  Few of food web theory hypotheses/predictions can be readily tested using
empirical data. An exception is represented by simple probabilistic models for
food web structure, for which the likelihood has been derived. Here I test the
performance of a more complex model for food web structure that is grounded in
the allometric scaling of interactions with body size and the theory of optimal
foraging (Allometric Diet Breadth Model - ADBM). This deterministic model has
been evaluated measuring the fraction of trophic relations correctly predicted.
I contrast this value with that produced by simpler models based on body sizes
and find that the data does not favor the more complex model: the information
on allometric scaling and optimal foraging does not significantly increase the
fit to the data. Also, I take a different approach and compute the p-value for
the fraction of trophic interactions correctly predicted by ADBM with respect
to three probabilistic null models. I find that the ADBM is clearly better at
predicting links than random graphs, but other models can do even better.
Although optimal foraging and allometric scaling could improve our
understanding of food webs, the models need to be ameliorated to find support
in the data.
