Cultural evolution in spatially structured populations: A review of alternative modeling frameworks

Anne Kandler, Charles Perreault, James Steele

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


We consider the dynamics of cultural evolution in spatially-structured populations. Most spatially explicit modeling approaches can be broadly divided into two classes: micro- and macro-level models. Macro-level models study cultural evolution at the population level and describe the average behavior of the considered system. Conversely, micro-level models focus on the constituent units of the system, and study the evolutionary dynamics that emerge out of the interaction between these units. In this paper, we give an overview of the general properties of micro- and macro-level models using the examples of agent-based simulations and of continuum models based in diffusion theory; we highlight how both frameworks account for spatially-dependent processes. We argue that both micro- and macro-level models are well-suited to describe the process of cultural evolution in spatial settings and stress that micro- and macro-level models should not be considered as competing alternatives, but rather as complementary tools that can provide different insights into cultural evolutionary dynamics. Although adding spatial components to any model increases its complexity, we argue (based on the findings presented by contributors to this Special Issue of Advances in Complex Systems), that the incorporation of space into the evolutionary framework is a necessary step towards a more complete understanding of the process of cultural evolution.

Original languageEnglish (US)
Article number1203001
JournalAdvances in Complex Systems
Issue number1-2
StatePublished - Mar 2012
Externally publishedYes


  • Agent-based simulation
  • Cultural evolution
  • Diffusion-reaction systems
  • Spatial modeling

ASJC Scopus subject areas

  • Control and Systems Engineering


Dive into the research topics of 'Cultural evolution in spatially structured populations: A review of alternative modeling frameworks'. Together they form a unique fingerprint.

Cite this