Planting the SEED: Towards a Spatial Economic Ecological Database for a shared understanding of the Dutch Wadden area

Journal of Sea Research 82 (2013) 153–164

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Planting the SEED: Towards a Spatial Economic Ecological Database for a shared understanding of the Dutch Wadden area Michiel N. Daams ⁎, Frans J. Sijtsma University of Groningen, Faculty of Spatial Sciences, Landleven 1, 9747 AD Groningen, The Netherlands

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Article history: Received 3 February 2012 Received in revised form 30 November 2012 Accepted 5 December 2012 Available online 20 December 2012 Keywords: Wadden Area Economy Ecology Spatial Planning Stakeholder Validated Integrated Evaluation

a b s t r a c t In this paper we address the characteristics of a publicly accessible Spatial Economic Ecological Database (SEED) and its ability to support a shared understanding among planners and experts of the economy and ecology of the Dutch Wadden area. Theoretical building blocks for a Wadden SEED are discussed. Our SEED contains a comprehensive set of stakeholder validated spatially explicit data on key economic and ecological indicators. These data extend over various spatial scales. Spatial issues relevant to the specification of a Wadden-SEED and its data needs are explored in this paper and illustrated using empirical data for the Dutch Wadden area. The purpose of the SEED is to integrate basic economic and ecologic information in order to support the resolution of specific (policy) questions and to facilitate connections between project level and strategic level in the spatial planning process. Although modest in its ambitions, we will argue that a Wadden SEED can serve as a valuable element in the much debated science–policy interface. A Wadden SEED is valuable since it is a consensus-based common knowledge base on the economy and ecology of an area rife with ecological–economic conflict, including conflict in which scientific information is often challenged and disputed. © 2012 Elsevier B.V. All rights reserved.

1. Introduction This paper explores the characteristics of a Spatial Economic Ecological Database (SEED) and its ability to support a common understanding among planners and experts about the Dutch Wadden area and its economy and ecology. As both a peripheral rural region and a natural UNESCO World Heritage Site, the Dutch Wadden area is characterized by high ecological integrity and quality. In recent decades the potential spatial conflict between economic and ecological values has played a crucial role in the development of the Wadden area and related policy debates (De Jong, 2007; Enemark, 2005; Floor et al., 2013; Oosterveld, 2011; Turnhout et al. 2008). Due to this potential conflict a sustainable approach to regional development in the Wadden area, which integrates economic and ecologic values and perspectives, has received increasing attention (De Jonge et al., 2012; Kabat et al., 2012). Regional development policy in the Wadden area is largely regulated by strategic spatial planning (Nota Ruimte, PKB-Waddenzee, Natura 2000). In strategic planning, stakeholders involved in the process define a shared vision of the desired future of a region which sets the aim for long-term regional development plans. A recent strategic vision which regards the management and development of the Wadden area is known as ‘Lèven in de Wadden’ by Regiecollege Waddengebied (2008).1 Empirically, strategic planning builds on planners' perceptions ⁎ Corresponding author. Tel.: +31 50 363 8655; fax: +31 50 363 3901. E-mail address: [email protected] (M.N. Daams). 1 Regiecollege Wadden gebied is a collaboration of the Dutch central government, provinces, municipalities, and Water Boards. 1385-1101/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.seares.2012.12.002

of place-specific qualities and assets and the wider context of perceived opportunities and threats (Albrechts, 2004; Wortelboer and Bischof, 2012). A shared vision(s) must therefore be rooted in a basic understanding of an area (Albrechts, 2004). At best, a strategic spatial plan serves as a framework for short-term (public and private) project-based spatial interventions (Albrechts, 2004; Faludi, 2000; Healey, 2004). Then, in the effort to maintain empirical consistency, models and data upon which evaluations are based need also to be coordinated. However, in practice, project-based interventions in the Wadden area, (e.g. cockle fisheries initiatives, gas extraction, energy plants in the Eemshaven, a waste burning plant in Harlingen) focus on project-based empirics, and every project evaluation (e.g. EIAs) generally builds its own set of empirical data. Several individual project-based evaluations (e.g. the EVA II evaluation of cockle fisheries (Ens et al., 2004)) were heavily discussed with regard to the appropriateness of the chosen economic and ecological indicators to permit a well-founded decision based on solid empirical evidence (Hanssen et al., 2009; Runhaar and Van Nieuwaal, 2010; Swart and Van Andel, 2008). In all of the sectoral projects mentioned above, we can see strong conflicts between economy and ecology, but we observe little integration of empirical data. With the aforementioned in mind, we see the need for ‘double integration’: first to integrate economy and ecology, and second to integrate strategic level decision making and project-based decision making. At the strategic level, the empirical base, that is, the factual spatial knowledge of planners often remains implicit. In the management of the Wadden area there is no common knowledge base that allows for an integrated spatial evaluation of regional development visions or projects. As a result, individual projects and visions seem

