BIOGEOGRAPHICAL BASIS OF RECENT PHENOTYPIC DIVERGENCE AMONG BIRDS: A GLOBAL STUDY OF SUBSPECIES RICHNESS
Bibliographic record
Abstract
Theory predicts that biogeographic factors should play a central role in promoting population divergence and speciation. Previous empirical studies into biogeography and diversification have been relatively restricted in terms of the geographical area, phylogenetic scope, and the range of biogeographic factors considered. Here we present a global analysis of allopatric phenotypic divergence (measured as subspecies richness) across more than 9600 bird species. The main aim of this study was to examine the extent to which biogeographical factors can explain patterns of phenotypic divergence. Analysis of the taxonomic distribution of subspecies among species suggests that subspecies formation and extinction have occurred at a considerably faster rate than has species formation. However, the observed distribution departs from the expectation under a random birth-death model of diversification. Across 19 phylogenetic trees, we find no significant linear relationship between species age and subspecies richness, implying that species age is a poor predictor of subspecies richness. Both subspecies richness and subspecies diversification rate are found to exhibit low phylogenetic signal, meaning that closely related species do not tend to possess similar numbers of subspecies. As predicted by theory, high subspecies richness was associated with large breeding range size, island dwelling, inhabitation of montane regions, habitat heterogeneity, and low latitude. Of these factors, breeding range size was the variable that explained the most variation. Unravelling whether species that have invaded previously glacial areas have more or fewer subspecies than expected proves to be complicated due to a covariation between the postglacial colonization, latitude, geographic range size, and subspecies richness. However, the effect of postglacial colonization on subspecies richness appears to be small. Mapping the distribution of species' subspecies richness globally reveals geographical patterns that correspond to many of the predictions of the statistical models, but may also reflect geographical variation in taxonomic practice. Overall, we demonstrate that biogeographic models can explain about 30% of the global variation in subspecies richness in birds.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".