# Assessment of Ecosystem Services across the Land-Sea Interface in Baltic Case Studies
## 2 Materials and Methods
### Indicator-Based Ecosystem Service Flow Assessment
\begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Ecosystem Service** & **Indicator (Unit)** & **Max. Flow** & **Schlei** & **GWB** & **CL** \\ \hline \multirow{6}{*}{**P1: Crops**} & T: Harvested crops (average yield of (winter) wheat (t/ha) & 10.5 & 8.7 (0.83) & 7.5 (0.71) & 0 (0.0) \\  & M: Harvest from marine aquaculture & 0.07 & 0 (0.0) & 0 (0.0) & 0 (0.0) \\  & production (seaweed) (t/km coastline) & & & & \\ \cline{2-6}  & T: Livestock (dairy cows) biomass per & 4 & 1.2 (0.30) & 0.7 (0.17) & 0 (0.0) \\  & ha agricultural land (t/ha UAA) & & & & \\  & M: Marine aquacultures production & 100 & 0 (0.0) & 0 (0.0) & 0 (0.0) \\  & (fin fish and mussels) (t/km coastline) & & & & \\ \cline{2-6}  & T: Hunting yield (deer and wild boar) & 1 & 0.2 (0.20) & 0.7 (0.70) & 0.2 (0.20) \\  & (t/km2) & 19 & 2.93 (0.15) & 0.78 (0.04) & 2.43 (0.13) \\ \cline{2-6}  & T: Wind and solar energy capacity & 19 & 0.65 (0.03) & 0.46 (0.02) & 0 (0.0) \\
**P4: abiotic energy** & (KW/ha) & 19 & 0.0 (0.0) & 0.0 (0.0) & 0.0 (0.0) \\  & (KW/ha) & 19 & 0.0 (0.0) & 0.0 (0.0) & 0.0 (0.0) \\ \hline \multirow{2}{*}{**RM1: Local**} & T: Evapotranspiration (mm/year) & 800 & 500 (0.48) & 550 (0.50) & 505 (0.63) \\  & M: Evaporation (mm/months) & 40 & 20 (0.50) & 20 (0.50) & 20 (0.50) \\ \cline{2-6}  & T: Nitrogen cleaning (nitrogen surplus) & 213 & 115 (0.46) & 60 (0.72) & 15 (0.93) \\
**RM2: Nutrient** & (kg N ha\({}^{-1}\) yr\({}^{-1}\)) (_reversed_) & & & & \\ \cline{2-6}  & M: Nitrogen cleaning ( denitrification, estimated based on TN) & \(-\)266 & \(-\)120 (0.45) & \(-\)51 (0.19) & \(-\)101 (0.38) \\  & (kg N ha\({}^{-1}\) yr\({}^{-1}\)) & & & & \\ \cline{2-6}  & T/M: Presence of pathogenic bacteria & 4 & 4 (1.00) & / & / \\  & (in lakes (T) and coastal waters (M)) & 4 & 3.63 (0.91) & 3.05 (0.76) & 3.82 (0.95) \\
**RM3: Pest and** & T: Micro algae biomass chl-a & 54 & 10.8 (0.20) & / & / \\ \cline{2-6}  & concentration (ug/l)—terrestrial: lakes & & & & \\ \cline{2-6}  & M: Micro algae biomass chl-a & & & & \\ \cline{2-6}  & concentration (ug/l)—marine: coastal & 48 & 32.5 (0.68) & 10.5 (0.22) & 113.2 (2.36) \\  & water bodies & & & & \\ \hline \multirow{2}{*}{**C1: Recreation**} & T/M: Ratio of local residents to tourists & 61,000 & 13,780 (0.23) & 16,667 (0.27) & 13,571 (0.22) \\  & (tourists/1000 inhabitants) & & & & \\ \cline{2-6}  & T/M: Habitat diversity based on & & & & \\ \cline{2-6}  & Simpson’s Index & & & & \\ \cline{2-6}  & T/M: Naturalness based on & & & & \\ \cline{2-6}  & Hemeroby Index & & & & \\ \cline{2-6}  & T/M: Proportion of area that is & & & & \\ \cline{2-6}  & predicted (Natura 2000) (\%) & 100 & 7 (0.07) & 14 (0.14) & 77 (0.77) \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Overview of the provisioning (P), regulating and maintenance (RM), and cultural (C) ecosystem services and corresponding indicators for terrestrial (T) and marine (M) areas, used in the ES flow assessment. In addition, results for the maximal flow value and the case study site flows are shown. Case study site flows are indicated as absolute values (bold) and proportionally to the maximal flow (in brackets). adjusted. A detailed description of the methods and data sources used to derive the maximal flow value for each indicator is provided as Supplementary Materials (File S2). In the third step of the flow assessment, the ES flow indicators were applied to the three CSS. To score the indicators, data on the smallest possible scale was used, that is the municipal level for indicators for terrestrial areas and the WFD water body level for indicators for marine areas. Data sources included regional and local statistics, geoporals, and scientific literature. Furthermore, experts were consulted in case no other data sources were available or to validate data-based values. In the final step, the ES flow values and the Baltic ESP Matrix were combined to derive an ES flow matrix for each CSS. Hereby, the maximal flow value was equated to the highest potential value found in the Baltic ESP Matrix (i.e., 80 or 90, indicator-dependent).