Linganisha mbinu

	Mfumo wa uchanganyaji wa SIAR (Stable Isotope Analysis in R)	Uchambuzi wa Topolojia ya Mtandao wa Chakula
Nyanja	Ikolojia	Ikolojia
Familia	Process / pipeline	Process / pipeline
Mwaka wa asili	2010	2000
Mwanzilishi	Andrew Parnell	Richard Williams and Neo Martinez
Aina	diet and source apportionment analysis	ecological network characterization
Chanzo asilia	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.	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.
Majina mbadala	isotope mixing model, Bayesian mixing model, source apportionment, diet analysis	food web structure, network topology, trophic network, food chain analysis
Zinazohusiana	4	4
Muhtasari	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.	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.