The functional significance of facultative hyperthermia varies with body size and phylogeny in birds
Bibliographic record
Abstract
Abstract Facultative hyperthermia, the elevation of body temperature above normothermic levels, during heat exposure, importantly affects the water economy and heat balance of terrestrial endotherms. We currently lack a mechanistic understanding of the benefits hyperthermia provides for avian taxa. Facultative hyperthermia has been proposed to minimize rates of water loss via three distinct mechanisms: M1) by maintaining body temperature (Tb) above environmental temperatures (Te), heat can be lost non‐evaporatively, saving water; M2) by minimizing the thermal gradient when Te > Tb, environmental heat gain and evaporative water loss rates are reduced; and M3) by storing heat via increases in Tb which reduces evaporative heat loss demands and conserves water. Although individuals may benefit from all three mechanisms during heat exposure, the relative importance of each mechanism has not been quantified among species that differ in their body size, heat tolerance and mechanisms of evaporative heat dissipation. We measured resting metabolism, evaporative water loss and real‐time Tb from 33 species of birds representing nine orders ranging in mass from 8 to 300 g and estimated the water savings associated with each proposed mechanism. We show that facultative hyperthermia varies in its benefits among species. Small songbirds with comparatively low evaporative cooling capacities benefit most from (M1), and hyperthermia maintains a thermal gradient that allows non‐evaporative heat losses. Other species benefited most from (M2) minimizing evaporative losses via a reduced thermal gradient for heat gain at high Te. We found that (M3), heat storage, only improved the water economy of the sandgrouse, providing little benefit to other species. We propose that differences in the frequency and magnitude of hyperthermia will drive taxon‐specific differences in temperature sensitivity of tissues and enzymes and that the evolution of thermoregulatory mechanisms of evaporative heat dissipation may contribute to differences in basal metabolic rate among avian orders. Understanding the mechanistic basis of heat tolerance is essential to advance our understanding of the ecology of birds living in hot environments that are warming rapidly, where extreme heat events are already re‐structuring avian communities. A plain language summary is available for this article.
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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 | 0.000 | 0.001 |
| 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".