A clustering optimization strategy to estimate species richness of Sebacinales in the tropical Andes based on molecular sequences from distinct DNA regions

Fungi are believed to be diverse in the tropics, but because many groups are only known from their DNA sequences this hampers comparative diversity studies. We investigated mycorrhizal Sebacinales (Basidiomycota) of 67 individuals of Ericaceae and Orchidaceae in a tropical mountain ecosystem in Southern Ecuador to provide a first estimate of whether these fungi are particularly diverse in the Northern Andes. We partially sequenced the internal transcribed spacer (ITS) and large subunit (LSU) regions of the nuclear ribosomal DNA and analyzed them together with all Sebacinales sequences available from GenBank. The clustering optimization technique was used to determine clustering parameters that maximize the comparability between molecular operational taxonomic units (MOTUs) obtained from the distinct loci. Sampling effort and species richness were estimated with rarefaction-accumulation curves and non-parametric estimation using Chao2 and compared between Southern Ecuador and France. Clustering optimization indicated that a 1% LSU distance threshold corresponds to the commonly used 3% dissimilarity threshold for ITS, and that a clustering algorithm close to single-linkage clustering is optimal. The resulting clusters show that about 8-9% of observed Sebacinales MOTUs occur in the study area and that most of these MOTUs are endemic (74%). The widespread MOTUs from Southern Ecuador were also found in Panama, North America and Europe. The estimation of species richness revealed unsaturated sampling of Sebacinales in general and also in our study area. Our results suggest a high diversity of Sebacinales associated with Ericaceae and Orchidaceae at the study site in Southern Ecuador, but no hotspot of Sebacinales in comparison with other areas.