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Record W1514360038 · doi:10.1080/14634988.2013.826115

Microbial foodweb comparison of the Laurentian Great Lakes during the summers of 2001–2004

2013· article· en· W1514360038 on OpenAlexaffabout
M. Munawar, I. F. Munawar, M. Fitzpatrick

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsFisheries and Oceans Canada
FundersU.S. Environmental Protection Agency
KeywordsPicoplanktonMicrobial loopTrophic levelPhytoplanktonAutotrophBiomass (ecology)HeterotrophBacterioplanktonEnvironmental sciencePlanktonTrophic state indexEcologyProductivityMixotrophBiologyNutrientBacteria

Abstract

fetched live from OpenAlex

A structural and functional assessment of the microbial foodweb of Lakes Superior, Huron, Erie and Ontario was undertaken during late summer (August) between 2001 and 2004. One lake was sampled in each year. Our analysis included microscopic enumerations of bacteria, autotrophic picoplankton, phytoplankton, heterotrophic nanoflagellates and ciliates coupled with radioisotope tracer measurements of primary productivity (14C) and bacterial growth (3H). Phytoplankton biomass was highest on average in Lake Erie (≈1.9 g m−3) and lowest in Lake Ontario (≈0.2 g m−3), whereas microbial loop biomass was highest in Lake Ontario (≈2.4 g m−3) and lowest in Lake Huron (≈0.1 g m−3). The organic carbon pool was found to be predominantly autotrophic (>80%) in Lakes Superior (≈280 mg C m−3), Huron (≈195 mg C m−3) and Erie (≈660 mg C m−3) and smaller picoplankton had the highest carbon turnover rates (≈0.4–1.5 d−1). However, in Lake Ontario (≈335 mg C m−3) the carbon pool was about 75% heterotrophic and larger net plankton had the highest carbon turnover rates (≈6.8 d−1). Despite differences in trophic state, the microbial foodwebs of Lakes Superior, Huron and Erie appeared to function in a similar and efficient manner. In contrast, the microbial foodweb of Lake Ontario appeared to be unhealthy with autochthonous production being sequestered by heterotrophic nanoflagellates. More detailed work is needed to understand the foodweb linkages both within the Great Lakes and among them.

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 categoriesInsufficient 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 score0.210
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.238
Teacher spread0.226 · 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

Citations5
Published2013
Admission routes2
Has abstractyes

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