Potential movement paths for male grizzly bear (Ursus arctos) dispersal between the Northern Continental Divide and Greater Yellowstone Ecosystems, 2000-2015
Bibliographic record
Abstract
For several decades, grizzly bear (Ursus arctos) populations in the Greater Yellowstone Ecosystem (GYE) and the Northern Continental Divide Ecosystem (NCDE) have increased in numbers and range extent. Whereas the NCDE population is contiguous with grizzly bear populations in the Canadian Rocky Mountains, genetic evidence suggests the GYE population remains isolated. Recent analyses indicate the effective population size of GYE grizzly bears has increased and is approaching levels needed for long-term viability. With only ~110 km distance separating current estimates of occupied range for these populations, the potential for immigration into the GYE from an NCDE migrant, or vice versa, is likely greater now than it has been for many decades. Therefore, we sought to delineate potential movement paths providing connectivity for male-mediated gene flow between the two populations. Using GPS locations for 124 male grizzly bears monitored during 199 bear-years, and covariates describing ecological, physical, and anthropogenic features of the landscape, we first developed step-selection functions to generate conductance layers of bear movements for each ecosystem. We then used randomized shortest path (RSP) algorithms to estimate the average number of net passages for all grid cells in the study region, when moving from an origin to a destination node. Given the conductance layer, movement paths follow certain grid cell sequences more than others and resulting RSP values thus provide a measure of movement potential. Repeating this process for 100 pairs of random origin and destination nodes, we identified movement paths for 3 levels of random deviation (Θ) from the least-cost path. We observed broad-scale concordance between model predictions for paths originating in the NCDE and those originating in the GYE for all 3 levels of movement exploration. Our model predictions indicate that grizzly bear movement between the ecosystems could involve a variety of routes, and verified observations of grizzly bears outside occupied range support this finding.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.004 |
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; both teacher heads agree on what is shown here.
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".