2025/07/04 by Robin Sandfort, Jörg Fabian Knufinke, R.A. Koscher +2 · 1 voice
Energy · Environmental Science · Social Sciences · #Arctic and Russian Policy Studies #Coastal and Marine Management #Global Energy and Sustainability Research
paper · pdf · doi:10.1080/14615517.2025.2538951
openalex publication_date 2025/07/04 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/15
The urgent need to mitigate climate change and to transition towards renewable energy sources has intensified the pressure on land resources and biodiversity. This transition, while essential for reducing carbon emissions, poses significant challenges to biodiversity conservation. The complexity of ecosystems and the potential impacts of renewable energy development exacerbate these challenges. Current practices in spatial energy planning and Environmental Assessments (EAs), often suffer from deficiencies in data quality and availability. These deficiencies hinder the accurate assessment of impacts on species, habitats, and biodiversity, leading to delays in decision-making processes and potential conflicts between conservation goals and energy development objectives. Based on case study analysis in the field of SEA and EIA in two Austrian federal states as well as an expert workshop with practitioners from five Austrian federal states, this article discusses to what degree innovative methodological approaches, particularly those supported by advanced digitalization and artificial intelligence (AI), offer promising solutions to these challenges. Based on our findings, these advancements are likely to improve the accuracy and efficiency of environmental monitoring, facilitate early conflict identification, and support evidence-based decision-making in energy planning. By addressing the current limitations in data integration and quality control when implementing AI-supported methods, this research informs successful pathways towards more sustainable and biodiversity-friendly energy transitions.