Vulnerable Marine Ecosystems in the NPFC Convention Area
Bibliographic record
Abstract
The North Pacific Fisheries Commission’s (NPFC) Scientific Committee is required to develop a process to identify Vulnerable Marine Ecosystems (VMEs) and areas where VMEs are likely to occur. NPFC recently adopted i) a methodology to identify VMEs based on visual data; and ii) a framework that identifies predictive models as one means to identify likely VMEs (i.e., areas where VMEs are likely to occur above an identified threshold). To identify observed VMEs on Cobb Seamount between 400 m and 1,200 m deep, a threshold methodology was employed based on the United Nations Food and Agriculture Organization's (the FAO) criterion of structural complexity. A VME indicator density threshold was estimated based on visual data from Cobb Seamount. This resulted in Canada identifying five VME areas on Cobb Seamount with a combined area of 508 m2 (representing 5% of the area surveyed). The locations of likely VMEs in the broader Cobb-Eickelberg seamount chain, in the depth range from 400 m to 1,200 m, were predicted using spatial modelling of VME indicator density with selected environmental parameters. Likely VMEs were predicted to be present on seven seamounts and one ridge in the Cobb-Eickelberg seamount chain. A total of 99 km2 (representing 10% of the modelled area) was identified as likely VMEs, with Cobb Seamount having the largest total area (27.5 km2). Multiple sources of uncertainty were identified including: limited available data; the representativeness of Cobb Seamount and extrapolation to nearby seamounts that may have different environmental characteristics; areas outside the depth range remain that were unassessed; the impact of pre-existing fishery damage on the modeling and results; the exclusion of potential VME indicator taxa; limiting the assessment to only one of five FAO VME criteria; and the selection and resolution of modelled environmental variables. An important implication of these sources of uncertainty is that the identified VMEs and likely VME areas are expected to be a subset of the full VME extent in this seamount range, considering VMEs and likely VMEs outside the 400 to 1,200 m depth range have yet to be evaluated. Future research to advance Canada’s identification of VMEs in the NPFC Convention Area could include: additional visual surveys designed for VME identification; further analysis of the VME indicator density threshold and methodology; investigation of other approaches to identify VMEs and likely VMEs based on the other four FAO VME criteria; and ground truthing of predictive models of the location of likely VMEs throughout the Cobb-Eickelberg seamount chain.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| 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".