The Whole Is More Than the Sum of Its Parts: Modeling Community‐Level Effects of UVR in Marine Ecosystems
Bibliographic record
Abstract
The effect of UVB radiation (UVBR, 290-320 nm) on the dynamics of the lower levels of the marine plankton community was modeled. The model was built using differential equations and shows a good fit to experimental data collected in mesocosms (defined as large enclosures of 1500 L filled with natural marine waters). Some unexpected results appear to be possible by indirect effects in prey (bacteria, phytoplankton and heterotrophic flagellates). In particular, apparent competition appears between small phytoplankton and bacteria. This effect is caused by a shared predator (ciliates). Another remarkable effect is an increase in bacteria and flagellates populations due to enhanced UVBR. This effect is similar to that observed under mesocosm experimental conditions and is related to the decrease of predation due to the direct damage to predators (ciliates) by UVBR. The effect of UVBR changing interaction coefficients may be dramatic on the community structure, producing big changes in equilibrium populations, as demonstrated by sensitivity analysis of the model. In order to generalize these results to field conditions it will be necessary to increase model complexity and include extra organic mater sources, mixing and sinking effects and predation by large zooplankton. This work shows that UVBR may produce community global responses that are consequence of both direct and indirect effects among populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".