Description Usage Arguments Details Value Author(s) References See Also Examples
Compute METE SAR by downscaling from some larger area A0
to a smaller areas.
1 | downscaleSAR(x, A, A0, EAR = FALSE)
|
x |
an object of class meteESF |
A |
numerical vector of areas (<= |
A0 |
total study area |
EAR |
logical. TRUE computes the endemics area relatinship |
Downscaling is done non-iteratively (i.e. the SAD and SSAD are calculated based on state variables at the anchor scale A0) thus unlike the upscaling SAR function, downscaling can be computed for any arbitrary scale ≤q A_0.
an object of class sar
inheriting from data.frame
with
columns A
and S
giving area and species richness, respectively
Andy Rominger <ajrominger@gmail.com>, Cory Merow
Harte, J. 2011. Maximum entropy and ecology: a theory of abundance, distribution, and energetics. Oxford University Press.
meteESF, meteSAR, empiricalSAR, upscaleSAR
1 2 3 4 5 6 7 8 9 10 | data(anbo)
anbo.esf <- meteESF(spp=anbo$spp, abund=anbo$count)
anbo.thr.downscale <- downscaleSAR(anbo.esf, 2^(seq(-3, 4, length=7)), 16)
plot(anbo.thr.downscale)
## theoretical SARs from state variables only
thr.downscale <- downscaleSAR(meteESF(S0=40, N0=400), 2^seq(-1,4,by=1), 16)
thr.downscaleEAR <- downscaleSAR(meteESF(S0=40, N0=400), 2^seq(-1, 4, by=1), 16, EAR=TRUE)
plot(thr.downscale, ylim=c(0, 40), col='red')
plot(thr.downscaleEAR, add=TRUE, col='blue')
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