Environmental DNA (eDNA), the trace genetic material organisms release into their surroundings, has emerged as a sensitive, non-invasive complement to traditional capture-based fisheries surveys, capable of detecting species that conventional gear often misses. Realizing its potential for routine monitoring, however, depends on resolving two long-standing limitations: the lack of standardized sampling procedures, and the difficulty of translating molecular signals into reliable estimates of fish abundance. Addressing these obstacles is urgent as fisheries management seeks regular monitoring approaches that are less costly, less labour-intensive, and less ecologically disruptive than conventional surveys. This study evaluated two complementary eDNA approaches. The first benchmarked autonomous biosamplers, which standardize how eDNA is collected, against manual water sampling and trawl catches. The second paired inexpensive, passively deployed devices – ‘metaprobes’ – with joint Bayesian modeling that corrects species-specific amplification bias using mock communities, to test whether such data can yield quantitative abundance estimates. Collectively, findings from this study show that standardized eDNA collection and bias-corrected quantitative modelling form a coherent and scalable pathway toward integrating eDNA into operational fisheries stock assessment. In doing so, the work advances the broader transition of eDNA as a tool for species detection toward its use as a quantitative instrument for ecosystem assessment.
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