Best practices in metabarcoding of fungi: From experimental design to results
I prefer this to Kauserud 2023, though I suppose Tedersoo 2022 has the benefit of a larger team.
Tedersoo 2022 is a practical guide to fungi amplicon studies, a.k.a. metabarcoding, that includes helpful comparisons between older popular methods and newer approaches. The bioinformatics section explains how the variable length of fungal ITS breaks global alignment algorithms that work fine for 16S amplicons. Even calculations of percent identity are tricky when regions can vary in length!
If a modern denoiser makes ASVs but cannot support variable length reads, it may not be a good fit for ITS1 data, as this article correctly points out.
While quite a bit more balanced, this article still criticizes ASVs for being unlike species, while no definition of the species concept is provided. 
Remember, sequence variants are just real reads from a sample.
These are probably genes, but no other meaning is included in the definition.
Here's what I agree with:
The ESV approaches are certainly useful for separating as many species/haplotypes as possible based on conserved genes, but their utility for ITS and protein-coding genes is unclear (Antich et al., 2021). They may outperform traditional OTU clustering approaches in distinguishing very closely related species of Ascomycota with haploid genomes.
...
By reanalysing a data set from Furneaux et al. (2021), we show that the DADA2 ITS pipeline and UNOISE ESV approaches reduce phylogenetic richness by disproportionately eliminating rare members of the unicellular fungal groups, Glomeromycota and nonfungal eukaryotes (Figure Box 2).
Fungal-specific settings may help with this, and their recommended standards can help validate these settings are working as intended.
Here, they equate ASVs with OTUs with Taxa, a common mistake.
However, an ESV approach severely biased species richness estimates of metazoans based on the cytochrome oxidase 1 (CO1) gene (Antich et al., 2021; Brandt et al., 2021), and it is expected to perform poorly for fungal groups with dikaryotic (Basidiomycota ), diploid (most unicellular groups) or polyploid (Glomeromycota ) genomes that commonly exhibit two or multiple different rRNA gene and ITS copies per genome or even within haploid nuclei (Egan et al., 2018; Lindner et al., 2013; Runnel et al., 2022). Estensmo et al. (2021) demonstrated that in polypores, single species contained multiple ESVs.
And I would say:
"Sequence Varients capture multiple allies from diploid and polyploid taxa like Glomeromycota, leading to higher alpha diversity values compared to taxonomy-based methods."
I should remind the authors that after predicting taxonomy, ASVs can be collapsed by taxonomy if that's most helpful to readers.
Lots of people like named taxonomy. It's got that magic 
On a different topic, Tedersoo 2022 missed an opportunity here:
Scripts used for analyses should also be released in, for example, Github or zenodo, to secure reproducibility and potential reuse in other applications.
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-> ATCGG
