Influence of an oxygen minimum zone and macroalgal enrichment on benthic megafaunal community composition in a <scp>NE</scp> Pacific submarine canyon
Bibliographic record
Abstract
Abstract Megafaunal diversity in the deep sea shows a parabolic pattern with depth. It can be affected by factors such as low oxygen concentration, which suppresses diversity, or the presence of submarine canyons, which enhances it. Barkley Canyon, located off the west coast of British Columbia, Canada, is a submarine canyon that extends from the continental margin (200 m) into the deep ocean (2,000 m). This canyon receives drift kelp from shoreline kelp forests and contains an oxygen minimum zone (OMZ) at 500 to 1,500 m depth. Our study investigated the abundance and diversity of epibenthic megafauna over a range of depths (200–2,000 m) and oxygen concentrations (0.5–5.0 ml/L) within Barkley Canyon, as well as changes in abundance near detrital kelp. Video was collected using the remotely operated vehicle ROPOS along seven 1‐km cross‐canyon (i.e., across the axis of the canyon) transects and three 40‐m perpendicular cross‐transects over kelp. Taxonomic groups were associated with depth, temperature, and the presence of pebbles. The OMZ restricted pennatulids, and edge effects along OMZ boundaries were observed for ophiuroids. The geomorphology of the sea floor affected the distribution of taxa across the canyon, with Porifera mainly found along the walls and Echinoidea within the canyon axis. Expected richness exhibited a bimodal pattern, peaking at 300 and 2,000 m, possibly due to the combined effect of the OMZ and the submarine canyon. Echinoidea aggregated near drift kelp at 200 and 300 m. We found that faunal communities in Barkley Canyon were influenced by several confounded factors including depth, oxygen and substrate. Understanding faunal patterns is paramount with increased exploitation and a changing climate.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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".