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Record W2049972216 · doi:10.1890/13-0742.1

Linking secondary structure of individual size distribution with nonlinear size–trophic level relationship in food webs

2013· article· en· W2049972216 on OpenAlexaff
Chun‐Wei Chang, Takeshi Miki, Fuh‐Kwo Shiah, Shuh‐Ji Kao, Jiunn‐Tzong Wu, Akash R. Sastri, Chih‐hao Hsieh

Bibliographic record

VenueEcology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsUniversité du Québec à Montréal
FundersNational Taiwan UniversityNational Science Council
KeywordsTrophic levelNonlinear systemZooplanktonAbundance (ecology)EcologyDistribution (mathematics)Power lawBiologyMathematicsStatisticsPhysics

Abstract

fetched live from OpenAlex

Existing individual size distribution (ISD) theories assume that the trophic level (TL) of an organism varies as a linear function of its log-transformed body size. This assumption predicts a power-law distribution of the ISD, i.e., a linear relationship between size and abundance in log space. However, the secondary structure of ISD (nonlinear dome shape structures deviating from a power-law distribution) is often observed. We propose a model that extends the metabolic theory to link the secondary structure of ISD to the nonlinear size-TL relationship. This model is tested with empirical data collected from a subtropical reservoir. The empirical ISD and size-TL relationships were constructed by FlowCAM imaging analysis and stable isotope analyses, respectively. Our results demonstrate that the secondary structure of ISD can be predicted from the nonlinear function of size-TL relationship and vice versa. Moreover, these secondary structures arise due to (1) zooplankton omnivory and (2) the trophic interactions within microbial food webs.

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 score0.008
Threshold uncertainty score0.992

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)0.0080.000

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 head0.011
GPT teacher head0.213
Teacher spread0.202 · 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

Citations38
Published2013
Admission routes1
Has abstractyes

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