Nearshore–offshore differences in planktonic chlorophyll and phytoplankton nutrient status after dreissenid establishment in a large shallow lake
Bibliographic record
Abstract
In Lake Simcoe, a large lake in southern Ontario, Canada, with more than 50% of its surface area <15 m deep, dreissenid mussels are abundant in the extensive nearshore zone but not offshore. We hypothesized that mussel grazing would depress chlorophyll a (Chl-a) concentrations in the nearshore compared to the offshore while alleviating nearshore phosphorus (P) deficiency through nutrient regeneration. During both years of our study Chl-a concentration and other indicators of phytoplankton biomass, including particulate carbon (C), nitrogen, P, and silicon, were lower in the nearshore areas of Lake Simcoe where the exotic invader Dreissenia polymorpha was in contact with overlying epilimnetic water. In the first year of our study, grazing and associated nutrient regeneration activity seemed to reduce P deficiency in phytoplankton in the dreissenid-impacted shallow locations. In the second year, however, phytoplankton in the nearshore dreissenid-affected areas remained as strongly P deficient as phytoplankton in offshore waters physically separated from dreissenid grazing. Photoacclimation in the nearshore phytoplankton was evident in higher particulate C:Chl-a ratios and higher effective absorptive cross section of photosystem II (σPS II) throughout the stratified sampling season compared to offshore phytoplankton. A multiple linear regression utilizing the mean light intensity in the mixed layer as well as total P (TP) resulted in better predictions of Chl-a than TP alone. We conclude that, in shallow lakes where transparency is strongly impacted by dreissenid grazing, the comparison of Chl-a–TP relationships over time will require accounting for the effect of changing transparency.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 0.001 |
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 teacher head, 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".