Abstract
Computationally complex systems models are needed to advance research and implement policy in theoretical and applied population biology. Difference and differential equations used to build lumped dynamic models (LDMs) may have the advantage of clarity, but are limited in their inability to include fine scale spatial information and individual-specific physical, physiological, immunological, neural and behavioral states. Current formulations of agent-based models (ABMs) are too idiosyncratic and freewheeling to provide a general, coherent framework for dynamically linking the inner and outer worlds of organisms. Here I propose principles for a general, modular, hierarchically scalable, framework for building computational population models (CPMs) designed to treat the inner world of individual agents as complex dynamical systems that pass information to their outer world and to take information from this spatially detailed outer world to drive the dynamic inner world of these agents, simulate their ecology and the evolutionary pathways of their progeny. I also discuss development of a new software platform, called NOVA, for building CPMs, as well as the need for a cultural shift in the way population biologists communicate and share models and their modular components to develop Computational Population Biology as a field in its own right.
Wayne M. Getz
Department of Environmental Science, Policy and Management
140 Mulford Hall, University of California, Berkeley, CA 94720-3114
School of Mathematical Sciences, University of KwaZulu-Natal
Private Bag X54001, Durban 4000, South Africa