Trade-offs between light and nutrient availability across gradients of dissolved organic carbon concentration in Swedish lakes: implications for patterns in primary production
Bibliographic record
Abstract
Dissolved organic carbon (DOC) limits primary production in lakes when present at high concentrations by reducing light availability, but stimulates primary production at lower concentrations by releasing nutrients through photolysis. These dual influences create the potential for threshold relationships between DOC and primary production, but empirical tests for the prevalence of thresholds are scarce. We used Box–Cox regression and environmental monitoring data from 703 subarctic and boreal lakes to assess patterns and potential threshold relationships between light and nutrient availability along gradients of DOC in northern Sweden’s six major watersheds. We found consistent patterns of increasing nutrient concentration and light attenuation with DOC. Further, we identified thresholds (mean = 5.96 mg·L −1 ) below which nutrient concentrations increased more rapidly than light extinction and above where the opposite occurred. These results suggest consistent patterns in primary production with shifts from nutrient to light limitation with increasing DOC. Accordingly, the thresholds agree with the vertex of the curvilinear relationship between lake primary production and DOC. We estimated that most lakes in Sweden are within ±3 mg·L −1 of the threshold, indicating high potential for changes from positive to negative influences of DOC on primary production if forecasted increases in DOC concentrations due to climate and land cover change are realized.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".