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Modèle de mélange SIAR×Analyse de la topologie des réseaux trophiques×
DomaineÉcologieÉcologie
FamilleProcess / pipelineProcess / pipeline
Année d'origine20102000
Auteur d'origineAndrew ParnellRichard Williams and Neo Martinez
Typediet and source apportionment analysisecological network characterization
Source fondatriceParnell, A. C., Inger, R., Bearhop, S., & Jackson, A. L. (2010). Source partitioning using stable isotopes: coping with too much variation. PLoS ONE, 5(3), e9672. DOI ↗Dunne, J. A., Williams, R. J., & Martinez, N. D. (2002). Network structure and robustness of marine food webs. The American Naturalist, 160(1), 117-129. link ↗
Aliasisotope mixing model, Bayesian mixing model, source apportionment, diet analysisfood web structure, network topology, trophic network, food chain analysis
Apparentées44
RésuméThe Stable Isotope Analysis in R (SIAR) mixing model is a Bayesian framework for estimating the proportional contributions of dietary sources to a consumer, using stable isotope ratios. Developed by Parnell and colleagues (2010) and implemented in the R package siar (and its successor MixSIAR), this method integrates isotopic data from potential food sources and consumers to infer diets. It accounts for uncertainty in isotope fractionation (the shift in isotope ratios between diet and tissue) and natural variation among source populations, producing probability distributions rather than point estimates of diet composition.Food web topology analysis characterizes the structure of predator-prey interactions within ecological communities using network metrics. Pioneered by Williams and Martinez (2000) and extended by Dunne and colleagues (2002), this approach maps which species eat which and quantifies network properties (connectivity, clustering, robustness). Understanding food web structure reveals how ecosystems are organized, how stable they are to species loss, and what roles different species play in ecosystem function.
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ScholarGateComparer des méthodes: SIAR Mixing Model · Food Web Topology. Consulté le 2026-06-20 sur https://scholargate.app/fr/compare