title: Is there a way to calculate a gradient of dissimilarity across multiple sites using presence/absence data?
body: <p>I’ve been trying to come up with a metric for species (dis)similarity for fish in a series based on presence or absence data that gives a value of 1 or 0 for each lake. From my research, it seems like a Multi-site dissimilarity index using Jaccard index would work best, as single-site presence/absence for each lake doesn't need nestedness or special turnover caveats. Calculating a measure of beta-diversity in R through 'betapart' gives an overall value of 0.86. Now I want to come up with a value of (dis)similarity for each site, that I can then use to plug into an RDA as a continuous variable. Is there a method of calculating site-specific dissimilarity? The closest thing I can come up with is taking beta diversity across all sites =0.86, then calculating a measure of how many species are present in each lake divided by 0.86, kind of using a makeshift Jaccard index formula. For example site 1 would be =(1/7)/0.86; although I don't know if this violates any assumptions. Below is the data that I used.</p>
  
  <pre><code>        Species1 Species2 Species3 Species4 Species5 Species6 Species7
  Site 1      1       0         0       0         0        0       0
  Site 2      1       1         0       0         0        0       1
  Site 3      1       1         1       1         1        1       1
  Site 4      1       0         0       0         0        0       0
  Site 5      1       0         0       0         0        0       1
  Site 6      1       0         0       0         0        0       0
  Site 7      1       0         1       0         0        0       0
  Site 8      1       0         0       0         0        0       0
  Site 9      1       0         0       0         0        0       0
  </code></pre>
  
  <p>Any feedback would be greatly appreciated.</p>