Ecological networks comprised of diverse species interacting within habitats describe iconic self-organized complex systems. Their nodes are dynamic, highly heterogeneous and constantly evolving in response to their changing environment. Yet, these ungoverned highly diverse and complex ecological networks remain remarkably robust despite catastrophes that destroy huge fractions of the nodes and cause permanent alterations of the environment. Recent work to model these system employs network informatics, visualizations, and high performance computing simulations. Exploring these models demands that the parameters are both fit using rigorous informatics and also varied in innumerable combinations using efficient and powerful computer architectures. This presentation will describe the mechanics of this endeavor as well as several of the most interesting research results including the robustness enhancing roles of network architecture and organism's size and behavioral nonlinearities as well as network effects of species' loss and invasions. A particular future for such endeavors will also described with special attention to implications for general network science.