I have a dataset with about 80 different species. As usual, some species are very easy to identify with certainty whereas others are more difficult, which means that I am less certain of my identifications for some species than others. I would like to take this uncertainty into account when doing multivariate analyses so that patterns are less affected by potentially erroneous identifications.

I know that it is possible to downweight species with highly variable counts in replicates in PRIMER. But I was wondering if there is a way to do this manually, i.e., specify downweighting factors for each species, based on my level of confidence around the identification?

An alternative would be to lump species in tricky genera together, but then it seems that too much information is lost.

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