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Record W4281759974 · doi:10.1101/2022.06.02.494478

Variation in behaviour of native prey mediates the impact of an invasive species on plankton communities

2022· preprint· en· W4281759974 on OpenAlexaff
Sarah Hasnain, Shelley E. Arnott

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsQueen's University
Fundersnot available
KeywordsDaphniaBiologyPredationZooplanktonTrophic levelEcologyDaphnia galeataPopulationPredatorTrophic cascadeDaphnia pulexDiel vertical migrationBiomass (ecology)Population densityMesocosmCladoceraBranchiopodaEcosystem

Abstract

fetched live from OpenAlex

Abstract Population-level differences in predator trait expression influence predator impacts on prey species, altering ecological interactions and trophic dynamics. However, the effect of inter-population differences in prey traits on the impacts of predation on ecological communities remains poorly understood, especially for introduced predators where differences in prey traits could influence the outcome of biological invasions. We examined if differences in Daphnia vertical position influenced the impacts of the invasive predator Bythotrephes cederströmii on major zooplankton and algal groups. Our results show differences in Daphnia vertical position influenced Bythotrephes impacts on small cladocerans. Larger reductions in density were observed in mesocosms with greater proportion of hypolimnetic Daphnia . Larger increases in algal biomass were also observed in invaded mesocosms with greater proportion of hypolimnetic Daphnia . These results suggest that differences in Daphnia vertical position influence the magnitude and type of Bythotrephes impacts on zooplankton communities.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.017
GPT teacher head0.232
Teacher spread0.215 · 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 source (direct Gemma or distilled Codex), 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

Citations1
Published2022
Admission routes1
Has abstractyes

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