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Record W3034758734 · doi:10.1080/14634988.2020.1735230

Predation on planktonic ciliates in Kenyan soda lakes

2020· article· en· W3034758734 on OpenAlexaff
Andrew Yasindi, William D. Taylor

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Biodiversity
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsPredationZooplanktonCiliatePlanktonBiologyAbundance (ecology)EcologyProtozoaNutrientRotiferPredatorCompetition (biology)Botany

Abstract

fetched live from OpenAlex

Ciliated protozoa are important components of the plankton of aquatic systems with ability to recycle nutrients and to link microbial food webs to metazoans. This is because they are numerous and have higher growth rates compared to other unicellular eukaryotes of similar size. Predation and competition are some of the factors that negatively affect their abundance and growth. Studies documenting the impact of predation by zooplankton on ciliates have been conducted in marine and freshwaters waters but are lacking in tropical waters especially soda lakes in Kenya. In this study, growth rates of planktonic ciliates were estimated in four soda lakes, Lakes Bogoria, Elmenteita, Simbi and Sonachi, using predator exclusion experiments. In the experiments, ciliate populations increased faster in incubations of lake water with the >40 µm fraction removed than in untreated controls. The difference in these rates was taken as an estimate of predation by zooplankton >40 µm (Mz), and ranged from 0.091 to 3.171 d−1. Our best estimates of growth rates for particular ciliates abundant enough to derive estimates for ranged from 0.18 to 4.78 d−1. When removing the >40 µm fraction did not result in increased numbers of ciliates relative to controls, we hypothesized that this was due to predators within the <40 µm fraction (Mc) and their release from zooplankton predators. We assessed and supported this hypothesis by looking at the production of ciliates in different feeding guilds. The significance of predation on ciliates to the food webs of soda lakes is discussed.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.995

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.005

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 head0.022
GPT teacher head0.227
Teacher spread0.205 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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