Research

This research project will revolutionize forest inventory throughout Austria in a long-term and sustainable way. Thus, the project is of nationwide relevance . Due to the practical and target group oriented nature of the project, the research results will be available to a broad audience and will provide forest owners, forest enterprises, service providers and authorities with a planning tool for the creation and maintenance of climate-smart forests. The methods to be developed in the project should be implementable as a standard solution for the highly precise and spatially explicit inventory of raw wood reserves and the operational planning of forest enterprises based on it. By combining modern, laser-based field survey methods (partly with commercially available mobile devices such as Apple iPhone and iPad) and remote sensing methods, planning uncertainties of careful and sustainable forest management can be minimized, the productivity of different timber harvesting methods can be predicted and thus the risks and costs of forest enterprises can be reduced. The methods thus contribute to the preservation of protective forest tasks and nature conservation functions as well as to the establishment of "climate-smart" mountain forests in Austria. The Austrian forest ownership communities and larger forest enterprises with regular sample inventory and forest management benefit from digital inventory solutions with person-carried laser scanners (PLS) as well as the area-accurate stock and assortment and productivity forecasts achieved by combining PLS data with remote sensing data. Low-threshold access to an easy-to-use and digital inventory and planning tool will create incentives for regular and sustainable forest management in Austria's small private forests.

The forest inventory provides information and data as a basis for decision-making in forest planning with regard to the implementation of operational interventions and the achievement of economic objectives. In addition to traditional surveying methods, forest inventories with laser scanners have recently become increasingly important. While terrestrial laser scanners (TLS) have been in use for some time, the first experiences and research results on forest inventories with mobile person-carried laser scanners (PLS) have recently become available. In the last six years, automatic algorithms for the evaluation of 3D laser data have been developed at the BOKU Institute of Forest Growth, thus laying the foundation for a modern sensor-based forest inventory. The measurement process with PLS takes about 10 min for a sample circle with 20 m radius. In a series of publications, a large number of reference measurements have shown that tree cover rates of over 97% can be achieved. The mean deviation (bias) of the BHD measurement is 0 - 0.7 cm, with an average error (RMSE) of 1.5 to 3 cm. Tree heights can be automatically determined with a mean deviation of0 to 0.2 m and an average error of 1.5 to 2.1 m. With the portable laser scanner, precise measurement values can now be determined in three-dimensional space in a short time, and the new laser-based forest inventory procedure is thus on the verge of general practical applicability. Together with the Austrian Federal Forests, the new laser-based digital forest inventory procedure is now to be tested in practice on around 300 sample areas in the Ebensee forest district, both in the productive forest and in the protection forest of the Rindbach catchment area. Furthermore, the automatic evaluation routines are to be further developed. In addition to the traditional inventory parameters, the laser scans will be used to automatically and precisely derive indicators of regeneration density, crown closure for the establishment of fir regeneration, and deadwood stocks.

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.