Natural risks, unknown climate change (CC), adaptation capacity, fragmentation, human pressures etc., pose a threat to biodiversity at all levels, and thus to sustainability of forest ecosystems, and provision of ecosystem services. For this, it is important to have an efficient predictive model to be used in Sustainable Forest Management (SFM). To prepare applicable outputs for the EU forest areas, genetic, forest, and biodiversity data are to be implemented into the GenBioSilvi predictive model for SFM. To reach this goal in addition to data from B1, two tasks are planned.

B2.1 Biodiversity. Biodiversity is studied at three different levels as a model input: genetic, species and ecosystem level.

  • Genetic level: conservation of genetic diversity will be analysed with respect to different silviculture systems/measures. Effect of management on genetic diversity will be studied, correlations between characterised variables will be analysed.
  • Species and ecosystem level: common mycelial networks support ecosystem functioning, the carbon, nutrient and water cycling. All tree species that we shall study, rely on their ectomycorrhizal (fungal) symbionts which enhance and facilitate the functioning of fine roots in nutrient, water acquisition and translocation, and provide carbon supplies to the plants in need. However, the functional compatibility in symbiosis depends on species and provenance/population of trees, and species and strain of the symbiotic fungi, which further impacts interactions with other soil microorganisms. Therefore identification of the mycorrhizal fungi, their community structure and the soil microbiome is of utmost importance for understanding the functioning and consequently SFM of forest ecosystems, particularly post-disturbance regeneration and reforestation.

B2.2 Modelling. The elaborated information on biodiversity and genetic characterization allow to define biogenetic indicators useful to provide the best adaptive management for the forest, with respect to climate change, also taking into account the species and the different silvicultural treatment conditions. In this task a Decision Support System (DSS) will be implemented at the territorial level (forest district) for the territories to which the project is addressed. The DSS will contain the following information: (1) the distribution map of the project species; (2) the current bioclimatic map for the project species and that of the scenario expected in the following 50 years; (3) the map of the operating modes and treatment of the forests related to the project species. The DSS will be elaborated during the fourth year of the project and tested in Action B3. Our application of models will make use of national inventory data for national predictions as well as of local stand level data combined with genetic data for local conservation management support.

The final output of this Action will be the GenBioSilvi model for SFM, including adaptive forest management guidelines in collaboration with actions B1, B3 and B4, and professional background documents for forest biodiversity strategy for the EU forest areas