Ocean circulation drives zonation of deep-water coral communities and their traits in the Northwest Atlantic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
One of the main objectives of community ecology is to unravel the mechanisms that influence the composition of species assemblages, a process known as community assembly. While research in terrestrial and coastal marine ecosystems has provided extensive knowledge on community assembly, little is known about the processes that shape ecological communities in the deep sea. In this study, we focus on deep-water coral communities in the NW Atlantic to assess the importance of environmental variables and coral traits for community assembly, by using joint species distribution modelling and trait-based approaches. We found that oceanographic variables, such as bottom temperature and salinity, influence the composition and trait characteristics of deep-water coral communities. Model predictions revealed a bathymetric zonation of coral communities driven by the predominant water masses in the region. Coral skeletal material emerged as an important trait: increased bottom salinity associated with subtropical water masses promoted the occurrence of corals with aragonite-based skeletons, while low salinity associated with subarctic water masses promoted the occurrence of corals that use calcite. Coral communities located at sites influenced by subtropical water masses showed higher species and trait diversity, while communities within the Gulf of Maine showed signs of strong environmental filtering and disturbance. These results emphasize the importance of ocean circulation for the assembly of deep-water coral communities. Our findings advance our understanding of the mechanisms that influence community assembly in the deep sea and improve our ability to predict potential consequences of future shifts in ocean circulation caused by climate change.
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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) | 0.000 | 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 it