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Impact of <i>Bythotrephes longimanus</i> on zooplankton assemblages of Harp Lake, Canada: an assessment based on predator consumption and prey production

2001· article· en· W2011534621 on OpenAlexaffabout
Cristina Dumitru, W. Gary Sprules, Norman D. Yan

Bibliographic record

VenueFreshwater Biology · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsMinistry of the Environment, Conservation and ParksAurora CollegeUniversity of Toronto
FundersHellenic Ministry of Environment and Energy
KeywordsZooplanktonDaphnia galeataPredationBiologyCopepodPredatorCyclopsEcologyFisheryCladoceraCrustaceanBranchiopoda

Abstract

fetched live from OpenAlex

1. Following the 1993 invasion of Harp Lake by Bythotrephes longimanus a number of small‐bodied zooplankton declined dramatically compared to pre‐invasion densities, and some larger species increased. 2. To test whether these changes were caused by Bythotrephes, we measured its consumption of zooplankton in 1995 and compared this to production by the prey species with which it overlapped spatially and temporally. 3. On a seasonal basis Bythotrephes consumption was 199 mg dry mass (DM) m −2 , or 25% of zooplankton production which was 783 mg DW m −2 . However, for some species, such as the small copepod Tropocyclops extensus , consumption greatly exceeded production—this was one of the species noted to decline in Harp Lake following the appearance of Bythotrephes . By contrast, for the larger cladocerans Daphnia galeata mendotae and Holopedium gibberum , consumption was much less than production—these species were observed to increase following the invasion. 4. Our results thus support the hypothesis that zooplankton changes in Harp Lake were caused by Bythotrephes . We speculate that lower quality prey remaining in Harp Lake may lead to reduced densities of Bythotrephes , or impose strong selective forces that lead to new adaptations by this predator.

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 score0.691
Threshold uncertainty score0.956

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 head0.015
GPT teacher head0.282
Teacher spread0.267 · 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

Citations69
Published2001
Admission routes2
Has abstractyes

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