Norwegian deep‐water coral reefs: cultivation and molecular analysis of planktonic microbial communities
Bibliographic record
Abstract
Deep-sea coral reefs do not receive sunlight and depend on plankton. Little is known about the plankton composition at such reefs, even though they constitute habitats for many invertebrates and fish. We investigated plankton communities from three reefs at 260-350 m depth at hydrocarbon fields off the mid-Norwegian coast using a combination of cultivation and small subunit (SSU) rRNA gene and transcript sequencing. Eight months incubations of a reef water sample with minimal medium, supplemented with carbon dioxide and gaseous alkanes at in situ-like conditions, enabled isolation of mostly Alphaproteobacteria (Sulfitobacter, Loktanella), Gammaproteobacteria (Colwellia) and Flavobacteria (Polaribacter). The relative abundance of isolates in the original sample ranged from ∼ 0.01% to 0.80%. Comparisons of bacterial SSU sequences from filtered plankton of reef and non-reef control samples indicated high abundance and metabolic activity of primarily Alphaproteobacteria (SAR11 Ia), Gammaproteobacteria (ARCTIC96BD-19), but also of Deltaproteobacteria (Nitrospina, SAR324). Eukaryote SSU sequences indicated metabolically active microalgae and animals, including codfish, at the reef sites. The plankton community composition varied between reefs and differed between DNA and RNA assessments. Over 5000 operational taxonomic units were detected, some indicators of reef sites (e.g. Flavobacteria, Cercozoa, Demospongiae) and some more active at reef sites (e.g. Gammaproteobacteria, Ciliophora, Copepoda).
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.006 | 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".