aresCalc {ARES} | R Documentation |
Generates an allelic richness accumulation curve. This curve shows the expected
number of unique alleles in a population when taking a sample of individuals,
ranging from one till maxsize
individuals.
It takes a binary data matrix as input, showing the presence of alleles per
individual, and gives an accumulation curve (mean with 95% confidence bounds)
back. The total number of individuals present in the input data can be smaller
then maxsize
.
aresCalc(rawdata, bootsize = NULL, maxsize = NULL)
rawdata |
a binary data matrix with columns representing different individuals and rows representing different alleles |
bootsize |
the number of bootstrap runs to be made, for calculating confidence bounds (typically between 100 and 1000) |
maxsize |
the number of individuals to where the accumulation curve has to be calculated |
The function returns a table of 3 columns and maxsize
rows. The first column
holds the mean (named esti
), the second the lower 97.5 % conf. bound
(named lwr
) and the third the upper 97.5% conf. bound (named upr
)
The output can be visualised by the function aresPlot
.
Emiel van Loon, based on code by Chang Xuan Mao
Colwell RK, Mao CX, Chang J (2004) Interpolating, extrapolating and comparing incidence-based species accumulation curves. Ecology, 85, 2717-2727.
Mao CX, Colwell RK, Chang J (2006) Estimating the species accumulation curve using mixtures. Biometrics, 61, 433-441.
van Loon EE, Cleary DFR, Fauvelot C (2006) ARES: software to compare allelic richness between uneven samples. Molecular Ecology Notes, (in review)
# allelic richness of the butterfly Drupadia theda (Felder), # at a study site B1 in the year 1998 compared to that in 2000 data(butterfly_borneo) b198 <- aresCalc(bb198,bootsize=4,maxsize=60) aresPlot(b198, T="1998, B1") b100 <- aresCalc(bb100,bootsize=4,maxsize=60) aresPlot(b100, T="2000, B1") # display the results of aresCalc as a table in the R console b100 # write the results of aresCalc to a csv-file write.csv(b100, file = "b100.csv") # note!!! these examples use a very small bootstrap size (for speed of display). # A more realistic size is bootsize=200.