B1 Landscape genomics approach for sustainable forest management
Forest Genetic Resources (FGR) conservation requires the implementation of well-planned strategies including management in forest tree populations (stands) and productive plantations, and genetic improvement programs. The strategies in FGR conservation depend on the nature of the material (e.g. tree species), timing, specific objectives (management) and scope of the program. The aim of this action is to evaluate the possibility to maintain the genetic variability of a forest stand over time in relation to close-to-nature forest management. Action B1 applies for the first time a combination of two analyses across different European Forest Types (EFTs): traditional forest structure analysis using forest inventory data and adaptive landscape genomics approach by neutral and adaptive molecular markers (nSSRs and SNPs in candidate genes). To reach its goal action B1 is divided into 3 tasks.
B1.1 Forest plot analyses. Implementation of a harmonised forest monitoring system, providing relevant qualitative/quantitative information. Field work will be carried out within plots (2500-5000 m2); the positioning of living trees, and their size (DBH and height), standard volume, crown and/or decay classes, will be determined and recorded in a database.
B1.2 Genetic analyses. The analysis will be carried out on adult trees selected according to specific characteristics (B1.1) and to minimize kinship among individuals. Adaptive genetic diversity compared with neutral data serves to correct the effect of genetic structure on adaptive diversity. In order to assess adaptive diversity, environmental and genetic variables will be correlated: a total of 20 populations of up to five tree species in EFTs in the 3 participating countries will be analysed.
B1.3 Landscape genomics. Using the data from B1.1. and B1.2 to determine the spatial genetic structure of natural populations shall support the discovery of correlations between allele distributions and environmental variation. Landscape genomics and GIS approaches, STRUCTURE, GENELAND, and allele distribution models will be used. The data collected will be centralized for the creation of a pooled database for cause-effect relationship between climatic variables and biodiversity parameters. These results will be used to define/develop actions, thresholds for management considering genetics/genomic principles for long-term evolution/adaptability and lead to harmonised list of parameters needed to implement landscape genomics approach in Dynamic Genetic Conservation Units (DCUs) and other forests.
This action will allow the appropriate conservation and use of FGR as part of Sustainable Forest Management. The proposed approach is an innovative methodology to be applied in forest management. B1 is necessary to provide data and information for implementation of Actions B2, B3, and B4