SPATIAL AND TEMPORAL TRENDS IN RANGE-USE BY THE BATHURST CARIBOU DURING A POPULATION DECLINE, 1997-2019
Bibliographic record
Abstract
The Bathurst barren-ground caribou herd of Northwest Territories and Nunavut declined by 98% between 1986 and 2019; from an estimated population of 470,000 animals to just 8,200. Although caribou herds are known to fluctuate greatly between high and low populations, the recent population low has raised fears that this herd may go extinct. There are many factors which influence herd health, and disentangling how each contributes to decline is difficult. Our research goal was to examine broad scale spatial-temporal trends in range-use of the Bathurst herd from 1997-2019, in order to better speculate on how these caribou may be responding to external factors. We conducted a Residence Time movement analysis on animal collar data to determine specific timing of seasonal range-use. We used this timing information to create Brownian Bridge maps that capture seasonal ranges unique to herd behavior each year, as well as mapping their annual ranges. We applied linear regression models to our annual and seasonal range maps to explore temporal trends of habitat-use across space. We found significant decreases in the size of annual (90%) and seasonal (35 - 91%) ranges that mirrored the herd’s population decline. The duration of the herd’s spring migration significantly decreased, with caribou reaching their calving ground eight days earlier over the study period; potentially in response to an earlier onset of vegetation green-up. The time spent on the post-calving range increased over the monitoring period by thirteen days, suggesting that caribou have become more active; potentially as a mechanism to deal with insect harassment. Geographical analyses of the calving range showed that, unlike other ranges, there was little change in size and range-use. The consistent nature of this range may indicate that resources there are disproportionately important to caribou, relative to the other ranges. These temporal and geographic changes are not consistent with changes observed in other declining herds; a discrepancy that may indicate the Bathurst caribou are responding specifically to unique regional changes, such as timing in snowmelt, vegetative phenology, changes in insect activity, and industrial activity.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".