A catch history for Atlantic walruses (<i>Odobenus rosmarus rosmarus</i>) in the eastern Canadian Arctic
Bibliographic record
Abstract
Knowledge of changes in abundance of Atlantic walruses (Odobenus rosmarus rosmarus) in Canada is important for assessing their current population status. This catch history collates available data and assesses their value for modelling historical populations to inform population recovery and management. Pre-historical (archaeological), historical (e.g., Hudson Bay Company journals) and modern catch records are reviewed over time by data source (whaler, land-based commercial, subsistence etc.) and biological population or management stock.Direct counts of walruses landed as well as estimates based on hunt products (e.g., hides, ivory) or descriptors (e.g., Peterhead boatloads) support a minimum landed catch of over 41,300 walruses in the eastern Canadian Arctic between 1820 and 2010. Little is known of Inuit catches prior to 1928, despite the importance of walruses to many Inuit groups for subsistence. Commercial hunting from the late 1500s to late 1700s extirpated the Atlantic walrus from Quebec and the Atlantic Provinces, but there was no commercial hunt for the species in the Canadian Arctic until ca. 1885. As the availability of bowhead whale (Balaena mysticetus) declined, whalers increasingly turned to hunting other species, including walruses. Modest numbers (max. 278/yr) were taken from the High Arctic population in the mid-1880s and large catches (up to 1400/yr) were often taken from the Central Arctic population from 1899 -1911, while the Foxe Basin stock (Central Arctic population) and Low Arctic population were largely ignored by commercial hunters. Land-based traders (ca. 1895-1928) continued the commercial hunt until regulatory changes in 1928 reserved walruses for Inuit use. Since 1950, reported walrus catches have been declining despite a steady increase in the Inuit population. Effort data are needed to assess whether lower catches stem from declining hunter effort or decreased walrus abundance. The recent take of walruses by sport hunting has been small (n=141, 1995-2010), sporadic and local.These landed catch estimates indicate the minimum numbers of walruses removed but do not account for under-reporting or lost animals that were killed but were not secured. Unreported and lost animals may represent a significant fraction of the total removals and must be considered in any modelling exercise. The sources, quality and completeness of the catch data vary widely over time and space and between the different hunt types. This variability confounds interpretation and contributes to the uncertainty that needs to be incorporated into any modelling. The data on Inuit subsistence catches before ca. 1928 are particularly fragmentary and uncertain.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".