Ana Paula García-Nieto

Ilse R Geijzendorffer

Francesc Baró

Philip K Roche

Alberte Bondeau

Wolfgang Cramer

Impacts of urbanization around Mediterranean cities: changes in ecosystem service supply

Keywords: Land cover, population, urban, rural, spatial analysis, trend, nature's contributions to people

Urbanization is an important driver of changes in land cover in the Mediterranean Basin and it is likely to impact the supply and demand of ecosystem services (ES). The most significant land cover changes occur in the periurban zone, but little is known about how these changes affect the ES supply. For eight European and four North African cities, we have quantified changes in peri-urban land cover, for periods of sixteen years (1990)(1991)(1992)(1993)(1994)(1995)(1996)(1997)(1998)(1999)(2000)(2001)(2002)(2003)(2004)(2005)(2006) in the Northern African, and twenty-two years in the European cities, respectively. Using an expertbased method, we derived quantitative estimates of the dynamics in the supply of twenty-seven ES. The nature of land cover changes slightly differed between European and North African Mediterranean cities, but overall it increased in urban areas and decreased in agricultural land. The capacity of the peri-urban areas of Mediterranean cities to supply ES generally reduced over the last 20-30 years. For nine ES the potential supply actually increased for all four North African cities and three out of the eight European cities. Across all cities, the ES timber, wood fuel and religious and spiritual experience increased.

Given the expected increase of urban population in the Mediterranean Basin and the current knowledge of ES deficits in urban areas, the overall decrease in ES supply capacity of peri-urban areas is a risk for human wellbeing in the Mediterranean and poses a serious challenge for the Sustainable Development Goals in the Mediterranean basin.

Introduction

Approximately two thirds of the world's population (i.e., 6,4 billion people for the median projection) and 84% in Europe will be living in urban areas by 2050. In 2014 already more than half of the global population was urban, while in Europe this was 70% [START_REF] Kabisch | Diversifying European agglomerations: evidence of urban population trends for the 21st century[END_REF]United Nations, 2015a, 2014). The increase in total population entails a corresponding increase in demand for natural resources [START_REF] Ma | MA) Millennium Ecosystem Assessment, 2005. Ecosystems and Human Well-being: Synthesis[END_REF], particularly for energy and water. The demand for water is expected to increase with 55% between 2000 and 2050 (United Nations World Water Assessment Programme, 2014). The effect of urban population growth on peri-urban landscapes is expected to be particularly prominent since urban land cover increases even faster than could be expected from demographic pressure, resulting in substantial land use conversions [START_REF] Angel | The dimensions of global urban expansion: Estimates and projections for all countries, 2000-2050[END_REF][START_REF] Seto | A Global Outlook on Urbanization[END_REF][START_REF] Seto | Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools[END_REF][START_REF] Seto | A Meta-Analysis of Global Urban Land Expansion[END_REF].

Urban populations in countries around the Mediterranean Sea increased from 152 million to 315 million between 1970 and 2010 (an average rate of 1.9 % per year) (UNEP/MAP, 2012). By 2030, the Mediterranean Basin will be the global biodiversity hotspot with the highest percentage of urban land (5%) [START_REF] Elmqvist | History of Urbanization and the Missing Ecology[END_REF]. Urbanization rates have been accelerated by environmental change; for example, intense drought conditions contributed to a rural exodus in Morocco between 1980and 1990, and in Algeria and Tunisia in 1999(FAO, 2001;[START_REF] Hervieu | Rethinking rural development in the Mediterranean[END_REF]. Tourism and housing development have led to the development of infrastructure close to coastal areas and near culturally important cities [START_REF] Eea | Biogeographical regions in Europe. The Mediterranean biogeographical regionlong influence from cultivation, high pressure from tourists, species rich, warm and drying[END_REF][START_REF] Houimli | The factors of resistance and fragility of the littoral agriculture in front of the urbanization: the case of the region of North Sousse in Tunisia[END_REF].

Mediterranean cities are considered attractive places to settle for retirees from northern Europe [START_REF] Membrado-Tena | Costa Blanca: Urban Evolution of a Mediterranean Region through GIS Data[END_REF], and for return migrants to the Maghreb countries [START_REF] Cassarino | Return migrants to the Maghreb Countries: Reintegration and development challenges[END_REF].

The growth of urban areas often takes place at the expense of agricultural land and this can potentially lead to environmental degradation and socio-economic challenges [START_REF] Orgiazzi | Global soil biodiversity atlas[END_REF]. Although probably the most studied, the direct conversion of agricultural land into urban land is only one of the many impacts of urbanization on the structure and function of ecosystems and their services [START_REF] Mcdonnell | The use of gradient analysis studies in advancing our understanding of the ecology of urbanizing landscapes: current status and future directions[END_REF][START_REF] Modica | Spatio-temporal analysis of the urban-rural gradient structure: an application in a Mediterranean mountainous landscape[END_REF].

Examples of other impacts of urbanization include changes in demand patterns [START_REF] Bennett | Linking biodiversity, ecosystem services, and human well-being: three challenges for designing research for sustainability[END_REF][START_REF] García-Nieto | Mapping forest ecosystem services: From providing units to beneficiaries[END_REF][START_REF] Schulp | Uncertainties in Ecosystem Service Maps: A Comparison on the European Scale[END_REF], or the infrastructure construction for water distribution facilities, energy plants and internet connection [START_REF] Kasanko | Are European cities becoming dispersed?: A comparative analysis of 15 European urban areas[END_REF][START_REF] Seto | Global forecasts of urban expansion to 2030 and direct impacts on biodiversity and carbon pools[END_REF], agricultural land abandonment [START_REF] Hasse | Land resource impact indicators of urban sprawl[END_REF][START_REF] Hervieu | Rethinking rural development in the Mediterranean[END_REF] or the protection of traditional landscapes with the aim to maintain the aesthetic quality [START_REF] Baró | Mapping ecosystem service capacity, flow and demand for landscape and urban planning: a case study in the Barcelona metropolitan region[END_REF]. Urbanization may also affect the diversity of the landscape, with agricultural land being managed by hobby farmers rather than for commercial production [START_REF] Jarosz | The city in the country: Growing alternative food networks in Metropolitan areas[END_REF][START_REF] Zasada | Multifunctional peri-urban agriculture-A review of societal demands and the provision of goods and services by farming[END_REF].

