Learn R Programming

meteR (version 1.0)

meteSAR: Compute METE species area relationship (SAR)

Description

Uses raw data or state variables to calculate METE SAR and EAR (endemics area relatiohsip) as well as compute the observed SAR or EAR from data, if provided

Usage

meteSAR(spp, abund, row, col, x, y, S0 = NULL, N0 = NULL, Amin, A0,
  upscale = FALSE, EAR = FALSE)

Arguments

spp
vector of species identities
abund
numberic vector abundances associated with each record
row
identity of row in a gridded landscape associated with each record, or desired number of rows to divide the landcape into
col
identity of column in a gridded landscape associated with each recod, or desired number of columns to divide the landcape into
x
the x-coordinate of an individual if recorded
y
the y-coordinate of an individual if recorded
S0
total number of species
N0
total abundance
Amin
the smallest area, either the anchor area for upscaling or the desired area to downscale to
A0
the largest area, either the area to upscale to or the total area from which to downscale
upscale
logical, should upscaling or downscaling be carried out
EAR
logical, should the EAR or SAR be computed

Value

  • an object of class meteRelat with elements [object Object],[object Object]

Details

Currently only doublings of area are supported. Predictions and comparison to data can be made via several options. If spp and abund are not provided then only theoretical predictions are returned without emperical SAR or EAR results. In this case areas can either be specified by providing Amin and A0 from which a vector of doubling areas is computed, or my providing row, col and A0 in which case row and col are taken to be the number of desired rows and columns used to construct a grid across the landscape. If data are provided in the form of spp and abund then either row and col or x and y must be provided for each data entry (i.e. the length of row and col or x and y must equal the length of spp and abund). If x and y are provided then the landscape is gridded either by specifying Amin (the size of the smallest grid cell) or by providing the number or desired rows and columns via the row and col arguments.

References

Harte, J. 2011. Maximum entropy and ecology: a theory of abundance, distribution, and energetics. Oxford University Press.

See Also

sad, meteESF, metePi

Examples

Run this code
data(anbo)

## using row and col from anbo dataset
anbo.sar1 <- meteSAR(anbo$spp, anbo$count, anbo$row, anbo$col, Amin=1, A0=16)
plot(anbo.sar1)

## using simulated x, y data
anbo.sar2 <- meteSAR(anbo$spp, anbo$count, x=anbo$x, y=anbo$y, row=4, col=4)
plot(anbo.sar2)

## using just state variable
thr.sar <- meteSAR(Amin=1, A0=16, S0=50, N0=500)

Run the code above in your browser using DataLab