Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics

International Journal of Molecular Sciences
By: , and 

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Abstract

Recently, techniques available for identifying clusters of individuals or boundaries between clusters using genetic data from natural populations have expanded rapidly. Consequently, there is a need to evaluate these different techniques. We used spatially-explicit simulation models to compare three spatial Bayesian clustering programs and two edge detection methods. Spatially-structured populations were simulated where a continuous population was subdivided by barriers. We evaluated the ability of each method to correctly identify boundary locations while varying: (i) time after divergence, (ii) strength of isolation by distance, (iii) level of genetic diversity, and (iv) amount of gene flow across barriers. To further evaluate the methods' effectiveness to detect genetic clusters in natural populations, we used previously published data on North American pumas and a European shrub. Our results show that with simulated and empirical data, the Bayesian spatial clustering algorithms outperformed direct edge detection methods. All methods incorrectly detected boundaries in the presence of strong patterns of isolation by distance. Based on this finding, we support the application of Bayesian spatial clustering algorithms for boundary detection in empirical datasets, with necessary tests for the influence of isolation by distance. ?? 2011 by the authors; licensee MDPI, Basel, Switzerland.

Additional publication details

Publication type Article
Publication Subtype Journal Article
Title Comparison of Bayesian clustering and edge detection methods for inferring boundaries in landscape genetics
Series title International Journal of Molecular Sciences
DOI 10.3390/ijms12020865
Volume 12
Issue 2
Year Published 2011
Language English
Larger Work Type Article
Larger Work Subtype Journal Article
Larger Work Title International Journal of Molecular Sciences
First page 865
Last page 889