Characterization of freshwater aquatic animal and plant communities across trophic levels, particularly detection of low abundance species, including threatened and endangered and aquatic invasive species (AIS), is critical for informing management decisions. Water samples (N=953) from 22 inland lakes in Michigan were collected and eDNAs were extracted and used to amplify regions of the 16S and 12S rRNA loci (vertebrates) and rbcL (plants). Samples were sequenced on an Illumina HiSeq. Species were identified by comparing the eDNA sequence data to a Michigan vertebrate and plant reference sequence databases. Measures of fish diversity and site occupancy based on eDNA metabarcoding were compared to estimates based on traditional sampling methods used in fish community surveys. Estimates of fish species total number, relative abundance, and community composition and diversity (Shannon index) derived from eDNA metabarcoding were comparable with estimates derived from traditional gear types used in fisheries assessments. Relative species metabarcode sequence abundance was correlated to species biomass and relative abundance. eDNA metabarcoding identified more species generally than did traditional gear, particularly low abundance species including AIS. Species accumulation curves demonstrated that more fish species were added per additional water sample interrogated than was the case for traditional gear. AIS fish species richness was associated with lake area and connectivity to other water bodies. Heat maps characterized spatial heterogeneity in fish and plant species richness and distribution of AIS within lakes. Plant species were represented by aquatic, wetland and terrestrial vascular plants and algae. Collectively, results demonstrate that eDNA metabarcoding is amenable to monitoring aquatic community diversity, species relative biomass, as well as early AIS detection.