Effects of oceanography on North Pacific armorhead recruitment in the Emperor Seamounts
Bibliographic record
Abstract
Abstract The North Pacific armorhead (NPA), Pentaceros wheeleri , is thought to exhibit an extended post‐spawning epipelagic phase in which larvae disperse to the northeast Pacific Ocean. Current understanding of juvenile distribution, development, and mechanisms that drive recruitment variation, however, remains largely incomplete. The objective of this study was to compare a time series of NPA recruitment to established climate indices and to environmental covariates to explore drivers of the NPA life cycle. Additionally, this work investigates potential larval NPA transport pathways and their positional relationships to the proposed northeastern nursery grounds. Using Lagrangian particle tracking, trajectories of passive larvae were simulated at depths of 0 and 15 m for 18 years (2001–2018) from the Southern Emperor‐Northern Hawaiian Ridge (SE‐NHR) natal habitat. Dispersal distances and particle end positions were examined for their potential relationships with recruitment. Sea surface temperature and net primary productivity were evaluated as predictor variables using generalized additive modeling. Neither regression of particle end‐point characteristics nor environmental covariates resulted in significant correlations with recruitment here, perhaps owing to data limitations surrounding the nursery zone. Particles were found to be advected largely within the North Pacific transition zone in the central north Pacific. Significant seasonal correlations were found between recruitment and the Arctic Oscillation, Pacific Decadal Oscillation and North Pacific Gyre Oscillation, suggesting that NPA recruitment mechanisms respond to interannual ocean‐atmospheric climate oscillations. Better knowledge of the connections between recruitment and the environment would be valuable for stock management, and improvements for advection predictions are discussed.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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 teacher head, 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".