Evaluating the importance of mesopelagic prey to three top teleost predators in the northwest Atlantic Ocean
Bibliographic record
Abstract
Abstract The ocean’s twilight zone is a vast area of the global ocean that lies between the sunlit surface waters and perpetually dark midnight zones, covering depths from ∼200 to 1000 m. Recent work in the twilight (or mesopelagic) zone has revealed unexpected biomass and diversity that may not only challenge scientific understanding of marine systems but also provide a new and largely untapped resource for fisheries harvest. A key knowledge gap in our understanding of the mesopelagic is how its food webs support foraging activity by commercially valuable, highly migratory top predators. Here, we use compound-specific stable isotope analyses to trace the flow of carbon through pelagic ecosystems in the northwest Atlantic to three predators: bigeye tuna (Thunnus obesus), swordfish (Xiphias gladius), and yellowfin tuna (Thunnus albacares). Temperate mesopelagic-associated carbon was estimated as both a direct and an indirect source of predator carbon, alongside temperate epipelagic and mixed epi-mesopelagic tropical carbon, via Bayesian mixing models. The contribution of temperate mesopelagic carbon to individual predators ranged from 5% to 94%, with means of 62%, 46%, and 28% for bigeye tuna, yellowfin tuna, and swordfish, respectively. We also found that carbon sources of predators shifted seasonally as they moved between temperate and tropical waters by contrasting tissues (liver, muscle) and season of sampling (summer, fall). These results inform our understanding of the adaptive value of deep diving behaviors in large marine predators and provide key estimates of food web linkages to inform multi-species fisheries management of both mesopelagic prey and migratory predators.
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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 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".