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to build their own empirics, and may hardly refer to the relevant wider spatial or multi-sectoral context. An integration of the economy and the ecology of a rural region such as the Wadden area is complicated and the literature often focuses at a conceptual level (Chapin et al., 2006; Collins et al., 2011; De Jonge et al., 2012; Holling, 2004). The issue of double integration is obviously a complex one, and no magic bullet, and no single model, concept, or bright idea on management or governance can solve every issue arising. Nevertheless, spatial relations can allow for effective ways to integrate economy and ecology in spatial planning (Albrechts, 2004). Against this background, we discuss the construction of a Spatial Economic Ecological Database (SEED) as an empirical building block for a shared understanding of the Wadden area. This SEED contains a comprehensive set of stakeholder validated data on key economic and ecological indicators at various spatial scales. Its functions are to integrate economic and ecologic values in support of addressing specific (policy) questions, and to permit a connection between project level and strategic level in spatial planning (see Fig. 1). Stated briefly, we think that a publicly available SEED showing spatially explicit data regarding key variables of the Wadden area, and its socio-economics and ecology from multiple spatial scales, is pivotal to a wider basic understanding of the area. The wider understanding at which such a SEED aims, is the widespread basic understanding of the Wadden area: more people active in government, as stakeholders in various types of decision making, or as scientific experts, etc., should have a shared common spatial database. Experts on the Wadden economy could benefit from a basic spatial insight into the ecology of the area, while experts on the Wadden ecology or morphology could benefit from basic spatial insights into the area's economy. The Wadden-SEED discussed here may provide a common knowledge base useful as empirical support and evaluation of projects and strategic spatial visions if data quality in the SEED are already agreed on by experts, and if it is accessible to stakeholders. A Wadden-SEED will not be a panacea for all ills, nor will it prevent all conflict, but it will provide a link in the chain of informed decision making, and be able to address the double integration challenge to manage the Wadden area wisely. The paper is structured as follows. In Section 2 we describe the study area and then, in Section 3, identify the core conceptual structure of the SEED in a discussion of theoretical strands referring to its construction. We elaborate on these concepts using Wadden-specific empirical illustrations of a SEED's data requirements and by discussing key issues of spatial scales. The elements and characteristics of a SEED for the Wadden area are synthesized in Section 4 and the paper ends with a discussion.

strategic goal. The implication here is to prevent degradation of the area by external forces and economic activities: several ecology-driven protection regimes have been formalized, such as the Dutch 1998 Nature Conservation Act, operational at national scale; Natura 2000 at EU scale — covering nearly the complete Wadden Sea, large parts of the islands, and a small percentage of the mainland land surface area; and World Heritage regulations in force at the global scale (see Fig. 2). The second general perspective of the Wadden area is as a rural area, “with one or more small or medium-sized cities surrounded by large areas of open space, with a regional economy comprising agricultural, industrial and services activities, and a relatively low population density” (Terluin, 2003, pp. 328–329). Fig. 2 depicts the degree of urbanization at the neighborhood level for the Dutch Wadden area. This figure also shows that the Wadden area is located peripheral to the central urban core of the Netherlands. The sea surface of the Dutch Wadden area covers 264,224 hectares (4.3% of total Dutch sea surface). In 2009 the land surface of the Dutch Wadden area comprises 179,254 hectares (5.1% of total Dutch land surface), and residential locations for 257,620 individuals (1.6% of total Dutch population), and provides space to firms that supply a total of 102,167 jobs (1.3% of total Dutch employment).2 Employment levels for the Dutch Wadden area in the economic sectors mentioned by Terluin (2003) are shown in Fig. 3. Although the agricultural sector (agriculture, foresting and fisheries) is a modest supplier of employment, it is nevertheless dominant in individuals' experience of rural areas, given its extensive land use (Strijker, 2005). Economic structure and performance in the Wadden area are heterogeneous and differentiated across different areas. Fig. 3 shows the heterogeneity of both absolute and relative employment levels in the typically ‘rural’ economic sectors for Wadden area municipalities. Inter-municipal differences in relative employment levels in the chosen sectors indicate spatial differentiation in regional specialization. We can observe that employment in the Wadden area is predominantly concentrated in the service sector. However, in a number of municipalities, including Delfzijl, Dongeradeel and Harlingen, the rural economy is shown to be relatively specialized in industrial activities. 3. Theory 3.1. Introduction In the next three subsections we will discuss the main theoretical building blocks for the Wadden SEED in support of a shared understanding among planners and experts of the Wadden area's economy and ecology. These building blocks are:

2. Description of the study area In this paper we define the Wadden area by the (2009) borders of the municipalities as situated adjacent to the Wadden Sea. The Wadden area can in general be approached from two perspectives. Firstly, it may be perceived as a valuable natural area and towards its furtherance as a natural area, the conservation of its current ecological qualities is an essential

• (Subsection 3.2) a basic understanding of rural economic development and issues of spatial scale, • (Subsection 3.3) a basic understanding of interaction between rural economic development and ecology and issues of spatial scale, and • (Subsection 3.4) a basic understanding of the methodological and spatial issues in project evaluation. In our discussion of the building blocks we will touch upon four issues highly relevant to the SEED. These major issues are highlighted explicitly in the text. At the end of each theoretical subsection we provide Wadden-specific (empirical) illustrations of the issues and related data requirements for the SEED. 3.2. A basic understanding of rural economic development and the issue of spatial scale 3.2.1. Competitiveness of regions Rural economic development is often defined as a change in GDP, physical output, or productivity per capita and its success can be defined

Fig. 1. Issues of double integration to be addressed by a SEED.

