A major issue in the study of ecological networks is making comparisons between multiple empirical networks as well as between empirical and modeled networks. There are any number of network properties that can be used in comparing different networks including, but not limited to connectance, proportion top, intermediate, and basal species, diameter, mean path length, degree (and the associated distribution), cluster coefficient, nestedness, modularity, stability, and patterns of subgraph representation. Many of these properties are strongly correlated, however. In a recent study Vermaat et al. found that there was a significant correlation between the most commonly used indices of networks. Importantly they found that connectance, size, and net primary productivity explained almost 85% of the variance between food webs.
There are a number of other issues related to network comparisons as well. Dormann et al. (2009) notes that there is a significant effect of network size as well as sampling intensity on many network indices, though the direction of the impact is variable. In 2006 Fox showed that many network indices are robust to small changes in structure (e.g. minor re-wiring). While this may sound good when there is an issue of sampling intensity, when comparing networks it becomes a more serious issue. What robustness means is that two networks can appear to be similar based on indices yet can be fundamentally very different.
So how have networks been compared in the literature?