Finding the way to the top: how the composition of oceanic mid-trophic micronekton groups determines apex predator biomass in the central North Pacific
Bibliographic record
Abstract
We updated and expanded a model of the pelagic ecosystem for the area of the central North Pacific occupied by the Hawaii-based longline fishery. Specifically, results from the most recent diet studies were used to expand the representation of the lesser-known non-target fish species (e.g. lancetfish, opah, snake mackerel) and 9 mid-trophic micronekton functional groups. The model framework Ecopath with Ecosim was used to construct an ecosystem energy budget and to examine how changes in the various micronekton groups impact apex predator biomass. Model results indicate that while micronekton fishes represented approximately 54% of micronekton biomass, they accounted for only 28% of the micronekton production. By contrast, crustaceans represented 24% of the biomass and accounted for 44% of production. Simulated ecosystem changes resulting from changes to micronekton groups demonstrated that crustaceans and mollusks are the most important direct trophic pathways to the top of the food web. Other groups appear to comprise relatively inefficient pathways or 'trophic dead-ends' that are loosely coupled to the top of the food web (e.g. gelatinous animals), such that biomass declines in these functional groups resulted in increased biomass at the highest trophic levels by increasing energy flow through more efficient pathways. Overall, simulated declines in the micronekton groups resulted in small changes in biomass at the very top of the food web, suggesting that this ecosystem is relatively ecologically resilient with diverse food web pathways. However, further understanding of how sensitive micronekton are to changes in ocean chemistry and temperature resulting from climate change is needed to fully evaluate and predict potential ecosystem changes.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 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".