The spectral sensitivity of phytoplankton communities to ultraviolet radiation‐induced photoinhibition differs among clear and humic temperate lakes
Bibliographic record
Abstract
We determined the spectral sensitivity of phytoplankton communities to photoinhibition in six temperate lakes spanning a transparency gradient due to variation in dissolved organic carbon (DOC) content. Changes in variable fluorescence (FV : FM) were monitored during experimental irradiance exposures and used to estimate spectral weighting functions for damage by ultraviolet radiation (UVR) and recovery rates. DOC explained a high proportion of the variation in UVR sensitivity, with clear‐water phytoplankton communities showing greater resistance to UVR‐induced photoinhibition than those of browner waters. These differences were greater when assessed in September, after clear‐sky conditions, than in July, after several days of overcast skies, especially in the long‐wavelength UVA spectral region. Surprisingly, the most UVR‐sensitive phytoplankton communities were dominated by filamentous cyanobacteria, a putatively UVR‐resistant taxon, whereas small unicellular eukaryotes were common in the most UVR‐tolerant assemblages. Model estimates of in situ photoinhibition after 2 h exposure to an incident solar spectrum were only slightly higher in the clear lakes than browner ones, despite appreciably higher UVR exposure in the former. Phytoplankton in clear lakes can maintain values of FV : FM comparable to communities protected from UVR by high concentrations of DOC.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".