Population demography maintains biogeographic boundaries
Bibliographic record
Abstract
Abstract Global biodiversity is organized into biogeographic regions that comprise distinct biotas. The contemporary factors maintaining differences in species composition between biogeographic regions are poorly understood. Given the evidence that populations with sufficient genetic variation can adapt to fill new habitats, it is surprising that we do not see more homogenization of species assemblages among regions. Theory suggests that the expansion of populations across biogeographic transition zones could be limited by environmental gradients that affect population demography in ways that could limit adaptive capacity, but this has not been empirically explored. Using three independently curated data sets describing continental patterns of mammalian demography and population genetics, we show that populations closer to biogeographic transition zones have lower effective population sizes and genetic diversity, and are more genetically differentiated. These patterns are consistent with reduced adaptive capacity near biogeographic transition zones. The consistency of these patterns across mammalian species suggests they are stable, predictable, and generalizable in their contribution to long-term limits on expansion and homogenization of biodiversity across biogeographic transition zones. Understanding the contemporary processes acting on populations that maintain differences in the composition of regional biotas is crucial for our basic understanding of the current and future organization of global biodiversity. The importance of contemporary, population-level processes on the maintenance of global biogeographic regions suggests that biogeographic boundaries are susceptible to environmental perturbation associated with human-caused global change.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".