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Msaidizi

Linganisha mbinu

Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.

Muundo wa Bioaccumulation×Mfumo wa uchanganyaji wa SIAR (Stable Isotope Analysis in R)×
NyanjaIkolojiaIkolojia
FamiliaProcess / pipelineProcess / pipeline
Mwaka wa asili20062010
MwanzilishiFrank GobasAndrew Parnell
Ainapollutant accumulation dynamicsdiet and source apportionment analysis
Chanzo asiliaArnot, J. A., & Gobas, F. A. (2006). A review of bioaccumulation factor (BAF) and bioconcentration factor (BCF) assessments for organic chemicals in aquatic organisms. Environmental Reviews, 14(4), 257-297. DOI ↗Parnell, 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 ↗
Majina mbadalaaccumulation model, toxicokinetics, persistent organic pollutants, POPsisotope mixing model, Bayesian mixing model, source apportionment, diet analysis
Zinazohusiana44
MuhtasariBioaccumulation models predict how chemical contaminants accumulate in organisms from environmental exposure (water, food, sediment). Developed by Gobas and colleagues (2006), these models quantify the kinetics of chemical uptake, metabolism, and clearance. Bioaccumulation factors (BAF) and bioconcentration factors (BCF) measure the ratio of chemical concentration in organisms to concentration in the environment. Understanding bioaccumulation is critical for assessing ecological risk from persistent organic pollutants (POPs), heavy metals, and other contaminants.The 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.
ScholarGateSeti ya data
  1. v1
  2. 3 Vyanzo
  3. PUBLISHED
  1. v1
  2. 3 Vyanzo
  3. PUBLISHED

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ScholarGateLinganisha mbinu: Bioaccumulation Model · SIAR Mixing Model. Imepatikana 2026-06-18 kutoka https://scholargate.app/sw/compare