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Record W4406346015 · doi:10.1002/edn3.70029

Estimating Rapid Diversity Changes During Acute Herbicide Contamination Using Environmental DNA

2025· article· en· W4406346015 on OpenAlexafffund
Alessandra Loria, Orianne Tournayre, Marie‐Pier Hébert, Vincent Fugère, Rowan D. H. Barrett, Beatrix E. Beisner, Andrew Gonzalez, Melania E. Cristescu

Bibliographic record

VenueEnvironmental DNA · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental DNA in Biodiversity Studies
Canadian institutionsUniversité de MontréalUniversité du Québec à MontréalUniversité du Québec à Trois-RivièresYork UniversityMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaLiber Ero FoundationFonds de recherche du QuébecGroupe de recherche interuniversitaire en limnologieCanada Foundation for InnovationMcGill University
KeywordsEnvironmental DNAContaminationEnvironmental scienceDiversity (politics)Environmental chemistryBiologyEcologyBiodiversityChemistry

Abstract

fetched live from OpenAlex

ABSTRACT The biodiversity of freshwater ecosystems globally is facing severe threats due to various anthropogenic stressors, such as habitat degradation, introduction of invasive species, and pollution. Assessing the effects of human‐induced environmental stressors on population and community persistence requires accurate biodiversity estimates. While environmental DNA (eDNA) metabarcoding has emerged as a promising tool, its effectiveness in capturing rapid biodiversity responses to acute stressors across levels of biological organization (community, population, and intra‐specific levels) remains to be investigated. In this study, we tested the efficacy of eDNA metabarcoding in assessing rapid changes in aquatic zooplankton and insect communities by conducting a two‐month mesocosm experiment with pulses of glyphosate‐based herbicide under contrasting nutrient levels (mesotrophic and eutrophic). We examined the effects of treatments on community assemblages, family richness, and intraspecific diversity, and compared our findings with those obtained through a microscopy approach. Metabarcoding revealed partially congruent ecological findings with microscopy, indicating its potential in assessing rapid community changes. The herbicide induced shifts in community composition and differentially impacted zooplankton and insect family richness (increase in insects, and decrease in crustaceans and rotifers), suggesting a gradient of tolerance to the herbicide among taxa and potential top‐down regulation by insect larvae that may counteract the advantage gained by herbicide‐tolerant zooplankton. Finally, we showed that nutrient enrichment exacerbated the negative effects of the herbicide on intraspecific diversity, highlighting concerns about genetic erosion. Our findings underscore the complexity of responses to herbicide and nutrient enrichment in freshwater ecosystems. We conclude that eDNA metabarcoding can not only be used to estimate rapid changes in invertebrate communities but also provides additional value by offering a broader perspective on diversity dynamics and potential cascading effects at different scales of biological organization.

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), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.304
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.001
Open science0.0010.005
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.010
GPT teacher head0.207
Teacher spread0.197 · 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; both teacher heads agree on what is shown here.

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

Citations4
Published2025
Admission routes2
Has abstractyes

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