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Record W2152195450 · doi:10.4319/lo.2009.54.3.0757

Effects of the Bythotrephes invasion on native predatory invertebrates

2009· article· en· W2152195450 on OpenAlexafffundabout
Sophie E. Foster, Gary Sprule

Bibliographic record

VenueLimnology and Oceanography · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Invertebrate Ecology and Behavior
Canadian institutionsUniversity of Toronto
FundersUniversity of TorontoMinistry of EnvironmentMinistry of Natural Resources
KeywordsZooplanktonBiologyPredationInvertebrateEcologyAbundance (ecology)PredatorFishery

Abstract

fetched live from OpenAlex

We explore the effects of the invasive predatory cladoceran Bythotrephes longimanus on the abundances and seasonal zooplankton consumption by the native predatory invertebrates Leptodora kindtii , Chaoborus spp., and Mysis relicta in inland lakes of Ontario. In lakes with Bythotrephes , the seasonal consumption by all invertebrate predators combined ranged from 2.39 to 13.50 g m −2 and was 300% higher than in lakes without the invader. This was due to Bythotrephes because there was no invasion effect on Chaoborus or Mysis consumption, while it actually decreased Leptodora consumption. Leptodora and Chaoborus abundances were lower in invaded lakes, but only Leptodora abundance was negatively correlated with Bythotrephes abundance. There was no effect of Bythotrephes on Mysi s abundance. Bythotrephes consume more zooplankton than most other predatory invertebrates, including copepods, and often consume more zooplankton than planktivorous fish. The large increase in predatory invertebrate abundance and consumption due to Bythotrephes means that substantial portions of zooplankton production are probably being diverted from other consumers, such as juvenile and planktivorous fish, and that the role of predatory invertebrates in the pelagia of inland lakes has been intensified by the arrival of Bythotrephes .

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 score0.075
Threshold uncertainty score0.313

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 studies0.0000.001
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 head0.004
GPT teacher head0.190
Teacher spread0.186 · 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

Citations39
Published2009
Admission routes3
Has abstractyes

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