Grizzly bear connectivity mapping in the Canada–United States trans‐border region
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Bibliographic record
Abstract
ABSTRACT Fragmentation is a growing threat to wildlife worldwide and managers need solutions to reverse its impacts on species' populations. Populations of grizzly bears ( Ursus arctos ), often considered an umbrella and focal species for large mammal conservation, are fragmented by human settlement and major highways in the trans‐border region of southern British Columbia, northern Montana, Idaho, and northeastern Washington. To improve prospects for bear movement among 5 small fragmented grizzly bear subpopulations, we asked 2 inter‐related questions: Are there preferred linkage habitats for grizzly bears across settled valleys with major highways in the fragmented trans‐border region, and if so, could we predict them using a combination of resource selection functions and human settlement patterns? We estimated a resource selection function (RSF) to identify high quality backcountry core habitat and to predict front‐country linkage areas using global positioning system (GPS) telemetry locations representing an average of 12 relocations per day from 27 grizzly bears (13F, 14M). We used RSF models and data on human presence (building density) to inform cost surfaces for connectivity network analyses identifying linkage areas based on least‐cost path, corridor, and circuit theory methods. We identified 60 trans‐border (Canada–USA) linkage areas across all major highways and settlement zones in the Purcell, Selkirk, and Cabinet Mountains encompassing 24% of total highway length. We tested the correspondence of the core and linkage areas predicted from models with grizzly bear use based on bear GPS telemetry locations and movement data. Highway crossings were relatively rare; however, 88% of 122 crossings from 13 of our bears were within predicted linkage areas (mean = 8.3 crossings/bear, SE = 2.8, range 1–31, 3 bears with 1 crossing) indicating bears use linkage habitat that could be predicted with an RSF. Long‐term persistence of small fragmented grizzly bear populations will require management of connectivity with larger populations. Linkage areas identified here could inform such efforts. © 2015 The Wildlife Society.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 it