Different evolutionary histories underlie congruent species richness gradients of birds and mammals
Bibliographic record
Abstract
Abstract Aim The global species richness patterns of birds and mammals are strongly congruent. This could reflect similar evolutionary responses to the Earth’s history, shared responses to current climatic conditions, or both. We compare the geographical and phylogenetic structures of both richness gradients to evaluate these possibilities. Location Global. Methods Gridded bird and mammal distribution databases were used to compare their species richness gradients with the current environment. Phylogenetic trees (resolved to family for birds and to species for mammals) were used to examine underlying phylogenetic structures. Our first prediction is that both groups have responded to the same climatic gradients. Our phylogenetic predictions include: (1) that both groups have similar geographical patterns of mean root distance, a measure of the level of the evolutionary development of faunas, and, more directly, (2) that richness patterns of basal and derived clades will differ, with richness peaking in the tropics for basal clades and in the extra‐tropics for derived clades, and that this difference will hold for both birds and mammals. We also explore whether alternative taxonomic treatments for mammals can generate patterns matching those of birds. Results Both richness gradients are associated with the same current environmental gradients. In contrast, neither of our evolutionary predictions is met: the gradients have different phylogenetic structures, and the richness of birds in the lowland tropics is dominated by many basal species from many basal groups, whereas mammal richness is attributable to many species from both few basal groups and many derived groups. Phylogenetic incongruence is robust to taxonomic delineations for mammals. Main conclusions Contemporary climate can force multiple groups into similar diversity patterns even when evolutionary trajectories differ. Thus, as widely appreciated, our understanding of biodiversity must consider responses to both past and present climates, and our results are consistent with predictions that future climate change will cause major, correlated changes in patterns of diversity across multiple groups irrespective of their evolutionary histories.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".