Giant mice on small islands: mechanisms of gigantism in Peromyscus maniculatus Gulf Island populations
Bibliographic record
Abstract
Island rodent populations frequently exhibit island gigantism, presenting with larger body sizes in comparison to mainland counterparts. Proposed mechanisms to explain gigantism include benign island habitats and lack of mainland predators and competitors. However, island populations tend to be denser than mainland populations, increasing conspecific competition. With extrinsic sources of pressure largely missing from island habitats, conspecific competition may become a selecting force for larger body sizes in island populations. Here we examine presence of gigantism in North American deermouse (Peromyscus maniculatus) populations throughout the Gulf Islands of British Columbia, Canada and assess if population density is an underlying mechanism. Deermouse populations were live trapped on nine of the Gulf Islands as well as on the lower mainland of British Columbia to assess gigantism. We found that deermouse populations on islands have larger body mass than populations inhabiting the mainland. However, no significant relationship was found between population density and body mass. Due to the large variation in ecological composition of islands selected for study, follow-up analyses were conducted on other possible mechanisms. Study sites with reports of higher predator species richness were found to have smaller mice in comparison to islands with few to no predator species reported. Gigantism continues to be a complex phenomenon likely driven by several mechanisms. Furthermore, these mechanisms may vary across metapopulations, requiring further study.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".