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Record W2026496215 · doi:10.2989/ajas.2007.32.2.9.206

The community composition and biomass of pelagic ciliated protozoa in East African lakes

2007· article· en· W2026496215 on OpenAlexaff
Andrew Yasindi, William D. Taylor, Denis H. Lynn

Bibliographic record

VenueAfrican Journal of Aquatic Science · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsCiliateChlorophyll aEutrophicationPlanktonCanonical correspondence analysisBiologyBiomass (ecology)EcologyPelagic zoneAbundance (ecology)BotanyNutrient

Abstract

fetched live from OpenAlex

The community composition and biomass of planktonic ciliates were studied in 17 tropical East African lakes varying from freshwater to saline, and from oligotrophic to eutrophic. The conductivity of the lakes varied from 207μS cm−1 to 70 000μS cm−1. Chlorophyll a concentration ranged from <5mg m−3 to >50mg m−3, while bacterial numbers were between 2.9 × 106 and 2.55 × 108 bacteria ml−1. Principal components analysis based on environmental variables revealed a single strong environmental gradient across the lakes related to conductivity, alkalinity, bacterial abundance, chlorophyll a, and (negatively) to Secchi depth. Oligotrichs (e.g. Strombidium, Strobilidium, Halteria) and scuticociliates (e.g. Cyclidium, Pleuronema, Cristigera) dominated the ciliate communities numerically. The species-environment correlations, as revealed by canonical correspondence analysis, indicate a strong relationship between ciliate genera and the environmental gradient. Herbivorous oligotrichs were characteristic of oligotrophic and mesotrophic lakes, which were also freshwater to moderately saline lakes. On the other hand, scuticociliates, primarily bacterivores, were most abundant in alkaline and saline lakes with high chlorophyll a concentrations. Biomass of ciliates was related to chlorophyll, as has been observed in temperate and subtropical lakes, but was more strongly related to bacterial concentration.

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)0.007
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 score0.183
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.014
GPT teacher head0.240
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.

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

Citations6
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueAfrican Journal of Aquatic ScienceSame topicAquatic Ecosystems and Phytoplankton DynamicsFrench-language works237,207