upscaleSAR: upscale SAR

In cmerow/meteR: Fitting and Plotting Tools for the Maximum Entropy Theory of Ecology (METE)

Description

Based on information at an anchor scale (A0) calcuate predicted species area relationship at larger scales

Usage

upscaleSAR(x, A0, Aup, EAR = FALSE)

Arguments

x	an object of class meteESF
A0	the anchor scale at which community data are availible.
Aup	the larges area to which to upscale
EAR	logical. TRUE computes the endemics area relatinship; currently not supported

Details

Currently only doublings of area are supported and only the SAR (not EAR) is supported. Upscaling works by iteratively solving for the constraints (S and N at larger scales) that would lead to the observed data at the anchor scale. See references for more details on this approach.

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, empiricalSAR, downscaleSAR

Examples

data(anbo)
anbo.sar <- meteSAR(anbo$spp, anbo$count, anbo$row, anbo$col, Amin=1, A0=16)
anbo.sar
plot(anbo.sar, xlim=c(1, 2^10), ylim=c(3, 50), log='xy')

## get upscaled SAR and add to plot
anbo.esf <- meteESF(spp=anbo$spp, abund=anbo$count) # need ESF for upscaling
anbo.sarUP <- upscaleSAR(anbo.esf, 16, 2^10)
plot(anbo.sarUP, add=TRUE, col='blue')

             

cmerow/meteR documentation built on May 13, 2019, 8:23 p.m.