Cold-water coral assemblages on vertical walls: distribution patterns from the Northeast Atlantic
Bibliographic record
Abstract
Aim: In this study, we assess patterns of cold-water coral assemblages observed on deep-sea vertical walls. Similar to their shallow-water counterparts, vertical and overhanging walls in the deep sea can host highly diverse communities, but because of their geometry, these habitats are generally overlooked and remain poorly known. These vertical habitats are however of particular interest, because they can protect vulnerable coral ecosystems from trawling activities. As such, it is important to understand their ecology and assess their global importance. Location: Vertical walls on complex geomorphic features, in particular walls of the Rockall Bank Slope Failure Escarpment, Whittard and Explorer Canyons, Northeast Atlantic. Methods: Video analysis of ROV transects carried out at five sites is used to investigate differences in species composition and diversity across walls and to compare those to nearby cold-water coral sites on flat terrain. A high-resolution photogrammetric reconstruction is further employed to examine whether wall complexity plays a role in promoting niche differentiation at very fine spatial scales. Results: The investigated walls showed differences in species assemblage both across walls as well as in comparison to flat sites, with the fine-scale heterogeneity engendered by walls allowing niche differentiation between closely-related taxa. Main Conclusions: Vertical walls represent an important cold-water coral habitat with differences in species composition across walls within a region, illustrating their role in driving diversity patterns. Based on publicly available bathymetric datasets and a catalogue of broad-scale terrain features, globally over 8,000 features are likely to have vertical walls and cold-water corals, which highlights the need to consider deep-sea vertical habitats in current conservation efforts.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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 | 0.005 |
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 teacher head, 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".