Caribou herd dynamics : impacts of climate change on traditional and sport harvesting
Bibliographic record
Abstract
Caribou (Rangifer tarandus) are a key species in Arctic ecosystems including northern Québec and Labrador. They play a central role in the ecology of predators and the structure of Arctic plant communities. In addition, caribou provide socioeconomic and cultural benefits from subsistence and sport hunting \nactivities. Changes in the distribution and abundance of caribou due to global climate change would \nhave serious biological, societal, and economic implications. Direct and indirect consequences of climate \nchange on migratory caribou herds may include alteration in habitat use, migration patterns, foraging \nbehaviour and demography. For example, caribou may experience a further northerly shift in distribution \ndue to several factors including longer ice-free periods, increases in snowfall and extreme weather events, \nalterations in the fire regime, and changes in the distribution of insects and predators. Future research by \nCaribou Ungava, a research group interested in the ecology of migratory caribou in the context of climate \nchange, will address the factors outlining variations in the population dynamics of caribou, implications for survival and reproduction, as well as the response of caribou habitat to different climate change \nscenarios. Management efforts focusing on mitigating greenhouse gases to reduce the potential effects \nof climate change, preserving high quality habitat, limiting anthropogenic landscape disturbances, and \nmanaging hunting in a sustainable manner, could alleviate stressors on migratory caribou of the QuébecLabrador peninsula.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".