  We adapt existing statistical modeling techniques for social networks to
study consumption data observed in trophic food webs. These data describe the
feeding volume (non-negative) among organisms grouped into nodes, called
trophic species, that form the food web. Model complexity arises due to the
extensive amount of zeros in the data, as each node in the web is predator/prey
to only a small number of other trophic species. Many of the zeros are regarded
as structural (non-random) in the context of feeding behavior. The presence of
basal prey and top predator nodes (those who never consume and those who are
never consumed, with probability 1) creates additional complexity to the
statistical modeling. We develop a special statistical social network model to
account for such network features. The model is applied to two empirical food
webs; focus is on the web for which the population size of seals is of concern
to various commercial fisheries.
