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| Модели за биоакумулация× | Модел за смесване SIAR× | |
|---|---|---|
| Област | Екология | Екология |
| Семейство | Process / pipeline | Process / pipeline |
| Година на възникване≠ | 2006 | 2010 |
| Създател≠ | Frank Gobas | Andrew Parnell |
| Тип≠ | pollutant accumulation dynamics | diet and source apportionment analysis |
| Основополагащ източник≠ | Arnot, 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 ↗ |
| Други названия≠ | accumulation model, toxicokinetics, persistent organic pollutants, POPs | isotope mixing model, Bayesian mixing model, source apportionment, diet analysis |
| Свързани | 4 | 4 |
| Резюме≠ | Bioaccumulation 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. |
| ScholarGateНабор от данни ↗ |
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