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Int. J. Mol. Sci. 2011, 12(2), 865-889; doi:10.3390/ijms12020865
Article

Comparison of Bayesian Clustering and Edge Detection Methods for Inferring Boundaries in Landscape Genetics

1,2
, 3,†
, 4
, 5
 and 1,6,*
Received: 15 December 2010; in revised form: 18 January 2011 / Accepted: 19 January 2011 / Published: 25 January 2011
(This article belongs to the Special Issue Advances in Molecular Ecology)
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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.
Keywords: landscape genetics; genetic boundaries; spatial Bayesian clustering; edge detection methods landscape genetics; genetic boundaries; spatial Bayesian clustering; edge detection methods
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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MDPI and ACS Style

Safner, T.; Miller, M.P.; McRae, B.H.; Fortin, M.-J.; Manel, S. Comparison of Bayesian Clustering and Edge Detection Methods for Inferring Boundaries in Landscape Genetics. Int. J. Mol. Sci. 2011, 12, 865-889.

AMA Style

Safner T, Miller MP, McRae BH, Fortin M-J, Manel S. Comparison of Bayesian Clustering and Edge Detection Methods for Inferring Boundaries in Landscape Genetics. International Journal of Molecular Sciences. 2011; 12(2):865-889.

Chicago/Turabian Style

Safner, Toni; Miller, Mark P.; McRae, Brad H.; Fortin, Marie-Josée; Manel, Stéphanie. 2011. "Comparison of Bayesian Clustering and Edge Detection Methods for Inferring Boundaries in Landscape Genetics." Int. J. Mol. Sci. 12, no. 2: 865-889.



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