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Record W4407184115 · doi:10.1002/edn3.70059

<scp>eDNA</scp> Sampling Systems for Salmon Ecosystem Monitoring

2025· article· en· W4407184115 on OpenAlexafffundabout
Christoph Deeg, Rob Saunders, Christopher Tam, Karia H. Kaukinen, Shaorong Li, Arthur L. Bass

Bibliographic record

VenueEnvironmental DNA · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsNuu Chah Nulth Tribal CouncilUniversity of British ColumbiaFisheries and Oceans Canada
FundersPacific Salmon Foundation
KeywordsEcosystemSampling (signal processing)Environmental scienceFisheryEnvironmental DNAEcologyEnvironmental resource managementComputer scienceBiologyBiodiversityTelecommunications

Abstract

fetched live from OpenAlex

ABSTRACT Environmental DNA (eDNA) is transforming the way aquatic ecosystems are monitored and managed by scientists, resource managers, ENGOs, First Nations communities, and citizen scientists alike. However, available sampling systems currently don't allow for combined high filtration volumes, rapid sample collection, and preservation in the field, thus far hindering broad scale eDNA studies in the ocean specifically for small and medium scale organizations. To overcome these challenges, several modular water sampling systems that utilize hollow‐membrane (HM) filtration cartridges were developed by RKS laboratories and tested by the Fisheries and Oceans, Canada, Molecular Genetics Laboratory. Compared to Sterivex filters, an industry standard for eDNA filtration, the HM filtration cartridges allowed for a six‐fold increase in filtration volume and threefold increase in filtration speed. The field sampling systems, which combine pumps, a programmable controller, an air pump, an ozone generator, and up to eight filters at once, enabled efficient direct eDNA filtration from diverse aquatic environments, from creeks to the open ocean. To evaluate ease of deployment, we present the results of a 3 day workshop where technical staff of an Indigenous resource management organization, without any prior knowledge in eDNA sampling, were trained and performed independent eDNA sample collection. The samples were analyzed by metabarcoding and qPCR to reveal the distributions of salmon and other species co‐occurring in salmon ecosystems, from large ephemeral predators, to the planktonic prey of salmon, even including their pathogens. In this example study, we further observed a substantial shift in community composition in the vicinity of aquaculture facilities where marine species associated with aquaculture feed were detected in freshwater at high relative abundance. This study demonstrates how these sampling systems provide an efficient entry point for small and medium scale organizations to utilize eDNA to fulfill their research and monitoring objectives.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.239
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.227
Teacher spread0.210 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations5
Published2025
Admission routes3
Has abstractyes

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