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Sources: Statistics Netherlands and LISA (www.lisa.nl).

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Fig. 2. The Wadden area as both rural and natural area. Sources: Statistics Netherlands; Common Wadden Sea Secretariat.13 In Fig. 2 the degrees of urbanization are defined by levels of mean address density per square kilometre, following the definitions of Statistics Netherlands: b500 for ‘not urbanized’; 500–1000 for ‘little urbanized’; 1000–1500 for ‘fairly urbanized’; 1500–2500 for ‘urbanized’; and >2500 for ‘highly urbanized’.

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by economic growth (Armstrong and Taylor, 1993; Illge and Schwarze, 2009; Terluin, 2003). While in traditional economics the Ricardian perspective that factor-based comparative advantages in production determine economic growth has been dominant, the paradigm of competitive advantage has gained precedence over approximately the past 25 years (Kitson et al., 2004). Terluin (2003) describes competitiveness as central to the description of rural economic development. Regional competitiveness can be defined by “the ability of an (urban) economy to attract and maintain firms with stable or rising market shares in an activity while maintaining or increasing standards of living for those who participate in it” (Storper, 1997, p. 20), and the ability of a region's firms to acquire or utilize competitive advantages in order to sell their products at market prices that exceed the cost of provision (Ketels, 2006; Porter, 1990). Regional competitiveness can be assessed through measures of competitive advantage. Useful measures are (labor or total) productivity rates, which should be interpret in a combination with measures of

20,000

Wadden municipalities (west to east)

regional employment rates because this allows researchers to identify possible distortions in a region's productivity rates that are caused by sudden reductions in employment (Armstrong and Taylor, 1993; Kitson et al., 2004; Terluin, 2003). Although competitiveness can be measured and compared for a specific selection of regions or at a specific spatial scale, the economic unit within which a region's firms compete cannot be derived entirely from statistics. The identification of the economic unit requires entrepreneur or expert knowledge (e.g. who competes with whom?) because competition between firms or regions has to be revealed explicitly (Porter, 1990). In general, rural areas are known to be less competitive than urban areas because highly educated human capital and R&D activities have a tendency to concentrate in urban areas (Glaeser, 1999; Rodríguez-Pose, 2001). This may cause rural areas to face higher unemployment rates, lower incomes, lower participation rates, lower educational levels and also (selective) out-migration resulting in population decline (Armstrong and Taylor, 1993). Mainland coast municipalities (west to east)

18,000

0 10,000

16,000

Employment

12,000

30,000

10,000 40,000

8,000 6,000

Population

20,000

14,000

50,000

4,000 60,000

2,000 0

70,000

Agriculture, foresting and fisheries sector

Industrial sector

Service sector

Population

Fig. 3. Employment in traditional rural-economic sectors (left axis) and total population (right axis) for all 18 municipalities in the Wadden area in 2009. Source: LISA.14 The service sector is defined by plural subsectors and distinguished by two digit SBI'08 codes: financial institutions; advisory, research and other specialized business services; rental of movable property and other business services; public administration services, government services and obliged social services; education; healthcare and well-being; other services. The industrial sector is defined by SBI'08 category C. SBI'08 category A is used to operationalize the agriculture, foresting and fishing sector.

