Evidence of different climatic adaptation strategies in humans and non-human primates
Bibliographic record
Abstract
To understand human evolution it is critical to clarify which adaptations enabled our colonisation of novel ecological niches. For any species climate is a fundamental source of environmental stress during range expansion. Mammalian climatic adaptations include changes in size and shape reflected in skeletal dimensions and humans fit general primate ecogeographic patterns. It remains unclear however, whether there are also comparable amounts of adaptation in humans, which has implications for understanding the relative importance of biological/behavioural mechanisms in human evolution. We compare cranial variation between prehistoric human populations from throughout Japan and ecologically comparable groups of macaques. We compare amounts of intraspecific variation and covariation between cranial shape and ecological variables. Given equal rates and sufficient time for adaptation for both groups, human conservation of non-human primate adaptation should result in comparable variation and patterns of covariation in both species. In fact, we find similar amounts of intraspecific variation in both species, but no covariation between shape and climate in humans, contrasting with strong covariation in macaques. The lack of covariation in humans may suggest a disconnect in climatic adaptation strategies from other primates. We suggest this is due to the importance of human behavioural adaptations, which act as a buffer from climatic stress and were likely key to our evolutionary success.
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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 | 0.001 |
| 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) | 0.003 | 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".