Management approaches in decision support systems to mitigate the risk of natural disturbances in European temperate and boreal forests –a review

• Forest management needed to mitigate impact of disturbances on forest productivity. • DSSs with disturbance models enable identify and mitigate disturbance risks. • Proactive strategies reduce disturbance risk but trade off with ecosystem services. • Reactive measures address immediate damage but offer limited long-term mitigation. • Forest managers can use DSSs to enhance boreal and temperate forest resilience. Natural disturbances such as windthrow, bark beetle outbreaks, root rot, wildfire and snow or ice damage are increasingly affecting temperate and boreal forests under climate change, creating a need for adaptive management to maintain forest resilience and productivity. Decision Support Systems (DSSs) integrating disturbance dynamics can support managers in adjusting management to these evolving risks. This review synthesizes management recommendations derived from DSSs incorporating natural disturbance models in European temperate and boreal forests. The results reveal that most DSSs rely on simulation models applied at strategic spatial and temporal scales, with particular emphasis on windthrow risk, bark beetle outbreak, and root rot damage. Conifer-dominated, even-aged plantations appear most vulnerable to multiple disturbances, whereas mixed-species stands show greater resilience. Simulations underscore that proactive strategies, such as shortening rotation length, species mixing, and targeted thinning, can reduce disturbance risks, but compromise timber revenues and other ecosystem services. Reactive strategies, including salvage logging and sanitary cuttings, address immediate damage but offer limited long-term mitigation. Optimization methods can help mitigate the trade-offs between profitability and forest resilience by minimizing disturbance risk and maximizing economic outcomes. While several DSSs can integrate single disturbances, only few DSSs can simulate interactions among disturbance models and climate scenarios. Complex data requirements constrain DSS application for operational forest management, restricting their use to researchers. Future DSS development should prioritize simple, applicable and accessible solutions while integrating advanced models capable of addressing diverse disturbance regimes. By leveraging advanced DSSs, forest managers can enhance forest resilience amid increasing climate-driven disturbance pressures.