The browning and re-browning of lakes: Divergent lake-water organic carbon trends linked to acid deposition and climate change
Bibliographic record
Abstract
Dissolved organic carbon (DOC) concentrations and water colour are increasing in many inland waters across northern Europe and northeastern North America. This inland-water "browning" has profound physical, chemical and biological repercussions for aquatic ecosystems affecting water quality, biological community structures and aquatic productivity. Potential drivers of this "browning" trend are complex and include reductions in atmospheric acid deposition, changes in land use/cover, increased nitrogen deposition and climate change. However, because of the overlapping impacts of these stressors, their relative contributions to DOC dynamics remain unclear, and without appropriate long-term monitoring data, it has not been possible to determine whether the ongoing "browning" is unprecedented or simply a "re-browning" to pre-industrial DOC levels. Here, we demonstrate the long-term impacts of acid deposition and climate change on lake-water DOC concentrations in low and high acid-deposition areas using infrared spectroscopic techniques on ~200-year-long lake-sediment records from central Canada. We show that acid deposition suppressed naturally higher DOC concentrations during the 20th century, but that a "re-browning" of lakes is now occurring with emissions reductions in formerly high deposition areas. In contrast, in low deposition areas, climate change is forcing lakes towards new ecological states, as lake-water DOC concentrations now often exceed pre-industrial levels.
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.
How this classification was reachedexpand
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 | 0.001 | 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 teacher head, 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".