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Rotifer population spread in relation to food, density and predation risk in an experimental system

2011· article· en· W1502185143 on OpenAlexafffund
Daniel Kuefler, Tal Avgar, John M. Fryxell

Bibliographic record

VenueJournal of Animal Ecology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAnimal Ecology and Behavior Studies
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRotiferPredationBrachionus calyciflorusBiologyPopulation densityDensity dependencePopulationEcologyPredatorReplicateRange (aeronautics)StatisticsDemographyMathematics

Abstract

fetched live from OpenAlex

1. Despite the popular use of diffusion models to predict the spatial spread of populations over time, we currently know little about how diffusion rates change with the state of the environment or the internal condition of individuals. To address this gap in our understanding, we measured rates of spread for many populations of the rotifer Brachionus calyciflorus in a suite of well-replicated experiments. 2. In one set of experiments, we manipulated food availability and population density along a continuous range of densities. In a second set, we manipulated the internal state of entire populations via food deprivation and exposure to predator kairomones. 3. Across replicate populations, diffusion rates were positively correlated with conspecific density. Diffusion rates were negatively correlated with food availability, especially when conspecific density was high. Diffusion rates of food-deprived populations or those exposed to predation risk were lower than controls. 4. Our results provide direct experimental evidence that rates of population spread are conditional on population density, food availability, body condition and predation risk.

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)0.000
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 score0.010
Threshold uncertainty score0.565

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.032
GPT teacher head0.267
Teacher spread0.234 · 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

Citations40
Published2011
Admission routes2
Has abstractyes

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