Chariton, Anthony A.Stephenson, SarahMorgan, Matthew J.Steven, Andrew D.L.Colloff, Matthew J.Court, Leon N.Hardy, Christopher M.2025-06-012025-06-010269-7491PubMed:25909325ORCID:/0000-0002-3765-0627/work/171152896http://www.scopus.com/inward/record.url?scp=84928124767&partnerID=8YFLogxKhttps://hdl.handle.net/1885/733756307DNA-derived measurements of biological composition have the potential to produce data covering all of life, and provide a tantalizing proposition for researchers and managers. We used metabarcoding to compare benthic eukaryote composition from five estuaries of varying condition. In contrast to traditional studies, we found biotic richness was greatest in the most disturbed estuary, with this being due to the large volume of extraneous material (i.e. run-off from aquaculture, agriculture and other catchment activities) being deposited in the system. In addition, we found strong correlations between composition and a number of environmental variables, including nutrients, pH and turbidity. A wide range of taxa responded to these environmental gradients, providing new insights into their sensitivities to natural and anthropogenic stressors. Metabarcoding has the capacity to bolster current monitoring techniques, enabling the decisions regarding ecological condition to be based on a more holistic view of biodiversity.Financial support for the project was provided by the CSIRO Oceans and Atmosphere. The authors wish to thank John Ferris and James Fells (Queensland Environmental Protection Agency) for their assistance in the collection of samples, Ray Williams (Queensland Department of Environment and Heritage Protection) for facilitating access to the physico-chemical data, and Chris Moeseneder (CSIRO) for his map illustration.10en18S rRNABiomonitoringDNAEukaryotesHigh-throughput sequencingIndicator taxaMetabarcodingSedimentsThreshold analysisMetabarcoding of benthic eukaryote communities predicts the ecological condition of estuaries2015-08-0110.1016/j.envpol.2015.03.04784928124767