DISPERSAL, PHILOPATRY, AND INFIDELITY: DISSECTING LOCAL GENETIC SWTRUCTURE IN SUPERB FAIRY‐WRENS (MALURS CYANEUS)
MC Double, R Peakall, NR Beck, A Cockburn - Evolution, 2005 - academic.oup.com
MC Double, R Peakall, NR Beck, A Cockburn
Evolution, 2005•academic.oup.comDispersal influences evolution, demography, and social characteristics but is generally
difficult to study. Here we combine long‐term demographic data from an intensively studied
population of superb fairy‐wrens (Malurus cyaneus) and multivariate spatial autocorrelation
analyses of microsatellite genotypes to describe dispersal behavior in this species. The
demographic data revealed:(1) sex‐biased dispersal: almost all individuals that dispersed
into the study area over an eight‐year period were female (93%; n 5 153);(2) high rates of …
difficult to study. Here we combine long‐term demographic data from an intensively studied
population of superb fairy‐wrens (Malurus cyaneus) and multivariate spatial autocorrelation
analyses of microsatellite genotypes to describe dispersal behavior in this species. The
demographic data revealed:(1) sex‐biased dispersal: almost all individuals that dispersed
into the study area over an eight‐year period were female (93%; n 5 153);(2) high rates of …
Abstract
Dispersal influences evolution, demography, and social characteristics but is generally difficult to study. Here we combine long‐term demographic data from an intensively studied population of superb fairy‐wrens(Malurus cyaneus) and multivariate spatial autocorrelation analyses of microsatellite genotypes to describe dispersal behavior in this species. The demographic data revealed: (1) sex‐biased dispersal: almost all individuals that dispersed into the study area over an eight‐year period were female (93%; n 5 153); (2) high rates of extragroup infidelity (66% of offspring), which also facilitated local gene dispersal; and (3) skewed lifetime reproductive success in both males and females. These data led to three expectations concerning the patterns of fine‐scale genetic structure: (1) little or no spatial genetic autocorrelation among females, (2) positive spatial genetic autocorrelation among males, and (3) a heterogeneous genetic landscape. Global autocorrelation analysis of the genotypes present in the study population confirmed the first two expectations. A novel two‐dimensional local autocorrelation analysis confirmed the third and provided new insight into the patterns of genetic structure across the two‐dimensional landscape. We highlight the potential of autocorrelation analysis to infer evolutionary processes but also emphasize that genetic patterns in space cannot be fully understood without an appropriate and intensive sampling regime and detailed knowledge of the individuals genotyped.
Oxford University Press
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