Using complementary approaches to study diatom diversity and its environmental drivers

Benthic algal communities are widely used in river bioassessment; different identification approaches may show a complementary picture of community structure and its environmental drivers. Three datasets were studied in the Marcal and Rába river network (western Hungary): the (i) identification of phytobenthos including a broad taxonomic range of all algal phyla using microscopy, (ii) microscopical identification of diatoms, and (iii) diatom eDNA metabarcoding of 130 samples from 67 sites. Taxonomic inventories, richness and Shannon diversity, rank-order agreement in species abundances, and the community environment relationships were investigated in the three datasets. Metabarcoding yielded the highest per-sample diatom richness and diversity, whereas microscopic identification yielded lower per-sample richness and diversity. Phytobenthos microscopy captured the broadest algal spectrum but the lowest richness and diversity. A minor overlap was observed in the species list when applying the different methods. Correlations between microscopic and molecular abundances ranged from weak to strongly positive, indicating agreement for some widespread taxa but marked discrepancies for others. Shannon diversity for diatom amplicon sequence variants (ASVs) described unimodal responses to the main environmental gradient that was dominated by agricultural land use, conductivity, and nutrient enrichment. Co-inertia analysis revealed the tightest correlation between community structure and environmental variables for the metabarcoding dataset, followed by diatom and phytobenthos microscopy. In summary, the three approaches capture separate but complementary dimensions of benthic algal diversity and its environmental drivers. Integrating diatom metabarcoding into established microscopy-based programmes can enhance the sensitivity and interpretability of river biomonitoring. This integration is promising for developing indices that remain comparable with traditional diatom metrics while exploiting high-resolution molecular information. • Compared phytobenthos microscopy, diatom microscopy, and diatom metabarcoding across river samples. • Diatom metabarcoding detected the highest within sample richness and finer taxonomic resolution. • ASV-level data showed the clearest coupling between diatom communities and environmental conditions. • Shannon diversity described environmental patterns more consistently than richness across all methods.