Predicting trophic relations in ecological networks: a test of the Allometric Diet Breadth Model

TL;DR

This study tests the Allometric Diet Breadth Model's ability to predict trophic relations in ecological networks, finding it outperforms random models but is not significantly better than simpler models based on body size alone.

Contribution

The paper evaluates a complex, theory-based model for food web structure against simpler models and null hypotheses, highlighting its limited improvement in predictive power.

Findings

ADBM predicts trophic links better than random models.

Simpler models based on body size perform similarly to ADBM.

Data does not strongly support the added complexity of ADBM.

Abstract

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.