Microbes control the light-dependent production and dark decay of hydrogen peroxide in eutrophic surface waters
Bibliographic record
Abstract
Hydrogen peroxide (H 2 O 2 ) is hypothesized to be related to Microcystis bloom dynamics. To test this hypothesis, absolute H 2 O 2 production rates and H 2 O 2 decay rate constants were quantified from waters collected from the western basin of Lake Erie during the summer and fall of 2017–2019 and summer 2021 where harmful blooms are common and vary in duration, magnitude, and intensity. To quantify the range of and controls on microbial H 2 O 2 production and decay, incubations of water samples were designed to minimize or maximize microbial production and decay of H 2 O 2 (light-exposed and dark whole waters) alongside controls (light-exposed and dark 0.2 μm and 105 μm-filtered water). Microbial production of H 2 O 2 was predominantly dependent on visible light. Microbial production rates of H 2 O 2 were significantly, positively correlated with chlorophyll a and rates of whole-water respiration and primary production. Removing large colony-forming Microcystis cells and their physically attached bacteria with a 105-µm filter showed that visible light-dependent production of H 2 O 2 was due to free-living organisms such as phototrophic or heterotrophic microbes. Decay constants for H 2 O 2 were highest in waters containing high bloom biomass, and were significantly, positively correlated with whole-water respiration rates and with a proxy for labile dissolved organic nitrogen. Bacterial community composition predicted H 2 O 2 production and decay by random forest regression and by principal coordinate analysis. Results predict high microbial production and decay of H 2 O 2 during Microcystis blooms, with neither production nor decay due directly to large colony-forming Microcystis cells and their physically attached bacteria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".