CLIMATE CHANGE AND SIZE EVOLUTION IN AN ISLAND RODENT SPECIES: NEW PERSPECTIVES ON THE ISLAND RULE
Bibliographic record
Abstract
As stated by the island rule, small mammals evolve toward gigantism on islands. In addition they are known to evolve faster than their mainland counterparts. Body size in island mammals may also be influenced by geographical climatic gradients or climatic change through time. We tested the relative effects of climate change and isolation on the size of the Japanese rodent Apodemus speciosus and calculated evolutionary rates of body size change since the last glacial maximum (LGM). Currently A. speciosus populations conform both to Bergmann's rule, with an increase in body size with latitude, and to the island rule, with larger body sizes on small islands. We also found that fossil representatives of A. speciosus are larger than their extant relatives. Our estimated evolutionary rates since the LGM show that body size evolution on the smaller islands has been less than half as rapid as on Honshu, the mainland-type large island of Japan. We conclude that island populations exhibit larger body sizes today not because they have evolved toward gigantism, but because their evolution toward a smaller size, due to climate warming since the LGM, has been decelerated by the island effect. These combined results suggest that evolution in Quaternary island small mammals may not have been as fast as expected by the island effect because of the counteracting effect of climate change during this period.
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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 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".