Seawater browning alters community composition and reduces nutritional quality of plankton in a subarctic marine ecosystem
Bibliographic record
Abstract
Inflows of coloured terrestrial organic matter cause seawater browning and reduced phytoplankton production in subarctic coastal ecosystems, potentially deteriorating the nutritional quality of marine food webs. We analyzed the fatty-acid (FA) compositions of seston and the zooplankton taxa Eurytemora affinis and cladocerans at three locations of the northern Baltic Sea. At the coastal and northerly locations, salinity and phosphorus concentrations were low, while concentrations of humic substances (i.e., terrestrial organic matter) were high. The southerly location showed the opposite trend. The ratio between alga-specific ω3 polyunsaturated FA and terrigenous monounsaturated FA (MUFA) in Eurytemora decreased from south to north, as did the ratio between the alga-specific docosahexaenoic acid (DHA) and terrigenous MUFA in cladocerans. With increasing humic substances, the biomass of DHA-rich phytoplankton decreased and the zooplankton MUFA content increased. Our results indicate that coloured terrestrial organic matter alters the phytoplankton composition, consequently affecting the zooplankton nutritional quality.
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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) | 0.000 | 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".