Deep chlorophyll maxima in small boreal forest lakes after experimental catchment and shoreline logging
Bibliographic record
Abstract
In situ profiles of chlorophyll fluorescence combined with depth-specific water chemistry and biotic analysis were used to assess deep chlorophyll maxima (DCM) in four boreal shield lakes that were subjected to different levels of watershed disturbance by clear-cut logging. Phytoplankton communities within the DCM varied among lakes, but were generally comprised of chrysophytes, diatoms, and cryptophytes. One lake also had deep cyanobacterial populations. Relative in situ fluorescence (absolute fluorescence at each peak minus background fluorescence) at the fluorescence peaks was significantly correlated with the level of chlorophyll a at the peak (r2 = 0.81, p < 0.025) for all lakes. In general, DCM peak heights were consistent in each lake over the four-year post-logging sampling period, whereas DCM depths declined slightly in the most heavily logged lakes associated with increases in dissolved organic carbon. Therefore, on the basis of DCM data, only mild effects on lake water quality were apparent after the logging activity.
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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 | 0.000 | 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 | 0.001 |
| 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".