Ecophysiological limits to aerobic metabolism in hypoxia determine epibenthic distributions and energy sequestration in the northeast Pacific ocean
Bibliographic record
Abstract
Abstract Expansion of oxygen deficient waters (hypoxia) in the northeast Pacific Ocean (NEP) will have marked impacts on marine life. The response of the resident communities will be a function of their ecophysiological constraints in low oxygen, although this remains untested in the NEP due to a lack of integrative studies. Here, we combine in situ surveys and lab‐based respirometry experiments were conducted on three indicator species (spot prawnPandalus platyceros, slender soleLyopsetta exilis, squat lobsterMunida quadrispina) of seasonally hypoxic systems in the NEP to test if metabolic constraints determine distributions and energy sequestration in a hypoxic setting. These experiments were integrated with a global review of critical oxygen levels ( ; lower threshold of aerobic metabolism) for crustaceans to determine if ‐based hypoxia thresholds are different among ocean basins. Our results show that species‐specific differences in and standard metabolic rates (1) determine the lowest environmental oxygen ([O2]env) at which in situ populations occur, (2) result in disproportionate shifts in distributions among co‐occurring species during summer hypoxia expansion events, and (3) characterize shifts in megafaunal community respiration rates due to marked spatio‐temporal variability in [O2]env. Our results show that ‐based hypoxia thresholds are significantly lower in the East Pacific Ocean relative to other major ocean basins, which suggests that the physiological response of local fauna to deoxygenation can be determined by the natural variability and oxygen exposure in a region. In order to establish realistic predictions on the biological consequences of marine deoxygenation, we suggest integrating metabolism‐based traits to calculate hypoxia thresholds for marine ecosystems.
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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 | 0.000 | 0.000 |
| 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".