# Assessment of Ecosystem Services across the Land-Sea Interface in Baltic Case Studies
## 3 Results
### Comparison of Ecosystem Service Potential and Flow  
Figure 5 combines the results of the previous sections. 'Development capacities' were calculated as the difference between ES potential and ES flows for the ten ES that were included in the flow assessment and are shown on an aggregated level for the three ES sections. Moderate to high development capacities for provisioning ES are shown for the marine areas of all CSS. The development capacities for terrestrial areas are comparably low (15 to 22) and indicate that the ES potential at land in all CSS has been mostly exhausted in comparison to the sea. For the German CSS, in which agricultural areas are dominating, this could be explained by the relatively high flow values for 'crops' (P1) and 'wild food' (P3) (for CSS Greifswald Bay). In the Lithuanian CSS, the low development capacity for provisioning ES is also a result of the dominance of natural habitats which have a generally low ES potential for provisioning ES. Development capacity for regulating and maintenance ES is visible especially for the Lithuanian CSS and in particular for its marine area, as well as the forest and natural areas within the CSS Greifswald Bay. Development capacities for cultural ES are highest for CSS Schlei. In general, habitat-weighted development capacities are highest for the marine area of the CSS. Yet, in the terrestrial area high development capacities for cultural ES are also shown for forest habitats. The maps in Figure 5 are useful for comparisons across land and sea and between CSS. They can be used to visualize gaps between ES potentials and flows and thereby support decision-making for future development. On an aggregated level, differences between CSS become attenuated. Thus, a closer look at the results for single ES is needed, to assess differences between the land-dominated, balanced, and sea-dominated CSS. We chose one ES from each section to analyze differences. Furthermore, we point out some of the specificities of our approach that shall be addressed in the subsequent discussion. Figure 6 shows the spatial distribution of development capacities for each ES across the CSS. For 'wild food' (P3), strong differences between land and sea are shown for all CSS. The difference in development capacities between land and sea is most pronounced for the CSS Greifswald Bay (P3-GWB: T9, M:85). At first glance, this might be surprising, because Greifswald Bay is among the areas with the highest commercial fisheries catches in the German Baltic Sea area [51]. In contrast, the area is popular for hunting wild boar and red deer, but it is not among the most intensively used hunting areas in Germany [52]. In Section 3.3, the differences in the maximal flow values were already addressed. It was shown that the absolute flow values for 'wild food' (P3) were lower for terrestrial areas compared to marine areas in all CSS (cf. Table 2). Yet, in order to understand why there is a high development capacity for marine areas, but not for terrestrial areas, a closer look at the approaches to determine the maximal flow values is needed. As hunting data is largely lacking or not harmonized across Europe [53], the maximal value flow for hunting yield was based on statistical data from Germany. It is likely that the indicated maximal flow is underestimated, as for instance hunting yield on a regional level in Poland is likely to be higher. Furthermore, the data for Germany showed that the hunting yield of deer and wild boar species is currently at a long-term peak. Thus, the maximal flow will soon be exceeded if the increasing trend continues. In contrast, fisheries are currently highly regulated in order to recover exploited fish stocks and are thus far below historical yields. Since the maximal flow value for fishing yield is based on historical values, the difference between maximal flow and the actual flow in the CSS is much higher in comparison to  
hunting yields. Furthermore, the maximal flow value was based on fishing yields from Denmark.