Multiple Trophic Tracer Analyses of Subarctic Rhodolith (Lithothamnion glaciale) Bed Trophodynamics Uncover Bottom-Up Forcing and Benthic-Pelagic Coupling
Bibliographic record
Abstract
We paired a survey of cryptofaunal abundance and rhodolith morphology with lipid, fatty acid, and stable isotope analyses to quantify nutritional patterns and trophic linkages of six dominant echinoderm, bivalve, gastropod, and polychaete species, two macroalgal species, seawater, and underlying sediment in a large (>500 m 2 ) rhodolith ( Lithothamnion glaciale ) bed in southeastern Newfoundland (Canada). We found high densities of chitons ( Tonicella marmorea and T. rubra ) and daisy brittle star ( Ophiopholis aculeata ), and overall species composition, rhodolith morphology (shape and size), and total rhodolith biomass were consistent with other studies of the bed, indicating high temporal stability. Our lipid and fatty acid analyses revealed high levels of phospholipids and unsaturated fatty acids combined with low sterols in all animal species, suggesting adaptation for enhanced cell membrane fluidity in a cold-water environment. They also showed that most taxa sampled feed on a shared resource; diatoms, and that (non-kelp) macroalgal detritus are a key food source within rhodolith communities. Our stable isotope analysis uncovered three distinct trophic levels; producers, suspension/filter feeders and grazers, and predators, and unveiled potential resource partitioning between first- ( H. arctica ) and second- ( O. aculeata and Tonicella spp.) order consumers, whereby differences in feeding strategies enable utilization of specific components of the same organic and inorganic material. The unprecedented analytical resolution enabled by the combined use of three trophic tracers indicate that bottom-up forcing (as a mechanism of trophic control) and benthic-pelagic coupling (as a pathway of nutrient and energy flow) operate simultaneously, at least seasonally, in subarctic rhodolith beds.
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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 | 0.000 |
| 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) | 0.001 | 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".