Realised Thermal Niches in Marine Ectotherms Are Shaped by Ontogeny and Trophic Interactions
Bibliographic record
Abstract
Understanding the response of marine organisms to temperature is crucial for predicting climate change impacts. Fundamental physiological thermal performance curves (TPCs), determined under controlled conditions, are commonly used to project future species spatial distributions or physiological performances. Yet, real-world performances may deviate due to extrinsic factors covarying with temperature (food, oxygen, etc.). Using a bioenergetic marine ecosystem model, we evaluate the differences between fundamental and realised TPCs for fish species with contrasted ecology and thermal preferences. Food limitation is the primary cause of differences, decreasing throughout ontogeny and across trophic levels due to spatio-temporal variability of low-trophic level prey availability with temperature. Deoxygenation has moderate impact, despite increasing during ontogeny. This highlights the lower sensitivity of early life stages to hypoxia, which is mechanistically explained by lower mass-specific ingestion at older stages. Understanding the emergence of realised thermal niches offers crucial insights to better determine population's persistence under climate warming.
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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".