Effect of agriculture and presence of American beaver Castor canadensis on winter biodiversity of mammals
Bibliographic record
Abstract
Abstract Several metrics of biodiversity are used to assess the variability and abundance of multiple species across various ecological levels. Previous research suggests that biodiversity in agricultural areas is diminished due to habitat fragmentation and alterations to natural vegetation. Contrary to the effects of agriculture, the American beaver Castor canadensis has been shown to have a significant contribution to increased biodiversity. Our study focuses on the biodiversity of mammals in wetland areas of the southern mixed‐wood boreal forest natural region of east‐central Alberta, Canada. We compared various measures of biodiversity levels of mammals in the winter months between wetlands on agricultural land and wetlands in Miquelon Lake Provincial Park (MLPP). Similarly, we compared wetlands with active and inactive beaver colonies to determine differences in winter biodiversity of mammals and the amount of water coverage within a pond. We collected data using winter tracking surveys and analyzed the data using geographic information systems (GIS) techniques. We found that winter biodiversity of mammals was higher at the sites within the protected area (MLPP) than at those on agricultural lands. However, our data also suggest that forested areas surrounding agricultural wetlands may play an important role in maintaining biodiversity within agricultural areas. The presence of beavers alone was not a significant factor in relation to winter biodiversity, but the presence of the species was important for maintaining water levels of agricultural wetlands, which in turn plays a role in resource heterogeneity.
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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".