Winter ecology of the North American Badger (Taxidea Taxus Jeffersonii) in the Cariboo Region of British Columbia
Bibliographic record
Abstract
The purpose of this study was to examine the winter activities and burrow characteristics of North American badgers (Taxidea taxus jeffersonii). At the northern range-limit of these animals (British Columbia, Canada) winter is long and harsh and habitat patchy and atypical; thus, badgers may respond to winter differently here than elsewhere. Using radio-telemetry and remote-cameras, I documented winter activities of 16 badgers (12♀, 4♂) between 2007 and 2011. Similar to limited and anecdotal data collected elsewhere, badgers during winter reduced home range 3.5 (SD = 0.6) km2 and movements 110.5 (SD = 12.2) m /day and\nintensively used burrows 1.3 (SD = 0.8) burrows per winter. Total winter burrow stay averaged 34 days (SD = 25.0) per winter and this use coincided with the onset of torpor (first week in January). Despite intensive burrow-use, badgers emerged frequently (0.30 ± 0.07 events/camera-night) and displayed foraging behaviour (mean foray length: 46.70 ± 65.44 min). Burrow emergence was not related to temperature or snow depth; rather it was best explained by the amount of time elapsed since the badger entered the burrow in mid-winter (Julian Day). Despite these trends, winter activity was quite variable among individual badgers. I also compared the thermal properties of the burrows used by the badgers to those previously used in summer or for rearing offspring (natal). As expected, all burrow temperatures remained relatively mild and constant throughout the winter; however, winter burrows were significantly cooler during this time than burrows that had been used in the previous summer, albeit a small difference (average 1.9o C). Snow depth at winter burrows did not differ from ‘summer burrows’, yet natal burrows had significantly less snow. Analysis revealed that soil fan size, number of entrances, horizontal cover, presence of infrastructure, and a coarse description of habitat differentiated seasonal burrow types relatively well. I suggest that individual variation (strategies) may be a response to local conditions. Relatively small, patchy, atypical habitat, in combination with extremely large summer home ranges may limit the ability of some animals to gain sufficient fat reserves, thus necessitating additional foraging during winter. Moreover, my research suggests that seasonal burrows differ with respect to measurable habitat features that can be used to identify and protect important burrows (natal and winter burrow). This study has been the first dedicated winter ecology study of free ranging North American badgers and has expanded our knowledge about the winter activities, movements and burrow use of this endangered species. As winter is a critical time in the life history of many mammals, an effective management plan will require an understating of species ecology across all seasons.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".