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Record W4415629342 · doi:10.1016/j.watbs.2025.100507

Influence of light intensity on the toxicity of herbicides, alone or in mixture, to freshwater phytoplankton

2025· article· en· W4415629342 on OpenAlex
Haifeng Xu, Alexandre Gauthier, Beatrix E. Beisner, Johann Lavaud, Philippe Juneau

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, 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".

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueWater Biology and Security · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsTakuvik Joint International LaboratoryUniversité LavalNexen (Canada)Université du Québec à Montréal
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of CanadaGroupe de recherche interuniversitaire en limnologieDairy Farmers of Ontario
KeywordsSimazineAtrazinePhytoplanktonAquatic ecosystemPhotosynthesisLight intensityPrimary producers

Abstract

fetched live from OpenAlex

Light intensity directly affects phytoplankton and can alter the toxicity of phytotoxic pollutants present in natural water bodies. Light fluctuation in aquatic ecosystems often occurs as a function of water turbidity, water movement, cloud cover, and seasonality. Atrazine and simazine are commonly used herbicides that inhibit photosynthesis, posing significant risks to aquatic primary producers, and may be found simultaneously in aquatic ecosystems. The interactions between light and herbicide mixtures on phytoplankton growth and physiological state are poorly understood. Therefore, we addressed the toxicity of the herbicides, atrazine and simazine (individually and mixed), on the growth and photosynthetic activity of three freshwater phytoplankton under three light intensities. We found that the toxic effects of single and mixed herbicides are species-specific and significantly modulated by light intensity, with synergistic effects observed for herbicide mixtures under high light conditions. Atrazine and simazine (individually and mixed) toxicities on photosynthesis were greater for the three species grown under low light than under very low light. However, high-light adapted strains of M. aeruginosa were less sensitive to single and mixed herbicides than those adapted to low- and very low-light conditions. Under low- and high-light conditions, the photoprotective ability was extremely sensitive to the inhibitory effects of atrazine and simazine, individually and when mixed. Understanding these interactions is important because microalgae form the base of aquatic food webs and their impairment can have cascading effects on ecosystems. These findings underscore the importance of considering multiple environmental stressors in assessing the ecological risks of herbicides, highlighting potential impacts on aquatic primary productivity. • The sensitivity to herbicides (alone or mixed) differs among freshwater algae. • The toxicities of single and binary herbicides are modulated by light intensity. • Two cyanobacteria adapted to high light are sensitive to herbicides. • High-light adaptation decreased the toxicity of single and mixed herbicides.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.600
Threshold uncertainty score0.615

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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