Climate‐Driven Body Size Changes in Birds and Mammals Reveal Environmental Tolerance Limits
Bibliographic record
Abstract
Climate change contributes to widespread shifts in body size across taxa which can impact population and community dynamics. However, the reasons for variability in the direction and intensity of responses remain uncertain. Smaller body size improves thermoregulatory efficiency but can increase dehydration risk. Changes in species' body size is likely to balance the tradeoffs of thermoregulation and osmotic balance when responding to shifts in thermal and aridity regimes associated with climate change. Using 119,183 bird and 183,087 mammal body mass, and 15,562 bird and 239,600 mammal body length records, along with species' thermal and aridity limits based on their range geographies, we tested for associations between body size and climatic conditions. We also assessed the impacts of human land use extent and interactions with species thermal environments. We found that smaller body mass measurements across taxa are associated with conditions closer to species' upper thermal (hot) and lower aridity (dry) tolerance limits. Agricultural land use extent was found to be positively associated with body mass measurements for both bird and mammal species. Shorter body lengths were observed for both birds and mammals the closer species were to their upper thermal limits. Further we found that thermal and aridity conditions interacted resulting in stronger negative associations between body mass and hotter temperatures the closer species were to their dry tolerance limits. Our results are consistent with predictions that differences in body size within bird and mammal species are driven by thermoregulatory pressures associated with thermal and aridity regimes. While species' range geographies and phenology are widely known to respond to anthropogenic climate change, the shifts in species' body sizes detected here are a third biotic response that exerts similarly profound ecological, evolutionary, and conservation effects.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".