I am perplexed by the qiime2 visualization tool for generating rarefaction curves from a microbiome dataset, and I'm hoping someone can explain! As near as I can tell, there are only two options in qiime2: either alpha-rarefaction or beta-rarefaction.

According to Legendre & Legendre's (Numerical Ecology) explanation of Hurlbert's (1971) method and formula for rarefaction curves is calculated on "true (untransformed) counts of individuals". Therefore, using alpha or beta diversity metrics (i.e. transformed counts) seems to violate this core assumption in the calculation of rarefaction curves.

Given that context, I have so many questions:

why does qiime2 lack an option to plot rarefaction curves as richness vs. read counts? (or am I just failing to find it?!) ...basically I'm looking for the qiime2 analog of the rarecurve() function in the vegan package for R...

How exactly does qiime2 calculate rarefaction curves? Does it follow Hurlbert's formula, or something else? Is there a method for correcting for diversity vs. richness when calculating a rarefaction curve?

Secondly, have you found the Moving Pictures Tutorial?
This is a common starting point for learning Qiime2, and relates to many of the questions you ask.
And it has data we can use for examples!

This is the default option. From the Moving Pictures tutorial:

Recently I had this same doubt but can you please suggest this qiime2 alpha_rarefaction plots can be used as similar to vegan package rarefaction plot in R? @iamfisch Thanks