Picocyanobacteria abundance in relation to growth and loss rates in oligotrophic to mesotrophic lakes
Bibliographic record
Abstract
The relative importance of growth versus loss rates of picocyanobacteria (PC) and the influence of physical and chemical variables on their in situ abundance were examined during summer 2000 in 48 lakes in Quebec, Ontario and New York State. The lakes were selected based on their trophic state. For the resulting range in total phosphorus (TP) (1 to 42 g l -1 ), PC abundance varied from <10 2 ml -1 in a eutrophic lake dominated by a cyanobacterial bloom to over 10 5 ml -1 in oligotrophic and more mesotrophic lakes. Growth rates on average exceeded loss rates in the lakes with maximum rates of 1.93 and 1.25 d -1 , respectively, as estimated using a selective metabolic inhibitor method. On average the doubling time of PC was about 1.7 d. Growth rates were positively correlated with loss rates in the lakes. The multiple regression model that explained the most variation in PC abundance included SRP, loss rates, conductivity and the ratio of total Kjeldahl nitrogen (TKN) to TP. The results suggest that biotic control of the abundance of PC may be as important as abiotic control. However, the model could only explain 44% of the variation in PC abundance among the lakes. This could be in part the result of considering PC as one ecological group when in fact considerable diversity is likely present among freshwater PC.
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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 | 0.001 |
| 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) | 0.000 | 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".