In this module the rationale of AlpES indicators will be presented, with a focus on metadata, sources and calculation. First of all, we have to explain the reasons why AlpES chose them and, afterwards, the way they are built and calculated. The aim of this article is to provide a clear insight Into the most important AlpES tool for ES assessment, so it Is necessary to explain the process from data source to the final algorithms, organising the text in short paragraphs referring to each step, with links to external documents (e.g. list of data sources).

In the light of the myriad ES provided by the Alps, all participating AlpES partners first had to agree upon eight representative ES and their related indicators for mapping and assessment. To do so, one ES for each CICES division was selected (CICES, v4.3) considering its geographic, political and socio-ecological relevance. Then, ES indicators were chosen to describe the selected ES on the basis of data availability and the indicator’s employability and comprehensibility for AlpES target groups. Each indicator needed to represent the related ES in a way that stakeholders could easily understand and use.

For each of the eight selected ES, the AlpES team calculated three different indicators, to describe their supply, flow and demand. The project defines the term supply as the amount of an ES that is delivered by an ecosystem in a specific time period, irrespective of its actual use. The flow is the de facto amount of an ES that is utilized from an ecosystem in a specific time period. The demand is the amount of a specific good or service consumed by society in a particular area over a given period, regardless of its origin. Within the WIKIAlps platform, for each ES selected in AlpES, you can find detailed information about each indicator.

Once the ES indicators have been selected, the relevant data for their calculation have to be gathered. First, the temporal and spatial scales need to be carefully chosen. Ecological processes are heavily dependent on time (e.g. seasons) and space (e.g. global, national, municipal scale). The AlpES team mapped the spatial distribution of ES at the municipal level for over 16.000 municipalities throughout the Alpine Space cooperation area; this scale is the finest resolution that is possible across all selected indicators, while still being useful for management purposes. For the municipalities’ boundaries we used the EuroBoundaryMap (v10), kindly provided by EuroGeographics. The selected time scale varied between indicators and is reported in the individual map descriptions.

Data requirements varied greatly from indicator to indicator and encompassed land-cover and climate data, statistical information, protected area networks and digital elevation models, just to name a few. Detailed data sources for each individual ES indicator map can be found on the interactive WebGIS, using the link provided in its description. The datasets were obtained from a variety of sources, which are either nationally or internationally organized. For example, data has been acquired from the national statistical offices of Alpine countries, from European institutions like Eurostat and the European Environment Agency (EEA), and from global datasets, such as OpenStreetMap. If the definition or interpretation of a common concept varied between data sources, the collected data were harmonised, which may have led to minor inaccuracies. In general, it is important to remember that the characteristics of the input data (i.e. accuracy, scale, precision, etc.) will be reflected in the output indicators. Therefore, the resulting indicator values are not absolute or “true” values, but have to be interpreted in the light of the available input data sources.

An important part of ES indicator development lies in finding appropriate methods and procedures for their measurement and calculation.

The methods and instruments used for indicator calculation vary greatly between indicators. GIS-software tools were used to map and model ecosystem services and to perform analyses of remote sensing data. Depending on the nature of the indicator and the type of data used for its calculation, the models were based either on statistical data or on biophysical quantifications. Specific software (e.g. InVEST – a suite of free, open-source software models used to map and value ecosystem services) and guidelines from scientific papers and project reports were consulted for the development and calculation of indicators.

The AlpES partnership decided to apply a three-level “tier approach” to the mapping and assessment of ES, thus allowing for consistent but flexible methods. Tier 1, the most basic approach, uses existing, widely available (large-scale) datasets (e.g. CORINE databases for Europe) as a proxy for the provision of certain ES. For example, Corine Land Cover data can be used to quantify ES that are directly dependent on specific ecosystems. Tier 2 builds on the previous approach by linking different indicators with land use data to map ES. The output indicator will be more complex, depending on different datasets interlinked according to known relationships between, for example, land use and ES provision. Tier 3 is the most refined approach and consists of modelling biophysical processes in GIS or other software instead of linking indicator data through simple relationships. The tier 1 approach is useful to estimate ES for which data are difficult to obtain. Tiers 2 and 3 deliver a higher resolution of results; however, they require a higher degree of expert knowledge about modelling and ES provision.

ES indicators are fundamental to creating cartographic representations of the assessed ecosystem services in geographic space and time. In this way, the information derived from the assessment is visually accessible and easily understandable, especially to those who are not familiar with the ES concept.

AlpES created a uniform layout for the maps of all three assessed indicators. The external boundaries of the maps match those of the Alpine Space cooperation area, while national borders are shown too. The spatial scale of the maps corresponds to the municipal level and the temporal scale is described in the related metadata. To each indicator a specific colour was assigned, for a better understanding of the maps in printed form and on the AlpES WebGIS.