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Record W2233463112 · doi:10.1890/15-1084.1

A meta‐analysis of zooplankton functional traits influencing ecosystem function

2015· article· en· W2233463112 on OpenAlexaff
Marie‐Pier Hébert, Beatrix E. Beisner, Roxane Maranger

Bibliographic record

VenueEcology · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversité du Québec à MontréalUniversité de Montréal
Fundersnot available
KeywordsEcologyEcosystemBiologyZooplanktonTrophic levelAquatic ecosystemHabitatNutrient cycleFunctional ecologyEcological stoichiometryCommunityFood webBiogeochemistryCommunity structure

Abstract

fetched live from OpenAlex

The use of functional traits to characterize community composition has been proposed as a more effective way to link community structure to ecosystem functioning. Organismal morphology, body stoichiometry, and physiology can be readily linked to large-scale ecosystem processes through functional traits that inform on interspecific and species-environment interactions; yet such effect traits are still poorly included in trait-based approaches. Given their key trophic position in aquatic ecosystems, individual zooplankton affect energy fluxes and elemental processing. We compiled a large database of zooplankton traits contributing to carbon, nitrogen, and phosphorus cycling and examined the effect of classification and habitat (marine vs. freshwater) on trait relationships. Respiration and nutrient excretion rates followed mass-dependent scaling in both habitats, with exponents ranging from 0.70 to 0.90. Our analyses revealed surprising differences in allometry and respiration between habitats, with freshwater species having lower length-specific mass and three times higher mass-specific respiration rates. These differences in traits point to implications for ecological strategies as well as overall carbon storage and fluxes based on habitat type. Our synthesis quantifies multiple trait relationships and links organisms to ecosystem processes they influence, enabling a more complete integration of aquatic community ecology and biogeochemistry through the promising use of effect traits.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.191
Threshold uncertainty score0.995

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)0.0060.000

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 head0.044
GPT teacher head0.227
Teacher spread0.182 · 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.

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

Citations116
Published2015
Admission routes1
Has abstractyes

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