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Record W4415720315 · doi:10.3390/toxins17110536

Biological Control of Microcystis aeruginosa Through Sequestration in Pseudofaeces Produced by the Freshwater Gastropod, Sinotaia aeruginosa

2025· article· en· W4415720315 on OpenAlexafffund
BM Madison, Mingzhi Qu, Elliot Gavrin, Wenwei Ren, Yuxiang Wang, Daniel D. Lefebvre

Bibliographic record

VenueToxins · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsQueen's UniversityBrandon University
FundersMinistry of Science and Technology, TaiwanQueen's UniversityMinistry of Science and Technology of the People's Republic of ChinaOntario Centre of InnovationOntario Centres of Excellence
KeywordsMicrocystis aeruginosaCyanobacteriaBivalviaMolluscaClearance rateEcosystemFiltration (mathematics)

Abstract

fetched live from OpenAlex

Cyanobacteria harmful algal blooms (CHABs) are most commonly caused by the proliferation of the toxic species, Microcystis aeruginosa. It is therefore of considerable interest to develop biological control processes which are economically feasible and scalable for this cyanobacteria that produces the cyanotoxin, microcystin. Some gastropods that are abundant in freshwater ecosystems can filter feed on floating planktonic microphytes. We investigated this in the freshwater snail, Sinotaia aeruginosa which indiscriminately accumulated M. aeruginosa, Chlorella vulgaris, and Trichormus variabilis (syn. Anabaena variabilis) The initial filtration rates were approx. 44 and 19 mL · gwwt−1 · h−1 for unicellular and colony-forming M. aeruginosa, respectively. The pseudofaeces that were formed directly by filtration possessed a limited period of stability, and the bulk of the M. aeruginosa from pseudofaeces was eventually released back to the water column as undigested cyanobacteria. Nevertheless, the rate of sequestration of colonial M. aeruginosa into pseudofaeces was greater than its rate of release, thereby indicating that the temporary stability of pseudofaeces alone would be adequate to impede bloom formation. Therefore, these results provide evidence for using this gastropod in an effective preventative strategy for CHABs formation. Our results highlight the importance of understanding the impact of feeding mechanisms on ecosystem structure when proposing their use in biomanipulative processes aimed at correcting cyanobacteria impacted ecosystems.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.411

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 head0.008
GPT teacher head0.227
Teacher spread0.220 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations1
Published2025
Admission routes2
Has abstractyes

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