Observed and predicted effects of climate change on Arctic caribou and reindeer
Bibliographic record
Abstract
The ability of many species to adapt to the shifting environmental conditions associated with climate change will be a key determinant of their persistence in the coming decades. This is a challenge already faced by species in the Arctic, where rapid environmental change is well underway. Caribou and reindeer (Rangifer tarandus) play a key role in Arctic ecosystems and provide irreplaceable socioeconomic value to many northern peoples. Recent decades have seen declines in many Rangifer populations, and there is strong concern that climate change is threatening the viability of this iconic Arctic species. We examine the literature to provide a thorough and full consideration of the many environmental factors that limit caribou and reindeer populations, and how these might be affected by a warming climate. Our review suggests that the response of Rangifer populations to climate change is, and will continue to be, varied in large part to their broad circumpolar distribution. While caribou and reindeer could have some resilience to climate change, current global trends in abundance undermine all but the most precautionary outlooks. Ultimately, the conservation of Rangifer populations will require careful management that considers the local and regional manifestations of climate change.
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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 | 0.002 | 0.004 |
| 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) | 0.002 | 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".