- rad.fit(ec_data, plot = T)

# Plot with names
outcomes <- rad.fit(ec_data, name=T, plot = T)

# Plot mixing
outcomes <- rad.fit(ec_data, plot = T, mixing = T)

patauchi/unsaacBEA documentation built on May 23, 2019, 7:19 a.m.