Brain Size Predicts the Success of Mammal Species Introduced into Novel Environments
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Large brains, relative to body size, can confer advantages to individuals in the form of behavioral flexibility. Such enhanced behavioral flexibility is predicted to carry fitness benefits to individuals facing novel or altered environmental conditions, a theory known as the brain size-environmental change hypothesis. Here, we provide the first empirical link between brain size and survival in novel environments in mammals, the largest-brained animals on Earth. Using a global database documenting the outcome of more than 400 introduction events, we show that mammal species with larger brains, relative to their body mass, tend to be more successful than species with smaller brains at establishing themselves when introduced to novel environments, when both taxonomic and regional autocorrelations are accounted for. This finding is robust to the effect of other factors known to influence establishment success, including introduction effort and habitat generalism. Our results replicate similar findings in birds, increasing the generality of evidence for the idea that enlarged brains can provide a survival advantage in novel environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it