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Record W2162782099 · doi:10.1093/plankt/fbq064

Meso-scale distributions of lake zooplankton reveal spatially and temporally varying trophic cascades

2010· article· en· W2162782099 on OpenAlexaff
Sonya Lévesque, Beatrix E. Beisner, Pedro R. Peres‐Neto

Bibliographic record

VenueJournal of Plankton Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicAquatic Ecosystems and Phytoplankton Dynamics
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsZooplanktonTrophic levelEnvironmental scienceTrophic cascadeScale (ratio)OceanographyEcologyBiologyFood webGeographyGeology

Abstract

fetched live from OpenAlex

The horizontal distribution of crustacean zooplankton is known to vary spatially in large lakes. Patterns in smaller dimictic lakes and variation through time (hourly and monthly) are less well established. Currents, chlorophyll and predators are all factors that vary through time, potentially affecting zooplankton distribution in stratified waters. Along an intermediate-length transect extending from the littoral area to the pelagic zone, we measured crustacean zooplankton size and horizontal position, as well as chlorophyll, currents and predators. We also assessed zooplankton vertical distribution patterns near each transect end. Horizontally, zooplankton were highly spatially structured in high summer, especially during daytime, when they preferred pelagic regions. A regular diel vertical migration pattern in early summer was replaced by an inverse one, suggesting a strong role for predation. Chlorophyll and zooplankton were inversely related, indicating a strong grazing interaction. The weakest signal was detected for currents. Results indicate that there can be large spatial fluctuations in zooplankton abundance apparently driven by predation. Furthermore, zooplankton distribution correlates inversely with chlorophyll only in the absence of a higher trophic level. We expect that plankton distribution in many small dimictic lakes will similarly be dominated by biotic factors, indicating that spatial variation should be taken into account when trophic interactions are considered.

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)0.003
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 score0.184
Threshold uncertainty score0.877

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
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 integrity0.0000.001
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 head0.021
GPT teacher head0.298
Teacher spread0.277 · 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

Citations35
Published2010
Admission routes1
Has abstractyes

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