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Record W1971871664 · doi:10.1139/f06-059

Changes in spring phytoplankton communities and nutrient dynamics in the eastern basin of Lake Erie since the invasion of <i>Dreissena</i> spp.

2006· article· en· W1971871664 on OpenAlexvenueno aff
Richard P. Barbiero, David C. Rockwell, Glenn J. Warren, Marc L. Tuchman

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
FundersChina Scholarship CouncilU.S. Environmental Protection Agency
KeywordsDreissenaPhytoplanktonDominance (genetics)DiatomNutrientSpring (device)Environmental scienceOceanographyEcologySpring bloomStructural basinGrazing pressureBiologyGrazingBivalviaGeologyMollusca

Abstract

fetched live from OpenAlex

Distinct changes have occurred in the size and composition of the spring phytoplankton community in the eastern basin of Lake Erie following the introduction of Dreissena. Since 1996, total phytoplankton biovolume has decreased to approximately 20% of pre-Dreissena levels, whereas postinvasion concentrations of spring soluble nutrients, particularly silica, have been substantially elevated compared with earlier years. Spring dominance has shifted from a mix of pennate and large centric diatoms and pyrrophytes to three centric diatoms with high silica requirements: Aulacoseira islandica, Stephanodiscus hantzschii, and Stephanodiscus parvus, and the overall diversity and species richness of the spring phytoplankton community has declined significantly. In addition, current April silica concentrations are approximately twice as high as historical (i.e., 1960s–1980s) winter maxima, indicating that the silica content of the lake has increased since the dreissenid invasion. These results suggest that the severe silica depletion caused by increased anthropogenic inputs of nutrients during the last century has been mitigated through a decrease in diatom production, most likely brought about by dreissenid grazing.

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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.906
Threshold uncertainty score0.954

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 studies0.0000.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.017
GPT teacher head0.198
Teacher spread0.181 · 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.

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

Citations95
Published2006
Admission routes1
Has abstractyes

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