Research

In the NextBON project we will transform European biodiversity monitoring from its current fragmented state into an integrated, policy-responsive system as the present monitoring landscape reflects decades of parallel development under different European and global frameworks. NextBON responds directly to the Horizon-CL6-2025-01-BIODIV-04 call by operationalising the EuropaBON framework and advancing Europe’s biodiversity monitoring capacity through the deployment of innovative technologies, systematic integration, and harmonisation of national observation programmes. Rather than replacing existing efforts, the project fills critical gaps, strengthens validation and comparability, and ensures that the diverse datasets can be mobilised at European scale. We will systematically integrate existing frameworks by strengthening and aligning national, regional, and thematic initiatives under a common structure, ensuring interoperability and FAIR data principles. We will validate and deploy innovative monitoring techniques through eDNA metabarcoding for multi-taxa and invasive species detection, AI-supported passive acoustic and camera-trap networks for scalable species and habitat monitoring, and satellite and drone-based Earth observation combined with machine-learning habitat classification and Essential Biodiversity Variables (EBVs) derivation. We will also deploy a tiered in-situ network in 9 Case Study areas across terrestrial, freshwater, and marine ecosystems to generate Essential Biodiversity Variables and transform them into policy-relevant indicators and decision-support tools. To fill the gap between theory and applications we will establish a scientifically rigorous foundation for operationalizing EBVs into policy relevant Enhanced Biodiversity Indicators (EBIs) across terrestrial, freshwater, and marine systems allowing monitoring the success of the European and global frameworks and mechanisms by systematic assessment of biodiversity state, its drivers, and trends across all ecosystems. From the resulting pool of indicators, key policy-relevant indicators are prioritized in one or more workshops with participation of internal colleagues, competent authorities, external experts and interested stakeholders. The indicators will directly feed NRR targets, which support directly the achievement of the goals of the EU Biodiversity Strategy for 2030 and of the EU Climate Law. All activities work in concert to harmonise Europe’s monitoring landscape, deliver high-resolution biodiversity data, and provide actionable insights for restoration and conservation policy.

In the WindPlan project as part of IEA Wind Task 62, a practical, participatory and inclusive planning process is conducted. Various 3D and data visualisation methods are combined with gamification and planning methods in so-called LandscapeLabs! The aim is to develop and test suitable tools to improve the local to regional planning and communication of wind energy projects. Styria will be used as a case study, where a prototype revision of existing wind suitability and exclusion zones will be carried out with decision-makers, stakeholders and laypeople. The project also seeks to involve groups in the planning process that have so far been underrepresented in policy- and decision-making. The results will make a valuable contribution to achieve the Austrian climate and energy targets for 2040 and will serve as an international example of best practice within the framework of the IEA Wind Task 62.

The restoration of peatlands is increasingly perceived as a cost-effective and efficient way of reducing greenhouse gas emissions. It is therefore expected that the restoration of peatland soils can make a significant contribution to achieving national emission targets. Cultivated and drained organic soils also represent a potentially significant source of emissions in Austria. However, there is currently a lack of information and analysis on the cost-effectiveness of peatland restoration measures in Austria, taking into account different restoration measures and analyzing the reasons for the differences and ranges in costs and effectiveness. Efforts must therefore be made to systematically collect data on costs and assess the factors that explain cost differences, including spatial factors. The Money4Moor research project aims to collect detailed data on restoration costs to enable a more nuanced analysis of cost differences between different spatial scales and restoration measures.