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Record W2040486994 · doi:10.1139/f04-188

The impact of a benthic filter feeder: limitations imposed by physical transport of algae to the benthos

2005· article· en· W2040486994 on OpenAlexvenueno aff
William J. Edwards, Chris R. Rehmann, Ellen McDonald, David A. Culver

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBenthic zoneDreissenaBenthosPelagic zoneEnvironmental scienceWater columnBiomass (ecology)OceanographyPhytoplanktonAlgaeEcologyFisheryBiologyBivalviaMolluscaGeologyNutrient

Abstract

fetched live from OpenAlex

We used an acoustic Doppler profiler to investigate the hydrodynamics of a nearshore site in western Lake Erie, and we incorporated the measured parameters in numerical simulations of phytoplankton consumption by benthic zebra mussels (Dreissena polymorpha) to examine the link between pelagic production and benthic filter feeders. Daily-averaged eddy diffusivities varied from 10 –5 to 10 –4 m 2 ·s –1 at our site. Our simulations demonstrate that diffusivities of this order decrease near-bed algal biomass, while algal biomass in the pelagic remains relatively unaffected. Between 8% and 67% of the algal biomass in the water column could be consumed daily, depending on the shape and magnitude of the diffusivity profile. Correspondingly, in situ vertical biomass profiles showed a near-bed zone of algal depletion, but no impact was observed near the surface. The impact of the zebra mussel in nearshore regions is expected to be stronger than in deeper open water. The flow of algal biomass into the benthos was tightly coupled with turbulent mixing, suggesting that open water algal consumption by zebra mussels is small compared with previously published estimates that ignored vertical turbulent mixing processes.

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 score0.151
Threshold uncertainty score0.972

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 science0.0000.000
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 head0.021
GPT teacher head0.242
Teacher spread0.221 · 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

Citations46
Published2005
Admission routes1
Has abstractyes

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