Patterns of population structure and adaptive genetic variation in alpine populations of Picea abies (L.) Karst.

Forest trees dominate many alpine landscapes and are currently exposed to changing climate. Picea abies (L.) Karst (Norway spruce) is one of the most important conifer species of the Italian Alps due to its ecological and economical relevance. Natural populations of this species are found across steep environmental gradients with large differences in temperature and moisture availability. Steep environmental gradients represent interesting models to study the interaction between natural selection and gene flow, especially when aiming to understand adaptation processes under global change. The present work aims to understand adaptive responses to changing climate by determining and quantifying patterns of genetic diversity in natural population of P.abies. a wide array of potential candidate genes was tested, by means of Single Nucleotide Polymorphisms (SNPs), for correlation with climatic and environmental parameters at different spatial scales: i) a geographical scale corresponding to the natural distribution of P.abies across the Italian Alps and ii) at a regional scale on the Eastern Italian Alps. Weak population structure was revealed at the geographical scale with only one population clearly divergent from the unique major genetic cluster identified. At the regional scale, hierarchical analyses of molecular variance revealed that most of the genetic variability was found within populations (ca. 99%), and small but significant variation was also found due landscape features (ca. 0.38%). In order to detect potentially adaptive markers, classical FST outlier approaches were first applied and five outlier loci were revealed at broad scale, while contrasting results were obtained at the regional scale according to the model used. Subsequently, environmental association analysis were performed: at the geographical scale temperature and precipitation were found to influence allelic variation at seven polymorphic loci, while at the regional scale, the Alpine topography resulted a potential adaptive determinants at 19 polymorphic loci, thus considered of ecological relevance. The results obtained in this study may provide relevant information for forestry management and genetic conservation, to understand and quantify the effect of climate change on conifer species as well as their adaptive potential.