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Research project (§ 26 & § 27)
Duration : 2016-12-01 - 2020-05-31

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.
Research project (§ 26 & § 27)
Duration : 2012-01-01 - 2016-06-14

Growth and yield of tree species as compared between mono-specific and in mixed species stands is an old, yet still unsolved problem. While there are quite a lot of recent studies for the mixtures of Norway spruce and common beech, there is a lack of studies of larch- and spruce mixtures, which frequently grow in the mountainous areas of the Eastern Alps. Thus, the growth efficiency of these two species, growing in mono-specific and in mixed stands will be studied. There are two reasons why a species’ growth may be different in a mixed and in a monospecific stand. First, a tree with a given leaf area may receive different amounts of light if the neighbouring trees are of the same species or from another species. In this case the light use efficiency (growth per absorbed light) could be the same even if the leaf area efficiency (growth per m² leaf area) were different. Second, depending on the mixture the tree species may change its rooting behaviour or its shade tolerance and thus exhibit different light use efficiency. Both these effects depend additionally on the trees’ dominance and on the crown disengagement, thus on the proportion of the stand area which is available to the tree. A tree, even with the highest light use efficiency, may be very inefficient on the level of the stand area if it has too much space available. Thus, at first we will investigate in 12 stands how the light use efficiency and the leaf area efficiency depend on the species, the mixture, the stand age and the stand density on the one hand; and on the dominance, on the other hand. Then we will find a definition of the stand area available for a species by comparing an individual tree approach with the approach via potential stand density. Once, this definition found, we will investigate how the area efficiency (growth per unit of stand area) depends on the stand age, the stand density and the species mixture.
Research project (§ 26 & § 27)
Duration : 2012-05-02 - 2016-01-31

One difficulty for the evaluation of climate change impact studies arises from the use of spatially interpolated climate data as ecosystem model input. Climate interpolation models are usually validated by cross validation, using weather stations that have not been included in the data set used for interpolation. Here, error statistics cannot be given for places where there are no weather stations. This applies especially to alpine regions, where the effect of topography on climate is highly relevant. The objective of this project is to use forest growth data (increment cores and dendrometer measurements) sampled along altitudinal gradients with different aspect as proxy data to validate a climate interpolation model in terms of its predictions of temperature, precipitation and solar radiation. The project focuses on Norway spruce and Swiss stone pine at 4 high altitude regions near alpine barrier lakes in Tyrol, Austria.

Supervised Theses and Dissertations