## 4 Discussion and Conclusions  
Multisilva, a forest management DSS, has been developed to support forest managers in addressing the demand of ESs from local stakeholders, to understand the trade-offs between different management alternatives, and to communicate the management strategy and the expected outcomes in a straightforward way. For these reasons, Multisilva could be a useful tool to support the definition and design of ES validation claims, such as the ones recently introduced by the FSC. The novelties of Multisilva, compared to existing forest management DSSs, are (i) the focus on multiple ecosystem services and the specific focus on forest management for ES provision and (ii) the coupling of different models (3 PG-mix and the different ES models) under one single simulation coordinated over a time computational model. The system presented here is based on a process-based forest growth model (3 PG-mix), which has been extended to account for six ESs: air quality, carbon sequestration, timber production, water protection, biodiversity conservation, and outdoor recreation. The Mapping tool of the system allows for visualisation and calculation of statistics of the current provision of these ESs. This supports the user in identifying ES hotspots, which can then be examined in more detail with the Simulation tool, which models a series of management actions such as thinning, trail maintenance, habitat tree retention, selective harvesting, and setting aside areas for nature conservation. A 27 ha forest plot near Flaxweiler in eastern Luxembourg has been used to demonstrate the functionality of the Simulation tool. In addition to defining various management strategies to consider, the user has the option to specify possible future climate scenarios. The tool then calculates the ES indicators for each scenario, providing a level of uncertainty for the results. Comparison of these ranges for various management strategies allows the user to determine whether any differences in the simulated results are statistically significant. The current version (v0.1.6) requires shapefiles of the area and Excel files containing the forest inventory. Possible improvements in the future could include remote data acquisition, eliminating the need for field work. The current version is developed for Luxembourg, and it is particularly well suited for extension to temperate and boreal forest regions, where only minor adjustments are needed (formatting of the inventory data and adaptation of management practice parameters). The Simulation tool could readily be adapted for application across Europe by leveraging widely accessible datasets, including meteorological data, air quality records, elevation models, and open map services. Given the availability of species-specific parameters, the tool shows strong potential for adaptation to temperate and boreal zones, making these regions especially promising for immediate implementation. For Mediterranean areas, however, the major limitation today is the lack of species-specific parameters, with only two pine species available to the best of our knowledge. For tropical areas, the tool's adaptability would face additional challenges primarily due to limited species-specific parameter data and differences in forest dynamics compared to temperate or boreal regions. While some parameters are available for common tropical species like _Eucalyptus_ and _Tectona grandis_, many tropical species lack the necessary calibration, which could impact the precision of ES simulations in these biodiverse forests. Additionally, tropical regions often experience distinct climatic conditions, such as high