Mathematical Modeling of Phytoplankton in Lake Ontario,Part 2 Simulations Using Lake 1 Model
Why this work is in the frame
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Bibliographic record
Abstract
The results of a series of simulations of the response of the open lake region of Lake Ontario to various levels of nutrient input are described in this report. The simulations use a simplified dynamic model of phytoplankton nutrient interactions in a vertically segmented structure. \nThe lake is assumed to be well-mixed in the horizontal direction. The problem of long term simulations (10-20 years) that draw on short term observation and verification periods (5 years) is discussed and it is indicated that the overall \nloss rates of nutrient are of particular importance. Under a hypothesized, but reasonable, set of model parameters, the simulations indicate that the present observed open lake phytoplankton biomass of Lake Ontario does not appear to be in equilibrium with the present input nutrient load. \nTherefore, if the present load is continued, it is estimated that spring peak phytoplankton chlorophyll in the epilimnion will continue to increase to a new level about 45% higher \nthan present levels. The interaction of nitrogen and phosphorus is also described by the simulations and the results indicate a tendency for nitrogen limitation to be an increasing dominant factor in controlling the spring \nbloom. \nA pastoral" simulation using load estimates, indicative of conditions prior to man's intensive activity provides an approximation of an early state of the lake. This "hindcast" indicates that spring phytoplankton levels were some 40% less than present levels and average \nannual epilimnion biomass under equilibrium with present loads is about twice that under pastoral conditions. A series of analyses is also conducted comparing simulations \nfrom the dynamic model to estimates made from simplified plots of loading versus lake geometry. The results from the dynamic model indicate that a reduction in external nutrient load does not result in an accompanying decrease in \nphytoplankton biomass, due to the hypothesized non-equilibrium condition of Lake Ontario. The dynamic model results are therefore in contrast to the results one would obtain from \nusing "admissable" loading concept which indicates an improvement in lake trophic status. \nAnalysis of lake response to the U.S.-Canada Water Quality Agreement (WQA) loads using the hypothesized parameters indicates about a 6% reduction in peak phytoplankton at \nequilibrium. The implications of the results appear to be of some importance since the analyses indicate that it may difficult to achieve measurable reductions below present \nlevels of phytoplankton biomass in the open lake. From a decision and policy making viewpoint then, the simulations tend to indicate that maximum point source nutrient control for Lake Ontario will, at best, be a "ho1ding" action rather than a significant improvement in the status of the \nbe open lake. This report was submitted in partial fulfillment of Grant Number R 800610 to the Environmental Engineering and Science Program, Manhattan College, Bronx, New York \nby the U.S. Environmental Protection Agency. Work was completed as of April, 1975.
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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) | 0.001 | 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) | 0.075 | 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