Historical Landscape Use of Migratory Caribou: New Insights From Old Antlers
Bibliographic record
Abstract
Accumulations of shed caribou antlers (Rangifer tarandus) are valuable resources for expanding the temporal scope with which we evaluate seasonal landscape use of herds. Female caribou shed their antlers within days of giving birth, thus marking calving ground locations. Antler geochemistry (87Sr/86Sr) reflects the isotopic signature of regions used during antler growth, thereby providing data on a second component of seasonal landscape use. Here, we evaluate shed caribou antlers from the Coastal Plain of the Arctic National Wildlife Refuge, Alaska. The Central and Eastern regions of the Coastal Plain are calving grounds for the Porcupine Caribou Herd, while the Western Coastal Plain supports calving by the Central Arctic Herd. We found that antler 87Sr/86Sr from the Central and Eastern Coastal Plain were isotopically indistinguishable, while antler 87Sr/86Sr from the Western Coastal Plain was significantly smaller. For each region, we compared isotopic data for “recent” antlers, which overlap the bulk of standardized state and federal caribou monitoring (early 1980s and younger), with “historical” antlers shed in years predating these records (from the 1300s to the 1970s). For Porcupine Herd females calving in the Arctic Refuge, comparisons of antler 87Sr/86Sr through time indicate that summer ranges have been consistent since at least the 1960s. However, changes between historical and recent antler 87Sr/86Sr for the Central Arctic Herd indicate a shift in summer landscape use after the late 1970s. The timing of this shift is coincident with multiple factors including increased infrastructural development in their range related to hydrocarbon extraction. Accumulations of shed caribou antlers and their isotope geochemistry extend modern datasets by decades to centuries and provide valuable baseline data for evaluating potential anthropogenic and other influences on caribou migration and landscape use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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 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".