# Assessment of Ecosystem Services across the Land-Sea Interface in Baltic Case Studies
## 2 Materials and Methods
### Indicator-Based Ecosystem Service Flow Assessment  
For a subset of ES, a complementary ES flow assessment was conducted to allow for subsequent comparisons of ES potential and flow. A shortcoming of the matrix-based assessment by [PERSON] et al. (2018) and previous matrix-based applications is the lack of reference points. For instance, the habitat type 'non-irrigated arable land' is considered to be the one with the highest potential for the ES 'crops (for human nutrition)' and has thus an ES potential value of 90. However, no information is provided on what a potential of 90 would correspond to in an absolute value. This hampers direct comparisons of ES potential and flow, as they remain mostly hypothetical. The initial ecosystem service potential matrix presented by [PERSON] et al. (2020), and subsequent Baltic ESP Matrix, was developed to fit the conditions of Northern German ecosystem complexes. Similar conditions exist for the same ecosystem types within the same climatic zone, which is the Cfb-climate zone (Warm temperate-fully humid-warm summer), according to an updated map of the Koppen-Geiger climate classification, representing the time period between 2001 to 2025 ([PERSON], 2001). As background for our indicator-based ES flow assessment we assume that the highest ES potential represented in the Baltic ESP Matrix reflects the highest ES flow that exists within the Cfb-climate zone. The assessment then consisted of four main steps:  
In the first step, we selected suitable ES and indicators. Selected ES should equally cover provisioning, regulating and maintenance, and cultural ES. Furthermore, they needed to be applicable for both land and sea. In total, 10 ES were selected for the ES flow assessment. For each ES, we identified indicators to assess the ES flow in terrestrial (incl. coastal) and marine ecosystem types. Selection criteria were: (a) applicability in all study sites, (b) policy relevance, and (c) data availability. Additional quality criteria for ES indicators as defined by [PERSON] et al. (2019) were taken into account in the indicator selection. These include precision, sensitivity, specificity, scalability, and transferability. Previous mappings and assessments of ES ([PERSON] et al., 2019; [PERSON], 2019), as well as the structured indicator pool for marine ES assessments by [PERSON] et al. (2019), served as sources for the indicator selection. An overview of the selected ES and their corresponding flow indicators is provided in Table 2 (Section 3.3). In the second step, a maximal flow value for each indicator was defined. We searched for the highest flow value within the Cfb-climate zone, which ranged from Ireland to the coast of Lithuania and from Denmark to France (excluding the Alps region). First, the country with the highest flow value on the national level (NUTS 1 level) was identified, using international geoportals and databases, such as EMODnet [36], Eurostat [37], or the FAO databases [38; 39]. Afterwards, geo- and statistical portals and reports from national and regional authorities were reviewed to obtain more precise values for the regional or county level (NUTS 2 or 3 level) for the respective country. This approach was used for the majority of indicators. Yet, for single indicators (e.g., the Simpson's and Hemeroby indices, used for the ES 'Landscape aesthetics and inspiration') it was not applicable and therefore