Seamount science scales undersea mountains: new research and outlook
Bibliographic record
Abstract
Abstract Conventional wisdom suggests that seamounts harbour high levels of biodiversity and endemism, play important roles in marine biogeography, are hotspots of biological carbon processing, and support substantial fisheries. However, since fewer than 300 seamounts have been thoroughly sampled, these generalizations remain largely untested. This has provided the motivation for a number of seamount‐focused research projects in recent years, including CenSeam, a field project within the Census of Marine Life. This issue presents some of the research output facilitated by CenSeam. Here we summarize the main findings and provide a précis of future research directions highlighted by contributors to the issue. Recent studies show that seamounts can have comparable levels of benthic diversity and endemism to continental margins, but their communities also include a distinct composition of species that can attain higher biomass. Reported geographic differentiation among seamount communities suggests limited larval dispersal, local speciation, geographic isolation, or a combination of these processes. Genetic studies contained in the issue address these themes explicitly, documenting complex patterns of connectivity that depend on spatial scale and life history characteristics. Globally, seamount ecosystems are also under pressure from bottom‐contact fishing and ocean acidification. Contributions detailing the footprint of trawling and a risk assessment confirm what has long been suspected: seamount ecosystems are highly vulnerable to disturbance by bottom trawling and recovery from fishing impacts is a lengthy process, likely requiring decades at a minimum. A predicted shallowing of the aragonite saturation horizon caused by ocean acidification is predicted to place deep‐water corals at risk, but seamounts may yet provide a spatial/chemical refuge from these impacts. The issue concludes with a ‘myth‐buster’ synthesis that updates the status of the various seamount ecological paradigms.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.014 | 0.001 |
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".