• Adenia;
  • cascading failure hypothesis;
  • cost of selection;
  • evolutionary modularity;
  • plant functional anatomy;
  • posterior predictive P-value;
  • small-world networks;
  • stem succulence

Biological systems are remarkably robust in the face of environmental, mutational, and developmental perturbations. Analyses of molecular networks reveal recurrent features, such as modularity, that have been implicated in robustness and evolvability. Multiple theoretical models account for these features, yet few empirical tests of these models exist. Here I develop a set of broadly applicable methodologies to enable expanded empirical evaluation of model predictions. The methodologies focus on the inference and analysis of networks that depict evolutionary correlations among characters. I apply these methodologies to analyze an evolutionary network at a larger scale of organization among 42 stem anatomical and morphological characters of 52 species in the genus Adenia (Passifloraceae). I evaluate a model predicting that modular evolutionary networks will evolve in response to environmental change. The evolutionary network of Adenia is modular and “small-world,” and the three diagnosed modules correspond roughly to functions of transport, storage, and mechanical support. The phylogenetically informed analyses suggest that the storage module is more impacted by environmental change than expected by chance. These results corroborate the hypothesis that modularity reduces the impact of environmental change, but this result requires further empirical evaluation that can be aided by the proposed methods in additional study systems.