Long-term patterns in dissolved organic carbon in boreal lakes: the role of incident radiation, precipitation, air temperature, southern oscillation and acid deposition
Bibliographic record
Abstract
Abstract. Both lake-specific (e.g. pH) and regional (e.g. precipitation) factors affect DOC concentration and pattern. Using annual DOC concentration in nine boreal lakes in the ice-free season, the potential influences of five regional factors, air temperature, precipitation, SO4 deposition, solar radiation (photosynthetically active radiation, or PAR) and the southern oscillation index (SOI) have been explored through multiple regression. Mean solar radiation, winter precipitation and summer precipitation explained 59% of the variation in the mean DOC concentration (F3,17= 8.29, p= 0.0013). Solar radiation and winter precipitation were correlated, negatively, while summer precipitation was correlated, positively, with DOC concentration. Because these relationships were based on only 21 years of data (1978 to 1998), the significance of the parameters in the regression model was evaluated with a randomisation test. This re-analysis indicated that summer precipitation did not contribute significantly to the regression model ( prand= 0.183). The final multiple regression explained 50% of the variation in DOC (F2,18 = 9.33, prand= 0.002) based on solar radiation and winter precipitation. These results suggest that solar radiation and winter precipitation have a significant role in determining long-term DOC concentration in boreal lakes. Keywords: dissolved-organic-carbon, lakes, climate, solar-radiation, precipitation, acid-precipitation, Precambrian-Shield-Ontario
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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".