As these examples show, the influence of urban areas on ecosystems extends well beyond the urban boundaries [START_REF] Lead | Drivers of change in ecosystem condition and services[END_REF], but it is unclear how the changes in the peri-urban landscapes affect human well-being. A growing number of studies of human well-being and quality of life in urban areas focus on the benefits provided by natural elements within cities, so called urban ecosystem services [START_REF] Bolund | Ecosystem services in urban areas[END_REF][START_REF] Kremer | Key insights for the future of urban ecosystem services research[END_REF]. Many of these studies have found that the natural elements currently present in cities often do not seem to provide ecosystem services (ES) in sufficient quantities in comparison to the demand for these services [START_REF] Folke | Ecosystem Appropriation by Cities[END_REF][START_REF] Jansson | Reaching for a sustainable, resilient urban future using the lens of ecosystem services[END_REF]. [START_REF] Baró | Mismatches between ecosystem services supply and demand in urban areas: A quantitative assessment in five European cities[END_REF] have recently shown mismatches between ES in supply and demand for five European cities. These mismatches may depend on many factors, e.g. differences in spatial distribution of goods and needs or access restrictions to resources for particular groups, such as women [START_REF] Geijzendorffer | Improving the identification of mismatches in ecosystem services assessments[END_REF]. Some of these factors can be addressed through governance or land use management [START_REF] Jansson | Reaching for a sustainable, resilient urban future using the lens of ecosystem services[END_REF]. Potentially, land cover changes around cities affect ES supply, and these changes may therefore potentially reduce or enhance deficits for ES within cities.

The objective of this study is to assess how growing urban areas in the Mediterranean Basin modify the periurban landscapes and, consequently, ES supply. With the current urban population being expected to increase to 385 million people by 2025 (UNEP/MAP, 2012) and the objective of improved human well-being of the Sustainable Development Goals (United Nations, 2015b), an increase of ES is required for this growing urban population. Therefore, there is a particular need to assess the recent dynamics in ES supply, both within cities and in their peri-urban areas. The European Mediterranean areas are estimated to be particularly vulnerable with respect to ES supply, mostly due to climate and land use change [START_REF] Schröter | Ecosystem Service Supply and Vulnerability to Global Change in Europe[END_REF]. Although similar studies for the north-African Mediterranean countries are missing [START_REF] Nieto-Romero | Exploring the knowledge landscape of ecosystem services assessments in Mediterranean agroecosystems: insights for future research[END_REF], it is highly likely that these countries are subject to similar, if not higher, anthropogenic pressures, experience more rapid population increases and are undergoing significant landscape changes. The importance of this knowledge gap goes beyond its implications for regional assessments, by additionally increasing the uncertainty of supra-regional assessments of sustainable futures.

The need to evaluate land use and land cover changes and their impacts for future conditions is increasingly being recognized [START_REF] Eea | Biogeographical regions in Europe. The Mediterranean biogeographical regionlong influence from cultivation, high pressure from tourists, species rich, warm and drying[END_REF][START_REF] Fichera | GIS and Remote Sensing to Study Urban-Rural Transformation During a Fifty-Year Period[END_REF]. To inform land management improvements, land use -land cover assessments should take into account spatial and temporal patterns along urban-rural gradients [START_REF] Kroll | Rural-urban gradient analysis of ecosystem services supply and demand dynamics[END_REF]. Previous land use -land cover assessments in the Mediterranean have focused on areas where spatial data was available and, as a consequence, the north-African region has received little attention [START_REF] Haase | A quantitative review of urban ecosystem service assessments: concepts, models, and implementation[END_REF][START_REF] Luederitz | A review of urban ecosystem services: six key challenges for future research[END_REF]. Also, most studies to date focus on single city case studies and are limited to the dense urban fabric. A multi-city analysis therefore fills an important knowledge gap by allowing for a comparison of the impacts of urbanization in peri-urban land and its consequences for ES supply in the Mediterranean Basin.

For this study we selected both European and north-African Mediterranean cities: eight Mediterranean European cities (Lisbon, Madrid, Barcelona, Marseille, Florence, Rome, Athens, Thessaloniki) and four Northern African cities (Nabeul, Sfax, Tunis, Rabat).

Material and methods

For this study, we analyzed: 1) whether land cover changes around cities differed significantly from trends at national level; 2) whether different specific conversions of land cover are common for groups of cities occurred over time and finally 3) whether the spatio-temporal supply patterns of ES over the period 1990 -2012 were shared among these Mediterranean cities, depending on data availability.

The assessment was carried out in six steps. First, we selected twelve major Mediterranean cities as case studies.

We used a systematic approach to define the peri-urban area for each city. Based on time series of available land cover maps (Fig. 1), we assessed land cover changes in each peri-urban area and we compared them with national dynamics per country. In addition, we identified the main patterns in land cover changes across all periurban areas. Finally, we identified changes in land cover with expert based estimates of ES supply [START_REF] Stoll | Assessment of ecosystem integrity and service gradients across Europe using the LTER Europe network[END_REF] and searched for specific or general dynamics in ES supply.

Data were available for the period 1990-2006 for Northern African cities, and for 1990-2012 for European cities (Table 1). These periods allowed for the analysis of important dynamics and they correspond to the used expertbased ES estimates (see below).

-Insert Fig. 1 around here -

Selection of Mediterranean cities

In the selection of cities we aimed to achieve a geographical distribution in the Mediterranean biogeographical region [START_REF] Olson | Terrestrial Ecoregions of the World: A New Map of Life on Earth A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity[END_REF] (Fig. 2), with a special attention to include both cities on northern and southern Mediterranean shores. An additional search criterion was that land cover data should be available on at least two moments in time. These criteria allowed for the selection of twelve cities in total, four in Northern Africa (Nabeul, Sfax, Tunis, Rabat) and eight in Southern Europe (Lisbon, Madrid, Barcelona, Marseille, Florence, Rome, Athens, Thessaloniki).

Spatial land cover data is available for the entire Mediterranean basin, but the categories, spatial resolution and time series differ (Fig. 1). CORINE Land Cover (CLC) [START_REF] Feranec | European landscape dynamics: CORINE land cover data[END_REF] is a spatial database with a resolution of 100 m and it is available for all European countries for the years 1990, 2000, 2006 and 2012 (Table 1). For the North African countries, CLC is available only for 1990. We used GlobCorine Land Cover (GLC) [START_REF] Bontemps | GlobCorine-A joint EEA-ESA project for operational land dynamics monitoring at pan-European scale[END_REF] to include another point in time ( 2006) for these countries. The GLC land cover map was developed by the European Environmental Agency and European Space Agency attempting to ensure compatibility with CLC (Appendix 1).

-Insert Fig. 2 around here -

Defining the peri-urban areas

There are many different approaches to define the urban and peri-urban areas of a city [START_REF] Orgiazzi | Global soil biodiversity atlas[END_REF].