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3.2.2. Spatial scales of rural economic development The competitiveness of regions is determined on multiple spatial scales. This can be characterized by the increasing shift towards dominant international markets as globalization processes instigate a restructuring and relocation of rural economic production. Globalization is a main driver of change in the specification of the rural production structure developed over the past decades. Rural areas in Western European countries are increasingly typified by a decline in employment in primary sectors, which is counterbalanced by employment growth in the service sector, concentrating mostly in cities within these rural areas (Bryden and Bollman, 2000; Ward and Brown, 2009). Primary economic sectors in these high-cost producing countries have partly been outcompeted in international markets by low-cost producing countries, but are nevertheless still important pillars of rural economies (Terluin, 2003). On a lower spatial scale, rural economies are often tied in with urban economies (Irwin et al., 2009). Agarwal et al. (2009, p. 316) find that “lack of accessibility to big cities” depresses economic productivity in rural areas, and Partridge and Olfert (2009) and Partridge et al. (2008) verify a negative relation between distance to metropolitan area and job and population growth, which is in line with the observation of Van Jaarsveld et al. (2005), that peripherality or remoteness may constrain a rural area's economic competitiveness. This seems to be a rather straightforward relation, since urban regions contain high concentrations of economic activity. The degree of relative peripherality impacts on rural-economic development may, however, change due to emergent spaces of flows, in particular through improved telecommunications leading to an increased dominance of urban cores in the globalizing economy (Castells, 1996). One can assume “that rurality lies a long way from the organizing centers of the networks”, given “the urban concerns that lie at the center of Castells' work” on global economic networks (Murdoch, 2000, p. 408). And yet, economic actors may become increasingly footloose, thereby causing a spatial de-coupling of the supply and demand for labor as a result of higher mobility and intensifying socio-technological networks that untie traditional spatial relations (Ward and Brown, 2009). People may tend to choose to live in amenity-rich rural areas and commute to work in an urban location (Heins, 2004; Irwin et al., 2009; Van Dam et al., 2002). Schindegger and Krajasits (1997) and Bryden and Bollman (2000) observe that rural areas are often net suppliers of labor to urban areas (shown below in illustration 1 for the Wadden area). One might think that globalization leads to a decreasing relevance of local competitive advantage in economic competition. However, Camagni (2008, p. 34) argues in the context of globalization that regions should “rely on local assets and potentials and their full — and wise — exploitation”. Similarly, given the substantial flows of capital, labor, information, and goods and services to urban areas, Bryden and Munro (2000) assert that specialization towards immobile resource-based sectors may provide a stable basis for rural economic development (shown by illustration 2 for the Wadden area). The tourism sector, which is driven by the appreciation of immobile environmental capital, is a dominant component of the economies of several municipalities in the Dutch Wadden area (Sijtsma et al., 2012a, 2012b). We have in this section identified the theoretical centrality of the concept of competitiveness in rural economic development and touched on two significant theoretical issues in the analysis of competitiveness: the rural tie-in with the urban economy and (sectoral) specialization. Empirical illustrations of the relevance of these issues for the SEED are given in the next two sections. 3.3. Empirical illustration 1: Rural tie-in with the urban economy 3.3.1. Objectives and data Next we will set out an illustration of the tie-in of the rural Wadden area within (external) urban economies in accordance with a key observation in Section 3.2.2. Such economic relations can be revealed through

flows of goods and production factors between areas, the spatial market areas of firms, both internal and external to the Wadden area, and the economic structure in which firms in the Wadden area compete. Commuting data is presented in order to illustrate a tie-in between the rural Wadden area and Dutch regional (urban) economies through labor flows. To construct figures for 2009 we use commuting relations between individual Wadden municipalities and all Dutch urban municipalities, drawing on data from Statistics Netherlands.3 These national data provide us for each individual municipality with figures of the number of commuting inhabitants (rounded to nearest hundreds) and their (in some cases estimated) work municipality. For a spatially explicit illustration of commuting relations we apply a set of survey-based primary data, for the year 2012, which connects the employment and residential locations of 412 Wadden residents with Euclidean spider lines. We do not claim that this sample is representative for the Wadden area working population.The spatial distribution of respondents roughly approximates the actual population distribution in the research area, but it does not include samples from some of the smaller (peripheral) population cores. Data from Statistics Netherlands (2009) are used to define the degree of urbanization at both municipal and neighborhood level. At both municipal and neighborhood level we define urban areas by OAD≥1000, and rural areas by OADb 1000. By following this definition, Den Helder and Harlingen appear to be the only urban municipalities out of all 17 Wadden municipalities in 2009. 3.3.2. Issues of spatial relations and scale When we examine the net commuting figures for commutes between individual Wadden municipalities and urban municipalities (including Den Helder) in Fig. 4a, we can observe that most Wadden municipalities are net-suppliers of labor to urban areas within the Netherlands, except those showing inflows and outflows of labor to urban areas which are equal. Fig. 4b meanwhile provides insight into the differentiation between municipalities in the magnitude of these commuting relations. These spatially-aggregated data indicate how Wadden area municipalities are embedded in urban economies. But these data at the municipal scale lack the spatial detail needed for the analysis of commuting patterns, because they neither incorporate flows, which are internal to municipalities, nor do they allow us to identify potential scale differences in commuting patterns for the multiple municipal population cores. Analysis of such patterns requires spatially explicit data. In Fig. 5 destinations of commuting trips of 412 residents of the Wadden area are overlayed on a base map which gives a measure of the degree of urbanization at neighborhood level. When we consider the spatial scale of commuting activity by Wadden area residents, the figure indicates that these commutes are predominantly regional; their spatial extent often being limited to the most proximate larger urban core (external to the Wadden area). In the analysis of the economic tie-in of the Wadden area with external areas, the national scale is apparently too high of a spatial scale. However, we observe outliers, whereby most observations describe commutes from the Wadden area to the central urban core of the Netherlands. The scale in Fig. 5 therefore seems appropriate for the analysis of the economic tie-in of the Wadden area with external areas through labor flows. Overall, urban areas seem to be dominant purveyors of employment to residents from throughout the Wadden area, as 37% of commuters travel to an urban destination. Of these observations of urban destinations, 58% is situated external to the Wadden area. We can also discern several smaller population cores that are dominant in providing employment to their surveyed residents. This may indicate differentiation in the function of population cores in the Wadden area as places to live and work. The potential existence of such differentiation highlights 3 Statistics Netherlands (2011) ‘Banen van werknemers naar woon-en werkgemeente, 2006–2009.’

