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An introduced invertebrate predator (<i>Bythotrephes</i>) reduces zooplankton species richness

2002· article· en· W2140327027 on OpenAlexaffabout
Norman D. Yan, R. Girard, Stephanie A. Boudreau

Bibliographic record

VenueEcology Letters · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsYork UniversityMinistry of the Environment, Conservation and Parks
Fundersnot available
KeywordsSpecies richnessZooplanktonEcologyInvertebrateBiologyBiodiversityIntroduced speciesPredatorHabitatBiological dispersalInvasive speciesPredationPopulation

Abstract

fetched live from OpenAlex

Rarely do ecologists have the data needed to assess the impacts of invading species on biodiversity, i.e. pre‐ and post‐invasion census information from both invaded and control sites. Using a 21‐year time series, we demonstrate that the invasion of Harp Lake, Ontario, Canada, by the Eurasian spiny water flea, Bythotrephes longimanus, a zooplanktivore, was accompanied by a rapid and long‐lasting reduction in the average species richness of crustacean zooplankton, particularly of cladoceran taxa. No such reduction was observed in seven nearby un‐invaded lakes over the same two decades. If the Harp Lake results are typical, we predict a widespread reduction in crustacean zooplankton richness on the Canadian Shield for three reasons. Shield lakes provide the invader with good habitat. Its dispersal rates and colonization success are high. Zooplankton richness in Harp Lake is now unusually low for a Shield Lake of its size and acidity.

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)0.000
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 score0.192
Threshold uncertainty score0.381

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.010
GPT teacher head0.195
Teacher spread0.185 · 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

Citations133
Published2002
Admission routes2
Has abstractyes

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