Data were analyzed by GLM to reveal differences among the different categories of areas regarding the ES capacity. Correlations among landscape properties (elevation, slope and aspect) and the ES capacity were also tested. A Principal Component Analysis (PCA) for 29 variables that correspond to the examined ES was carried out in order to group the variables and specify the synergies and trade-offs between ES as proposed by Raudsepp-Hearne et al. (2010) and tested by Depellegrin et al. (2016). All statistical analysis was performed using SPSS v. 21 (IBM Corp 2012).

In all studied catchments (data not shown) a great percentage of surfaces (over 50%) are occupied by forests and semi-natural areas, while agricultural areas cover also significant parts (22 to 47%). Hence supporting, regulating, provisioning and cultural services (capacity score >0) are provided respectively from the 99.9 %, 98.2%, 97.1% and 95.9% of total study areas surface. Aliakmonas and Acheloos have all the 29 ES while Pinios has 28 and Evia 26 ES, respectively. The missing ES are related mostly to absence of coastal lagoons and wetlands from the Evia catchment.

Fig. 2 shows the areas of different or multiple designation types. Areas with no designation (ND) have the highest amount of area in the four catchments (13266 km², 38% of the total surface) followed by Quiet Areas (QAs) (12467 Km², 36% of the total surface) and by areas that are both Quiet and Protected (PAQAs) (5455 Km², 16% of the total surface). The least amount belongs to the type Protected Areas only (PAs) (3335 Km², 9.6% of the total surface) and much less fulfill the criteria of all designation types (PAQAW) (132 Km², 0.4% of the total surface).

Table 1 shows the average score of each ES (the capacity based on land cover type) at each of the five categories of areas as well as results of ANOVA comparing differences among them. Scores of supporting services such as “Biodiversity” and “Reduction of Nutrient Loss” were significantly higher in PAQAs intermediate in PAs, and QAs and lowest in the ND areas . “Abiotic Heterogeneity” had a higher score in PAQAW while the reverse was observed for “Biotic Waterflow” and “Exergy capture”. Provisioning services (except those related to water, i.e “Capture Fisheries”, “Aquaculture” and “Freshwater” as well as ''Wild foods'') were highest in ND intermediate in PAs, QAs, or PAQAs and lowest in PAQAW . Regulating services such as “Local” and “Global Climate Regulation”, “Air Quality” and “Erosion Regulation”, “Water purification” and “Pollination” had significantly higher scorers in PAQAs and lower in PAQAW. A similar pattern presented also the “Nutrient regulation” except that the score for this ES exhibited the lowest values in ND areas. “Flood protection” and “Groundwater Recharge” decreased significantly from PAQAW to ND. Cultural services had highest values in PAQAW intermediate in PAs and QAs and lowest values in ND.

Overall, our results showed that areas with most designations (i.e PAQAW) presented the highest capacity in 10 out of 29 ES (most of them as expected were relevant to aquatic ecosystems). Areas that combined two designation types (i.e. PAQA) showed the highest capacity in 13 out of 29 ES. Those ES were mostly linked with natural and forest ecosystems. Areas with no designation (ND) displayed stronger capacity in provisioning services - ES that are linked to human activity. Areas with single designation (PA or QA) displayed highest capacity in few (<10) ES and among those two categories QAs scored in general better than PAs.

Table 2 displays the correlation coefficients of ES capacity towards the landscape properties of aspect, slope and elevation. Strong positive correlations (cor. coef. >0.4) were found among the ES “Biodiversity”, “Reduction of nutrient loss” and “Intrinsic value of biodiversity” to slope as well as elevation, while the same holds among “Pollination” and slope. On the other hand the ES “Crops” displayed strong negative correlation to slope and elevation while the same holds among “Fodder” and “Energy” to slope.

As regards aspect the correlation coefficients were in general lower, showing a less important influence of this landscape property on ES capacity. Highest positive correlations were observed for “Reduction of nutrient loss”, “Biodiversity” and “Intrinsic value of biodiversity” (cor. coef.: 0.24-0.26), and highest negative for “crops” and “energy” (cor. coef.: -0.26 and -0.22, respectively).

