Historical contingency, niche conservatism and the tendency for some taxa to be more diverse towards the poles
Bibliographic record
Abstract
Successful explanations for diversity gradients should account for both the generalized tendency towards a higher tropical diversity and its exceptions. Moreover, identifying exceptions to general trends, such as the latitudinal diversity gradient can give insight into the mechanistic explanations responsible for structuring them. The Cenozoic biotic exchange of mammals across the Bering land-bridge provides an illuminating case-study. It allows comparing the diversity of clades that participated in the exchange (colonizers), whose ancestors withstood the Beringian cold temperatures, with that of the clades that did not participate (sedentaries). We find that assemblages of colonizers are more diverse towards higher latitudes, opposing the traditional latitudinal diversity gradient which is followed by sedentaries. Despite the long passage of time since this major dispersal event, the geographic distribution of colonizers is more strongly correlated to the distributions of other colonizers inhabiting a different continent than by the distribution of sedentary species. These results highlight the importance of historical migrations and dispersal in configuring present-day diversity gradients. Importantly, we also suggest that colonizers may be particularly vulnerable to projected climate change because of the predicted decrease in climate space in the extra-tropical realm where they are currently most diverse.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".