Population genetics of Silene acaulis in the High Arctic , RiS ID 6166

Although temperature seems to be the overriding driving factor of population genetics in the Arctic, local factors like edaphic conditions and competition, are also influencing. In addition, the stochasticity related to environmental variables is expected to affect several demographic traits of species inhabiting the Arctic. Therefore, it is important that we extend our basic knowledge about plant responses to various environmental variables; especially those that are expected to increase or decrease beyo nd their presently known fluctuation. Linking the investigation of demography and life history traits with molecular analyses seems a promising approach in this manner. Based on various species properties, Silene acaulis has been chosen as a study species . The cushion grows successively in size, as the individual plant gets older. Thus, growth rates have been calculated and age can be estimated. The flowers are usually gynodioecous (females or hermaphrodites), and there has been recorded variation in the sex ratio depending e.g. on environmental conditions. Foremost, these properties strongly facilitate a retrospective and indirect investigation of various population properties and investigation of associations/correlations with environmental variables. I n order to reveal which factors it is that cause the variation present, it is necessary to sample from populations over a large spatial area so that regional and local influence may be separated. Although several studies have looked at the demography of t his plant, none in depth population genetic studies has been performed. Our main aim is to investigate how important life history parameters like reproduction, dispersal, establishment and gender distribution are affected by dominant environmental variabl es in two different habitat types. Further we will use microsatellites to look for correlations between genetic structure and possible trends in relation to the different parameters and environmental variables.