Marker-Dependent Biases and Contrasting Fungal and Prokaryotic Community Patterns in Hypersaline and Oligohaline Lagoons

Inland hypersaline lagoons are distinctive microbial habitats, yet their fungal diversity remains poorly characterized, particularly in Europe. We compared sediment fungal and prokaryotic communities from Salada Grande de Chiprana, the only permanent deep hypersaline lagoon in Western Europe, and the nearby oligohaline lagoon La Estanca using ITS1 and ITS2 metabarcoding for fungi and 16S rRNA gene amplicon sequencing for prokaryotes. Fungal communities were dominated by Ascomycota, Rozellomycota and Basidiomycota, when the ITS1 and ITS2 datasets were considered jointly, whereas prokaryotic assemblages were mainly composed of Pseudomonadota, Cyanobacteriota, Bacteroidota, and Chloroflexota. Alpha diversity did not differ significantly between lagoons for fungal communities, although ITS2 recovered a significantly higher number of observed ASVs than ITS1 ( p = 0.016). Bray–Curtis-based PERMANOVA indicated that fungal community composition was significantly associated with lagoon identity and molecular marker, with marker choice explaining more variation than lagoon identity and a significant lagoon × marker interaction. Conductivity, used as a proxy for salinity, explained a limited and non-significant fraction of fungal community variation; however, its independent contribution could not be separated from other environmental differences between the two lagoons. In contrast, prokaryotic communities showed taxonomic differences between lagoons but no statistically significant beta-diversity separation, with substantial within-lagoon variability. A large fraction of fungal ASVs remained taxonomically or functionally unclassified, suggesting that these sediments harbor poorly characterized fungal diversity. Overall, our results indicate that fungal and prokaryotic communities respond differently across contrasting lagoon environments and show that ITS1 and ITS2 recover complementary views of fungal diversity, underscoring the need to consider marker choice when interpreting metabarcoding-based ecological patterns.