Linking observed changes in pelagic catches to temperature and oxygen in the Eastern Tropical Pacific
Bibliographic record
Abstract
Abstract Warming increases the metabolic rates of fishes and drives their oxygen demands above environmental oxygen supply, leading to declines in fish growth and smaller population sizes. Given the wide variability in species' sensitivity to changing temperature and oxygen levels, warming and oxygen limitation may be altering the composition of fish communities and hence, that of fisheries catches. Here, we test the hypothesis that changing temperatures shape the composition of pelagic fisheries catches in the Eastern Tropical Pacific. We expect that under warmer conditions, pelagic fisheries catches will be dominated by tropical species with higher oxygen demands and less surplus oxygen for growth. To test this hypothesis, we combined an index of the physiological vulnerability of exploited large pelagic fishes (e.g. tuna and billfish) to changing ocean temperatures and oxygen levels with fisheries catch data from 1970 to 2016. We found that warming is the main driver of changes in the physiological performance and catch composition of this fishery, and that oxygen limitation may be causing a significant breakpoint in the relationship between sea surface oxygen and the index of vulnerability of pelagic catches in the Ecuador and Galapagos Exclusive Economic Zones. Warm temperature anomalies due to El Niño were projected to cause reductions in the physiological performance of large pelagic fishes, although this only led to changes in catch composition during the extremely warm events. Our results suggest that catches are vulnerable to future warming, as the increasing frequency, duration and magnitude of marine heatwaves associated with climate change impact catch composition.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".