Deep-sea benthic biodiversity and ecosystem functioning in cerianthid fields and adjacent sediments of a subarctic fjord
Bibliographic record
Abstract
Epibenthic megafaunal species may serve as ecosystem engineers by creating novel niches for associated fauna. Here we consider cerianthid (tube anemone, Ceriantharia) fields, a common but understudied feature of North Atlantic shelf and deep-sea ecosystems, and their effect on macrofaunal community ecology and ecosystem functioning. Based on remotely operated vehicle push-core sampling of sediments in Hebron Fjord (northern Labrador, Canada) and complementary shipboard incubations, we found that cerianthid fields influence macroinfaunal communities and shift ecosystem functioning. Specifically, increased macrofaunal density and differences in community composition and biodiversity through sediment layers inside cerianthid fields contrasted adjacent sites, along with shifts in nutrient fluxes. Greater degradation of organic matter inside cerianthid fields enhanced silicate efflux. We attribute differences in abundance patterns to predation pressure from cerianthids and altered hydrodynamics inside cerianthid fields that might enhance pelago-benthic coupling, supporting greater densities of deposit-feeding and opportunistic polychaetes.
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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 | 0.001 |
| 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".