Beta diversity demonstration

install.packages(devtools)
library(devtools)
install_github('mobiodiv/mobr', ref = 'dev')

Load mobr and example data

library(mobr)
data(inv_comm)

Calculate Whittaker’s beta

calc_comm_div(inv_comm[1:2, ], 'S')
##   scale  index sample_size effort gamma_coverage     value
## 1 alpha      S           1     NA             NA 12.000000
## 2 alpha      S           1     NA             NA  7.000000
## 3 gamma      S           2     NA             NA 14.000000
## 4  beta beta_S           2     NA             NA  1.473684

Calculate beta for ENS of PIE (beta S_PIE)

calc_comm_div(inv_comm[1:2, ], 'S_PIE')
##   scale      index sample_size effort gamma_coverage    value
## 1 alpha      S_PIE           1     NA             NA 6.680108
## 2 alpha      S_PIE           1     NA             NA 3.512354
## 3 gamma      S_PIE           2     NA             NA 5.996554
## 4  beta beta_S_PIE           2     NA             NA 1.176665

Calculate beta for S given a specific coverage (beta C)

calc_comm_div(inv_comm[1:2, ], 'S_C')
##   scale    index sample_size effort gamma_coverage     value
## 1 alpha      S_C           1    142      0.9787356 15.128899
## 2 alpha      S_C           1    142      0.9787356  8.786157
## 3 gamma      S_C           2    142      0.9787356 13.937069
## 4  beta beta_S_C           2    142      0.9787356  1.165548

Calculate beta for rarefied richness (S_n) for 20 individuals

calc_comm_div(inv_comm[1:2, ], 'S_n', effort = 20)
##   scale    index sample_size effort gamma_coverage    value
## 1 alpha      S_n           1     20             NA 7.859347
## 2 alpha      S_n           1     20             NA 4.708249
## 3 gamma      S_n           2     20             NA 7.431042
## 4  beta beta_S_n           2     20             NA 1.182572

More than two sites can be used at a time

calc_comm_div(inv_comm[1:10, ], 'S')
##    scale  index sample_size effort gamma_coverage     value
## 1  alpha      S           1     NA             NA 12.000000
## 2  alpha      S           1     NA             NA  7.000000
## 3  alpha      S           1     NA             NA 11.000000
## 4  alpha      S           1     NA             NA 11.000000
## 5  alpha      S           1     NA             NA  5.000000
## 6  alpha      S           1     NA             NA  5.000000
## 7  alpha      S           1     NA             NA  4.000000
## 8  alpha      S           1     NA             NA 11.000000
## 9  alpha      S           1     NA             NA  7.000000
## 10 alpha      S           1     NA             NA  9.000000
## 11 gamma      S          10     NA             NA 38.000000
## 12  beta beta_S          10     NA             NA  4.634146

It is also possible to just calculate beta diversity but it is generally not recommended to examine beta without reference to alpha and gamma diversity.

calc_beta_div(inv_comm[1:10, ] , 'S')
##   scale  index sample_size effort gamma_coverage    value
## 1  beta beta_S          10     NA             NA 4.634146