Effects of Water Withdrawal From Ice‐Covered Lakes on Oxygen, Temperature, and Fish<sup>1</sup>
Bibliographic record
Abstract
Abstract: In northern regions, large volumes of water are needed for activities such as winter road construction. Such withdrawals, particularly from small lakes, can reduce oxygen concentrations and water levels, potentially affecting aquatic organisms. Withdrawal limits have been developed by regulatory agencies, but are largely theoretical. Water withdrawal thresholds were tested in two small lakes by removing 10% and 20% of their respective under‐ice volumes and comparing oxygen parameters, temperature, over‐wintering habitat, and northern pike (Esox lucius) abundance to reference conditions. Because of a milder winter, oxygen parameters were elevated in reference lakes in the period following withdrawal compared to the prewithdrawal period. The 10% withdrawal resulted in a −0.2 m shift in the oxygen concentration profile at 4 mg/l in that lake, but had no effect on total volume‐weighted oxygen, or volume of over‐wintering habitat. In contrast, the 20% withdrawal caused 0.7 m reduction in the oxygen concentration profile at 4 mg/l compared to the previous year, a 26% decline in the volume‐weighted oxygen concentration, and a 23% reduction in the volume of over‐wintering habitat compared to prewithdrawal conditions. Water temperatures were slightly (≤ 10%) colder in the upper strata in the year following the withdrawal in both withdrawal and reference lakes. Northern pike abundance was not impacted by water withdrawals in either of the lakes. The results of this study show that the effects of water withdrawal on the parameters investigated reflected the characteristics of the lakes, and would therefore be expected to vary from lake to lake. Policy development to mitigate impacts must therefore reflect the site‐specific nature of water withdrawal.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".