Liming for the mitigation of acid rain effects in freshwaters: A review of recent results
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Acid rain has affected freshwater ecosystems for more than 50 years in much of northern Europe and North America. The acidification of waters, along with concurrent reduction in acid neutralization capacity, has caused deleterious changes to aquatic populations in much of these regions. To reverse some of the changes to aquatic ecosystems, a number of governmental and nongovernmental groups have applied lime and other neutralizing substances to streams, rivers, lakes, and catchments in the most affected or most ecologically valuable regions. We review the scientific literature published since the late 1980s on liming to provide an overview of successes and failures of various approaches. We discuss the rationale behind liming programs and why certain approaches may not be helpful in mitigating acidification effects under varying conditions. One of our main conclusions is that though water chemistry may be restored if only temporarily, aquatic communities probably will not return to their original states, though targeted fish species can be restored using active management approaches. The communities restored, however, are usually more unstable than those from undisturbed, or pre-acidification conditions. We also show that liming may have to be conducted for 50 to 60 years in some affected locations, which should affect the choice of approaches used in mitigation.Key words: acid rain, mitigation, liming, freshwaters, catchments, salmonids.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.001 |
| 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) | 0.000 | 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 it