Movement ecology of the Qamanirjuaq caribou (Rangifer tarandus groenladicus) herd with focus on their wintering grounds
Bibliographic record
Abstract
With a rapidly changing climate in the arctic there is concern that specialized species, such as caribou (Rangifer tarandus), may not be able to adapt. Currently, the importance of climatic changes for North-American caribou herds is unclear. In an effort to reduce this knowledge gap I have analysed the movement behaviour of caribou in the Qamanirjuaq herd, in the central Canadian Arctic, in relation to data regarding the presence/absence of snow and snow depth. \nUsing collar data (n=69) from female caribou over a 16 year period (1993-2008) and snow data from the climate model described by Liston and Hiemstra (2011), I identified where the caribou spent each winter and how long they remained in an area. First, I investigated the relationship between the presence/absence of snow and seasonal migration movements. Second, I investigated the relationship between snow depth and the start of seasonal activity periods, and more specifically whether patterns in the snow melt could explain why the calving area differed between years. Finally, I investigated the movement behaviour during winter, as determined by First Passage Time values (Fauchald and Tveraa, 2003), in relation to snow depth. \nMy results indicate that the presence/absence of snow as well as snow depth has an impact on the movement rates of caribou cows in the Qamanirjuaq herd. During their fall migration the collared caribou traveled south ahead of accumulating snow. Although there were observational indications that the timing of the annual snow melt might affect their spring migration, my results did not suggest this. Thus it was determined that the presence/absence of snow did not affect the location of calving. It was hypothesized that snow depth influenced the start dates of seasonal activity periods. My results only indicated this to be the case for the Post Rut season, where the start date became later as snow depth increased. Additionally, it was determined that snow depth hampers movement. Increases in snow depth resulted in the caribou cows staying in an area longer.
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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 | 0.000 |
| Science and technology studies | 0.001 | 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".