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Record W3160340513 · doi:10.3354/meps13741

Conservation implications of demographic changes in the horse mussel Modiolus modiolus population of the inner Bay of Fundy

2021· article· en· W3160340513 on OpenAlexaffabout
JA Sameoto, Kelly E. Hall, SE Gass, David Keith, Sonja Kirchhoff, Craig J. Brown

Bibliographic record

VenueMarine Ecology Progress Series · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsNova Scotia Community CollegeDalhousie UniversityBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsPopulationBayFishingModiolus (cochlea)FisheryBiologyEcologyGeographyDemography

Abstract

fetched live from OpenAlex

Horse musselsModiolus modioluscan occur in dense aggregations and form areas of ecological and biological significance. In the Bay of Fundy, Canada, aggregations of horse mussels are associated with flow parallel bedforms, and this area is under consideration for designation as a sensitive benthic area which would provide protective measures. Basic demographic information is required to inform the development of effective conservation and management strategies and although general life-history characteristics ofM. modiolusare known, detailed quantitative demographic information on this population is limited. The objective of this study was to characterize the population structure of horse mussels in the Bay of Fundy and assess change in key demographic characteristics since the last study in this area in 1997/1998. There have been significant changes in the population since 1998: the 2017 population contains larger, older, mature individuals, with significantly more females; 35% of the current population is over 20 yr of age. Direct evidence that this population has been impacted by bottom-contact fishing gear was also observed. Consistent withM. modioluspopulations worldwide, this population demonstrates life-history traits (e.g. slow growth rates, late age of maturity, long lifespan) that make it sensitive and susceptible to disturbance. Coupled with the knowledge that this population overlaps with significant fishing activity, this study supports the assumption that this population is vulnerable to bottom-contact fishing and that recovery from adverse impacts would be slow and uncertain.

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 score0.926
Threshold uncertainty score0.148

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.240
Teacher spread0.227 · 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

Citations4
Published2021
Admission routes2
Has abstractyes

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