Aquaponics systems are closed-loop food production models that act as a critical One Health interface. While system stability depends on complex microbial communities, conventional metagenomic workflows rely on reference-based taxonomic assignment, causing biologically coherent but uncharacterised sequence populations, collectively termed microbial dark matter, to remain unresolved. To address this limitation, water samples were collected across an operational aquaponics facility, followed by DNA extraction and full-length 16S rRNA gene sequencing using Oxford Nanopore Technologies. Sequence reads were analysed using NaMeco, a taxonomy-independent pipeline that clusters sequences directly in sequence space before taxonomic assignment, preserving biologically coherent populations irrespective of their representation in reference databases. Results were compared with a conventional reference-based profiling workflow. NaMeco resolved multiple sequence clusters lacking close reference representatives, accounting for approximately 12-21% of reads and showing marked enrichment within solid waste compartments. Among these, one of the most abundant lineages was a Legionellaceae variant sharing only 88% identity with currently described species. Solid waste compartments also concentrated known fish and human pathogens, including Aeromonas spp., Edwardsiella tarda and Plesiomonas shigelloides. In contrast, reference-based profiling fragmented or discarded many divergent sequences, preventing their recognition as coherent biological populations. By separating biological structure discovery from taxonomic annotation, taxonomy-independent clustering enables previously unresolved microbial populations to be retained, characterised and tracked across complex environments. This provides a practical framework for investigating candidate microbial dark matter while supporting biosecurity monitoring in One Health production systems.