Climate control of the spring clear‐water phase through the transfer of energy and mass to lakes
Bibliographic record
Abstract
We analyzed decade‐long time series of water transparency, algal abundance, zooplankton density, heat income, hydrology, and climate from six polymictic lakes of the northern Great Plains to determine how energy and mass transfers interact to regulate lake structure during the spring clear‐water phase (CWP). Timing (date of occurrence) and intensity (Secchi transparency) of CWP were highly variable among lakes (mean lake‐pair synchrony, S = 0.072, p = 0.53); however, CWP occurred in all lakes when water overlying the sediments reached 16.1°C ± 3.7°C and Daphnia cleared the water column of diatoms. At a decadal resolution, timing and intensity of CWP were correlated strongly and positively (r2 > 0.90, p < 0.05) with the net heat income (θ) and lake volume, but not with other independent lake, catchment, or climate features. Instead, at an annual resolution, the strength of correlations between CWP characteristics and heat income (r CWP‐θ ) was itself correlated inversely with the winter index of the North Atlantic Oscillation ( r < −0.55, p < 0.05) and with precipitation during February‐April ( r < −;0.675, p < 0.05). We conclude that the transfer of energy interacts with lake volume to regulate differences in timing and intensity of CWP among lakes, whereas the transfer of mass overrides energetic regulation to introduce temporal variation in CWP characteristics among years.
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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) | 0.000 | 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 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".