|With the increasing use of cyberinfrastructure and popularity of e-Science initiatives, science is becoming truly globalized, reducing barriers to entry and enabling formation of open and global networked innovation communities. Yet, relatively little is known about the mechanisms that govern such globalized communities. Meanwhile, creative artificial ecosystem metaphors and interaction processes among communities have potential to shed light on the effects of communication styles in the emergence of global knowledge communities. So, this study explores how networks of scientific communities and epistemic cultures form and evolve, what network patterns emerge from different socio-technical communication theories, and the relationship between environmental constraints, community traits, and innovation performance and potential. Understanding scientific communities and their associated communication networks is key to understanding the dynamics of knowledge creation, as well as formation and growth of scientific communities to facilitate informed science and innovation policy-making. A benefit of this research is to offer federal agencies a computer-aided decision-making tool so as to evaluate investment decision and policies. To this end, an agent-based simulation model combining boundary processes and theories of communication is developed. The model is verified and validated with respect to empirical network data. Simulation results suggest that communities with highly connected clusters are likely to thrive if resource availability is low. So far as the resource allocation strategy is concerned, key area investment with technology transferring results in the highest variety. Exploration of the impact of socio-technical communication theories suggest that under low communication frequency, openness and receptivity lead to higher variety. On the contrary, variety decreases with increasing receptivity under high communication frequency.