Developmental and reproductive physiology of small mammals at high altitude: challenges and evolutionary innovations
Bibliographic record
Abstract
ABSTRACT High-altitude environments, characterized by low oxygen levels and low ambient temperatures, have been repeatedly colonized by small altricial mammals. These species inhabit mountainous regions year-round, enduring chronic cold and hypoxia. The adaptations that allow small mammals to thrive at altitude have been well studied in non-reproducing adults; however, our knowledge of adaptations specific to earlier life stages and reproductive females is extremely limited. In lowland natives, chronic hypoxia during gestation affects maternal physiology and placental function, ultimately limiting fetal growth. During post-natal development, hypoxia and cold further limit growth both directly by acting on neonatal physiology and indirectly via impacts on maternal milk production and care. Although lowland natives can survive brief sojourns to even extreme high altitude as adults, reproductive success in these environments is very low, and lowland young rarely survive to sexual maturity in chronic cold and hypoxia. Here, we review the limits to maternal and offspring physiology – both pre-natal and post-natal – that highland-adapted species have overcome, with a focus on recent studies on high-altitude populations of the North American deer mouse (Peromyscus maniculatus). We conclude that a combination of maternal and developmental adaptations were likely to have been critical steps in the evolutionary history of high-altitude native mammals.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".