## 3 Illustrative Example
### Management Scenarios and Uncertainty  
In this example, different management strategies are considered. For each of them, a 10-year simulation period, starting in January 2024, is calculated with identical initial starting conditions. The annual discount rate is fixed at 3%, the maximum slope for harvesting is 40 degrees, the percentage of bark and branches as fuelwood is 50%, the maximum diameter for firewood is 15 cm, and the annual loss to recreation without trail maintenance is set at 2%. In the first (base) case, no management actions are planned for the duration of the simulation. To identify reasonable management actions, the study area was then examined using the Mapping tool, with two potential hotspots identified (Figure 6). Two stands (35.1 and 35.2) were found to have significant overlap with the waterbodies (the Donwerbach and its tributaries). Furthermore, the hiking and cycling paths within (and along the border of) the area are clearly visible. Figure 5: The Flaxweiler study area in Luxembourg. Figure 6: Flaxweiler hotspots identified with the Mapping tool. (**Left**) recreation potential; (**right**) overlap with water bodies. One of the management actions considered is the removal of conifers in the areas overlapping water bodies to improve the water purification potential. In parcel 35.1, there are spruce trees determined to be 55 years old during the 2017 inventory, which corresponds to the rotation age of 60 recommended by the Luxembourg Ministry of Environment [55]. Furthermore, oaks in parcel 33.1 are recorded as 180 years old in the inventory. Given the rotation age of 200 years [55], their harvest also represents a reasonable management option. For the illustrative purposes of this case study, harvests of both these tree groups will be considered in some simulations, set to be performed in October 2026, with post-harvest cleaning taking place, followed by natural regeneration. A further parameter incorporated into the simulations is the investment in the maintenance of hiking and cycling trails. It is not the contention of the authors to promote any of these strategies; the parameters have been chosen purely for the purpose of illustrating the functionality of the software. An important source of uncertainty in forest management planning is forecasting of the future climatic parameters [22; 27; 56]. To address this, the software gives the user an opportunity to consider several meteorological scenarios. This is optional; if no such scenarios are provided, the climatic parameters will be obtained from the background data (as described in Section 2.4), and the output will contain single values for each predefined ecosystem service indicator for each management alternative. When alternatives are specified, by attaching a filled-in template file containing the details of each forecast, additional simulations will then be performed. In the output, ES indicators will then consist of ranges for each management alternative, giving an indication of the uncertainty associated with each indicator and allowing for more meaningful comparison of the results of management strategies. In the example here, five climatic scenarios were considered in addition to the core one: an increase in precipitation by 25%, a decrease by 25%, and three scenarios with a temperature increase of 0.2 degrees, and the rainfall unchanged, increasing, and decreasing by 25%. These values are only for illustrative purposes; users will have the opportunity to specify detailed parameters according to forecasting scenarios of their choice. A further source of uncertainty is the parameter specifying the site fertility rating (FR). While this indicator contains information about the quality of the soil and features in the 3-PG algorithms, it is a subjective estimate, with approaches for its estimation ranging from expert opinion to soil chemistry studies [57; 58; 59]. In Multisilva, this parameter is one of the input parameters required in the management scenario template.