Hypoxia Performance Curve: Assess a Whole-Organism Metabolic Shift from a Maximum Aerobic Capacity towards a Glycolytic Capacity in Fish
Bibliographic record
Abstract
The utility of measuring whole-animal performance to frame the metabolic response to environmental hypoxia is well established. Progressively reducing ambient oxygen (O2) will initially limit maximum metabolic rate as a result of a hypoxemic state and ultimately lead to a time-limited, tolerance state supported by substrate-level phosphorylation when the O2 supply can no longer meet basic needs (standard metabolic rate, SMR). The metabolic consequences of declining ambient O2 were conceptually framed for fishes initially by Fry’s hypoxic performance curve, which characterizes the hypoxemic state and its consequences to absolute aerobic scope (AAS), and Hochachka’s concept of scope for hypoxic survival, which characterizes time-limited life when SMR cannot be supported by O2 supply. Yet, despite these two conceptual frameworks, the toolbox to assess whole-animal metabolic performance remains rather limited. Here, we briefly review the ongoing debate concerning the need to standardize the most commonly used assessments of respiratory performance in hypoxic fishes, namely critical O2 (the ambient O2 level below which maintenance metabolism cannot be sustained) and the incipient lethal O2 (the ambient O2 level at which a fish loses the ability to maintain upright equilibrium), and then we advance the idea that the most useful addition to the toolbox will be the limiting-O2 concentration (LOC) performance curve. Using Fry & Hart’s (1948) hypoxia performance curve concept, an LOC curve was subsequently developed as an eco-physiological framework by Neil et al. and derived for a group of fish during a progressive hypoxia trial by Claireaux and Lagardère (1999). In the present review, we show how only minor modifications to available respirometry tools and techniques are needed to generate an LOC curve for individual fish. This individual approach to the LOC curve determination then increases its statistical robustness and importantly opens up the possibility of examining individual variability. Moreover, if peak aerobic performance at a given ambient O2 level of each individual is expressed as a percentage of its AAS, the water dissolved O2 that supports 50% of the individual’s AAS (DOAAS-50) can be interpolated much like the P50 for an O2 hemoglobin dissociation curve (when hemoglobin is 50% saturated with O2). Thus, critical O2, incipient lethal O2, DOAAS-50 and P50 and can be directly compared within and across species. While an LOC curve for individual fish represents a start to an ongoing need to seamlessly integrate aerobic to anaerobic capacity assessments in a single, multiplexed respirometry trial, we close with a comparative exploration of some of the known whole-organism anaerobic and aerobic capacity traits to examine for correlations among them and guide the next steps.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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; both teacher heads agree on what is shown here.
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".