Marsh interspersion and muskrat (Ondatra zibethicus) habitat use
Bibliographic record
Abstract
Muskrat (Ondatra zibethicus) populations have been declining in North America for decades. The precise cause of these widespread declines has not yet been identified. Over a similar timeframe, wetlands across large regions of North America have been experiencing an invasion of cattails (Typha). Non-native T. angustifolia readily hybridizes with native T. latifolia to produce T. x glauca, which tends to dominate over parental species and other wetland plants alike. T. x glauca invasions are associated with many negative consequences for wetlands, including a reduction in biodiversity, open water habitat, and interspersion of water and vegetation. Muskrats are strongly tied to wetlands, especially where there is a high degree of interspersion of water and emergent vegetation. Therefore, a widespread reduction in interspersion caused by T. x glauca invasions may be contributing to widespread muskrat population declines. We sought to understand the impact of reduced marsh interspersion on fine-scale muskrat habitat use which will shed more light on broad-scale population trends. We measured intensity of habitat use by muskrats in a large, Typha-dominated marsh in south-central Ontario using remote cameras, stratifying camera placement along a gradient of marsh interspersion. We found no correlation between interspersion and intensity of use, suggesting that factors other than interspersion may drive intensity of use. Our study site, like most marshes in the region, was highly dominated by T. x glauca. Further research is needed to determine the impact of T. x glauca invasions on muskrats, as well as the cause of widespread muskrat declines. Keywords: muskrats, intensity of use, camera traps, invasive species, Typha, wetlands
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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 | 0.000 |
| 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 | 0.000 |
| 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".