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Fig. 4. a) Absolute net quantification of commuting flows between Wadden municipalities and Dutch urban municipalities; b) Absolute gross quantification of outward commuting flows from Wadden municipalities towards Dutch urban municipalities.

the fact that observations at municipal level (Fig. 4a and b) may not be transferable to observations at the lower level of population cores (Fig. 5). 3.4. Empirical illustration 2: rural specialization towards tourism 3.4.1. Objectives and data In this section we provide an illustration of rural specialization towards the tourism sector in the Wadden area with regard to a significant observation in Section 3.2.2. Such sectoral specialization of regions in the Wadden area towards tourism can be derived from a location quotient (LQ). A location quotient is calculated by LQ ¼ ðei =eÞ=ðEi =EÞ

ð1Þ

where LQ describes the outcome of the share of the tourism sector i in a region's total economy e divided by the share of the tourism sector i in the total economy E at the national level, which serves as a reference. The relative degree of an area's specialization is given by the location quotient's deviation from 1, as LQ=1 would indicate an equally relative specialization in the tourism sector for both areas. LQs are most often computed over employment figures, although other variables disaggregated at regional level may also be used (Capello, 2007). We use recreation sector employment figures 4 as an input for the calculation of LQs for the Wadden area municipalities in 2010, with employment level at the national scale as reference. The source of these employment data is LISA, a dataset of locations of firms, their employment, and their location at the six-digit postal area level on a national scale. The LISA dataset gives us 1,181,546 observations, of which 26,466 firms are located in the Wadden area. In the LISA dataset the sector in which a firm operates is classified by the Standard Business Categorization (SBI'08). The tourism sector is operationalized using the narrow definition of employment in accommodation services (SBI'08 code 55) following Sijtsma et al. (2012a, 2012b). The tourism sector in the Wadden area provides 2573 local jobs, amounting to 3.6% of total Dutch employment in this sector. LISA is also our source data for an illustration of employment in the tourism sector at firm level in 2010. Although temporal employment data are available, this data is not appropriate in this illustrative section.

of these, i.e. De Marne, Wûnseradiel, Harlingen, Dongeradeel and Anna Paulowna, show a (modest) relative specialization in a tourism-based economy compared to the national average, but taken altogether figures for the mainland coast municipalities indicate an underdeveloped area in relation to the national average. Fig. 6b provides a spatially explicit view of employment in the tourism sector in the Wadden area. We have detected a sharp contrast between tourism employment on the islands and at the mainland coast. The Wadden isles are clearly dominant in the recreation sector, with Texel having overall dominance. At the mainland coast, however, some concentrations of employment can be identified, but in total, these amount to fewer jobs than the concentrations on the islands. Concentrations at the mainland coast are mostly located in urban areas, and in the Lauwerslake area between Dongeradeel and De Marne. We can approximate that the relative differences in the number of jobs in the tourism sector in municipalities do not always correspond with the relative differences in the specialization of the municipalities' tourism sector at the national scale. 3.4.3. Summary We can summarize our theoretical and empirical discussion on rural economic development and its spatial scales most relevant to a Wadden-SEED in that: ▪ the competitiveness of firms and regions is an important factor in spatial rural economic development and can be addressed by ‘regular’ statistics and stakeholder-generated data (entrepreneur or expert knowledge); ▪ the competitiveness of rural areas is determined by increasingly urban economic systems at higher spatial scales, which can lead to economic relations between noncontiguous regions;

3.4.2. Issues of spatial relations and scale The location quotients presented in Fig. 6a show spatial differentiation in the degree to which Wadden area municipalities have specialized in a tourism-based economy. A sharp contrast is noteworthy between the five isles and the mainland coast. The economies of the five isle-municipalities all show comparatively (relatively) high shares of employment in the tourism sector. For tourism, Schiermonnikoog, Ameland and Vlieland are the most specialized economies in the Wadden area, as their share of employment in tourism is approximately 20 to 30 times higher than the national share of 0.88%. Conversely, economic specialization in the tourism sector is very low for municipalities on the mainland coast. Five 4 We subscribe to the LISA definition of the accommodation sector, which is SBI'08 code ‘55’.

Fig. 5. Euclidean lines connecting stated commuting destinations of inhabitants of the Wadden area to their residential locations.

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Fig. 6. a) Location quotients for employment in the tourism sector at municipal level in 2010; b) Employment in the tourism sector at firm level in 2010.

