Exploring the phylogenetic history of mammal species richness
Bibliographic record
Abstract
ABSTRACT Aim At broad geographical scales, species richness is a product of three basic processes: speciation, extinction and migration. However, determining which of these processes predominates is a major challenge. Whilst palaeontological studies can provide information on speciation and extinction rates, data are frequently lacking. Here we use a recent dated phylogenetic tree of mammals to explore the relative importance of these three processes in structuring present‐day richness gradients. Location The global terrestrial biosphere. Methods We combine macroecological data with phylogenetic methods more typically used in community ecology to describe the phylogenetic history of regional faunas. Using simulations, we explore two simple phylogenetic metrics, the mean and variance in the pairwise distances between taxa, and describe their relationship to phylogenetic tree topology. We then use these two metrics to characterize the evolutionary relationships among mammal species assemblages across the terrestrial biome. Results We show that the mean and variance in the pairwise distances describe phylogenetic tree topology well, but are less sensitive to phylogenetic uncertainty than more direct measures of tree shape. We find the phylogeny for South American mammals is imbalanced and ‘stemmy’ (long branches towards the root), consistent with recent diversification within evolutionarily disparate lineages. In contrast, the phylogeny for African mammals is balanced and ‘tippy’ (long branches towards the tips), more consistent with the slow accumulation of diversity over long times, reflecting the Old World origin of many mammal clades. Main conclusions We show that phylogeny can accurately capture biogeographical processes operating at broad spatial scales and over long time periods. Our results support inferences from the fossil record – that the New World tropics are a diversity cradle whereas the Old World tropics are a museum of old diversity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".