Does density-dependent diversification mirror ecological competitive exclusion?
Bibliographic record
Abstract
Density-dependence is a term used in ecology to describe processes such as birth and death rates that are regulated by the number of individuals in a population. Evolutionary biologists have borrowed the term to describe decreasing rates of species accumulation, suggesting that speciation and extinction rates depend on the total number of species in a clade. If this analogy with ecological density-dependence holds, diversification of clades is restricted because species compete for limited resources. We hypothesize that such competition should not only affect numbers of species, but also prevent species from being phenotypically similar. Here, we present a method to detect whether competitive interactions between species have ordered phenotypic traits on a phylogeny, assuming that competition prevents related species from having identical trait values. We use the method to analyze clades of birds and mammals, with body size as the phenotypic trait. We find no sign that competition has prevented species from having the same body size. Thus, since body size is a key ecological trait and competition does not seem to be responsible for differences in body size between species, we conclude that the diversification slowdown that is prevalent in these clades is unlikely due to the ecological interference implied by the term density dependence.
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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 | 0.005 |
| 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 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".