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Abstract Bycatch and discards, representing unwanted catches, undermine sustainable fisheries and hinder the conservation of vulnerable and endangered species. To effectively monitor bycatch and enhance the effectiveness of management measures while promoting sustainable fishing practices, reliable data is essential. Here, we explore the use of Nanopore metabarcoding to analyze the catch composition in demersal bottom fisheries. We collected eDNA samples directly from an onboard catch holding tank (catch water) for 10 fishing hauls from a fishing vessel operating in the Skagerrak (North‐East Atlantic). The approach involved sequencing a combination of long (~2 kb) and short (~170–313 bp) mitochondrial amplicons and was validated by analyzing a fishery‐related mock community sample and fishing haul replicates. Overall, the detection rate accuracy was 95% for landed species, and replicates obtained from the same fishing haul showed consistent results, validating the robustness of this approach. The detection rate accuracy for all caught species observed on board (including the non‐landed fraction) was 81%. Undetected species were always limited to species in low abundance, but may also be attributed to problems with identifying closely related species due to the impact of sequencing errors and limited diagnostic variation in the genetic regions used. In the future, such biases may be reduced by using additional markers to increase species discrimination power and applying newly available technological advantages in flow cell chemistry to improve sequencing accuracy. In conclusion, this study demonstrates the effectiveness of Nanopore eDNA sequencing of catch water for estimating species composition in demersal bottom trawl fisheries, including catches of non‐commercial and threatened and vulnerable species, without disrupting fishing activities. Incorporating eDNA analysis of catch water may therefore help facilitate effective monitoring, leading to better‐informed fisheries management, biodiversity conservation efforts, and the implementation of relevant legislation such as the EU landing obligation.

Abstract In recent years, the analysis of environmental DNA (eDNA) has significantly improved, allowing for high‐resolution species identification and possible biomass quantification from water samples. Fisheries management typically requires monitoring of catches, including precise information about bycatch quantities to make sound assessments of exploitation rates. Bycatch assessment is particularly challenging in large catches (>500 T), and the current practice of visual assessment of subsampled catches is time‐consuming, requires extensive labor, and often has low precision. We explored the feasibility for applying eDNA‐based methods for studying catch composition using the pelagic North Sea herring fishery with bycatch of mackerel as a case. First, we experimentally simulate a series of catches using a range of herring and mackerel weight proportions to establish relationships under real fisheries scenarios. The relationship is subsequently used to estimate the biomass of mackerel bycatch from eDNA from three herring catches, by sampling and comparing processing water both onboard ships and at the processing factory. All samples are analyzed using species‐specific quantitative PCR (qPCR). The experiments reveled a strong correlation between DNA and weight fractions characterized by a constant overrepresentation of mackerel DNA compared to expected mackerel weight. We found that eDNA‐based and visual methods applied to the same landing reflect the within catch variability in species composition alike, however, the methods can show disparity in total estimates of mackerel biomass. Accounting for haul mixing within total landed catches increases the precision of the factory and ship eDNA‐based estimates for the same catch. We show that eDNA‐based bycatch estimates provide coherent quantitative data, and likely improve quality and reduce costs of collecting fisheries‐dependent data and thereby contribute to securing sustainable fisheries.

The naturally occurring ectoparasite salmon lice (Lepeophtherirus salmonis) poses a great challenge for the salmon farming industry, as well as for wild salmonids in the Northern hemisphere. To better control the infestation pressure and protect the production, there is a need to provide fish farmers with sensitive and efficient tools for rapid early detection and monitoring of the parasitic load. This can be achieved by targeting L. salmonis DNA in environmental samples. Here, we developed and tested a new L. salmonis specific DNA-based assay (qPCR assay) for detection and quantification from seawater samples using an analytical pipeline compatible with the Environmental Sample Processor (ESP) for autonomous water sample analysis of gene targets. Specificity of the L. salmonis qPCR assay was demonstrated through in-silico DNA analyses covering sequences of different L. salmonis isolates. Seawater was spiked with known numbers of nauplii and copepodite free-swimming (planktonic) stages of L. salmonis to investigate the relationship with the number of marker gene copies (MGC). Finally, field samples collected at different times of the year in the vicinity of a salmon production farm in Western Norway were analyzed for L. salmonis detection and quantification. The assay specificity was high and a high correlation between MGC and planktonic stages of L. salmonis was established in the laboratory conditions. In the field, L. salmonis DNA was consequently detected, but with MGC number below that expected for one copepodite or nauplii. We concluded that only L. salmonis tissue or eDNA residues were detected. This novel study opens for a fully automatized L. salmonis DNA quantification using ESP robotic to monitor the parasitic load, but challenges remain to exactly transfer information about eDNA quantities to decisions by the farmers and possible interventions.

The naturally occurring ectoparasite salmon lice (Lepeophtherirus salmonis) poses a great challenge for the salmon farming industry, as well as for wild salmonids in the Northern hemisphere. To better control the infestation pressure and protect the production, there is a need to provide fish farmers with sensitive and efficient tools for rapid early detection and monitoring of the parasitic load. This can be achieved by targeting L. salmonis DNA in environmental samples. Here, we developed and tested a new L. salmonis specific DNA-based assay (qPCR assay) for detection and quantification from seawater samples using an analytical pipeline compatible with the Environmental Sample Processor (ESP) for autonomous water sample analysis of gene targets. Specificity of the L. salmonis qPCR assay was demonstrated through in-silico DNA analyses covering sequences of different L. salmonis isolates. Seawater was spiked with known numbers of nauplii and copepodite free-swimming (planktonic) stages of L. salmonis to investigate the relationship with the number of marker gene copies (MGC). Finally, field samples collected at different times of the year in the vicinity of a salmon production farm in Western Norway were analyzed for L. salmonis detection and quantification. The assay specificity was high and a high correlation between MGC and planktonic stages of L. salmonis was established in the laboratory conditions. In the field, L. salmonis DNA was consequently detected, but with MGC number below that expected for one copepodite or nauplii. We concluded that only L. salmonis tissue or eDNA residues were detected. This novel study opens for a fully automatized L. salmonis DNA quantification using ESP robotic to monitor the parasitic load, but challenges remain to exactly transfer information about eDNA quantities to decisions by the farmers and possible interventions.