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Record W1972169618 · doi:10.5194/bg-10-1877-2013

Copepod community growth rates in relation to body size, temperature, and food availability in the East China Sea: a test of metabolic theory of ecology

2013· article· en· W1972169618 on OpenAlexaff
Ke Lin, Akash R. Sastri, Guangcai Gong, Chih‐hao Hsieh

Bibliographic record

VenueBiogeosciences · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPhysiological and biochemical adaptations
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCopepodZooplanktonEcologyBiologyGrowth rateEcosystemMarine ecosystemCommunity structureChina seaEnvironmental scienceOceanographyCrustaceanMathematics

Abstract

fetched live from OpenAlex

Abstract. Zooplankton play an essential role in marine food webs, and understanding how community-level growth rates of zooplankton vary in the field is critical for predicting how marine ecosystem function may vary in the face of environmental changes. Here, we used the artificial cohort method to examine the effects of temperature, body size, and chlorophyll concentration (a proxy for food) on weight-specific growth rates for copepod communities in the East China Sea. Specifically, we tested the hypothesis that copepod community growth rates can be described by the metabolic theory of ecology (MTE), linking spatio-temporal variation of copepod growth rate with temperature and their body size. Our results generally agree with predictions made by the MTE and demonstrate that weight-specific growth rates of copepod communities in our study area are positively related with temperature and negatively related to body size. However, the regression coefficients of body size do not approach the theoretical predictions. Furthermore, we find that the deviation from the MTE predictions may be partly attributed to the effect of food availability (which is not explicitly accounted for by the MTE). In addition, significant difference in the coefficients of temperature and body size exists among taxonomic groups. Our results suggest that considering the effects of food limitation and taxonomy is necessary to better understand copepod growth rates under in situ conditions, and such effects on the MTE-based predictions need further investigation.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.326
Threshold uncertainty score0.541

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.015
GPT teacher head0.221
Teacher spread0.206 · 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

Citations34
Published2013
Admission routes1
Has abstractyes

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