Sea pens as indicators of macrofaunal communities in deep-sea sediments: Evidence from the Laurentian Channel Marine Protected Area
Bibliographic record
Abstract
Pennatulacean octocorals (sea pens), one of the primary conservation targets of the Laurentian Channel Marine Protected Area (MPA) in eastern Canada, occur at high densities in some deep-sea sedimentary habitats. Considered important habitat-forming organisms for many megafaunal organisms, the effect of sea pens on nearby sedimentary macrofaunal communities remains unexplored. During two cruises in September 2017 and July 2018, we sampled 9 stations within the MPA (336-445 m depth), including sea pen fields and bare sedimentary habitats, targeting individual sea pens in a subset of the cores to assess small-scale effects. We evaluated macrofaunal density, taxonomic diversity, vertical distribution, community composition, and biological trait expression, and investigated variation between sea pen fields and other (bare) sedimentary habitats, as well as between cores with and without sea pen specimens. Using multivariate analyses, we identified abiotic and biotic drivers of macrofaunal community composition and biological trait expression. Enhancement of macrofaunal density and taxonomic diversity and higher percentages of organisms in the upper sediment layers characterized sea pen fields in autumn, with more variable results in summer. Community composition and biological trait expression consistently differed in sea pen fields compared to bare sedimentary habitats, with Pennatula sea pen density as one of the primary drivers of variation especially for community composition, along with other environmental drivers (depth, grain size, and organic matter quantity and quality). We also detected small-scale enhancement of macrofaunal diversity in cores containing sea pens at stations characterized by predominantly bare sediments. Our results indicate that macrofaunal communities within sea pen fields differ from those in bare sediments and we propose sea pens play a role in influencing those patterns by increasing food availability, stability, and small-scale heterogeneity in sedimentary habitats, acknowledging that other environmental factors might also play a role in determining the observed patterns. Characteristics of macrofaunal communities within sea pen fields also suggested potentially higher sensitivity to disturbance, which amplifies the need for protection of sea pen fields in deep-sea sedimentary environments.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".