Spring isothermal mixing in the Great Lakes: evidence of nutrient limitation and nutrient-light interactions in a suboptimal light environment
Bibliographic record
Abstract
During the spring isothermal mixing period (April-May) in 1993-1995, photosynthesis-irradiance and growth-irradiance experiments were conducted in Lakes Erie, Huron, Michigan, and Ontario to assess light limitation. Additionally, nutrient enrichment experiments were conducted in Lake Ontario. Results from the photosynthesis-irradiance experiments suggested that phytoplankton communities in all the lakes can be either light limited or light saturated, as the threshold parameter (Ik) was similar to mean water column irradiances (mean Iwc, ratio = 1.0). Growth-irradiance experiments also suggested the potential for light saturation; mean daily irradiance exceeded the threshold growth irradiance (Ik,g) in 95% of cases. Growth rates became light saturated at lower irradiances than photosynthetic rates. Evidence for a nutrient-light interaction in controlling in situ growth rates was also found in the nutrient enrichment experiments at incubation irradiances [Formula: see text] mean Iwc. Our results suggest that an interaction between nutrients and light is often controlling phytoplankton growth during spring mixing in the Great Lakes. The role of these nutrient-light interactions has increased in the past decade due to increased light availability in the lower lakes caused by phosphorus load reductions and the filtering activities of nonindigenous mussels.
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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 | 0.000 | 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".