R: Estimate the expected species abundance distribution of both...

expected.SAD.Guilds.Conditional {GUILDS} | R Documentation

## Estimate the expected species abundance distribution of both guilds using the guilds model, provided theta, alpha_x, alpha_y, conditional on the size of guild X, Jx and the size of guild Y, Jy.

### Description

This function estimates the expected species abundance distribution of both guilds using the guilds model, provided theta, alpha_x, alpha_y and J. The expected species abundance distribution is approximated by first drawing px from equation 9. Because the abundance distributions of the two guilds are independent, the distributions can now be obtained using equation 6 in Etienne and Alonso 2005. Because drawing from the beta distribution and equation 3 is inherently stochastic, this function returns the average over a specified number of replicates.

### Usage

    expected.SAD.Guilds.Conditional(theta, alpha_x, alpha_y, Jx, Jy, n_replicates = 100)

### Arguments

`theta` | Fundamental biodiversity number theta
`alpha_x` | Dispersal ability of guild X
`alpha_y` | Dispersal ability of guild Y
`Jx` | Total number of individuals in guild X
`Jy` | Total number of individuals in guild Y
`n_replicates` | Number of replicates to use to estimate the abundance distributions.

### Value

`guildX` | Vector containing the mean abundances of species in Guild X, binned into log2 bins
`guildY` | Vector containing the mean abundances of species in Guild Y, binned into log2 bins

### Author(s)

Thijs Janzen & Bart Haegeman

### References

Etienne, R.S., & Alonso, D. (2005). A dispersal-limited sampling theory for species and alleles. Ecology Letters, 8(100), 1147-1156.

### Examples

      SADs <- expected.SAD.Guilds.Conditional(theta = 42,
                                              alpha_x = 0.01,
                                              alpha_y = 0.1,
                                              Jx = 100,
                                              Jy = 200,
                                              n_replicates = 3)

      par(mfrow=c(1,2))
      barplot(SADs$guildX, names.arg=0:(length(SADs$guildX) - 1),
    	  xlab = "Number of individuals (log2)",
    	  ylab = "Number of Species", main = "Guild X" )
      barplot(SADs$guildY, names.arg = 0:(length(SADs$guildY) - 1),
    	  xlab = "Number of individuals (log2)",
    	  ylab = "Number of Species", main = "Guild Y" )

[Package GUILDS version 1.4.4 Index]