The effects of ultraviolet-B radiation on freshwater ecosystems of the Arctic: Influence from stratospheric ozone depletion and climate change
Bibliographic record
Abstract
Depletion of stratospheric ozone, the principal atmospheric attenuator of ultraviolet-B (UVB) radiation, by man-made chemicals has raised scientific and public concern regarding the biological effects of increased UVB radiation on Earth. There is an increased awareness that existing levels of solar UV radiation have an important influence on biological and chemical processes in aquatic ecosystems. For aquatic organisms, numerous studies have shown direct detrimental effects of UVB radiation at each trophic level. Fortunately, many aquatic organisms also possess a range of photoprotective mechanisms against UV radiation toxicity. In addition to its direct impact, harmful effects of UVB radiation at a single-trophic level can cascade through the food web and indirectly affect organisms from other trophic levels. Because UV radiation photochemically reacts with humic substances and other photosensitive agents in the water, increases in solar UVB can also indirectly affect aquatic organisms through the production and (or) release of different photoproducts like biologically available nutrients and harmful reactive oxygen species. Polar aquatic ecosystems have been of particular concern, since stratospheric ozone-related UVB increases have been the greatest in these regions. With the influences of climate warming and the possibility of future volcanic eruptions, ozone losses are expected to get worse in the Arctic stratosphere, and the ozone layer recovery may not follow the slow decline of industrial ozone-depleting compounds in the atmosphere. Climate warming is also expected to bring important changes in underwater ultraviolet radiation (UVR) penetration in Arctic freshwaters that would be more significant to the aquatic biota than stratospheric ozone depletion.Key words: Arctic, UV radiation, UVB, ozone depletion, climate change, aquatic ecosystems.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".