For our study we searched for a simple, yet objective delineation of the urban areas that could be adapted to include peri-urban areas. We defined the peri-urban area as the rural area located in proximity around the urban area. In addition, the delineation method should be able to deal with the differences in data resolutions between the European countries and the north-African Mediterranean countries. The approach published by [START_REF] Kasanko | Are European cities becoming dispersed?: A comparative analysis of 15 European urban areas[END_REF] assumes a fixed relationship to estimate the boundary of the urban area, separating it into the urban core area (A) and the adjacent urban area (W u ) (

). For our study, we used this method to additionally define the peri-urban areas (Wp). To parameterize the equation of [START_REF] Kasanko | Are European cities becoming dispersed?: A comparative analysis of 15 European urban areas[END_REF] for the boundary of the peri-urban area (W p ), we used the peri-urban estimate published by [START_REF] Kroll | Rural-urban gradient analysis of ecosystem services supply and demand dynamics[END_REF], obtaining a general equation for peri-urban areas: (see Fig. 3). By using these criteria, the width of the adjacent urban area and the peri-urban area are assumed to depend only on the area of the urban core in each city. Table 2 shows the resulting urban core areas and the corresponding W u and W p areas for 2006.

The urban core area (A) was computed for the Mediterranean cities using the urban land cover determined by CLC and GLC using 2006 as reference time period. In the case of CLC, from the 44 land cover classes (Appendix 2), we selected the polygons belonging to continuous and discontinuous urban fabric (categories 111 and 112) whose centroid was inside the administrative boundary of the city. From the fourteen land cover classes of GLC (Appendix 1), class 10 (urban and associated areas) was used to determine the urban core area. In a second step, we repeated this process including those polygons whose centroid was within a radius of 1 km from the selected urban polygons, to calculate the final size and location of urban core area (A).

-Insert Fig. 3 around here -

Identification of land cover changes

Focusing the analysis on the peri-urban area (W p ), we identified land cover changes from 1990 to 2012 for the European cities and from 1990 to 2006 for Northern African cities. Spatial land cover data was extracted for the different time periods in each city and its belonging country, considering the Mediterranean biogeographical region boundaries [START_REF] Olson | Terrestrial Ecoregions of the World: A New Map of Life on Earth A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity[END_REF]. The land cover data (area by land cover category) for each year in each W p area was normalized using the size of each peri-urban area, to be comparable across the different case studies. The same normalization was made for each country based on the proportion of that country classified as Mediterranean. In the remainder of this text we will refer to this area as the "national area". The spatial information was analyzed using ArcGIS 10.2.2 (ESRI, 2013).

To allow for the comparison between land cover categories from CLC (1990) and GLC (2006) in North Africa, we developed weighing factors using Andalusia and Sicily as most closely representative sampling sites for the Northern African Mediterranean setting. The spatial information of CLC and GLC in 2006 was intersected and extracted to measure the contributions of each CLC category in each GLC class. To transform the spatial GLC information of North African cities into information on each of the 44 CLC classes, we defined X x as the area of a specific GLC category and computed weighing factors (W x ) based on how the GLC categories in Andalusia and Sicily were composed of the different CLC categories. We applied these weighing factors in all calculations on North African areas to transform all GLC data into CLC data to allow for multiplication with the Stoll capacity matrix. This means that the surface of each CLC category (Y x ) is equal to a multiplication of the surface (km 2 ) for each GLC category (X x ) by weighing factors (W x ) (Equation 1).

Equation 1:

For the statistical analysis, the CLC categories were summarized in 7 different CLC groups (Table 3). To obtain the urbanization trends in Mediterranean cities, we estimated the total standardized surface by CLC group coming from W p and compared it with the total standardized land cover from the respective Mediterranean parts of countries (Portugal, Spain, France, Italy and Greece; Tunisia and Morocco) over the different periods.

Assessments for Europe and North Africa follow the same methods, but were applied separately because the uncertainties and applied methods for the input data are different.

Conversion of land cover changes into ecosystem services supply dynamics

Following an approach developed by [START_REF] Burkhard | Landscapes' capacities to provide ecosystem services-a concept for land-cover based assessments[END_REF][START_REF] Burkhard | Mapping ecosystem service supply, demand and budgets[END_REF], we related land cover data to expert-based values of the capacity for ES supply. In a recent study, [START_REF] Stoll | Assessment of ecosystem integrity and service gradients across Europe using the LTER Europe network[END_REF] developed an ES supply capacity matrix based on CLC types combined with expert-based estimates of the supply capacity for thirty-one ES for European countries. Capacity estimates for ES supply range from 0 (no relevant capacity of the land cover type to provide this particular ecosystem service) to 5 (very high capacity).

To assess how land cover changes around the case study cities influence ecosystem service supply over time, we translated our land cover changes into ES dynamics using the ES supply matrix published by [START_REF] Stoll | Assessment of ecosystem integrity and service gradients across Europe using the LTER Europe network[END_REF].

Estimates for each ES (ES x ) at different time periods in every peri-urban area were calculated by multiplying the area of each CLC class (X x ) by the corresponding ES value from ES matrix (ESstoll xn ) (Equation 2). The resulting ES assessment included twenty-seven ES supplied by peri-urban landscapes.

Equation 2:

Statistical analysis

The chosen statistics in this study responded to type of variables, sampling distribution and scientific objectives:

1) analysis of land cover changes around cities and comparison with trends at national level; 2) identification of common specific conversions of land cover among cities over time; and 3) assessment of spatio-temporal supply patterns of ecosystem services over the period 1990 -2012 in Mediterranean peri-urban areas.

For each objective, a group of statistical analysis was conducted. To assess whether land cover change patterns around cities differ from trends at the national level, the standardized total surface of land cover groups was statistically compared over time. For this purpose, we selected the non-parametric Wilcoxon test and the parametric Two-sample t-test. According to sampling distribution of CLC and paired groups, non-parametric Wilcoxon test was suitable for the case of permanent crops, complex cultivation patterns and shrub and/or herbaceous. Based on the assumptions of normal sampling distribution and paired groups, the parametric Twosample t-test was conducted for urban, non-irrigated and irrigated arable land, and forest land cover groups. Appendix 4). The data for the European cities was assessed using Within-class Correspondence Analysis (WCA) [START_REF] Benzécri | Analyse de l'inertie intraclasse par l'analyse d'un tableau de correspondance[END_REF][START_REF] Chessel | Méthodes K-tableaux[END_REF] through the "within.coa function" in the R package ade4 [START_REF] Rstudio | RStudio: Integrated development environment for R (Version 0.96.122[END_REF].

