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Record W2329140671 · doi:10.3354/meps10975

Semi-annual spawning in marine scallops strengthens larval recruitment and connectivity on Georges Bank: a model study

2014· article· en· W2329140671 on OpenAlexafffundabout
KTA Davies, Wendy C. Gentleman, Claudio DiBacco, Catherine L. Johnson

Bibliographic record

VenueMarine Ecology Progress Series · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine and fisheries research
Canadian institutionsFisheries and Oceans CanadaBedford Institute of OceanographyDalhousie University
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsSpawn (biology)Biological dispersalFisheryLarvaBiologyFecundityEcologyOceanographyPopulationDemography

Abstract

fetched live from OpenAlex

MEPS Marine Ecology Progress Series Contact the journal Facebook Twitter RSS Mailing List Subscribe to our mailing list via Mailchimp HomeLatest VolumeAbout the JournalEditorsTheme Sections MEPS 516:209-227 (2014) - DOI: https://doi.org/10.3354/meps10975 Semi-annual spawning in marine scallops strengthens larval recruitment and connectivity on Georges Bank: a model study K. T. A. Davies1,*, W. C. Gentleman1, C. DiBacco2, C. L. Johnson2 1Department of Engineering Mathematics and Internetworking, Dalhousie University, 1340 Barrington St., Halifax, NS B3J 1Y9, Canada 2Fisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, NS B2Y 4A2, Canada *Corresponding author: kim.davies@dal.ca ABSTRACT: Sea scallops Placopecten magellanicus on Georges Bank in the northwest Atlantic exhibit semi-annual spawning phenology, where the autumn spawn is dominant and the spring spawn is smaller and more variable. The spring spawn is thought to contribute little to total annual larval settlement on the Bank because fecundity is lower, larval development is slower and off-Bank transport is higher during spring. We tested the hypothesis that larval settlement during spring is negligible compared to autumn by incorporating spatially and temporally explicit information about spawning and larval mortality into a coupled biological-physical larval tracking model to investigate dispersal and connectivity during each spawning period. To accomplish this, we assimilated field data on adult density-at-size and seasonal fecundity-at-size as initial conditions into the model. We discovered that larval production varied in time (spring production on the Bank is half that of autumn) and space (spawners are concentrated along the advective pathway of the along-Bank gyre). Particle settlement and connectivity was reduced, but not negligible, during spring compared to autumn due to stronger dispersal off-Bank and into uninhabitable areas during spring. When mortality was made constant in space and time, lower larval production combined with slower growth during spring resulted in a minimal contribution of the spring spawn to annual settlement. When mortality was correlated with environmental variation in time and space, the spring spawn contributed up to one-third of the total annual larval settlement between the immediate upstream-downstream connected aggregations. We conclude that the spring spawn can make a substantial contribution to total annual larval production, and that settlement on Georges Bank and should be given more attention in field studies. Larval mortality has a strong influence on settlement during spring and autumn, and future field studies should focus on quantifying space and time variation in mortality in relation to the environment. KEY WORDS: Sea scallop · Placopecten magellanicus · Georges Bank · Connectivity · Larval tracking model Full text in pdf format Supplementary material PreviousNextCite this article as: Davies KTA, Gentleman WC, DiBacco C, Johnson CL (2014) Semi-annual spawning in marine scallops strengthens larval recruitment and connectivity on Georges Bank: a model study. Mar Ecol Prog Ser 516:209-227. https://doi.org/10.3354/meps10975 Export citation RSS - Facebook - Tweet - linkedIn Cited by Published in MEPS Vol. 516. Online publication date: December 03, 2014 Print ISSN: 0171-8630; Online ISSN: 1616-1599 Copyright © 2014 Inter-Research.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.084
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.003
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.274
Teacher spread0.251 · 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 teacher head, not a consensus.

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

Citations13
Published2014
Admission routes3
Has abstractyes

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