title: Cautions on direct gene flow estimation in plant populations.
abstract: Through simulations we have investigated the statistical properties of two of the main approaches for directly estimating pollen gene flow (m) in plant populations: genotypic exclusion and mating models. When the assumptions about accurately known background pollen pool allelic frequencies are met, both methods provide unbiased results with comparable variances across a range of true m values. However, when presumed allelic frequencies differ from actual ones, which is more likely in research practice, both estimators are biased. We demonstrate that the extent and direction of bias largely depend on the difference (measured as genetic distance) between the presumed and actual pollen pools, and on the degree of genetic differentiation between the local population and the actual background pollen sources. However, one feature of the mating model is its ability to estimate pollen gene flow simultaneously with background pollen pool allelic frequencies. We have found that this approach gives nearly unbiased pollen gene flow estimates, and is practical because it eliminates the necessity of providing independent estimates of background pollen pool allelic frequencies. Violations of the mating model assumptions of random mating within local population affect the precision of the estimates only to a limited degree.
authors.affiliation: Institute of Biology and Environmental Protection, Department of Genetics, Bydgoszcz University, ul. Chodkiewicza 30, 85-064 Bydgoszcz, Poland. burczyk@ab-byd.edu.pl
authors.forename: Jaroslaw
authors.initials: J
authors.lastname: Burczyk
authors.forename: Igor J
authors.initials: IJ
authors.lastname: Chybicki
mesh_terms: D003198:Computer Simulation; D004641:Emigration and Immigration; D005787:Gene Frequency; D005828:Genetics, Population; D005838:Genotype; D008957:Models, Genetic; D010944:Plants / Q000235:genetics*; D011058:Pollen / Q000235:genetics*; D012098:Reproduction / Q000235:genetics; D015983:Selection Bias