▪ spatially explicit data can provide useful insights into patterns of competitiveness among areas in a specific economic sector; ▪ spatially-aggregated data can be useful for a Wadden-SEED if it is accompanied by spatially explicit data; ▪ the competitiveness of an aggregated spatial area (e.g. a municipality) in a specific sector requires insight into the sector's share within the area's total economy to allow measures of competitiveness to be compared between areas; ▪ the scale at which economic relations are assessed should be the outcome of analysis.

3.5. Interaction of rural economic development with ecology 3.5.1. Economic–ecologic interaction and the issue of spatial scale There is abundant literature describing models of economic–ecologic interaction, in which the interaction is characterized by the ecological provision of services that sustain and enhance economic systems and their externalities. Economic development is often assumed to inflict ecologic degradation, mainly through the systems of production (Gómez-Sal et al., 2003). The models that address economic–ecologic interaction can be divided into descriptions of direct interactions and descriptions of indirect interactions. Direct interaction in space between economic activity and ecology occurs when an economic activity competes in space with ecological systems through land use, extracts resources, or returns waste (Daly and Farley, 2010). Such interactions occur at a local scale and are often studied at merely one scale level at a time, but can be driven by economic supply and demand systems stretching across a larger spatial realm (Kissinger and Rees, 2010; Polasky and Segerson, 2009).5 Swaffield and Primdahl (2006) state that a spatial understanding of landscape dynamics in local places at the micro- and meso- scale levels of analysis may benefit from the incorporation of socio-economic flows at higher spatial scales. These flows are related to ecology in an indirect way. Indirect interactions can be described through several approaches to economic–ecologic modeling, such as the ecological footprint and the metabolism and material flow analysis approach (Erb, 2012; Haberl et al., 2009; Wiedmann and Barrett, 2010). These approaches focus mostly on economic consumption in one area and its impacts on ecosystems inflicted by the production system by which the goods consumed are provided. The spatial locations of impacted ecosystems may be external to the region of consumption. It is clear that a debate on the appropriate spatial scale of analysis is inherent to the analysis of economic development and its relations with ecology (Gibson et al., 2000; Jordan and Fortin, 2002; Wätzold et al., 2006) Gibson et al. (2000) argue that scale should be the outcome of the analysis rather than its mere starting point. 3.5.2. Ecosystem Services framework A framework which allows for the integration of both direct and indirect interactions between rural economic development and ecology, at multiple spatial scales, is known as the Ecosystem Services (ESS) 5 Although these direct interactions are local, through feedback systems dynamics in local ecosystem service provision may have an impact on ecosystems at larger spatial scales (Holling, 2004).

framework (Collins et al., 2011; Polasky and Segerson, 2009; Turner et al., 2010). Ecosystem services may be understood as “the benefits that people obtain from ecosystems,” following the Millennium Ecosystem Assessment (2003) definition. Ecosystem services theory states that ecosystems may offer “provisioning services such as food and water; regulating services such as flood and disease control; cultural services such as spiritual, recreational and cultural benefits; and supporting services, such as nutrient cycling, that maintain the conditions for life on Earth” (Millennium Ecosystem Assessment, 2003). Aspects of ecosystems can be used actively or passively, and by so doing add to human welfare (Turner et al., 2010). We can discriminate between direct and indirect (non-)consumptive benefits derived from ecosystems: in the case of the Wadden area, consumptive use may consist of the extraction of resources such as shrimps and gas; direct non-consumptive benefits may consist of the enjoyment of scenery. Meanwhile, dikes and salt marshes provide indirect non-consumptive benefits to people as flood barriers by preventing the lands they use from flooding. An area's “potential to deliver services is assumed to be influenced by (a) land use, (b) net primary production, and (c) bioclimatic and landscape properties such as mountainous terrain, adjacency to coastal and wetland ecosystems, as well as adjacency to landscape and nature protection zones” (Haines-Young et al., 2012). Spatial heterogeneity for example, in actors' appreciation for ecologic areas — which can be assessed using participatory mapping tools (Alessa et al., 2008) — as providers of specific ecosystem services means however, that ecosystem service potential does not necessarily correlate in space with the physical characteristics of areas (Raymond et al., 2009). (An empirical study for the Wadden area is provided in illustration 3.) Ecosystems may simultaneously (potentially) deliver interrelated multiple services, despite the possibility that trade-offs may also occur (Polasky and Segerson, 2009). Now that we have distinguished between direct and indirect economic–ecologic relations, and identified the use of the ESS framework for the analysis of these relations — which may be heterogeneous in space, we will next discuss an empirical illustration in relation to the SEED. 3.6. Empirical illustration 3: Cultural ecosystem services potential of the Wadden area 3.6.1. Objectives and data This section provides an illustration of the spatial heterogeneity of the cultural ecosystem service (ESS) market potential of ecosystems in the Wadden area. We use data on nature target types from the Netherlands Environmental Assessment Agency to describe the natural land use types and their locations in the Wadden area. A nature target type is an ecosystem characterized by a certain level of biodiversity and natural integrity, as stipulated by Dutch nature policy. Types are set out in three main categories: sensitive, multifunctional and large-scale nature and their sub-categories comprise 102 nature target types (Bal et al., 2001). Not all physical space in the Wadden area is covered by nature target types, therefore we have added agricultural land, sea, and the category “other land use types” (built residential environment, industrial areas, sports facilities, etc.) to our nature target-types map. The source for these additional land use data, except for the intertidal flats data, is

