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Record W4410906334 · doi:10.22621/cfn.v138i3.3391

The history of commercial freshwater mussel harvest in southern Ontario: a short-lived fishery with long-lasting consequences

2025· article· en· W4410906334 on OpenAlexafffundvenueabout
Todd J. Morris

Bibliographic record

VenueThe Canadian Field-Naturalist · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsFisheries and Oceans Canada
FundersFisheries and Oceans Canada
KeywordsFisheryMusselEnvironmental scienceOceanographyGeographyBiologyGeology

Abstract

fetched live from OpenAlex

Freshwater mussels (Bivalvia: Unionidae) have long been an important aquatic resource for humans, and North America’sIndigenous nations have harvested them for over 10 000 years. European exploitation began in the latter half of the 19th century, initially focussing on the collection of pearls and later shifting to the manufacture of buttons at the onset of the 20th century. By 1911, Canadian pearl button factories operated in Windsor, Berlin (now Kitchener), and Trenton, Ontario, and, by 1921, Ontario shell was being exported to factories in the United States. The Canadian harvest did not last long and ended by the mid-1940s as resources dwindled because of overexploitation, pollution, and industrial shifts to other raw materials for buttons (e.g., plastics). Annual river-specific harvest ranged from ~ 66 to 110 tonnes with a maximum of 291 tonnes (~1.1–4.4 million animals) collected at Dunnville on the lower Grand River in 1915. Although detailed collection information is lacking, species such as Mucket (Actinonaias ligamentina), Threeridge (Amblema plicata), and Round Pigtoe (Pleurobema sintoxia, now listed federally as Endangered) were targetted, while Purple Wartyback (Cyclonaias tuberculata, also now Endangered) was discarded (i.e., killed). Commercial harvests typically targetted adults, because they provided the desired quantity and type of material, resulting in death. Recent studies have shown that this type of directed mortality can have the greatest impact on the long-term persistence of these populations and, although the specific impacts of the historical harvest cannot be determined, it is likely that these harvests contributed to the current state of imperilment of this fauna.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0060.003
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.021
GPT teacher head0.216
Teacher spread0.196 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2025
Admission routes4
Has abstractyes

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