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Record W2083884740 · doi:10.1139/f2011-028

<i>Mysis diluviana</i>population and cohort dynamics in Lake Ontario before and after the establishment of<i>Dreissena</i> spp.,<i>Cercopagis pengoi</i>, and<i>Bythotrephes longimanus</i>

2011· article· en· W2083884740 on OpenAlexaffvenueabout
Ora E. Johannsson, Kelly L. Bowen, Kristen T. Holeck, Maureen G. Walsh

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsFisheries and Oceans Canada
Fundersnot available
KeywordsDreissenaBiologyEcologyBiomass (ecology)ZooplanktonPopulationHypolimnionFisheryAbundance (ecology)Water columnPredationGroundfishAlewifeFishingFisheries managementEutrophicationBivalviaDemography

Abstract

fetched live from OpenAlex

We investigated population responses of Mysis to ecosystem changes induced by invasion of dreissenids and predatory cladocerans, Cercopagis and Bythotrephes . Lake productivity declined as dreissenids invaded the offshore region. Whole-lake mysid biomass was compared before (early 1990s) and after (2002–2007) the invasion period; it declined 40%–45%. Abundance of young mysids and presence of a summer cohort increased with summer, epilmnetic, nighttime zooplankton biomass (i.e., food biomass index). Cercopagis + Bythotrephes biomass was negatively correlated with this index, implicating them in the mysid decline. Eggs per gravid female increased with autumn, total-water-column zooplankton biomass, reflecting the greater use of hypolimnetic waters by adults. Reproductive success was below replacement during the period 2002–2005. First-year mysid growth rate was maintained while population abundance declined, suggesting selection for individuals that feed effectively at low food concentrations. Mortality rates in the first and second years were dependent on cohort density, indicating that competition for food limited abundance in the first 2 years. Fish predation indices (smelt and alewife combined) were correlated positively with mortality rates and negatively with abundance in the third year. Thus, mysids cannot support as many fish in invaded compared with non-invaded lakes. They may also not be a stable food resource; unusual cohort losses occurred in some years.

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)0.000
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 score0.356
Threshold uncertainty score0.717

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.010
GPT teacher head0.183
Teacher spread0.173 · 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

Citations26
Published2011
Admission routes3
Has abstractyes

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