National Research Council of Italy

Institute of Biosciences and BioResources

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IBBR Webinars


Landscape genomics approaches for an adaptive silviculture applied to beech stand

Cesare Garosi 
DAGRI - Dip. di Scienze e Tecnologie Agrarie, Alimentari, Ambientali e Forestali - Italy

December 15, 2021 (11:30-12:30)
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Abstract: Genetic variation is crucial for the fitness and survival of individuals and the ability of species to adapt to environmental change. Within each population, genetic changes, plasticity and evolvability result from the combination of random and selectively oriented processes. Silviculture displays a direct impact on the evolution drivers by acting on environmental conditions: competition dynamics and other abiotic and biotic factors. Some types of silvicultural management can lead to selections that influence the spatial grouping of reproductive individuals and therefore the gene flow level. Forest practice should simultaneously accelerate genetic adaptation by promoting the response of forest populations to known environmental changes and preserve genetic diversity as a reservoir of future options for responding to unknown changes. In this context, landscape genomics, a research approach that combines population genetics, landscape ecology, and spatial analytical techniques, has emerged as a flexible analytical framework for understanding the interactions between environmental heterogeneity and adaptive genetic variation. The main goal of this project is to use Landscape genomics approach to evaluate the effects of silvicultural treatments on forest genetic resources (FGR) in Fagus sylvatica L. (Fs) forests through an adaptive approach. This approach will permit to determine if the silvicultural treatment applied is able to maintain or increase the genetic variability of Fagus sylvatica stands. Therefore, beech stands subjected to different silvicultural regimes will be analysed in order to assess the genetic structure and correlate it to environmental variables, and to develop adaptive silviculture strategies. The landscape genomics approaches that will be used involve the analysis of different types of data in order to define, through the use of spatial analytical techniques, any statistical correlations, so as to test the landscape-genetic relationships explicitly and quantitatively. The analyses conducted in this project will allow us to precisely investigate how environmental characteristics influence the micro-evolutionary processes of gene flow and drift, and consequently the spatial genetic structure of forest stands. Specifically, the analyses will allow us to identify many allelic variants associated with adaptation to environmental stresses; obtain correlation of adaptive diversity data with environmental variables; and provide data on the status and trends in adaptive capacity of forest stands. This information will be used to guide future silvicultural interventions toward maintaining and, if possible, increasing genetic variability

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