SHIFT FROM CHLOROPHYTES TO CYANOBACTERIA IN BENTHIC MACROALGAE ALONG A GRADIENT OF NITRATE DEPLETION<sup>1</sup>
Bibliographic record
Abstract
A survey of the spatial distribution of benthic macroalgae in a fluvial lake of the St. Lawrence River (Lake Saint-Pierre, Quebec, Canada) revealed a shift in composition from chlorophytes to cyanobacteria along the flow path of nutrient-rich waters originating from tributaries draining farmlands. The link between this shift and changes in water quality characteristics was investigated by sampling at 10 sites along a 15 km transect. Conductivity, current, light extinction, total phosphorus (TP; >25 μg P · L(-1) ), and ammonium (8-21 μg N · L(-1) ) remained fairly constant along the transect in contrast to nitrate concentrations, which fell sharply. Filamentous and colonial chlorophytes [Cladophora sp. and Hydrodictyon reticulatum (L.) Bory] dominated in the first 5 km where nitrate concentrations were >240 μg N · L(-1) . A mixed assemblage of chlorophytes and cyanobacteria characterized a 1 km transition zone where nitrate decreased to 40-80 μg N · L(-1) . In the last section of the transect, nitrate concentrations dropped below 10 μg N · L(-1) , and cyanobacteria (benthic filamentous mats of Lyngbya wollei Farl. ex Gomont and epiphytic colonies of Gloeotrichia) dominated the benthic community. The predominance of nitrogen-fixing, potentially toxic cyanobacteria likely resulted from excessive nutrient loads and may affect nutrient and trophic dynamics in the river.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".