I have a dataset composed by presence of different bacterial families in function at different pesticide treatment. I need to find a good representation of my data but I don't know which method (Principal Component analysis or Principal Coordinate analysis or Nonmetric Multidimensional Scaling) is better for species' abundance data.

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    $\begingroup$ In answers to this question it has been shown that PCoA is fundamentally PCA. When we use PCA approach in order to map in low dimension a matrix of distances between observations (rather than observations X variables data) we call it PCoA. Iterative forms of MDS (not necessarily nonmetric, NMDS) are more advanced tools to do the task: they can map the distances with less error (loss) and they have more options, such as selecting the loss function, for example. $\endgroup$ – ttnphns Jul 20 '15 at 12:36
  • $\begingroup$ It has also been shown that NMDS is better for zero-rich species abundance matrices because it has fewer assumptions. It is not clear, though, where the pesticide treatment comes into your question as currently worded. $\endgroup$ – katya Jul 20 '15 at 23:52

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