New migration and distribution patterns of Atlantic walruses (Odobenus rosmarus rosmarus) around Nunavik (Québec, Canada) identified using Inuit Knowledge
Bibliographic record
Abstract
Abstract Environmental changes are affecting the Arctic at an unprecedented rate, but limited scientific knowledge exists on their impacts on species such as walruses (Odobenus rosmarus). Inuit Traditional and Local Ecological Knowledge (Inuit TEK/LEK) held by Inuit walrus harvesters could shed light on walrus ecology and related environmental changes. Our main objective was to study spatial and temporal changes in Atlantic walrus (Odobenus rosmarus rosmarus) distribution in Nunavik (northern Québec, Canada) using Inuit TEK/LEK. To do so, we documented the knowledge and observations of 33 local hunters and Elders as part of a larger project on Atlantic walruses in Nunavik. We first gathered information on changes in Inuit land use patterns and harvesting practices through time and space, which was a crucial step to avoid potential biases in interpreting local observations on walrus distribution. We found that walrus hunters are now covering smaller hunting areas over shorter time periods, reducing in space and time their observations of Atlantic walruses around Nunavik. While clearly taking these limitations into account, we learned from interviews that some areas abandoned by Atlantic walruses in the past were now being re-occupied. Importantly, Atlantic walruses, which migrate following the melting ice, are now traveling along the eastern coast of Nunavik one month earlier, suggesting that Atlantic walrus migration has changed due to variations in sea-ice coverage around Nunavik. Our study not only highlighted important changes in Atlantic walrus distribution and migration in Nunavik, but also sheds light on the importance of documenting temporal and spatial changes in Inuit land use patterns and harvesting practices to understand the ecology of Arctic species using Inuit Knowledge.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".