Seasonal and diel changes of dissolved oxygen in a hypertrophic prairie lake
Bibliographic record
Abstract
Abstract Humboldt Lake, a hypertrophic prairie lake typical of many found on the Great Plains of North America, is usually ice‐covered from early November to about mid‐May. The lake is an important recreational fishery, now mainly stocked with walleye. It has a high potential risk of experiencing fish kills because of the very large cyanobacterial blooms that develop in it, the high rates of algal and bacterial production and the high concentrations of ammonia (NH 3 ‐N) and dissolved organic matter. Following the collapse of cyanobacterial blooms, shallow prairie lakes are known to undergo periods of anoxia that can lead to summer fish kills. In some of the lakes, anoxia forms during the long period of ice cover, causing winter fish kills. Two years of seasonal and diel data (total phosphorus, dissolved oxygen (DO), NH 3 ‐N and chlorophyll‐ a concentrations, and bacterial production) were analysed in this study to assess why significant fish kills did not occur during this period or during the ≈ 30 years of records from Saskatchewan Environment. Humboldt Lake did not become anaerobic, either following the collapse of the cyanobacterial bloom or under ice cover, indicating that the oxygen (O 2 ) influx (strong mixing) and production processes were greater than the microbial and chemical O 2 demands, both over seasonal and diel time scales. Several published risk threshold criteria to predict the probability of summer and/or winter fish kills were applied in this study. The threshold criteria of maximum summer chlorophyll and maximum winter NH 3 ‐N concentrations indicated that a summer fish kill was unlikely to occur in this hypertrophic prairie lake, provided its water quality remained similar to that during this study. Similarly, the threshold criteria of initial DO storage before ice cover and the rate of O 2 depletion under ice cover also indicated a winter fish kill was unlikely. However, recent development in the watershed might have resulted in significant water quality deterioration and the winter fish kill that occurred in 2005.
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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 | 0.000 | 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 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".