Limited heat tolerance in an Arctic passerine: Thermoregulatory implications for cold‐specialized birds in a rapidly warming world
Bibliographic record
Abstract
Abstract Arctic animals inhabit some of the coldest environments on the planet and have evolved physiological mechanisms for minimizing heat loss under extreme cold. However, the Arctic is warming faster than the global average and how well Arctic animals tolerate even moderately high air temperatures ( T a ) is unknown. Using flow‐through respirometry, we investigated the heat tolerance and evaporative cooling capacity of snow buntings ( Plectrophenax nivalis ; ≈31 g, N = 42), a cold specialist, Arctic songbird. We exposed buntings to increasing T a and measured body temperature ( T b ), resting metabolic rate (RMR), rates of evaporative water loss (EWL), and evaporative cooling efficiency (the ratio of evaporative heat loss to metabolic heat production). Buntings had an average (± SD ) T b of 41.3 ± 0.2°C at thermoneutral T a and increased T b to a maximum of 43.5 ± 0.3°C. Buntings started panting at T a of 33.2 ± 1.7°C, with rapid increases in EWL starting at T a = 34.6°C, meaning they experienced heat stress when air temperatures were well below their body temperature. Maximum rates of EWL were only 2.9× baseline rates at thermoneutral T a , a markedly lower increase than seen in more heat‐tolerant arid‐zone species (e.g., ≥4.7× baseline rates). Heat‐stressed buntings also had low evaporative cooling efficiencies, with 95% of individuals unable to evaporatively dissipate an amount of heat equivalent to their own metabolic heat production. Our results suggest that buntings’ well‐developed cold tolerance may come at the cost of reduced heat tolerance. As the Arctic warms, and this and other species experience increased periods of heat stress, a limited capacity for evaporative cooling may force birds to increasingly rely on behavioral thermoregulation, such as minimizing activity, at the expense of diminished performance or reproductive investment.
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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) | 0.000 | 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) | 0.000 | 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 teacher head, 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".