The assessment of ES can be carried out in different levels of detailedness and technical complexity. A common approach is to classify these approaches into 3 different “tiers”. They provide a rough orientation on the assessment characteristic with transitional versions being possible (Grêt-Regamey et al. 2017; Maes et al. 2014) 1) 2):
Tier 1: The most basic approach assesses ES by using existing, widely available (large-scale) datasets (like CORINE for Europe) as a proxy for the provision of certain ES. Most ES indicators on this tier can be served using land use and land-cover data, biodiversity monitoring maps, national forest inventories, etc. On this tier ES may also be scored by expert estimations based on simple cartographic representations or even without them. Therefore, the used indicators must be of direct dependency of specific ecosystems (or other mapped units), i.e. spatially explicit or area/size-based.
Tier 2: Land use data is linked to different datasets according to known relationships between land use and ecosystem services provision and supplemented with local/regional/national data. Based on these relationships, the capacities of different land use to provide ecosystem services can be quantified at different locations and aggregated at different scales. For example, in order to estimate wild berry production, literature data or expert based scores on berry production can be linked to different forest types and mapped at the country scale (up-scaling).
Tier 3: It describes the modelling of biophysical processes in a GIS or in other software instead of linking indicator data through simple relationships. E.g. berry production may be assessed by modelling the spatial distribution of wild berry species using climate data as well as other environmental data relevant to the distribution of plant species.
Within AlpES indication according to tier 1, 2 and 3 are used. Tier 1 will be used for direct stakeholder involvement particularly within the test regions and for cultural ecosystem services. Tier 2 and 3 will be used for all other indicators depending on their complexity and the available data and methods.