Has lake brownification ceased? Stabilization, re-browning, and other factors associated with dissolved organic matter trends in eastern Canadian lakes
Bibliographic record
Abstract
• The rise in DOC has ceased at some sites, but a renewed increase was also observed. • DOC and DON may be linked to distinct factors, resulting in asynchronous trends. • Climate change is becoming more influential on DOC than acid deposition. • New trends may emerge in the future due to the dynamic nature of their drivers. The increase in dissolved organic carbon (DOC) concentrations in freshwater systems has received considerable attention due to its implications for drinking water treatment and numerous limnological processes. While past studies have documented the influence of recovery from acidification and climate change on long-term DOC trends, the emerging importance of these explanatory factors remains less understood. In addition, few studies have followed up on recent trends in sites that have undergone increases in DOC. Using a dataset from 1980 to 2020, we investigated interannual variations in DOC and dissolved organic nitrogen (DON) in 49 lakes across four eastern Canadian regions with a history of increases in DOC. We identified recent shifts in DOC patterns using LOESS smoothing and piecewise regression. We observed a stabilizing pattern or even a decrease (p < 0.001) in high acidification regions (Dorset and Nova Scotia), where increases in DOC were previously documented. At the low acid deposition region, IISD-Experimental Lakes Area, an increasing pattern in DOC stabilized in the early 2000s; however, DOC appears to be increasing again in recent years (p = 0.03). Our analysis identified precipitation and SO 4 deposition as the primary explanatory variables for DOC patterns (explaining 56–71% of variance). However, because acid deposition has declined substantially, climate and local watershed factors are becoming increasingly influential, leading to the emergence of new DOC patterns. Long-term changes in DOC and DON were not always synchronous, as these were often correlated with different factors (e.g., DON with ammonium deposition). This resulted in observable shifts in DOC:DON ratios, indicative of changes in dissolved organic matter (DOM) composition. We underscore the importance of ongoing monitoring in diverse regions because of the changing nature of environmental variables and new emerging trends.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".