Chipping in: functional morphology of the American beaver under range expansion
Bibliographic record
Abstract
Abstract Climate warming combined with intensive human activities are modifying ecosystems globally, and the Arctic biota is shifting substantially faster than the global average, allowing many new species to expand their range poleward. One such species, is the American beaver ( Castor canadensis ), a highly specialized rodent capable of greatly modifying ecosystems by altering forest composition through selective foraging and by flooding the landscape through dam and channel building. As rodent cranial morphology is highly related to its functional requirements for foraging and feeding, the beaver provides an opportunity to evaluate the phenotypic response of species to changing environmental conditions. Here, we test the hypothesis that beaver skull morphology is optimized for its local environmental and habitat conditions across Canadian ecosystems. We found that temperature, precipitations, biomass, and local average tree hardness significantly affect the morphology of key masticatory functional traits of the skull, but not its size. Our results suggest that the beaver's phenotype is locally adapted to environmental conditions as a result of its selective foraging behavior. This work provides insight into the adaptive potential of newly established beaver populations in the sub‐Arctic to inform management strategies for this keystone species. More generally, our work emphasizes the need to consider traits other than body size in research seeking to better understand the response of species to current global change.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".