An interdisciplinary story-and-simulation approach for assessing forest type changes and shifts in ecosystem service potential

Abstract

Forest management has increasingly shifted from timber-focused production to multifunctionality, requiring scenario approaches that integrate socio-economic contexts and expert knowledge. For robust assessments of ecosystem service potentials (ESP), three key dimensions must be addressed: realism, by incorporating expert-based knowledge and socio-economic constraints; scalability, through standardized modeling techniques; and comparability, by ensuring applicability across different regions and forest types. We developed an interdisciplinary “story and simulation” approach, combining expert-based Delphi assessments with spatially explicit scenario modeling to assess ESP changes in Bavaria, Germany. This method integrates stakeholder perspectives with empirical ecosystem service models to enhance realism while maintaining scalability and comparability for broader applications. We assessed three scenarios of forest change: a Status Quo Scenario with stable drivers, an Intensified Use Scenario, and a Close-to-Nature Forestry Scenario. Across all scenarios, a transition from conifer-dominated forests toward mixed and broadleaf forests was expected, affecting between one-third and nearly half of the current coniferous forest area. The empirical ESP models revealed stable ESP levels at the landscape level, with only minor scenario-driven variations. We show that including socio-economic factors through an expert-driven approach reveals more moderate shifts than those predicted by purely optimization-based models. The projected transition towards mixed forests aligns with current European forest policy trends, but the speed and extent of this shift remain uncertain. Our interdisciplinary framework enhances realism by incorporating expert knowledge, improves scalability by utilizing empirical ESP models, and ensures comparability through a structured, transferable approach. This methodology provides a robust foundation for evidence-based forest policy, adaptable to diverse forest ecosystems and governance structures.