Data for the European and North-African cities was analyzed separately due to the differences in the input data (as discussed in section 2.3). Changes on ES supply in peri-urban areas over time were estimated conducting a Within-class Principal Component Analysis (WCP) [START_REF] Benzécri | Analyse de l'inertie intraclasse par l'analyse d'un tableau de correspondance[END_REF][START_REF] Chessel | Méthodes K-tableaux[END_REF], evaluating separately ES estimates for European and North African peri-urban areas (see Appendix 5 and 6).

WCA and WCP are similar to standard Correspondence Analysis with a single constraining factor to remove [START_REF] Chessel | Méthodes K-tableaux[END_REF]. As strong differences between cities may mask patterns over time, we used this analysis to compare spatio-temporal variations of land cover distributions and ES supply removing alternatively the effect of the city and the year variables as constraining factors.

Results

Land cover change under urbanization

Common patterns emerge for all selected Mediterranean cities when we compared land cover patterns over time between the selected Mediterranean cities and the trends in the respective countries (Fig. 4A and4B). Overall, changes were more pronounced in the peri-urban areas than at national level. As expected, all peri-urban areas demonstrated a significant increase of urban fabric. Around the European cities this took place mostly at the expense of complex cultivation patterns, non-irrigated and irrigated arable land, and shrub and/or herbaceous and pastures from 1990 to 2012. The parametric two-sample t-test revealed significant differences over the time between peri-urban areas from selected cities and countries in Europe in the case of urban, non-irrigated and irrigated arable land, and forest (p-value = 0.05) (Fig. 4A).

In the North African peri-urban areas, the increase of urban area from 1990 to 2006 occurred in parallel with an increase in irrigated arable land, permanent crops, complex cultivation patterns and shrublands and/or herbaceous and pastures, at the expense of non-irrigated arable land and forest, both around in peri-urban areas as well as at the national level (Fig. 4B).

-Insert Fig. 4 around here -

Mediterranean peri-urban areas, spatio-temporal dynamics in land cover

Within-class Correspondence Analyses (WCA) were performed separately to assess how land cover changes differed over time in peri-urban areas of Mediterranean European cities (from 1990 to 2012) and in peri-urban areas of Northern African cities (from 1990 to 2006) (Appendix 7). Results from European cities (where city as a variable was removed) showed that 4.56% of the variation was due to time patterns in land use; whereas when WCA was based on the time period or year (enhancing the differences between cities) 97.87% of the variation was due to the difference between cities and peri-urban land uses. This means that the differences of surrounding land use between cities are a dominant pattern that masks common trends if it is not removed beforehand.

In the case of European cities (Fig. 5A Results from WCA in North African cities (where city as a variable was removed) showed that 62.86% of the variation was due to temporal patterns in land use; whereas when removing year variable 82.18% of variation is due to differences between cities and land uses.

North African peri-urban areas (Fig. 5B) in 1990 were characterized by a clear pattern from non-irrigated arable land and forest patterns (in negative scores of F1) to an increase in 2006 of urban land, shrubs and herbaceous associated vegetation and pastures (in positive scores of F2). Peri-urban areas of Sfax showed transitions of permanent crops (in positive scores of F1) to urban land, shrubs and herbaceous associated vegetation and pastures (in positive scores of F2) also, with an increase of irrigated arable land.

-Insert Fig. 5 around here -

Ecosystem services supply: spatio-temporal patterns

The supply of ESs (Appendix 5 and 6) was estimated through multivariate within-class Principal Component Analysis (WCP), considering European and North African cities over the indicated periods respectively.

Trends in ES supply differed between EU cities (Fig. 6). -Insert Fig. 7 around here -All Mediterranean peri-urban areas show increases in the supply of air quality regulation, timber, wood fuel and religious and spiritual experience (Fig. 8). The European peri-urban areas show small or negative trends for the other ES. North-African peri-urban areas show much larger changes than those found in the European peri-urban areas, but this is maybe caused by the differences between CLC and GLC data. In general, the North-African peri-urban area showed stronger increases of ES supply capacities than the European peri-urban areas. In addition to the previously mentioned ES, the supply capacity of pollination, livestock, religious and cultural heritage increased in North-African peri-urban areas.

Peri-urban areas do not show the same patterns for ES supply over time (Fig. 9). In some peri-urban areas the supply of regulating and cultural ES was more important than for the provisioning ES (Lisbon, Barcelona, Marseille, Florence, Athens and Sfax) or the inverse in the case of Thessaloniki. In other cases, the supply of regulating ES was more important than provisioning and cultural ES (Madrid and Rome). Cultural ES increased around Nabeul, Rabat and Tunis.

-Insert Fig. 8 around here -

Discussion

Changes in land cover

Land cover changes in European Mediterranean peri-urban areas showed an expansion of urban and forested areas at the expense of agriculture land similar to described by d [START_REF] Amour | Future urban land expansion and implications for global croplands[END_REF] and [START_REF] Depietri | The urban political ecology of ecosystem services: The case of Barcelona[END_REF].

Especially irrigated (Marseille and Florence) and non-irrigated arable land (Madrid and Thessaloniki) were reduced. Around Barcelona, Lisbon and Athens, complex cultivation patterns, shrublands and pastures were more abandoned. In Rome's peri-urban areas where the urban area increased less, general land cover change patterns are also less pronounced.

Peri-urban areas of all North African cities, showed the same general pattern of increases in urban land, but instead this coincided with increases of agricultural land, herbaceous associated vegetation and pastures while irrigated agriculture and forest areas were reduced for Rabat, Nabeul and Tunis. In the peri-urban area of Sfax the area of irrigated arable land increased, while complex cultivation systems reduced in area. This expansion of both urban areas as well as agricultural areas in North Africa had been observed earlier [START_REF] Bouraoui | L'agriculture, nouvel instrument de la construction urbaine? Étude de deux modèles agri-urbains d'aménagement du territoire: le plateau de Saclay, à Paris, et la plaine de Sijoumi[END_REF].

Previous European focused studies demonstrated an expansion of woodlands in abandoned and marginal agricultural land [START_REF] Eea | Biogeographical regions in Europe. The Mediterranean biogeographical regionlong influence from cultivation, high pressure from tourists, species rich, warm and drying[END_REF][START_REF] Zanchi | Afforestation in Europe final version 26/01/07[END_REF]. Indeed, our results showed an increase in forest and shrublands for Europe at both peri-urban and national level. For the North African cities and countries, however, it is particularly shrublands which increased while the forest area showed a relatively slight decline.

