Genetic data linking seeds directly to parents through maternal seed tissue are often hailed as the best way to obtain information on seed dispersal distances. However, DNA quality in maternally derived seed tissue is often low, leading to high rates of genotyping errors, and usually much discarding of data. This study tested and applied methods for gleaning information on seed dispersal distances from incomplete and error-prone genetic data, using the tropical tree Tabebuia rosea as a case study. Genotyping error rates were calculated and then incorporated these rates into a model to estimate seed dispersal distances using all available data. Simulations were used to evaluate the effects of both genotyping error rates and the number of seeds genotyped upon dispersal estimates. Results demonstrate the importance of calculating error rates, and the value of including incomplete genetic data in analyses in order to increase power and obtain better parameter estimates.
University of Minnesota M.S. thesis. December 2012. Major: Ecology, Evolution and Behavior. Advisor: Helene Muller-Landau. 1 computer file (PDF); iv, 52 pages.
Vargas Timchenko, Marta Isabel.
Estimating seed dispersal distances with incomplete genetic data:new methods, power analyses and a case study of the tropical tree Tabebuia rosea.
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