Wind‐driven physical processes and sediment characteristics affect the distribution and nutrient limitation of nearshore phytoplankton in a stratified low‐productivity lake
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Lay Abstract Wind‐driven physical processes are expected to affect the spatial distribution and composition of algae in lakes and reservoirs, and to determine their access to nearshore nutrients. We used nutrient addition bioassays to detect changes in the nutrient status of phytoplankton, which indicate changes in nutrient availability in the water. We examined these effects at offshore and nearshore sites and at different times of the year, under different stratification conditions (prestratification, early and late stratification) and with different phytoplankton communities. Phytoplankton accumulated downwind, but their growth rate was usually higher at upwind than downwind sites. This suggests that the quantity and quality of algal food sources for higher trophic levels may vary in predictable but opposite ways. Wind‐driven surface waves and upwelling activity were associated with changes in phytoplankton nutrient limitation in nearshore areas, but these differences were site specific. Our results suggest that wind‐driven physical processes and sediment characteristics are both important in determining internal nutrient loading and phytoplankton nutrient limitation in nearshore areas. On windy days, nutrient limitation of offshore phytoplankton at the lake surface was always related to the conditions found upwind, suggesting rapid exchanges between nearshore and offshore areas. Wind‐driven physical processes affect the distribution and nutrient limitation of phytoplankton in lakes, and are likely to influence the efficiency of energy transfers through planktonic food webs. These wind‐driven processes should be included more specifically into food web models.
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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) | 0.000 | 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 it