Linganisha mbinu

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