Habitat selection and occupancy patterns of American mink (Neovison Vison) during winter in north-central British Columbia, Canada
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. Behavioural, physiological and morphological adaptations to these selecting agents have allowed members of the Order Carnivora (C. Mammalia) to occupy a wide range of environments, but at the same time, each combination of characteristics places constraints on the habitat a particular species is able to occupy. For example, many members of the Family Mustelidae are vulnerable to extreme temperatures as a result of their tubular body shape. The American mink (Neovison vison) likely faces these temperature constraints, being a smaller-bodied mustelid that ranges over a large portion of North America. Despite its large range, and its historical importance to the fur industry, the species has remained largely understudied in its native habitat. During 2011-2012, I conducted winter telemetry on 7 adult mink and used resource selection function models to assess habitat selection patterns while considering spatial scale and gender. I found that at a larger scale, the animals’ use of habitat was strongly linked to riparian features, whereas this effect was less noticeable at a fine scale. The larger males selected more lakeshore habitat, whereas the smaller females generally were near streams in more forested areas. I suggest this spatial separation could be linked to an inability of females to forage aquatically in winter as a result of their smaller body size. This may make females more sensitive to competition from other forest carnivores as well as impacts from resource development activities. During winter 2013, I surveyed for mink using remote cameras (n=37) deployed in riparian habitat, including lakeshore/stream confluences. I found that fish-bearing streams positively affected mink occupancy, while the amount of older (>40yrs) coniferous forests had a negative relationship with mink occupancy. I 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 are limited by environmental constraints (low winter temperatures) and competitive pressures in the system. Future work on mink and other carnivores should explore interspecific interactions 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 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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".