The role of environmental variables and sympatric meso-carnivores on the detection and occupancy of American mink during winter
Bibliographic record
Abstract
The spatial distributions of animals generally are affected by the availability of food, competition, predators, mates, and the need to communicate with conspecifics. An understanding of a given species' spatial distribution is essential when considering the ecological requirements of populations as well as the impacts of anthropogenic activities and environmental change. The American mink ( Neovison vison ) is a cryptic, semi-aquatic carnivore that ranges over a large portion of North America yet the ecological role of the species is not well understood. We sought to investigate the linkages between habitat and species co-occurrence on the occupancy patterns of mink within riparian habitats during winter. We monitored mink using remote cameras (n=37) which were deployed in riparian habitat along streams including lakeshore/stream confluences. We found that fish-bearing streams positively affected mink occupancy, while the amount of older (>40 years) coniferous forests had a negative relationship with mink occupancy. We postulate that while mink seem to occur at high densities in altered ecosystems and in areas where they are invasive, in their native range these animals may be limited by environmental and competitive pressures in the system. Future work should explore the interactions between carnivore species in addition to habitat selection in order to develop more robust monitoring and management practices.
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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 | 0.001 | 0.001 |
| 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".