Environmental and socio-economic developments induce land-use changes with potentially negative impacts on human well-being. To counteract undesired developments, a profound understanding of the complex relationships between drivers, land use, and ecosystem services is needed. Yet, national studies examining extended time periods are still rare. Based on the Special Report on land use, land management and climate change by the Austrian Panel on Climate Change (APCC), we use the Driver-Pressure-State-Impact-Response (DPSIR) framework to (1) identify the main drivers of land-use change, (2) describe past and future land-use changes in Austria between 1950 and 2100, (3) report related impacts on ecosystem services, and (4) discuss management responses. Our findings indicate that socio-economic drivers (e.g., economic growth, political systems, and technological developments) have influenced past land-use changes the most. The intensification of agricultural land use and urban sprawl have primarily led to declining ecosystem services in the lowlands. In mountain regions, the abandonment of mountain grassland has prompted a shift from provisioning to regulating services. However, simulations indicate that accelerating climate change will surpass socio-economic drivers in significance towards the end of this century, particularly in intensively used agricultural areas. Although climate change-induced impacts on ecosystem services remain uncertain, it can be expected that the range of land-use management options will be restricted in the future. Consequently, policymaking should prioritize the development of integrated land-use planning to safeguard ecosystem services, accounting for future environmental and socio-economic uncertainties.

Anthropogenic GHG emissions add a fast reinforcing feedback cycle to global carbon dynamics which continues to influence GHG concentrations in the Earth's atmosphere. When looking at forest carbon cycles there is potential in utilizing another feedback cycle, namely the carbon cycle involving harvested wood products. To assess the potential of the mitigation options arising from these carbon flows, the forest-based sector in Austria was modelled to assess causal links, dependencies and dynamics involved in GHG-relevant processes. Carbon dynamics were investigated in forests and forest soil carbon, the forest product chain and life-cycle analyses for substitution of conventional products with wood products in a cascade of different modelling approaches and paradigms, and the results synthesized. It was found that material use of products from domestic timber sources has the highest climate change mitigation efficiency when originating from sustainably managed forests regarding biomass stocks. The emissions saved through building up a carbon stock from harvested wood products and through emissions substitution can be as high as ∼20 years of total annual Austrian emissions in 90 years. Additional conservation measures while sustaining sawnwood production and the related GHG benefits at a high level had the highest contribution to an overall carbon sink.

Habitat degradation and fragmentation are two of the main drivers for biodiversity loss. To mitigate the negative impact of fragmentation in forests, conservation targets are increasingly addressing connectivity to facilitate the independent movement of species between habitat fragments to ensure genetic diversity and adaptation to climate change. In this article, we present a novel approach to identifying and prioritizing stepping stones for preserving connectivity based on national and regional biodiversity data for Austrian forest ecosystems. Our study identified forest areas where conservation measures should be taken to ensure future habitat connectivity by combining four indicator values with different requirements of a stepping stone habitat into a prioritization value. The four compounded indicators are: (i) the Protect Value , which includes distances to patches of protected areas with restricted management for the undisturbed development of retention areas, (ii) the Connect Value , which combines datasets of designated habitat corridors and connectivity areas in Austria based on landscape models and expert validation, (iii) the Species Value identifying species‐rich areas, and (iv) the Habitat Value identifying biotopes of high ecological value, key biodiversity areas, and sites of favorable protection status. Nonparametric tests revealed significant differences in prioritization value among the ecoregions of Austria and therefore encourage the consideration of stepping stone prioritization at local and regional context. Building upon the insights from this case study on Austrian forest ecosystems, we developed a robust framework derived from our methodology. This framework is designed to facilitate future implementations in diverse study regions, accounting for factors beyond connectivity crucial for identifying high value stepping stone habitats. We encourage adaptation of this framework to local data availability, species requirements, and local conditions. The compiled framework provides decision support for managers and conservationists for prioritizing areas to conserve and improve connectivity of forest habitats. However, it does not substitute on‐the‐ground field assessments of habitat quality and measures of functional connectivity.