Fig. 3 shows the results of the PCA analysis exploring synergies and trade-offs among ES. Four groups of ES were observed. Group 1 (displaying small distance between the variable points) had mostly regulating ES accompanied by some cultural, supporting and provisioning services related to natural production (Biochemicals, Timber, Wood fuel, Wild foods). Group 2 consisted of two supporting services (Reduction of nutrient loss, Biodiversity). Group 3 contained three provisioning services related to aquatic ecosystems (Aquaculture, Capture fisheries, Freshwater) and Abiotic heterogeneity. Group 4 comprised of provisioning services related to agricultural activity (Fodder, Energy, Crops, and Livestock).

a

b

Figure 3.

Relationship between Factor 1 and Factor 2 loadings as derived from PCA. Factor 1 explains the 52.51% and Factor 2 the 13.4% of the total variance. Dotted lines and numbers indicate the four groups identified. Orange colour = supporting services, red colour = provisioning services, green colour = regulating services, blue colour = cultural services. For abbreviations of services see Table 1 

a: All 4 groups of ES   
b: Details of group 1  

Factor 1 representing 52.51% of the total variance recognized synergetic interactions among ES of groups 1 and 2, which in turn showed antagonistic interactions with some of the ES of group 4, such as Livestock and Crops. Pronounced synergistic effects were observed between most ES of group 4 (Fodder, Crops, Energy). The low factor scores of group 3 (ES associated with the aquatic environment) might be explained by the fact that only a few land cover types have a high capacity (score = 5) to provide such services, while other types have no capacity at all.

As expected, areas with no designation (ND) were the most dominant and comprised the highest percentage (38%) of the studied areas. These areas were mostly dominated by more intensive land use and had in general a high score (capacity) in provisioning services. Surprisingly the next category, namely Quiet Areas (QAs) had an almost equal amount of surface (36%). Although human presence is taken for granted in our study areas, the fact that QAs occupy this great percentage of land surfaces, indicates that there are still many areas without noise pollution and low sound intensity anthropogenic activities, since their definition is based on the distance from multiple human activities producing noise (Votsi et al. 2012). QAs showed in general medium to high scores in ES capacity, with relatively higher scores for some supporting services but also for “Livestock” and some other forest related provisioning services.

Areas that had the single designation as Protected Areas (PAs) belonging to the Natura 2000 network (i.e not characterized as “quiet”) covered a smaller percentage of land surfaces in the four catchments (9.6%). Many scientists have assessed the ES of Protected Areas and their capacity to maintain ecological integrity (e.g. Castro et al. 2015, Maes et al. 2012a). There is a distinguished dependency between certain species or habitat types and ES, especially regarding socio-cultural and regulating services (Bastian 2013). Our findings show that PAs have medium relevant capacity to provide all ES and relatively higher capacity to provide some that correspond to the provision of suitable habitats for different species such as “Abiotic heterogeneity”. Moreover they have good capacity of some ecosystem services such as “Flood protection”, “Groundwater recharge” and “Nutrient regulation”. Surprisingly, PAs showed lower biodiversity than QAs, although their designation has as a major aim the protection of biodiversity. It has to be noted that many sites of Natura 2000 network are not “quiet” due to their fragmentation by a rapidly expanding transport network (Selva et al. 2011) and due to the fact that they comprise a significant amount of agricultural areas (Kallimanis et al. 2008, Tsiafouli et al. 2013, Vlami et al. 2017) in which also human-induced noise is produced.

