Contrasting pollution sensitivity for temperate reef assemblages revealed by microhabitat-resolved eDNA, algal sampling and visual surveys

Shallow reef ecosystems support diverse, functionally important assemblages, spanning bacteria to megafauna, and are shaped by natural gradients and anthropogenic stressors, including pollution. Monitoring these dynamics remains challenging, particularly across microhabitats that are difficult to access or quantify. Environmental DNA (eDNA) offers a non-invasive tool capable of detecting organisms across body sizes and trophic levels, but its utility for assessing pollution impacts requires further validation. We compared eDNA metabarcoding of microbes (16S rRNA), microbial eukaryotes (18S rRNA), and metazoans (COI Leray) with underwater visual surveys (UVS) and epifauna (fucoid algae) sampling, across 18 sites in New South Wales and Tasmania, spanning pollution and habitat gradients. Potential pollutant impacts on reef assemblages were analysed using distance-based linear models. Pollutant-associated variations in assemblages within reef microhabitats (rock, brown algae, coralline algae) were also assessed. eDNA showed comparable sensitivity to that of UVS and epifaunal sampling, with distinct strengths. Epifaunal sampling uniquely detected total nitrogen and dichloroethane effects, while eDNA captured broader pollutant signals and microhabitat-specific assemblage variation. Sea Surface Temperature (SST), metals, Total Organic Carbon (TOC), δ 15 N, and human pressure (human population index) were significantly associated with assemblage shifts. Bacterial, microbial eukaryote and metazoan assemblages and their microhabitats showed distinct pollutant sensitivities: 16S identified δ 15 N, TOC, and metals; 18S metals and TOC; COI TOC and SST; and all assemblages responded to the population index across brown and coralline algae. These findings position eDNA as a valuable complement to traditional methods, with strong potential for integration into high-resolution, long-term reef biomonitoring frameworks.