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Record W4416619086 · doi:10.1002/edn3.70223

Congruence of Fish Community Diversity and Composition Estimates Using Water and Sediment (Benthic Surface and Trapped Suspended Solids) Based Environmental <scp>DNA</scp> in a Recently Restored Creek

2025· article· en· W4416619086 on OpenAlexafffundabout
Kevin C. Morey, Erika Myler, Robert Hanner, Gerald R. Tetreault

Bibliographic record

VenueEnvironmental DNA · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsUniversity of GuelphEnvironment and Climate Change Canada
FundersRoyal Ontario MuseumOntario GenomicsUniversity of GuelphGenome Canada
KeywordsElectrofishingSpecies richnessEnvironmental DNASampling (signal processing)Species diversityBenthic zoneSedimentCommunity structureWater quality

Abstract

fetched live from OpenAlex

ABSTRACT Environmental DNA (eDNA) metabarcoding is increasingly paired with electrofishing efforts for aquatic biomonitoring and it has been shown that aquatic eDNA and electrofishing can be complementary when used together. Sedimentary eDNA is also used when monitoring rivers but is infrequently paired with electrofishing. Additionally, the utility of capturing eDNA from suspended solids as an alternative sampling medium in freshwater systems has not been explored. In this study, we used a common universal 12S metabarcoding assay for fishes on three different eDNA sampling media (water, benthic surface sediments, and trapped suspended solids) to determine which most similarly estimated fish community diversity with paired electrofishing efforts in a recently restored creek in Guelph, Ontario, Canada. A mock community comprised of DNA extracts from fish inhabiting the system was used as a positive control for species detection. Estimates of species richness were most comparable between electrofishing and trapped suspended solids though water samples estimated the greatest overall species richness. However, all three eDNA sampling media were found to generate estimates of community diversity that were more similar to each other than they were to estimates from electrofishing. Differences in community diversity were associated most strongly with collection method, weakly with sampling site, and were not associated with sampling period. Additionally, an indicator species analysis revealed that the taxa discriminating between the eDNA and electrofishing methods were all taxa that could not be amplified from the mock community. These findings suggest that the dissimilarity in diversity and indicator species observed between eDNA and electrofishing sampling methods is being primarily driven by methodological limitations relating to primer specificity and resolution.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.415
Threshold uncertainty score0.825

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.217
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations0
Published2025
Admission routes3
Has abstractyes

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