TMDL reevaluation: reconciling internal phosphorus load reductions in a eutrophic lake
Bibliographic record
Abstract
Total maximum daily loads (TMDLs) are assigned to impaired waterbodies and provide a prescription for recovery. It is implicit that both the existing conditions and targets identified in a TMDL are based on credible and accurate information, ensuring that management actions directed to recovery are appropriate and effective. We evaluated the TMDL for phosphorus in Bear Lake, Michigan, to assess if the prescribed reduction was appropriately based on existing annual internal loads. We developed 5 different annual internal load scenarios based on phosphorus release rates from laboratory-based sediment incubations and diel dissolved oxygen measurements, ranging from very conservative to very liberal estimates of phosphorus release. The most realistic scenarios indicate that the previously established TMDL for internal phosphorus loading is 3–7 times greater than what actually occurs in Bear Lake. Based on our assessment, Bear Lake is likely already meeting the TMDL internal loading target, without the implementation of any management action. Thus, management efforts aimed at reducing the water column phosphorus concentration to reach the TMDL target should instead be directed at controlling the external phosphorus load.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".