Do thermoregulatory costs limit altitude distributions of Andean forest birds?
Bibliographic record
Abstract
Summary Along tropical mountains, species often occupy narrow altitude ranges. Numerous biotic and abiotic factors have been proposed as determinants of altitude occupancy. We measured several aspects of thermal physiology of 215 bird species across a 2·6‐km altitude gradient in the Peruvian Andes. We predicted that highland species would show adaptation to the colder high‐altitude climate and that energy costs of thermoregulation might limit upslope dispersal of lowland natives. We found reductions in thermal conductance, body temperature and lower critical temperature in highland birds compared with lowland species. These combine to make highland natives more resistant to heat loss. We did not find convincing evidence that acute thermal limits or energy costs of thermoregulation constrained altitude distributions. Heat‐budget models predicted low‐to‐moderate long‐term costs at native altitudes. Costs increased for lowland natives modelled in the highland climate, but for all but a few species, costs remained within putative expenditure limits. Although we did not test heat tolerances, we measured all species at temperatures similar to the hottest air temperatures at the lowland site. There was no evidence that high lowland temperatures preclude downslope movements of highland birds. While thermal tolerances probably do not directly determine altitude occupancy by most species, the additional energy cost of thermoregulation experienced by lowland species moving upslope may trade off against investment in important life‐history components such as breeding, and thereby affect altitude range limits. A Lay 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 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".