Understanding ecological complexity has stymied scientists for decades. Recent elucidation of the famously coined "devious strategies for stability in enduring natural systems" has opened up a new field of computational analyses of complex ecological networks where the nonlinear dynamics of many interacting species can be more realistically modeled and understood. Here, we describe the first extension of this field to include coupled human-natural systems. This extension elucidates new strategies for sustaining extraction of biomass (e.g., fish, forests, fiber) from ecosystems that account for ecological complexity and can pursue multiple goals such as maximizing economic profit, employment and carbon sequestration by ecosystems. Our more realistic modeling of ecosystems helps explain why simpler "maximum sustainable yield" bioeconomic models underpinning much natural resource extraction policy leads to less profit, biomass, and biodiversity than predicted by those simple models. Current research directions of this integrated natural and social science include applying artificial intelligence, cloud computing, and multiplayer online games.

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.