Physical fluxes, pelagic ecosystem structure, and larval fish survival in Hauraki Gulf, New Zealand
Bibliographic record
Abstract
The ecosystem supporting snapper (Pagrus auratus) larvae was studied during three springsummer (NovemberJanuary 19851988) spawning seasons in Hauraki Gulf, New Zealand. Upwelling-favourable winds caused more incursion of shelf water into the Gulf in 19851986 and 19861987 than in 19871988, but in the first two seasons, the winds were relatively weak. Stronger winds in 19871988 drove greater vertical diffusivity and correlated with greater mixed-layer primary biomass and productivity. Effects of vertical mixing appeared to dominate horizontal incursion of upwelled shelf water in supporting upper water column productivity. The more productive 19871988 season had greater abundances of nauplii, copepodites, adult copepods, cladocerans, chaetognaths, hydromedusae, decapod larvae, and numerous larval fish taxa (including snapper). There was much higher survival of snapper between the late-stage egg and post-first-feeding larval stages in 19871988, which correlated spatially and temporally with high larval prey densities. Neither higher egg production, fewer predators, nor less horizontal advection accounted for these strong larval snapper cohorts. We hypothesize that larval competence improved within the superior larval feeding environment, reducing predatory losses. The ecosystem response to wind mixing may partially explain the correlation of sea temperatures with recruitment, previously observed for the Hauraki Gulf snapper stock.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".