Climate warming impacts tuttuk (caribou) forage availability in Tongait (Torngat) Mountains, Labrador
Bibliographic record
Abstract
Tuttuk (caribou ( Rangifer tarandus)) populations are in decline across Canada, making them a major conservation concern for Inuit of Nunatsiavut (Northern Labrador) and Nunavik (Northern Quebec). This study investigates changes to caribou forage over 14 years at two tundra sites in northern Nunatsiavut, Labrador. We ask: (1) How much of the total vegetation is suitable caribou forage and how has this changed with time and experimental warming; and (2) which forage species are most affected by recent climate change? At control and warming plots, we identified selected, edible, and avoided caribou forage based on published literature, and modeled observed changes in forage availability. We found that the relative frequency of selected winter forage was lower than summer forage at both sites. Caribou appear to be more forage limited in the winter than summer, and birch ( Betula spp.), and ericaceous shrub species ( Vaccinium spp.), increased over time. Our research provides valuable insight into recent changes in caribou forage availability and develops a novel methodology that can be applied across other caribou ranges. This knowledge will inform conservation and management measures by helping identify possible forage limitations and can contribute to recovery targets across Nunatsiavut and ultimately the social-ecological resilience of northern communities.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".