A statistical social network model for consumption data in trophic food webs
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Authors
Chiu, Grace
Westveld, Anton
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Elsevier BV
Abstract
We adapt existing statistical modeling techniques for social net-
works to study consumption data observed in trophic food webs.
Thesedatadescribethefeedingvolume(non-negative)amongor-
ganisms grouped into nodes, called trophic species, that form the
foodweb.Modelcomplexityarisesduetotheextensiveamountof
zerosinthedata,aseachnodeinthewebispredator/preytoonly
asmallnumberofothertrophicspecies.Manyofthezerosarere-
gardedasstructural(non-random)inthecontextoffeedingbehav-
ior.Thepresenceofbasalpreyandtoppredatornodes(thosewho
never consume and those who are never consumed, with proba-
bility 1) creates additional complexity to the statistical modeling.
Wedevelopaspecialstatisticalsocialnetworkmodeltoaccountfor
suchnetworkfeatures.Themodelisappliedtotwoempiricalfood
webs;focusisonthewebforwhichthepopulationsizeofsealsis
ofconcerntovariouscommercialfisheries
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Statistical Methodology