The importance of aquatic vegetation in beaver diets and the seasonal and habitat specificity of aquatic‐terrestrial ecosystem linkages in a subarctic environment
Bibliographic record
Abstract
The extent and ecological significance of trophic linkages across ecosystem boundaries have been the subject of considerable recent research attention. North American beavers Castor canadensis engineer terrestrial influences in aquatic ecosystems by constructing terrestrial food caches near their lodges and aquatic influences in terrestrial ecosystems by building dams and flooding low lying areas. However, it is poorly resolved to what extent beavers rely on aquatic food sources and whether this reliance is greater during winter when ice cover physically confines beavers to aquatic habitats or during summer when warm, ice free water promotes the growth and accessibility of aquatic vegetation. Working in a subarctic region, we surveyed the abundance of aquatic and terrestrial food sources in and around lotic and lentic environments and estimated their contributions to beaver diets during open water and ice covered periods using carbon and nitrogen stable isotope analysis of hair samples. Ponds had four times more aquatic vegetation than streams, but terrestrial habitats around ponds had less than half as much shrub cover as habitats adjacent to streams. Beaver diets in this subarctic environment are estimated to be comprised of 60 to 80% aquatic vegetation, with beavers occupying ponds consuming more aquatic vegetation in winter than beavers occupying streams, which rely more on terrestrial shrubs cached near their lodge. Collectively, these results show how the influence of physical barriers on ecosystem linkages can be modified by habitat‐ and season‐specific abundances of preferred resources and the potential for animals to consume food in ecosystems and seasons different from where and when the food was harvested.
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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 | 0.001 | 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".