Multi-Biomarker Analysis Uncovers High Spatio-Temporal Stability of a Subarctic Rhodolith (Lithothamnion glaciale) Bed Food Web
Bibliographic record
Abstract
We used lipid, fatty acid, and stable isotope analyses to investigate variation, over nine months, in the trophodynamics of 10 dominant cryptofaunal, macroalgal/algal, and environmental components from two sites within a rhodolith (Lithothamnion glaciale) bed in southeastern Newfoundland (Canada). There was an overall shift from a diatom-based food web following the spring phytoplankton bloom to a kelp/algae-based food web during fall, accompanied by preferred use of EPA (20:5ω3) over DHA (22:6ω3) in most cryptofauna. The food web contained three trophic levels that encompassed: (1) direct feeding relationships from primary producers (e.g., rhodoliths, macroalgae) to second-order consumers (e.g., sea stars, polychaetes); (2) trophic subsidy from within and outside the rhodolith bed via settlement, resuspension, and consumption of macroalgal fragments and other detrital organic matter; and (3) strong pelagic/benthic coupling. Riverine input did not affect cryptofaunal diets, as shown by the lack of terrestrial biomarkers at the study site nearest to the riverine input, and there were minor differences in trophodynamics between both study sites. The present study’s findings, applicable to relatively broad spatial and temporal domains, as well as those of complementary studies of the same rhodolith bed, uncover high spatio-temporal stability of the rhodolith bed framework and of resident cryptofaunal abundance, diversity, and trophodynamics.
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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 | 0.001 | 0.001 |
| 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".