Paradigms in seamount ecology: fact, fiction and future
Bibliographic record
Abstract
Abstract Despite a relatively short history, the field of seamount ecology is rife with ecological paradigms, many of which have already become cemented in the scientific literature and in the minds of advocates for seamount protection. Together, these paradigms have created a widely held view of seamounts as unique environments, hotspots of biodiversity and endemicity, and fragile ecosystems of exceptional ecological worth. However, closer examination reveals significant gaps in our knowledge, thereby calling the accuracy of some of these paradigms into question. Here, we review the evolution of the major paradigms in seamount ecology, assess their status against the weight of existing evidence to date, identify emerging paradigms, and suggest future research directions. We find the assertions that seamount communities are vulnerable to fishing, and that these communities have high sensitivity and low resilience to bottom trawling disturbance are well supported by existing data. We find plausible evidence that seamounts are stepping stones for dispersal, oases of abundance and biomass, and hotspots of species richness. Nonetheless, the poor sampling coverage of these discrete but globally distributed environments prevents us from accepting these ideas as paradigms. Also plausible, but requiring further investigation, are the emerging paradigms that seamount communities are structurally distinct, that populations of invertebrates on seamounts are the source of propagules for nearby slope sinks, and that seamounts have acted and can act as biological refugia from large‐scale catastrophic environmental events. In contrast, the generalizations that seamounts are island habitats with highly endemic faunas that comprise unique communities distinct in species composition from other deep‐sea habitats, and that they have high production supported by localized bottom‐up forcing, are not supported by the weight of existing evidence.
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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 | 0.013 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.039 |
| Scholarly communication | 0.007 | 0.020 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 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".