#Add in bottleneck data
mratios <- c(0.6,  #DG
             0.75, #EH
             0.82, #FV
             0.82, #GC
             0.78, #GOM
 	     0.78, #GRAC
             0.78, #LZ
             0.62, #M
             0.81, #PAL
             0.57, #PS
             0.47, #SG
             0.75, #TEID
             0.82 #TF
)

#This loop calculates bottleneck severity for each pair of populations
output <- mat.or.vec(1,1)

for(i in 1:length(mratios))
{
  for(j in 1:(length(mratios)-1))
  {
    if(j>=i)
    {
      output <- c(output,mratios[i] * mratios[j+1])
    }
  }
}
output <- output[2:length(output)]
length(output)

#assign the bottleneck index to a variable
myM <- -log(output)

#This variable will have the pairwise bottleneck distance between the pairs of populations and can be used for the mantel tests
