Away from darkness: a review on the effects of solar radiation on heterotrophic bacterioplankton activity
Bibliographic record
Abstract
Heterotrophic bacterioplankton are main consumers of dissolved organic matter (OM) in aquatic ecosystems, including the sunlit upper layers of the ocean and freshwater bodies. Their well-known sensitivity to ultraviolet radiation (UVR), together with some recently discovered mechanisms bacteria have evolved to benefit from photosynthetically available radiation (PAR), suggest that natural sunlight plays a relevant, yet difficult to predict role in modulating bacterial biogeochemical functions in aquatic ecosystems. Three decades of experimental work assessing the effects of sunlight on natural bacterial heterotrophic activity reveal responses ranging from high stimulation to total inhibition. In this review, we compile the existing studies on the topic and discuss the potential causes underlying these contrasting results, with special emphasis on the largely overlooked influences of the community composition and the previous light exposure conditions, as well as the different temporal and spatial scales at which exposure to solar radiation fluctuates. These intricate sunlight-bacteria interactions have implications for our understanding of carbon fluxes in aquatic systems, yet further research is necessary before we can accurately evaluate or predict the consequences of increasing surface UVR levels associated with global change.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".