Areas that have both designation types, i.e. are Protected & Quiet (PAQAs) were found to occupy greater land surface (16%) than the one occupied by PAs alone, indicating the predominance of “quiet protected areas” against “noisy protected areas” (Votsi et al. 2014) (such as the PA category). Sites of the Natura 2000 network which are located away of human activity are considered noise refuges (Votsi et al. 2014) that promote the conservation of certain species and their habitats (Wallace 2008). In our study we further found that they have a higher capacity in ES delivery. Specifically, PAQAs that could be characterized as “quiet protected areas” had the highest score in most supporting, regulating and cultural services compared to the other categories of areas investigated. Areas of the above category which in addition include wetlands/water bodies preserve also the quietness value. These areas (PAQAW) though have the smallest total area (covering less than 0.5% of the catchment surface) reflecting the rarity of landscapes that combine all these ecological features. Areas around wetlands and water bodies often suffer intense human activity, regardless their protection status, due to the surrounding fertile lands (Drakou et al. 2008). Despite their small expansion these areas have high capacity in providing many ES including of course provisioning services related to water, such as “Aquaculture”, “Freshwater” and “Capture fisheries”.

Among landscape properties investigated, aspect had the lowest influence on the capacity of ES. The most important correlations found (but with a relative low cor. coef.) showed that the potential of the ES “Reduction of nutrient loss”, “Biodiversity” and “Intrinsic value of biodiversity” tends  to increase from East to West, while the opposite happens for “Crops” and “Energy”. This differentiation could be related to differences in solar radiation from East to West.

As regards elevation and slope we found that increasing elevation and/or slope leads to a decrease in provisioning services such as “Crops”, “Fodder” and “Energy”. On the contrary major supporting, regulating and cultural ES such as “Biodiversity”, “Reduction of nutrient loss” and “Intrinsic value of biodiversity” increase with increasing slope and elevation while the ES “Pollination” increases also with slope. These results were expected as the altitude gradient (elevation and slope) cause climatic differences affecting land cover and land use types (Shrestha and Zinck 2001) which are interdependent of the ES potential. Hence increased elevation poses difficulty in management and access of farming machinery and might involve unfavorable climate conditions for cultivation as well. The decrease of the ES “Crops” with increasing altitude leads in turn to the “Reduction of nutrient loss” due to the positive influence of natural vegetation cover and the decrease of those agricultural activities degrading surface water bodies and groundwater (Shukla et al. 2010).

On the other hand “Biodiversity” and its “Intrinsic value” were found to thrive in higher altitudinal zones that are more remote and lacking of human disturbance and are dominated by natural vegetation cover (mostly forests). It should be noted though that Greece has a tremendous shoreline - zero altitude, with a high touristic value. This value is not covered by the methodology of Burkhard et al. (2009), which apparently gives higher scores mostly for forest land uses which are usually at higher-elevation habitats. This finding should be taken into consideration in future assessment studies.

Understanding interactions between ES is a critical step towards assessing the drivers of landscape change and how they influence the potential, flow and demand of ES (Depellegrin et al. 2016). Our results showed trade-offs between regulating and cultural services versus provisioning services such as “Crops”, “Livestock” and “Fodder”. So an area with increased ability to provide supporting services such as “Biodiversity” and “Reduction of nutrient loss” has less capacity to provide services such as “Crops”, “Livestock”, “Fodder”, “Energy” and vice versa. These results were similar irrespective of catchment area or type of area studied and this might be explained that in our study we analyzed the capacity of ES provision using data that derive from the type of land use only.

Regulating and cultural services provide intermediary benefits to mankind (Kumar and Wood 2010) including climate regulation, protection from extreme events (floodplains, erosion) (Braat and Groot 2012), spiritual enrichment and ecotourism development. Nevertheless enhancement of provisioning services may cause degradation of regulating and cultural services, with vital importance for sustaining ecological processes (Costanza et al. 2016). To ensure sustainability in the long-term there is need to focus on multiple services within a given area of land (Eastburn et al. 2017). In agricultural ecosystems, which comprise a large part of terrestrial ecosystems (22-47% in our study areas) the intensity of management plays a significant role from below-ground diversity (Tsiafouli et al. 2015) to landscape diversity (Tscharntke et al. 2005). A number of studies (e.g.Gardi et al. 2016, Marton et al. 2016, Sidhu and Joshi 2016, Winkler et al. 2017) show the way how to optimize the delivery of multiple ecosystem goods and services and reduce trade-offs (Tsiafouli et al. 2017).