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The aim of the project "Adaptation of autochthone and culturally valuable Austrian Pine Forests to future climatic conditions with special reference to aspects of forest pathology and interspecific genetic variation", which is described in detail in the project application of the BFW to the Austrian Ministry of Sustainability and Tourism, is to investigate measures of adaptation of ecologically valuable forest ecosystems dominated by Austrian Pine to climatically-induced epidemics of Diplodia shoot dieback (Diplodia sapinea). For that purpose the intraspecific variation of susceptibility of Pinus nigra to Diplodia sapinea should be tested and utilized. Within this project the following aspects will be adressed by the tasks carried out at the Institute of Forest Entomology, Forest Pathology and Forest Protection, BOKU, Vienna: • Laboratory investigations with regard to the selection and phenotyping of resistant mother trees of Pinus nigra (working package 1) • Providing assistance and support on investigations aiming to evaluate the resistance of clones or ramets from the clone archive (working package 2). • Development and implementation of a new seed control protocol taking into account infections by Diplodia sapinea (working package 3). • Assistance in the course of the revision of the currently approved seed lots for Pinus nigra in Austria (considering the genetic resistance of pine provenances to Diplodia sapinea) (working package 4). • Documentation of the above described tasks via protocols and scientific reports; data analyses and electronic data procession; provision of data to the BFW
Research project (§ 26 & § 27)
Duration : 2000-07-01 - 2002-12-31

Estimating regeneration establishment is a hampered by the difficulty in collecting regeneration data and random impacts in the occurrence of regeneration. Artificial neural networks represent a computational methodology widely used to uncover the structure of a large variety of data. In general, one may recommend the application of neural networks in areas characterized by noise, poorly understood intrinsic structure and changing characteristics. Each of those characteristics is present in predicting regeneration establishment within uneven aged mixed species stands. In this project we develop a design and estimation procedure to predict regeneration establishment using data from the experimental forest, University of Agriculture in Vienna, Austria. The result of the study should provide us with tools to estimate the number of juvenile trees per unit area, the relative percentage of individuals by tree species and the mean regeneration height needed to initialize existing juvenile tree growth models.
Research project (§ 26 & § 27)
Duration : 2016-12-01 - 2019-11-30

Forests are increasingly exposed to climate-driven biotic and abiotic disturbances. Climate change could thus jeopardize forests' capacity to deliver ecosystem services. There is therefore an urgent need to adapt forest management so as to promote and improve forest resilience at different spatial and temporal scales. Mixed forests are considered as one of the main options for adapting to and reducing risks of climate change. Higher tree species diversity is expected to provide higher productivity, higher temporal stability, higher resistance and resilience to disturbances and a more diverse portfolio of ecosystem services. However, knowledge about how to design and manage mixed forests to achieve these potential benefits is still lacking. REFORM aims at identifying the most optimal composition and management of mixed forests in order to reduce natural and socio-economic impacts of climate change. REFORM is based on data from observational, experimental and modelling platforms provided by twelve partners from ten countries covering different bioclimatic regions in Europe. It will investigate mixed forest features, like species composition, mixing patterns, stand age and density, that best explain resistance and resilience to biotic and abiotic disturbances. It will define the management options to achieve and maintain these optimal mixed forest features. The impact of these management alternatives on the provision of ecosystem services will be also evaluated. REFORM will provide forest managers with practical tools for increasing resilience of mixed forests using a scenario analysis at different scales, including local-adapted silviculture guidelines, forest models, and transnational training forest networks. The project will make recommendations to forest policy makers for the promotion of resilient mixed forestry.

Supervised Theses and Dissertations