High abundances of the nuisance raphidophyte Gonyostomum semen in brown water lakes are associated with high concentrations of iron
Bibliographic record
Abstract
Algal blooms occur frequently in lakes and oceans and the causes and consequences of those are often studied. In this study, we focus on a less well known type of algal bloom by the freshwater raphidophyte Gonyostomum semen. This species' abundance and occurrence is increasing, especially in brown water lakes, the most abundant lake type in the boreal zone. The aim of the study was to investigate which environmental factors are associated with G. semen by statistical evaluation of field data of 95 Swedish lakes over five years. Although we found G. semen to be associated with dark waters it was, contrary to our expectations, mainly high concentrations of iron, and only to a lesser extent high TOC (total organic carbon) concentrations, that were associated with blooms of G. semen. In addition, high phosphorus concentrations and low pH also appear to facilitate G. semen blooms. We suggest that browning of lakes caused by increased iron concentrations may decrease net heterotrophy by fostering heavy algal blooms, i.e. the opposite to commonly assumed effects of increased DOM (dissolved organic matter).
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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 | 0.001 | 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) | 0.001 | 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".