Effects of ultraviolet radiation on rates and size distribution of primary production by Lake Erie phytoplankton
Bibliographic record
Abstract
The impact of natural solar ultraviolet radiation (UVR), particularly UVB (297320 nm), on phytoplankton primary production in Lake Erie was investigated during the spring and summer of 1997. Radiocarbon incorporation and size-selective filtration was used to trace total production and its distribution among particulate and dissolved pools. On average, 1-h exposures produced half the UVB-dependent inhibition of total production realized in 8-h exposures, indicating rapid kinetics of photoinhibition. Cumulative UVB-dependent photoinhibition averaged 36% in 8-h simulated surface exposures. The efficiency of photoinhibition was greater for N-deficient than N-replete communities, but was not related to phytoplankton light history, P limitation, or the dominant genera. The proportion of recently fixed carbon occurring in the dissolved pool after 8-h exposures was significantly greater in higher-UVB treatments, whereas the share in picoplankton (<2 µm) was significantly lower. Significant UVB-dependent inhibition of total production was limited on average to relatively severe exposures, but the rapid kinetics of inhibition and the apparent effects on the allocation of carbon suggest it may be important to the lake's food web. Differences in optical properties and thermal stratification patterns suggested that the relatively turbid west basin was potentially more susceptible to UVR photoinhibition than the more transparent east or central basins.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".