
Simulating trait evolution for cross-cultural comparison.
Cross-cultural anthropologists have increasingly used phylogenetic methods to study cultural variation. Because cultural behaviours can be transmitted horizontally among socially defined groups, however, it is important to assess whether phylogeny-based methods--which were developed to study vertically transmitted traits among biological taxa--are appropriate for studying group-level cultural variation. Here, we describe a spatially explicit simulation model that can be used to generate data with known degrees of horizontal donation. We review previous results from this model showing that horizontal transmission increases the type I error rate of phylogenetically independent contrasts in studies of correlated evolution. These conclusions apply to cases in which two traits are transmitted as a pair, but horizontal transmission may be less problematic when traits are unlinked. We also use the simulation model to investigate whether measures of homology (the consistency index and the retention index) can detect horizontal transmission of cultural traits. Higher rates of evolutionary change have a stronger depressive impact on measures of homology than higher rates of horizontal transmission; thus, low consistency or retention indices are not necessarily indicative of 'ethnogenesis'. Collectively, these studies demonstrate the importance of using simulations to assess the validity of methods in cross-cultural research.
Duke Scholars
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Related Subject Headings
- Reproducibility of Results
- Phylogeny
- Models, Theoretical
- Humans
- Evolutionary Biology
- Cultural Evolution
- Cross-Cultural Comparison
- 32 Biomedical and clinical sciences
- 31 Biological sciences
- 11 Medical and Health Sciences
Citation

Published In
DOI
EISSN
ISSN
Publication Date
Volume
Issue
Start / End Page
Related Subject Headings
- Reproducibility of Results
- Phylogeny
- Models, Theoretical
- Humans
- Evolutionary Biology
- Cultural Evolution
- Cross-Cultural Comparison
- 32 Biomedical and clinical sciences
- 31 Biological sciences
- 11 Medical and Health Sciences