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Cyanobacteria reduce quagga mussel (Dreissena rostriformis bugensis) spawning and fertilization success

2018· article· en· W6921031246 on OpenAlexfundno aff

Bibliographic record

VenueHuman Biology · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
FundersNational Oceanic and Atmospheric AdministrationU.S. Geological SurveyEnvironment and Climate Change CanadaGrand Valley State University
KeywordsCyanobacteriaHuman fertilizationGameteMusselPhytoplanktonAlgal bloomAlgae

Abstract

fetched live from OpenAlex

Quagga mussels (Dreissena rostriformis bugensis) are highly fecund broadcast spawners invasive to freshwaters of North America and western Europe. We hypothesized that environmental cues from phytoplankton can trigger gamete release in quagga mussels. Nutritious algae may stimulate dreissenid spawning, but less palatable food, such as bloom-forming cyanobacteria, could be a hindrance. The objective of our study was to test whether exposure to cyanobacteria can inhibit quagga mussel spawning and fertilization. We assessed spawning in the presence of serotonin, a known spawning inducer, where adult quagga mussels placed in individual vials were exposed to 13 cyanobacteria cultures and purified algal toxin (microcystin-LR) with artificial lake water as the control. Fertilization success was evaluated by combining eggs with sperm in conjunction with cyanobacteria, and enumerating zygote formation marked by cellular cleavage. Several cyanobacterial strains reduced spawning and fertilization success, but microcystin-LR had no effect. Fertilization was more sensitive to cyanobacteria than gamete release. Only 1 culture, Aphanizomenon flos-aquae, inhibited spawning, whereas 6 cultures consisting of Anabaena flos-aquae, Dolichospermum lemmermanii, Gloeotrichia echinulata, Lyngbya wollei, and 2 Microcystis aeruginosa isolates reduced fertilization rates by up to 44%. The effects of cyanobacteria on reproduction in invasive freshwater mussels in the wild have not yet been identified. However, our laboratory studies show that concentrations of cyanobacteria that are possible during bloom conditions probably limit reproduction. Reproductive consequences on wild populations may become more prevalent as cyanobacteria blooms occur earlier in the year, making overlap between blooms and mussel spawning more common. Describing the mechanism by which cyanobacteria inhibit spawning and fertilization could reveal novel control methods to limit reproduction of this invasive species.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.024
GPT teacher head0.294
Teacher spread0.270 · 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 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

Citations0
Published2018
Admission routes1
Has abstractyes

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