-Insert Fig. 9 around here -

Implications of ES trends in peri-urban areas

The Mediterranean basin has some serious challenges to advance on global Sustainable Development Goals (UNEP/MAP, 2016), to which the ES supplied by peri-urban areas could positively contribute. In general, the ES supply capacity of peri-urban Mediterranean areas decreased over time, in particular for the supply of provisioning and regulating ES. If we consider the ES that are of most immediate concern for ensuring human well-being, i.e. supply of food, water and protection from hazards, then European and north-African peri-urban regions showed decreasing supply trends for the supply of food and protection from hazards. Supply of freshwater in Europe remains constant, but north-African peri-urban areas showed an increased supply of freshwater. This is linked to a growing surface of continental water bodies, since several dams and reservoirs have been built to address issues related to water scarcity and strong interannual variability of precipitation [START_REF] Tramblay | Future water availability in North African dams simulated by high-resolution regional climate models[END_REF]. However, as the ES of water purification decreased (Fig 8), we may have to be cautious as to the use of this water for all purposes.

Total area for crop production decreased over time in peri-urban areas, but this does not necessarily mean that the total food production also decreased. Changes in farm management may have increased the productivity of remaining agricultural land. Also, since these Mediterranean cities already rely heavily on food imports [START_REF] Lead | Drivers of change in ecosystem condition and services[END_REF][START_REF] Soulard | Peri-urban agro-ecosystems in the Mediterranean: diversity, dynamics, and drivers[END_REF], a reduction in locally produced food is likely not to lead immediately to a food deficit. However, an increased dependence on global food market prices does render countries more vulnerable to potential food crises.

Urbanization often implies the expansion of impermeable surfaces leading to an increase of surface water runoff, and consequently an increased risk of flooding [START_REF] Gómez-Baggethun | Urban Ecosystem Services[END_REF]. Our results show that the regulation of natural hazards has been decreasing over the years in Mediterranean peri-urban areas which pose a particular threat to people living around urban and peri-urban areas.

Depending on whether the supply of ES needs to be local in order to provide benefits, the peri-urban area can supply ES in the urban area. Recent studies on ES mismatches between supply and demand in urban areas have predominantly indicated deficits in local climate regulation (carbon sequestration, urban cooling), air quality regulation, and recreation and nature tourism [START_REF] Baró | Mapping ecosystem service capacity, flow and demand for landscape and urban planning: a case study in the Barcelona metropolitan region[END_REF][START_REF] Baró | Mismatches between ecosystem services supply and demand in urban areas: A quantitative assessment in five European cities[END_REF]. Of these deficits, peri-urban land could provide air quality regulation to reducing the deficit in the future. Although urban areas represent relatively small areas at a global scale, their increase could negatively impact local climate [START_REF] Foley | Global Consequences of Land Use[END_REF][START_REF] Verburg | Challenges in using land use and land cover data for global change studies[END_REF]. Our results indicate that Mediterranean peri-urban capacity to supply climate regulation has been decreasing. The steady trend or the increase of potential supply of some cultural ES by peri-urban areas (religious and spiritual experience) was not considered in previous assessment on ES around the Mediterranean, [START_REF] Nieto-Romero | Exploring the knowledge landscape of ecosystem services assessments in Mediterranean agroecosystems: insights for future research[END_REF][START_REF] Runting | Incorporating climate change into ecosystem service assessments and decisions: a review[END_REF] and this study offers therefore, a first reflection on its trends.

There are ES supplied by the peri-urban areas which may not actually reach inhabitants of urban areas, for instance trees only provide shade locally. We can assume however, that for other ES for which distances are less relevant (e.g. global climate regulation) or for which people are likely to travel short distances (e.g. recreation and nature tourism), ES supply by peri-urban areas can be considered relevant for urban areas. For instance, the increased potential of cultural ES in peri-urban areas that we found (due to predominantly an increase in the nonirrigated agricultural and forest areas) is increasingly relevant for people seeking to spend their leisure time outside of urban areas. As the urban population grows, it could be possible that the demand for cultural services, notably in the nearby surroundings of cities, will increase. To determine whether or not the identified increase in supply will be able to meet this presumed increase in demand would need to a more detailed study.

Our use of the capacity matrix developed by [START_REF] Stoll | Assessment of ecosystem integrity and service gradients across Europe using the LTER Europe network[END_REF] has several limitations, namely, 1) the capacity matrix was based on expert estimates only reflected the potential ES supply which can be different from the actual supply; 2) land cover information does not incorporate the type of management on arable lands and forest, prohibiting estimations of effects due to changes in land use intensity; 3) the matrix essentially represents a European perspective on land use and potential ES supply, so a capacity matrix adapted to the Mediterranean biome should be required to obtain more accurate estimates.

Despite those limitations, we consider that our approach allows assessing land cover and ES changing patterns across Mediterranean peri-urban areas based on openly available data, identifying potential influence on ES supply. The multi-city approach used for this study allowed addressing the complexity of landscapes and management around the Mediterranean basin reflected by the different evolution of supplied ES over time.

European peri-urban areas evolved from a bundle of ES provided mainly by agro-ecosystems to forest and natural vegetation ecosystems. Meanwhile, North African peri-urban areas supplied a bundle of ES from agroecosystems and natural vegetation ecosystems that change tending to rangelands over the years.

A first step to improve the estimates presented in this paper would be to take into account land management and its diversity, which is likely to entail a larger diversity in ES supply trends that can be obtained by focusing on land cover information only. In a second future step, the identified trends in ES supply should be confronted with the trends in demand for ES, to evaluate in a quantified manner how forecasted population increases in cities around the Mediterranean will affect ES deficits.

Conclusion

Mediterranean peri-urban areas can play an important role contributing to the supply of some ES to near urban areas (air quality regulation, timber, wood fuel and religious and spiritual experience). However, general trends indicated a decrease of ES supply due to land cover changes in Mediterranean peri-urban areas, induced by nearby urbanization. 111,112,121,122,123,124,131,132,133,141,142 Non

Land cover database

  Multivariate analyses were conducted to identify land cover changes over time and to detect spatio-temporal trends in ES supply around Mediterranean cities. Variables included land cover data for European cities (for theyears 1990years , 2000years , 2006years and 2012, see Appendix 3) , see Appendix 3) and data for North African cities(for 1990 and 2006, see

  ), different dynamics of land cover change over time occurred in the periurban areas. A clear pattern of change from non-irrigated arable land in 1990 (negative scores of F1) to urban in 2012 (positive scores of F1) was identified in Madrid and Thessaloniki. Barcelona, Lisbon and Athens showed transitions of complex cultivation patterns, shrublands and pastures (negative scores of F2) to forest (in positive scores of F2) in 1990, and to urban in 2012 (in positive scores of F1). Peri-urban areas of Marseille and Florence were characterized by a transition from irrigated arable land (negative scores of F1) towards urban. Land cover change patterns in the peri-urban area of Rome are less pronounced, but mostly correspond to permanent crops, shrublands and pastures in 1990 transforming into urban land in 2012. In conclusion, for European cities the temporal gradient was dominated by an increase of urban areas and marginal changes in agricultural land uses.

