ArticleHarmful algae2019
Evaluating putative ecological drivers of microcystin spatiotemporal dynamics using metabarcoding and environmental data.
Article in Harmful algae, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Network-Scale Patterns and Drivers of Microcystins in a Heavily Impacted Watershed.Ecosystems (New York, N.Y.) · 2026Article
- Linking Water Quality to Drinking Water Treatment Costs Using Time Series Analysis: Examining the Effect of a Treatment Plant Upgrade in Ohio.Water resources research · 2022Article
- Highlighting the promise of qPCR-based environmental monitoring: response of the ribosomal RNA:DNA ratio of calanoid copepods to toxic cyanobacteria.Ecotoxicology (London, England) · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Microcystin is a cyanobacterial hepatotoxin of global concern. Understanding the environmental factors that cause high concentrations of microcystin is crucial to the development of lake management strategies that minimize harmful exposures. While the literature is replete with studies linking cyanobacterial production of microcystin to changes in various nutrients, abiotic stressors, grazers, and competitors, no single biotic or abiotic factor has been shown to be reliably predictive of microcystin concentrations in complex ecosystems. We performed random forest regression analyses with 16S and 18S rRNA gene sequencing data and environmental data to determine which putative ecological drivers best explained spatiotemporal variation in total microcystin and several individual congeners in a eutrophic freshwater reservoir. Model performance was best for predicting concentrations of the congener MC-LR, with ca. 88% of spatiotemporal variance explained. Most of the variance was associated with changes in the relative abundance of the cyanobacterial genus Microcystis. Follow-up RF regression analyses revealed that factors that were the most important in predicting MC-LR were also the most important in predicting Microcystis population dynamics. We discuss how these results relate to prevailing ecological hypotheses regarding the function of microcystin.
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Registered trials
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