raupcrick.RdFunction finds the Raup-Crick dissimilarity which is a probability of number of co-occurring species with species occurrence probabilities proportional to species frequencies.
raupcrick(comm, null = "r1", nsimul = 999, chase = FALSE, ...)
| comm | Community data which will be treated as presence/absence data. | 
|---|---|
| null | Null model used as the  | 
| nsimul | Number of null communities for assessing the dissimilarity index. | 
| chase | Use the Chase et al. (2011) method of tie handling (not recommended except for comparing the results against the Chase script). | 
| ... | Other parameters passed to  | 
Raup-Crick index is the probability that compared sampling units have non-identical species composition. This probability can be regarded as a dissimilarity, although it is not metric: identical sampling units can have dissimilarity slightly above \(0\), the dissimilarity can be nearly zero over a range of shared species, and sampling units with no shared species can have dissimilarity slightly below \(1\). Moreover, communities sharing rare species appear as more similar (lower probability of finding rare species together), than communities sharing the same number of common species.
The function will always treat the data as binary (presence/ absence).
The probability is assessed using simulation with
  oecosimu where the test statistic is the observed
  number of shared species between sampling units evaluated against a
  community null model (see Examples).  The default null model is
  "r1" where the probability of selecting species is
  proportional to the species frequencies.
The vegdist function implements a variant of the
  Raup-Crick index with equal sampling probabilities for species using
  exact analytic equations without simulation. This corresponds to
  null model "r0" which also can be used with the
  current function.  All other null model methods of
  oecosimu can be used with the current function, but
  they are new unpublished methods.
The function returns an object inheriting from
  dist which can be interpreted as a dissimilarity
  matrix.
Chase, J.M., Kraft, N.J.B., Smith, K.G., Vellend, M. and Inouye, B.D. (2011). Using null models to disentangle variation in community dissimilarity from variation in \(\alpha\)-diversity. Ecosphere 2:art24 doi: 10.1890/ES10-00117.1
The test statistic is the number of shared species, and this is
  typically tied with a large number of simulation results. The tied
  values are handled differently in the current function and in the
  function published with Chase et al. (2011). In vegan, the
  index is the number of simulated values that are smaller or
  equal than the observed value, but smaller than observed value is
  used by Chase et al. (2011) with option split = FALSE in
  their script; this can be achieved with chase = TRUE in
  vegan.  Chase et al. (2011) script with split = TRUE
  uses half of tied simulation values to calculate a distance measure,
  and that choice cannot be directly reproduced in vegan (it is the
  average of vegan raupcrick results with 
  chase = TRUE and chase = FALSE).
The function is based on oecosimu. Function
  vegdist with method = "raup" implements a related
  index but with equal sampling densities of species, and
  designdist demonstrates its calculation.
## data set with variable species richness data(sipoo) ## default raupcrick dr1 <- raupcrick(sipoo) ## use null model "r0" of oecosimu dr0 <- raupcrick(sipoo, null = "r0") ## vegdist(..., method = "raup") corresponds to 'null = "r0"' d <- vegdist(sipoo, "raup") op <- par(mfrow=c(2,1), mar=c(4,4,1,1)+.1) plot(dr1 ~ d, xlab = "Raup-Crick with Null R1", ylab="vegdist") plot(dr0 ~ d, xlab = "Raup-Crick with Null R0", ylab="vegdist")par(op) ## The calculation is essentially as in the following oecosimu() call, ## except that designdist() is replaced with faster code if (FALSE) oecosimu(sipoo, function(x) designdist(x, "J", "binary"), method = "r1")