Figure 1 .

 1 Figure 1. Land cover information. A -Spatial information for 1990 (Corine Land Covergreen colour); B -Spatial information for 2006 (Globcorineblue colour); spatial information used in 2000, 2006 and 2012 covers only Europe (Corine Land Covergreen colour).

Figure 2 .

 2 Figure 2. Mediterranean biogeographical region (Olson et al. 2001) and selected study sites.

Figure 3 .Figure 4 .Figure 5 .

 345 Figure 3. Boundaries definition concept and applied example.

Figure 6 .Figure 7 .Figure 8 .Figure 9 .

 6789 Figure 6. Biplots of Within-class Principal Component Analysis (WCP) for the most statistical significant ecosystem services and their relationship with the European peri-urban areas (i.e., Lisbon, Madrid, Barcelona, Marseille, Florence, Rome, Athens, Thessaloniki). A: variables, B: observations.

Table 1 .

 1 Land cover data.

		Year	Spatial resolution	Cities	LC categories
		1990
	Corine Land Cover	2000 2006	100 m	Lisbon (Portugal), Madrid (Spain), Barcelona (Spain), Marseille (France), Florence (Italy), Rome (Italy), Athens (Greece), Thessaloniki (Greece)	44
		2012
		1990	250 m	Rabat (Morocco), Tunis (Tunisia), Sfax (Tunisia),
	GlobCorine	2006	300 m	Nabeul (Tunisia)	14

Table 2 .

 2 Urban and surrounding areas (km 2 )

	CLC groups

Table 3 .

 3 CLC categories summarized into CLC groups.

			LISBON	MADRID	BARCELONA	MARSEILLE	FLORENCE	ROME	ATHENS	THESSALONIKI	RABAT	TUNIS	SFAX	NABEUL
	Urban core (km	2 )	103,39	175,20	74,07	104,01	43,50	296,05	163,07	44,77	251,89	427,33	149,85	23,72
	Adjacent urban area Wu (km 2 )	348,61	431,82	219,95	441,96	145,01	1483,68	452,86	135,46	410,34	790,00	209,41	43,37
	Peri-urban area Wp (km 2 )	1412	2409,41	1000,45	1849,99	657,24	5031,76	2107,68	640,91	3451,95	5715,11	1884,03	350,25

  Appendix 4. Land cover standardized surface in peri-urban North African cities from 1990 to 2006. Appendix 5. Ecosystem service capacity provision estimated for European peri-urban areas from 1990 to 2012. Appendix 6. Ecosystem service capacity provision estimated for North African periurban areas from 1990 to 2006.

							2012	15,289			0,521				0,000				3,061			13,310		12,063	15,027	40,729
				THESSALONIKI		1990	7,124			29,634				7,175				0,443			14,032			7,117	14,420	20,055
							2000	7,678			29,709				7,088				0,000			13,938			5,893	15,634	20,060
	EESS PROVISI ON -EU (km 2 * estimatio n) EESS PROVISI ON -North Africa (km 2 * estimatio n)	Year Year	Global climate regulation Global climate regulatio n	Local climate regulatio n Local climate regulatio n	Air quality regulatio n Air quality regulatio n	Water flow regulatio n Water flow regulatio n	2006 2012 Water purificati on Water purificati on	15,018 15,045 Nutrient regulatio n Nutrient regulatio n	Erosion regulatio n Erosion regulatio n	19,820 19,839 Natural hazard protectio n Natural hazard protectio n	Pollinatio n Pollinatio n	Pest and disease control Pest and disease control	7,177 7,094 Regulatio n of waste Regulatio n of waste	Crops Crops	0,000 0,000 Energy (Biomass) Fodder Energy (Biomass ) Fodder	Livestock Livestock	16,724 16,765 Fibre Timber Fibre Timber	Wood fuel Wood fuel	5,446 5,472 Wild Wild food, semi-domestic livestock and ornament al s s resource food, semi-domestic livestock and ornament resource al	Biochemi cals and medicine Biochemi cals and medicine	15,971 15,942 Freshwat er Recreati on and tourism Recreati Freshwat on and er tourism	Landsca pe aesthetic , amenity and inspiratio n Landsca pe aesthetic , amenity and n inspiratio	19,845 19,843 Knowled ge systems Religious and spiritual experien ce Religious Knowled and ge spiritual systems experien ce	Cultural heritage and cultural diversity Cultural heritage and cultural diversity	Natural heritage and natural diversity Natural heritage and natural diversity
	NABEUL		312,489	242,464	17,653	52,478	286,019	288,058		51,679	150,971		66,351	240,647	233,519		163,389		137,769	133,886		44,313	89,420	20,001	37,991	250,279	204,304	0,457	308,984	311,816	331,790	32,051	234,060	271,570
			110,537	172,486	59,746	147,179	146,541	141,885		124,268	135,472		103,582	164,796	207,246		143,518		111,302	63,028		66,528	62,382	82,525	105,668	173,900	105,718	90,949	342,044	305,668	297,387	115,534	251,342	264,913
	SFAX		299,783	220,164	43,534	61,011	279,125	278,395		62,622	125,707		50,959	200,164	184,150		212,441		111,120	86,580		8,308	39,803	136,523	136,534	213,487	159,586	2,043	395,276	348,311	355,137	86,595	272,984	328,299
	RABAT		STANDARISED SURFACE % (land cover groups) 87,839 164,908 31,465 142,043 326,601 302,231 108,664 86,251	Year URBAN 121,429 110,244 316,500 313,650	106,321 122,225	NON-IRRIGATED ARABLE LAND 135,262 89,403 184,568 125,280	IRRIGATED ARABLE LAND 170,484 184,249 133,374 254,858 250,813 165,262	PERMANENT CROPS 93,498 59,496 162,117 128,870	COMPLEX CULTIVATION PATTERNS 64,994 68,992 36,825 52,307 11,538 70,644 107,736 114,476	FORESTS 153,494 308,826	SHRUB AND/OR 84,466 310,582 HERBACEOUS VEGETATION 90,600 282,710 ASOC AND PASTURES 246,184 6,067 321,737 322,791	OTHERS 269,165 66,221 CATEGORIES 331,931 67,908	207,049 227,962	247,250 292,171
				NABEUL			0,429		0,43			12,23				2,68				5,68				15,91	11,982	51,018
			121,146	182,818	71,328	147,142	148,046	144,343		137,294	133,701		120,929	164,786	198,491		172,874		124,335	71,461		72,245	70,545	101,461	128,755	174,431	116,848	75,826	334,781	304,327	302,295	113,677	258,980	268,210
								7,412		7,41			8,09				3,13				11,03				11,43	14,094	39,552
	TUNIS		216,298	224,977	37,844	88,996	177,533	176,861		76,849	135,210		98,911	181,707	174,019		273,091		189,307	136,028		42,442	114,581	43,040	59,951	189,404	158,934	4,822	251,206	248,653	285,513	42,793	235,044	196,021
			125,511	SFAX 190,205 75,822	139,873	132,022	0,219 130,222	137,189	0,22 122,203	129,075	156,309	5,48 172,357	232,339		154,723	0,00 90,106		83,330	96,172	34,76 116,172	142,650	10,29 158,694	119,711	1,256 50,553 311,060	285,848	47,984 294,556 108,999	268,805	248,358
								4,818		4,82			10,84				2,81				4,38				12,55	9,062	53,864
				RABAT			0,267		0,27			28,22				0,03				1,18				5,60	2,950	41,476
								3,754		3,75			11,11				2,44				14,08				13,35	16,647	32,238
				TUNIS			0,622		0,62			36,66				2,29				9,17				10,31	10,323	27,819
								2,691		2,69			16,20				4,94				17,78				15,17	16,383	20,464
	ROME		128,936	179,164	92,054	95,175	105,090	97,349	122,211	97,375	118,235	151,830	136,329	215,767		131,043	101,45 9	23,823	86,372	114,023	122,393			137,078	108,127	13,292	212,913	189,015	202,580	78,021	189,790	151,108
			119,253	ATHENS 173,531 91,193	94,273	93,847	8,237 86,800	121,234	1,344 93,358	118,361	147,843	0,000 132,092	216,578		3,223 125,779 101,79 0	22,568	19,286 90,082 114,381	120,867	11,588 129,743	102,619	20,912 13,082 201,318	181,481	35,410 194,963 78,664	186,099	142,797
			126,792	177,599	90,815	94,060	101,553	10,246 94,491	120,832	1,066 96,304	118,125	152,158	0,000 136,533	215,792		3,027 127,021 103,01 3	22,659	18,005 89,697 113,834	120,506		9,117 135,717	106,952	23,048 13,102 207,970	187,891	35,491 201,081 78,921	189,145	148,904
			126,792	177,599	90,815	94,060	101,553	15,122 94,491	120,832	0,574 96,304	118,125	152,158	0,000 136,533	215,792		3,070 127,021 103,01 3	22,659	13,413 89,697 113,834	120,506	14,310 135,717	106,952	16,822 13,102 207,970	187,891	36,689 201,081 78,921	189,145	148,904

