Version of Record online: 15 FEB 2012
© 2012 Blackwell Publishing Ltd
Volume 21, Issue 9, pages 2092–2105, May 2012
How to Cite
BANKS, S. C. and PEAKALL, R. (2012), Genetic spatial autocorrelation can readily detect sex-biased dispersal. Molecular Ecology, 21: 2092–2105. doi: 10.1111/j.1365-294X.2012.05485.x
- Issue online: 17 APR 2012
- Version of Record online: 15 FEB 2012
- Received 29 September 2011; revision received 12 December 2011; accepted 16 December 2011
Appendix S1 Steps in the simulation of sex specific dispersal patterns for multilocus spatial autocorrelation analysis.
Appendix S2 What is the effect of varying the autocorrelation analysis distance class size?
Appendix S3. Map showing the sampling locations of 380 agile antechinus (Antechinus agilis) captured near Tumut, NSW, Australia.
Appendix S4 Temporal variation in the first distance class (0–100 m) autocorrelation r values for males and females during a 100-generation simulation involving female dispersal over a mean distance of 100 m and male dispersal over a mean distance of 500 m.
Appendix S5 Effects of the number of individuals sampled (50, 100, 250 or 500), the number of loci genotyped (5, 10 or 25) and the number of alleles per locus (five or 10) on the distribution of 0–100 m multilocus spatial autocorrelation r values of simulated females and males under different dispersal scenarios.
Appendix S6 Spatial vs. random subsampling (10 loci/10 alleles).
Appendix S7 Quantification of the type I (false positive) and type II error rates for the three multilocus spatial autocorrelation heterogeneity tests (T2, Omega and bootstrap CI) using 50 m, 100 m and 200 m distance class sizes for the spatial analysis.
Appendix S8 Table and graph showing FST (between populations) and spatial autocorrelation r (at the 0–100 m distance class in a pooled population analysis) resulting from simulations of five populations with different migration rates.
Appendix S9 Spatial autocorrelation analysis for sub-populations.
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