Three-dimensional management needs of deep-sea hydrothermal vent ecosystems
Bibliographic record
Abstract
Deep-sea hydrothermal vents form small, unique, and fragile ecosystems that are widely recognized as sites in need of protection. Deep-seabed mining (DSM) is a future threat to hydrothermal ecosystem integrity. In most areas within, and in all areas beyond national jurisdiction, currently proposed protection measures from DSM are unlikely to be sufficient, as only the known active venting sites on the seafloor are intended to be protected from DSM impacts. To ensure effective protection, we propose protecting not only the active vent sites but the entire hydrothermal ecosystems and their transition zones, embracing the seafloor, subseafloor and overlying water column. We discuss how ecological knowledge supports the proposed three-dimensional (3-D) protection. We suggest no DSM extraction or indirect impacts on the seafloor and entire subseafloor within a minimum 50 km diameter (25 km radius) around visible active vents. This will ensure the maintenance of subseafloor connections that are key for ecosystem integrity, as changes in vent fluid conditions can alter all ecosystem functions and services linked to venting activity. In the water column, protection from pollution from the seafloor to surface is suggested to protect vent larvae. This extent spans the entire length of ridges or back-arc basins, with a cross-axial extent of 80 km. We further discuss how international law can contribute to the effective protection of vent ecosystems and transition zones in international waters, and provide guidance for coastal States to safeguard these ecosystems and transition zones within their own maritime areas.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".