Preston.dist {asbio} | R Documentation |
A diversity and richness analysis method based on the Preston (1948) log-normal distribution.
Preston.dist(counts, start = 0.2)
counts |
Vector of counts for species in a community dataset. |
start |
Starting value for non-linear least squares estimation of a in n = n_0 \times e^{-aR^2}. |
Preston (1948) proposed that after a log2 transformation species abundances, grouped in bins representing a doubling of abundance (octaves), would be normally distributed. Thus, after this transformation most species in a sample would have intermediate abundance, and there would be relatively few rare or ubiquitous species. The Preston model is based on the Gaussian function: n = n_0 \times e^{-aR^2}, where, n0 is the number of species contained in the modal octave, n is the number of species contained in an octave R octaves from the modal octave, and a is an unknown parameter. The paramter a is estimated using the function nls
, using a starting value, 0.2, reccomended by Preston. The area under Preston curve provides an extrapolated estimate of richness and thus an indication of the adequacy of a sampling effort. Preston called a line placed at the 0th octave the veil line. He argued that species with abundances below the veil line have not been detected due to inadequate sampling.
Graph of the Preston log-normal distribution for a dataset given by "counts", and a summary of the analysis including the fitted Gaussian equation, the estimated number of species, and an estimate for the percentage of sampling that was completed i.e. length(counts)/Est.no.of.spp*100
.
Ken Aho
Preston, F.W. (1948) The commonness and rarity of species. Ecology 29, 254-283.
library(vegan) data(BCI) BCI.count<-apply(BCI,2,sum) Preston.dist(BCI.count)