Comparing eDNA metabarcoding with morphological analyses: Fungal species richness and community composition of differently managed stages along a forest conversion of Norway spruce towards European beech in Germany

Analyzing fungal diversity and community composition through environmental DNA (eDNA) metabarcoding and high-throughput sequencing relies on sequence databases and their taxonomic coverage which are often doubted in regards of data accuracy. To assess the potential of eDNA metabarcoding to distinguish differently managed forest conversion stages, we compared an extant morphological dataset created through sporocarp surveys with a metabarcoding dataset from the same study sites. The study was conducted along a spruce forest conversion project of Norway spruce towards European beech in the Eifel National Park in Germany. Using the UNITE ITS reference database, a total of 198 fungal operational taxonomic units (OTUs) were assigned up to the species level. Comparing the morphological and metabarcoding dataset, a low species overlap was observed with 27 shared fungi. The metabarcoding dataset revealed that all investigated forest conversion management stages shared beech-associated fungi (even the spruce forests), while within the morphological dataset, only the beechinhabiting forest conversion management stages showed beech-associated fungi. The metabarcoding dataset could not show the same fungal community response patterns on the spruce forest conversion, compared to the morphological dataset, but revealed the genetic refugium of the soil fungal community. We conclude that fungal eDNA metabarcoding should always be evaluated by taxonomic experts to identify potential sequence database errors. eDNA metabarcoding cannot be used interchangeably for morphological community analyses to identify response patterns of fungal communities on forest management strategies. However, both approaches performed well in combination and showed that beech-associated fungal communities with high functional redundancy can develop after a spruce forest conversion by restoring natural European beech forests with an appropriate close-tonature management strategy.

Automated summary

This study compared fungal diversity in differently managed forest conversion stages using both eDNA metabarcoding and morphological datasets. The low species overlap between the two datasets was observed, indicating that eDNA metabarcoding may not accurately capture the same fungal community responses as morphological analysis. Additionally, the study revealed that beech-associated fungi were present in all forest conversion management stages, suggesting the potential for high functional redundancy in fungal communities after forest conversion.