Youth in the study of comparative physiology: insights from demography in the wild
Bibliographic record
Abstract
Of all the properties of individual animals of interest to comparative physiologists, age and stage of development are among the most consequential. In a natural population of any species, the survivorship curve is an important determinant of the relative abundances of ages and stages of development. Demography, thus, has significant implications for the study of comparative physiology. When Edward Deevey published his influential summary of survivorship in animal populations in the wild seven decades ago, he emphasized "serious deficiencies" because survivorship curves for natural populations at the time did not include data on the earliest life stages. Such data have accumulated over intervening years. We survey, for the first time, empirical knowledge of early-age survivorship in populations of most major animal groups in a state of nature. Despite wide variation, it is almost universally true that > 50% of newly born or hatched individuals die before the onset of sexual maturity, even in species commonly assumed to exhibit high early-age survivorship. These demographic facts are important considerations for studies in comparative and environmental physiology whether physiologists (i) aim to elucidate function throughout the life cycle, including both early stages and adults, or (ii) focus on adults (in which case early-age survivorship can potentially affect adult characteristics through selection or epigenesis). We establish that Deevey's Type I curve (which applies to species with relatively limited early mortality) has few or no actual analogs in the real, natural world.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".