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the 2008 land use statistics dataset of Statistics Netherlands. The source for the intertidal flats data is the Common Wadden Sea Secretariat. Stakeholder-generated Hotspotmonitor data from the University of Groningen are used for the description of spatial heterogeneity in cultural ESS market potential. Hotspotmonitor data provide spatially explicit observations of public appreciation for nature types. The Hotspotmonitor is an online Google Maps-based survey tool which allows individuals to pinpoint the natural areas within Dutch national borders they perceive as most attractive at different scales (local, regional and national).6 The appreciation measure may cover both use and non-use values. We use only the observations that mark places found to be attractive on a national scale. The attractiveness of natural land use types can therefore be compared between regions, as the complete Dutch land and water surface belongs to respondents' spatial choice set for marking attractive places. These attractive places are then imported into a GIS. The Hotspotmonitor dataset offers multiple subsets; we use the subset based on a nationwide survey conducted among 1,781 members of Natuurmonumenten in 2011. This subset contains the 320 observations of national attractive places located in the Wadden area. The spatial distribution of respondents approximates the spatial distribution of the total Dutch population and for each individual observation of an attractive natural area, the residential location of the respondent is known at the six-digit postal code area level. 3.6.2. Issues of spatial relations and scale The locations of natural land use types (Fig. 7a) and which of these parts of the Wadden area are highly appreciated by a Dutch public (7b) are shown below. The spatial locations of these appreciated natural land use types indicate where in space interactions between tourism-based economic activities and ecosystems may occur. The appreciated nature may serve as a valuable asset to the tourism economy, as they are competitive at the national scale. We observe a sharp distinction between the Wadden islands and the mainland coast, which resembles the distinction that can be observed in Fig. 6b of employment in the tourism sector. Interestingly, the sea is also highly appreciated by many Dutch people, as indicated by the dots in the Wadden Sea. Regional disparities exist in the degree of appreciation of environmental capital, but the spatial degree of appreciation for single natural land use types is also distributed heterogeneously in space (Sijtsma et al., in press). These patterns of appreciation indicate a spatially-heterogeneous market potential of ecosystems in the Wadden area to deliver cultural ESS. In the case of a change in the productiveness of an ecosystem (which could be a result of a project's direct impact) at providing a cultural ESS, the impact population would consist of the consumers of this service. Such a relation can be categorized as an indirect economic– ecologic relation. The spider lines presented in Fig. 8 allow us to examine the spatial scale at which cultural ESS are ‘exported’ by ecosystems within the Wadden area. Fig. 8 reveals that the appreciation for the Wadden area's nature is not merely local, but rather is shared throughout the whole of the Netherlands. This underscores how changes in the Wadden area production of cultural ESS may be felt by an impact population that lives throughout the Netherlands, in areas both contiguous and non-contiguous to the Wadden area. A substantial share, 59%, of national appreciation may be attributed to the urban 7 population of the Netherlands, for whom the Wadden area's ecosystems provide distinctive services that urban residents may be unable to consume in their home regions (Sijtsma et al., 2012b). The Wadden area seems to be a competitive producer of cultural ESS at the national scale. To illustrate this, in 2010 the Wadden area was the destination of 5.7% of 17.7 million holiday trips taken within 6 For a detailed description of this landscape valuation mapping tool, the reader is invited to www.hotspotmonitor.eu. 7 The definition of urban area presented in empirical illustration 1 is followed here at the neighborhood level. The data used for this calculation are presented in Figs. 2 and 8.

