Research

Hornbeam (Carpinus betulus) is an interesting tree species for climate fit forests of the future. It belongs to those species that are rarely affected by severe damaging factors. However, since 2024 extensive dieback of hornbeam trees in the natural oak-hornbeam forest community in forests of the owner “Urbarialgemeinde Schattendorf” (Northern Burgenland) has been observed. The aims of the pre sent project are to clarify the cause of this hornbeam dieback, which is presumably incited by pathogenic fungi. Likewise, the importance of tree species composition, density of hornbeam and environmental factors on hornbeam dieback shall be investigated. Moreover, differences regarding susceptibility respectively tolerance shall be examined, in order to assess the risk of the native tree species hornbeam towards the causal agents of horn beam dieback. Based on the forest pathological analyses, preventive and control measures as well as silvicultural measures will be reviewed, discussed with the forest owners and finally recommended for implementation. The investigations are carried out in the affected oak-horn beam forest of the “Urbarialgemeinde Schattendorf” as well as in the laboratories and experimental areas of the Institute of Forest Entomology, Forest Pathology and Forest Protection of BOKU University (IFFF-BOKU).

Bark beetle outbreaks, particularly by the European spruce bark beetle (Ips typographus), represent the most significant biotic disturbances in Austrian forests, with serious ecological and economic consequences. In view of the increasing damage recorded across Europe over the last two decades, there is a great demand for practical risk assessment and early warning systems to support bark beetle management. The aim of the proposed project is to further develop the Austrian bark beetle dashboard, which was published in May 2024, using machine learning-based risk assessment and prediction models. These models are intended to predict the expected extent of damage at the forest district level (impact model) and the probability of damage at a high resolution of 10 metres for the whole of Austria (probability model). Through the integration of modern remote sensing technologies and machine learning methods, the bark beetle dashboard is to be further developed in the medium term into a holistic risk assessment system that can also function as an early warning system. This will provide efficient support to the forestry industry in mitigating damage caused by the European spruce bark beetle and other bark beetles, adapting European forests to climate change by converting them into mixed forests, and preserving important ecosystem services for future generations.

The IPS project is developing an innovative sustainable control method to reduce the impact of forest insect infestations on forests. Bark beetle infestations (Ips typographus) and weevil infestations (Hylobius abietis) on various conifers are increasing, also as a result of increasingly frequent extreme events that weaken forest ecosystems. So far, there is no effective solution that could reduce these harmful effects, except to remove infested trees or trunks promptly. Our goal is to develop and test products that can reduce the impact of bark beetles and weevils by acting on their microbiome and leading to the death of the insect. These laboratory-proven products are based on plant extracts and mineral substances and are therefore ecologically neutral. They also help to protect forest ecosystems and thus contribute to waste reduction and the creation of new value chains in the sense of the circular economy.