## 2 Decision Support System
### The Mapping Tool
This function overlaps each management unit of the property with different types of nature protection areas (e.g., Natura 2000 areas, national natural reserves, etc.) and provides the percentage of each management unit area intersecting the different types of nature protection areas. As for the \"water protection computation\" case, this function warns the user on legal management constraints and supports the identification of biodiversity hotspots. The Mapping tool also offers three additional functions computing biodiversity indicators. First, the _butterflies forest specialist computation_ computes the number and type of forest-specialist butterfly species that are potentially present in each management unit. Similarly, the _butterflies generalist computation_ provides similar information for butterfly species that are found both in forests and open landscapes. Butterflies are one of the best indicators of biodiversity, and their monitoring records can be used to prioritise the types of land management and for environmental assessments of conservation strategies [26]. The third function computes the number and type of Habitat Directive [27] protected species that are potentially present in each forest stand. These three functions rely on the species distribution models (SDMs) computed by the Luxembourgish Ministry of Environment. An SDM aims to predict the presence records of a species with spatially explicit environmental variables (e.g., temperature, precipitation, topography, geology, and land use). Overall, mapping the predicted distribution of endangered species provides key information to support multifunctional forest management. By knowing the location in which certain species are more likely to be found, it is possible to identify stands in which specific forest management favouring this species can be applied. Such information can also help to identify potential management trade-offs with the conservation of other species or with other ESs. This function of the Mapping tool can be applied to other species of functional groups and in different countries, provided that SDMs are available. The final function offers indicators concerning cultural ESs and specific outdoor recreation. The _recreation computation_ command computes the average, maximum, and minimum score of the outdoor recreational attractiveness in accordance with two types of archetypical outdoor recreation user groups [28]: convenience recreationists and sportive recreationists. The former group reflects recreationists preferring an accessible and close-to-home landscape with a high level of attractiveness or scenic beauty, possibly with proximity to water with paths or trails. The sportive recreationists privilege landscapes allowing for outdoor sport recreation (running, Nordic walking, cycling, mountain biking, orienteering, etc. ), possibly with marked tracks and good air quality. Following the framework of [PERSON] et al. [29], the recreation potential module in the Mapping tool assigns a score between 1 (low) and 5 (high), reflecting the potential of a specific area (in our case, a 10 m \(\times\) 10 m pixel) for outdoor recreation of a specific user group. This recreation potential score is computed as the combination of landscape characteristics (e.g., vegetation structure, water proximity, air quality, and presence of marked tracks or paths) weighted by the value each user group assigns to them (data obtained from [29]). The pixels' scores are then averaged at the management unit level. The results generated by the seven functions are then displayed in the user interface in tabular and map formats. The user can download the map tables displayed on the user interface in csv and jpeg formats. Maps are generated automatically with a title, legend, background topographic map, scale, and north arrow, ready to be used in reports and other media.