Toward an ecoregion scale evaluation of eDNA metabarcoding primers: A case study for the freshwater fish biodiversity of the Murray–Darling Basin (Australia)

High‐throughput sequencing of environmental DNA (i.e., eDNA metabarcoding) has become an increasingly popular method for monitoring aquatic biodiversity. At present, such analyses require target‐specific primers to amplify DNA barcodes from co‐occurring species, and this initial amplification can introduce biases. Understanding the performance of different primers is thus recommended prior to undertaking any metabarcoding initiative. While multiple software programs are available to evaluate metabarcoding primers, all programs have their own strengths and weaknesses. Therefore, a robust in silico workflow for the evaluation of metabarcoding primers will benefit from the use of multiple programs. Furthermore, geographic differences in species biodiversity are likely to influence the performance of metabarcoding primers and further complicate the evaluation process. Here, an in silico workflow is presented that can be used to evaluate the performance of metabarcoding primers on an ecoregion scale. This workflow was used to evaluate the performance of published and newly developed eDNA metabarcoding primers for the freshwater fish biodiversity of the Murray–Darling Basin (Australia). To validate the in silico workflow, a subset of the primers, including one newly designed primer pair, were used in metabarcoding analyses of an artificial DNA community and eDNA samples. The results show that the in silico workflow allows for a robust evaluation of metabarcoding primers and can reveal important trade‐offs that need to be considered when selecting the most suitable primer. Additionally, a new primer pair was described and validated that allows for more robust taxonomic assignments and is less influenced by primer biases compared to commonly used fish metabarcoding primers. An in silico workflow, artificial DNA communities, and eDNA samples were used to evaluate the performance of previously published and newly developed metabarcoding primers for fishes on an ecoregion scale. The results show that the in silico workflow allows for a robust evaluation of metabarcoding primers, and the newly designed primer pair is less affected by primer biases.