Long-term records and modelling of acidification, recovery, and liming at Lake Hovvatn, Norway
Bibliographic record
Abstract
Lake Store Hovvatn and the adjacent Lake Lille Hovvatn (Norway) are acidified owing to long-term deposition of S and N. By 1974, pH was 4.46 and acid-neutralizing capacity was 42 µequiv.·L1. Following a lake SO4reduction from 92 to 33 µequiv.·L1, pH had increased to 4.8 and acid-neutralizing capacity had increased to 8 µequiv.·L1by 2003. The acidification history is well reconstructed using the dynamic model MAGIC. The model predicts that the lakes will not, however, recover to conditions adequate to support a self-reproducing brown trout (Salmo trutta) population. Lake Store Hovvatn was first limed in 1981 and subsequently annually or biannually until 1999, at which time the entire catchment was limed. Liming increased pH to above target levels of 6.0 and reduced inorganic Al to below 5 µequiv.·L1in the main water body. Only after the terrestrial liming in 1999, however, was pH potentially adequate for egg survival in the lake during winter, as pH at shallow depths below the ice stayed above 5.5. The results indicate that even the dramatic reduction in acid deposition in Europe will be insufficient to provide water quality adequate for fish populations; such lakes will require some sort of liming for many decades to come.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".