I want to study the impact of aquaculture on a hard rocky seafloor community which is naturally low in diversity.

4 replicate images (0.25 m2 each) were taken at fixed distances (0, 20, 40, 80, 120, 160 and 200 m) along 8 transects away from the aquaculture site.

The database has 15 different taxa, some of which are continuous (regular abundance data, from 0 to 16) and others are categorical:

0 = 0%
1 = 1-25% cover
2 = 25-50% cover
3 = 50-75% cover
4 = 75-100% cover

There’s also lots of zero in the database.

I want to know if the benthic community changes based on the distance away from the aquaculture site.

My 1st approach was to transform my species database to presence/absence. Results are interesting but presence/absence is a drastic transformation and I would like to know if other options are available.

My questions are:

1. When performing a single multivariate ANOVA (aka PERMANOVA) and dealing with a species database containing categorical and continuous data, is there other transformation possible than presence/absence?

2. Would a standardization be appropriate?


1 Answer 1


For the record, after discussions with other colleagues, I believe since my species in categories (from 0 = absence to 4 = 75-100% cover) are somewhat already transformed, the best way will be square root transform my species abundances (already fairly low). This way all species (either in category or abundance) fall between 0 and 4 and have the same potential range and weight across the matrix.


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