I am a bit frustrated looking for a competent function doing variation partitioning (e.g. on linear model output)

it should be able to tick the following boxes

• A) calculate all overlaps and "pure" partitions of explained variance of all explanatory variables
• B) deal with multivariate linear models with any number(!) of explanatory variables
• C) input: response variable and explanatory variables and/or lm()- or lmer()-output

optionally:

• D) deal with nested effect models
• E) deal with distance matrices (dbRDA)

There are a few functions ticking some of the boxes,

i.e. the varPart()-function from the modEvA package. The most obvious flaw imo here is that it can only deal with 2 or 3 explanatory variables. Secondly, the input is quite tedious, were you have to enter the numeric values of each R² for each combination of explanatory variables (although it is not to hard to write a workaround)

Then there is the varpart()-function from the vegan package, which only deals with distance matrices as far as I can tell. The variancePartition-package (from bioconductor) has a calcVarPart-function, which only seems to calculate the sum of 'pure' partition and overlaps (I think?)

I am confused that there is neither a tool for such a prevalent task nor an thread about it. Or am I missing something?