Acknowledgements

This work has received support from European Union FP7 projects OPERAs (Contract No. 308393, to APGN and WC), EU BON (Contract No. 308454, to IG and WC) and ECOPOTENTIAL project (Contract No. 641762, to IG). The authors acknowledge Labex OT-Med (ANR-11-LABX-0061) funded by the French Government Investissements d'Avenir program of the French National Research Agency (ANR) through the A*MIDEX project (ANR-11-IDEX-0001-02). Special thanks for valuable advice go to Berta Martín-López, Violeta Hevia-Martín, Claude Napoleone, Marina Cantabrana and Benjamin Mary. We also thank three anonymous reviewers for their constructive comments.

OTHERS CATEGORIES LISBON 10,739 4,419 0,830 0,129 27,795 7,248 11,590 37,250 18,272 2,955 0,513 0,889 23,866 5,928 10,585 36,992 19,499 2,857 0,548 0,865 23,133 5,798 10,263 37,037 19,998 2,649 1,682 0,624 21,883 6,040 10,005 37,119 MADRID 9,969 41,753 4,952 2,057 7,805 7,353 25,769 0,342 16,950 36,069 4,250 1,910 7,135 7,456 25,801 0,430 21,689 33,182 3,873 1,699 6,335 7,247 25,522 0,454 24,829 31,340 3,432 1,755 5,637 13,383 18,864 0,760 BARCELONA 19,749 8,023 4,481 1,261 4,204 15,084 8,750 38,447 22,411 7,078 3,820 1,232 3,768 14,851 8,356 38,483 25,470 6,233 3,082 1,180 3,411 14,914 7,378 38,332 25,990 4,807 2,566 1,294 1,545 17,633 7,888 38,278 MARSEILLE 10,020 2,773 0,000 2,252 9,017 17,166 14,777 43,994 11,291 2,566 0,000 2,144 8,871 17,120 15,056 42,953 11,541 2,530 0,000 2,135 8,738 16,552 15,328 43,176 12,172 2,268 0,000 2,136 8,441 16,364 15,975 42,644 FLORENCE 8,216 15,634 0,000 24,596 15,808 32,859 2,401 0,485 9,658 14,518 0,000 24,552 15,282 33,217 2,166 0,608 10,138 14,168 0,000 24,516 15,210 33,317 2,136 0,516 11,205 12,872 0,000 25,276 14,493 33,694 1,963 0,497 ROME 4,206 21,181 0,000 11,299 16,693 13,739 3,386 29,495 4,378 21,506 0,000 10,200 17,522 13,750 3,052 29,593 4,569 21,341 0,000 10,223 17,476 13,656 3,115 29,620 4,569 21,341 0,000 10,223 17,476 13,656 3,115 29,620 LISBON 104,945 146,094 52,712 76,263 93,706 83,958 104,976 91,634 97,049 165,774 154,361 136,308 93,783 99,078 48,168 90,359 48,780 69,098 113,234 73,984 9,905 186,355 186,888 189,761 71,990 174,361 140,182 81,677 118,387 46,108 66,024 63,712 53,603 91,949 63,890 90,640 126,148 114,791 120,533 81,791 86,971 46,470 75,527 43,413 62,703 88,290 56,307 9,135 165,358 153,388 153,729 88,236 153,579 105,086 91,473 123,161 45,036 64,557 83,133 74,155 89,405 79,142 89,591 143,037 135,594 118,531 89,452 88,420 44,721 73,541 41,897 60,720 108,176 62,028 9,083 189,302 178,143 174,508 91,149 164,917 120,896 79,364 115,634 47,099 65,324 62,740 53,385 92,397 61,996 88,735 121,708 111,654 116,718 84,229 83,894 50,448 73,522 44,639 62,422 91,044 54,868 9,705 162,858 151,809 150,777 92,415 152,091 102,510 MADRID 137,797 199,918 56,863 108,995 111,356 121,370 132,650 110,338 142,564 135,914 148,838 274,137 195,064 135,37 5 90,761 135,202 50,567 79,411 162,637 127,094 4,652 201,209 225,817 261,502 89,716 250,232 148,864 130,689 186,171 57,627 103,281 111,629 121,891 131,774 103,995 140,643 127,803 141,433 242,262 178,412 124,30 3 85,941 118,698 49,981 79,663 158,859 121,162 4,575 204,671 228,131 253,178 101,874 244,149 147,914 123,451 174,879 56,463 98,327 105,735 114,796 128,026 98,353 136,908 122,045 137,988 223,268 169,395 119,79 8 85,268 108,876 48,865 78,175 153,020 113,923 4,896 202,429 221,640 242,784 105,976 236,262 141,380 131,432 188,827 82,577 102,726 118,983 126,120 148,076 106,672 145,994 129,522 144,785 208,887 169,671 127,08 9 78,080 93,980 82,616 101,141 160,224 129,146 5,733 221,928 228,805 232,985 113,354 238,321 152,210 BARCEL ONA 104,597 139,139 88,391 65,725 107,207 106,103 105,470 84,387 109,993 114,706 115,719 90,618 93,764 46,019 43,271 52,729 68,616 85,006 111,394 85,945 3,829 170,836 189,225 175,857 117,118 176,564 136,369 90,790 126,253 86,867 62,620 94,903 93,991 102,600 75,901 