An evaluation of iron bioavailability and speciation in western Lake Superior with the use of combined physical, chemical, and biological assessment
Bibliographic record
Abstract
An iron‐dependent cyanobacterial bioreporter (Synechococcus strain KAS101) was used in unison with size‐fractionated iron content (>0.45, <0.45, <0.02 µm), and chemical characterization of iron complexation (C18 resin column) to elucidate the bioavailable forms of iron present in Lake Superior during periods of inverse thermal stratification (May) and strong thermal stratification (September) of the water column. The results provide evidence of organic complexation of iron in Lake Superior waters. Iron in most sampled water was complexed by organic compounds that behaved like fulvic acids, whereas some samples showed evidence for the presence of siderophore‐like compounds. The presence of dissolved organic matter suppressed the cellular luminescence of the bioreporter, indicating an increased iron bioavailability. This effect could result either from the presence of siderophores forming iron complexes that are bioavailable to the bioreporter, or from more indirect effects because of the presence of other organic compounds, such as fulvic acids or polysaccharides. Model ligand additions, iron bioaccumulation, and photo‐oxidation of dissolved organic matter were used to assess the bioavailability of organically complexed iron to the bioreporter. A significant fraction of the iron (40‐100%) was bioavailable to the bioreporter. Iron bioavailability was high enough for the bioreporter not to be iron limited in the water collected from Lake Superior. This measure of bioavailability to picocyanobacteria is relevant because picoplankton accounted for the majority of chlorophyll a in Lake Superior during this study.
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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".