This publication presents a dataset of saproxylic (dead wood) fungi which addresses the limited understanding of saproxylic fungal diversity, community structure and colonisation dynamics in fine woody debris (FWD). This knowledge gap is largely due to the microscopic or cryptic nature of most fungal species, which often exist primarily as mycelium. To overcome this challenge, the study employs metabarcoding of DNA extracted from pins representing FWD which were experimentally placed for decomposition in northern Finland. The dataset can be used to investigate the composition and progression of fungal communities across different stages of wood decay. It includes communities from distinct biotopes: one forest site protected from reindeer grazing, one exposed to reindeer and a forest area frequented by tourists. The use of standardised decomposition experiments combined with high-throughput eDNA analysis represents a notable methodological approach in characterising saproxylic fungal communities.

The dataset was generated using the novel MycoPins method, published by the authors in 2023, in which sterilised wooden pins were embedded beneath the forest litter and left to decompose for one year, while being periodically inspected. This innovative decomposition experiment was conducted at the Oulanka Research Station in Kuusamo, Northern Finland. As the first study in this region to investigate saproxylic fungi in fine woody debris (FWD) using MycoPins and DNA metabarcoding, it adds new knowledge to the fungal biodiversity data of the region. The resulting dataset of DNA-derived occurrences has been published through the Global Biodiversity Information Facility (GBIF), offering valuable insights into fungal diversity across different stages of decomposition. Agaricomycetes, a class of fungi strongly associated with their hosts via ectomycorrhiza, was selected from the dataset for comparison with fungal datasets from neighbouring regions. Remarkably, the MycoPins method revealed a high proportion of unique Agaricomycetes taxa not captured in existing species checklists from GBIF.org. These findings highlight the study's contribution to advancing biodiversity assessment. The results demonstrate the potential of this approach to enhance our understanding of fungal community dynamics in boreal forest ecosystems.