Computational population biology: linking the inner and outer worlds of organisms

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 take information from their spatially detailed outer worlds to drive the dynamic inner worlds of these agents and simulate their ecology and the evolutionary pathways of their progeny. All the modeling elements are in place, although improvements in software technology will be helpful; but most of all we need a cultural shift in the way in which population biologists communicate and share model components and the models themselves and fit, test, refute and refine models, to make the progress needed to meet the ecosystems management challenges posed by global change biology.

Keywords:

• population models
• agent-based models
• individual-based models
• ecosystem models
• GIS
• transformation web theory
• utilization distributions
• redistribution kernels

Acknowledgements

I would like to thank Norman Owen-Smith and Tony Starfield for many years of fruitful discussions during which my ideas have matured. I am also grateful for more recent discussions with Lev Ginzburg, Ran Nathan, Eloy Revilla, Richard Salter, and David Saltz. I would like to thank Andy Lyons for generating the data for Figure 5, as well as Carl Boettiger, Scott Fortmann-Roe, Noel Holmgren, Leo Polansky, Norman Owen-Smith, Nick Sipplswezey, Tony Starfield, and Anna Treydte and an anonymous reviewer for comments on an earlier draft. This work was supported by NIH GM083863 and BSF 2008255 grants to WMG and by the generous support of the Rosalinde and Arthur Gilbert Foundation.

Additional information

Notes on contributors

Wayne M. Getz

Wayne Getz has a Ph.D. in Applied Mathematics from the University of the Witwatersrand, Johannesburg, and a D.Sc. in Zoology from the University of Cape Town, South Africa. Since 1979 he has been on the faculty at the University of California, Berkeley.