The allometry of density within the space used by populations of mammalian Carnivora
Bibliographic record
Abstract
The relationship between body mass and population density has been used to develop theory of how energy is used in ecosystems. The usual allometric density slope, 0.75, was reduced to near zero among species of mammalian Carnivora after Smallwood and Schonewald and Blackburn and Gaston adjusted density estimates by the sizes of the corresponding study areas. In this paper, I restricted the allometric analysis to density estimates made at or near the threshold area, which is the species-specific minimum area likely to support a population. I excluded densities estimated from subpopulations and "megapopulations", thereby removing biases of study design that had previously confused the allometry of population density. Density at threshold area declined with increasing body mass. The population's mass density did not relate to threshold area, within which carnivore species averaged 9 kg/km2. The spatial intensity of oxygen consumption did not relate to body mass, but assuming that species with smaller threshold areas occur at more locations than species with larger threshold areas, one must conclude that smaller bodied species use more energy from the environment than do larger bodied species. Furthermore, threshold area and density at threshold area were most responsive to female brain mass, which provides an ecological allometry that links spatial scale, sensory perception, parental care, life-history attributes, basal metabolic rate, and body mass.
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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 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".