107,380 103,571 104,711 81,508 86,375 40,758 38,859 46,318 67,230 82,956 100,715 76,276 3,512 160,800 178,281 163,086 119,090 168,926 124,043 95,075 125,564 86,586 59,491 100,586 99,067 98,178 76,513 105,049 104,425 105,097 72,774 82,363 39,385 32,015 39,924 66,829 81,916 103,691 78,496 3,458 163,040 179,719 161,798 117,983 165,671 125,924 93,834 130,124 100,189 66,236 106,400 105,671 117,187 80,173 115,280 101,974 103,284 58,125 76,210 37,244 28,351 26,481 77,559 92,762 101,322 83,260 1,991 165,372 183,837 153,062 120,179 164,404 133,256 MARSEI LLE 111,411 157,355 106,099 82,843 131,348 131,976 133,360 108,164 135,612 133,547 131,249 67,212 72,312 45,323 23,159 32,200 73,884 107,622 120,187 114,603 1,850 189,120 215,081 184,777 113,303 172,073 183,176 106,295 151,825 107,475 82,517 126,013 127,594 133,514 107,041 138,397 131,674 128,779 65,940 70,985 44,775 21,833 32,220 73,202 108,238 118,007 116,612 1,643 186,608 215,665 182,889 117,600 172,633 180,830 105,661 149,557 104,906 81,011 124,507 126,091 130,315 105,637 136,935 130,942 128,995 65,374 70,968 44,759 22,872 32,533 70,935 106,469 118,177 114,907 1,635 185,909 214,075 182,918 117,106 171,136 178,250 103,419 146,747 104,621 80,854 122,703 124,202 129,828 104,603 138,177 129,288 128,160 63,504 70,686 43,747 24,031 31,800 70,143 106,866 117,562 113,602 1,643 186,138 214,294 182,850 120,036 171,013 177,062 FLOREN CE 193,919 258,570 195,260 128,613 196,728 192,867 215,729 138,292 177,815 215,029 198,635 241,838 150,413 113,10 9 15,457 75,417 236,077 256,816 189,705 173,841 5,022 339,559 321,765 305,446 182,269 289,536 266,320 193,160 256,651 196,341 127,204 197,859 194,424 216,145 137,630 177,685 213,766 197,500 234,689 147,249 110,60 6 13,717 72,073 236,730 256,974 189,730 173,045 4,846 340,556 322,355 303,497 184,748 288,627 266,316 193,097 256,172 196,780 126,939 198,312 194,873 216,556 137,464 177,697 213,674 197,462 232,615 146,659 109,85 4 13,635 71,143 237,083 257,356 189,882 172,910 4,874 340,651 322,917 303,481 185,496 288,566 266,537 193,283 254,591 199,142 126,494 200,625 197,478 218,644 137,548 178,392 212,681 195,734 226,819 145,902 107,36 4 12,309 66,968 237,373 257,985 190,031 173,269 4,195 345,555 324,019 301,760 187,129 288,851 266,849 ATHENS 113,068 146,677 85,671 82,287 114,243 110,934 129,314 92,356 134,158 148,577 139,569 96,617 78,479 63,284 46,926 65,878 60,262 101,040 120,086 105,884 5,750 181,755 208,424 201,081 18,556 61,988 39,373 92,633 126,313 75,064 77,396 92,753 89,640 117,404 80,931 129,405 132,619 127,237 89,870 74,853 58,148 51,204 63,888 49,300 94,418 105,749 92,215 5,618 164,652 191,603 188,511 18,317 58,793 34,432 110,525 142,303 94,250 77,242 121,486 118,819 129,790 91,032 132,630 139,484 131,413 74,723 74,514 57,621 36,942 44,376 67,672 106,038 121,562 109,146 4,423 190,175 211,711 189,463 19,716 59,197 38,499 88,793 125,752 81,091 74,093 101,116 98,565 120,289 81,288 121,935 124,459 111,326 74,026 68,138 55,001 38,090 42,742 58,631 93,117 105,010 96,477 4,395 180,025 197,139 172,515 19,749 57,520 35,183 THESSA LONIKI 117,510 178,528 55,660 100,109 91,191 94,486 100,697 101,271 116,576 144,519 131,552 240,847 167,882 125,32 8 52,279 129,664 42,002 63,560 134,987 107,776 5,141 162,875 186,291 213,034 318,720 597,785 561,152 100,224 165,622 49,362 95,119 69,034 70,128 91,844 92,801 114,360 133,498 125,396 238,606 165,581 121,46 2 61,864 134,154 37,186 61,732 115,665 97,525 4,977 146,246 169,680 201,209 311,819 555,889 495,746 102,450 155,985 49,606 91,497 81,958 84,854 92,892 90,083 110,168 138,786 123,525 201,948 146,025 113,64 6 51,704 119,170 35,295 61,316 121,027 96,828 4,753 155,449 185,303 203,661 383,423 574,958 543,387 88,737 147,750 49,704 91,528 68,256 71,084 93,205 84,663 110,227 130,477 115,218 201,783 143,016 110,94 6 51,495 118,924 35,482 61,417 110,027 88,646 4,798 144,593 174,359 192,603 349,169 530,562 499,209