empiricalSAR {meteR}

Empirical SAR or EAR

Description

computes observed SAR or EAR from raw data

Usage

empiricalSAR(spp, abund, row, col, x, y, Amin, A0, 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

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

EAR

logical, should the EAR or SAR be computed

Details

Currently only doublings of area are supported. There are several options for specifying areas. 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. If only row and col are provided these are taken to be the row and column identities of each data entry

Value

an object of class sar inheriting from data.frame with columns A and S giving area and species richness, respectively

Author(s)

Andy Rominger <[e-mail]>, Cory Merow

References

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

See Also

meteESF, meteSAR, downscaleSAR, upscaleSAR

Examples

data(anbo)
anbo.obs.sar <- empiricalSAR(anbo$spp, anbo$count, anbo$row, anbo$col, Amin=1, A0=16)
plot(anbo.obs.sar)
anbo.obs.ear <- empiricalSAR(anbo$spp, anbo$count, anbo$row, anbo$col, Amin=1, A0=16, EAR=TRUE)
plot(anbo.obs.ear)

## empirical SAR from simulated x, y data
anbo$x <- runif(nrow(anbo), 0, 1) + anbo$column
anbo$y <- runif(nrow(anbo), 0, 1) + anbo$row
meteSAR(anbo$spp, anbo$count, x=anbo$x, y=anbo$y, row=4, col=4)