interaction effect in capscale, how to calculate

Hello sig-r-eco community,

I would love to have some insights on my interpretation of capscale() and
how to assess the variance explained by the interaction effect.

Imagine a model like this: Var1 + Var2 + Var1:Var2

RsquareAdj(capscale(otu_table ~ Var1 + Var2 + Var1:Var2, metadata,

distance = "bray"))$adj.r.squared
[1] 0.281792

Then I can obtain the variance of the main factors

RsquareAdj(capscale(otu_table ~ Var1 , metadata, distance =

"bray"))$adj.r.squared
[1] 0.1270805

RsquareAdj(capscale(otu_table ~ Var2, metadata, distance =

"bray"))$adj.r.squared
[1] 0.09308548

Then, is this the right way to calculate the Adj.R2 for the interaction?

RsquareAdj(capscale(otu_table~ Var1:Var2 + Condition(Var1) +

Condition(Var2), metadata, distance = "bray"))$adj.r.squared
[1] 0.05174793

However, if I sum the variances altogether I do not get the variance
explained by the full model
0.09308548 + 0.1270805 + 0.05174793 = 0.2719139

I looked online but I could not find any decent explanation of this.
Thank you for your help,

Nico

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