Comparing traditional and DNA-based methods for deriving river health indices

Dr Michael Shackleton¹, Dr Katherine Dufforn, Dr Nicholas Murphy, Dr Paul Greenfield, Ms Michelle Cassidy, Dr Colin Besley

¹Latrobe University, Wodonga, Australia

Abstract: 

Methods for deriving river health indices traditionally involve collecting and morphologically identifying freshwater macroinvertebrates. DNA-based methods for identifying organisms have become increasingly popular and recent metabarcoding approaches now offer the ability to identify species from mixtures of whole animals (bulk-samples) or from environmental samples. However, producing accurate taxonomic lists from metabarcode data can be impacted by sample type, choice of primers, community composition within samples, and the availability of reference sequences. We compared the performance of molecular data extracted from bulk-samples against morphological data in calculating two biological indices and one metric: the family-level Stream Invertebrate Grade Number Average Level 2 (SIGNAL2), the genus-level equivalent of this index (SIGNAL_SG), and taxa richness. We further explored what effects DNA reference library completeness and read number threshold filtering have on deriving these. We found strong correlations between SIGNAL scores and moderate correlations between taxa richness measures between morphologically and molecularly derived data. Correlations were generally stronger for SIGNAL scores when local taxa were included in reference libraries and for taxa richness measures when non-target taxa were removed from analyses. Our study highlights the effectiveness of using molecular data as an objective and sensitive alternative to traditional freshwater biological assessment using macroinvertebrates.

Biography:

Dr Michael Shackleton’s research interests are in understanding the diversity and distributions of aquatic species and what drives those distributions. He develops and applies genetic tools that enable better detection of freshwater species and uses ecological data to model species distributions and responses to environmental impacts. Dr Shackleton works with regional, national and international organisations and collaborators. He has extensive experience in riverine ecology and biodiversity and has authored or co-authored 15 peer-reviewed articles since obtaining his PhD in 2014.