Metabarcoding unsorted kick‐samples facilitates macroinvertebrate‐based biomonitoring with increased taxonomic resolution, while outperforming environmental DNA

Abstract

AbstractWhile previous studies have highlighted the potential of DNA‐based methods for the biomonitoring of freshwater macroinvertebrates, a limited number have investigated homogenization of bulk samples that include debris, in order to reduce sample‐processing costs. This study explores the use of several DNA‐based survey methods for water quality and biodiversity assessment in South Africa, comparing morphological and molecular‐based identification of freshwater macroinvertebrates at the family level and the level of molecular operational taxonomic units (mOTUs). Seven sites were studied across three rivers with four different sample types collected per site: a standard SASS biomonitoring sample split into a picked sample (also used for morphological identification) and a leftover debris sample; a more intensive‐search comprehensive sample; and a filtered water eDNA sample. DNA‐based methods recovered higher diversity than morphology, but did not always recover the same taxa, even at the family level. Regardless of the differences in SASS taxon scores, most DNA‐based methods, except a few eDNA samples, returned the same water quality assessment category as the standard morphology‐based assessment. Homogenized comprehensive samples recovered more freshwater invertebrate diversity than all other methods, suggesting the standardized SASS method overlooks taxa. The eDNA samples recovered more diversity than any other method; however, 90% of the reads were nontarget and as a result eDNA recovered the lowest target (macroinvertebrate) diversity. However, eDNA did find some target taxa that all other methods failed to detect. This study shows that unsorted bulk samples have the potential to be used for water quality biomonitoring, providing higher diversity estimates for macroinvertebrates than either SASS picked or eDNA samples. These results also show the value of incorporating DNA‐based approaches into existing South African metrics, providing additional taxonomic resolution to develop more refined metrics for biodiversity management.