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the Netherlands by inhabitants of the Netherlands (source: Statistics Netherlands). 8 We also take into consideration that the specialized tourism service offered by the Wadden area satisfies international demand. Foreign tourists have traditionally mainly been German (around 90%), although the number of nights spent by German visitors has decreased remarkably in recent years: from around 1.7 million nights in 1998/1999 down to 1.0 million in 2009.9 3.6.3. Summary We can summarize our theoretical and empirical discussion on the interaction between rural economic development and ecology most relevant to a Wadden SEED in that: ▪ direct (e.g. competition between functions in space) and indirect (e.g. ecologic impacts of economic consumption) interactions between rural economic development and ecology can be identified; ▪ spatial analysis of economic–ecologic interactions achieves gains from a multi-scale perspective; ▪ the spatial scale of an examination of economic–ecologic relations should be the outcome of analysis; ▪ the ESS framework supports the multi-scale analysis of both direct and indirect relations of rural economic development with ecology; ▪ heterogeneity in a single ecosystem and the level of production of ESS can exist and this can be revealed through stakeholder-generated data of ESS consumption; ▪ the location of the impact population affected by changes in the productivity of the Wadden area in providing ESS can be spatially diffuse. 3.7. Project evaluation: judging pros and cons of economic development 3.7.1. Brief overview of the method Project evaluation tools such as Multi-Criteria Analysis (MCA) and Cost-Benefit Analysis (CBA) are used widely to integrate economic and ecologic values and aid decision makers in making informed choices between project alternatives (Sijtsma, 2006). Project evaluation tools differ in the number of criteria appearing in their end results, to the extent that they apply monetary measurement in relation to whether they accept alternatives as given, or they aim to discover new ones (Ananda and Herath, 2009; Belton and Stewart, 2002; Boardman et al., 2011; Keeney and Raiffa, 1976; Zeleny, 2011). In the literature it is deemed essential that any type of evaluation present ‘understandable metrics’ for all stakeholders (Mooney, 2010). SEED therefore plays an important role in improving the basic understanding of stakeholders and experts regarding the key variables to which economic evaluations and environmental impact assessments relate: employment growth and distribution, number of birds and seals, etc. Due to the breadth and scope of different evaluations in the Wadden area, an integrated evaluation approach that balances scope and detail in analyses is required (Gascoigne et al., 2011). Obviously, SEED has to balance scope and detail too. We have already addressed the economic and economy–ecology interaction in order to identify the scope, but what does evaluation theory tell us about the spatial detail of SEED? 3.7.2. Choice for the spatial detail of analyses Since economic–ecological interactions have an inherently spatial character, it can be argued that insight into these interactions should be provided at the most detailed spatial resolution possible (Bockstael, 1996; Troy and Wilson, 2006). In evaluation two scale levels are central. “The first scale level stays close to the political or decision-making reality 8 Statistics Netherlands, online database Statline concerning ‘Vakanties; kerncijfers’. Accessed December 2011. 9 Statistics Netherlands, online database Statline concerning ‘Gasten in alle logiesaccommodaties; naar herkomst en toeristengebied’. Accessed April 2011.

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Fig. 7. a) Land use types; b) Distribution of national Hotspotmonitor markers across the Dutch Wadden area.

and thus is proximal to administrative borders.10 The second scale level uses the global or the biggest spatial level on which impacts can be observed”11 (Sijtsma et al., 2011, in press, p. 6). In order to relate outcomes of project evaluations to the SEED data, i.e. to interpret them, the SEED must be multi-scale as well. Geographical Information System (GIS)-based evaluation tools may help us deal with this issue, as they underpin the spatially explicit analysis (Bateman et al., 2003). These tools have received increasing attention in recent literature (Arciniegas et al., 2011; Chang et al., 2008; Gorsevski et al., 2012; Malczewski, 2006; Recatalá Boix and Zinck, 2008). Although a very precise spatial analysis can support evaluation at the project level, the strategic scale of space in which projects are embedded, and the destinations of their impacts, seem to be absent in this branch of modeling. With regard to the involvement of stakeholders, GIS-based spatial evaluation tools nevertheless offer a significant value-added to ‘traditional’ evaluation tools because they allow for an interactive component in project-evaluation. Arciniegas et al. (2011) present an interactive GIS-based land-use tool (operated on a map table) that supports negotiation processes between stakeholders in land use planning by showing land use data that can be edited immediately. The assessment possibilities offered by interactive GIS-based tools, including the dynamic exploration of maps, may enhance the planning process; specific stakeholder questions may be answered on an ad-hoc basis, and the visualization of impacts may increase the understanding of a plan (Salter et al., 2009). But these statements presume that data is visualized properly and is therefore not misleading, and that stakeholders in the planning process are not confronted with an unwieldy amount of data (Andrienko et al., 2007).

Our SEED data-model consists of multiple economic and environmental GIS-data layers that give insight into the variables key to a basic understanding of the economy and ecology of the Wadden area. The power of GIS (tools) should be used to enhance the interpretation of data layers at different spatial levels. These layers are thematically grouped by the Wadden area's main economic sectors and key economic and ecologic drivers and assets (e.g. agricultural, industrial and tourism sectors, mussel beds, bird foraging areas). However, the inclusion of large amounts of relevant data may constrain the data-model in achieving its goal: understandable insights into the economy and ecology of the Wadden area. Data provision in the spatial database is question-driven: it answers so-called central questions about the competitiveness of the Wadden area on a specific subject. An example of a central question could be “where do people want to live?” This question can then be answered by a minimized set of core-indicators that provide the ‘best answer’ to the central question, and allow the spatial database to remain understandable. Some questions will be difficult to address in a SEED because they require additional monitoring, or cannot be addressed by the assessment of data in a GIS viewer. The core indicators consist of spatially explicit data to address spatial heterogeneity of economic or ecologic values, and should often contain data aggregated at a specific ‘higher’ spatial level to allow for regional interpretation. The preferred use of

3.7.3. Summary We can summarize the literature on project evaluation which is most relevant to a Wadden-SEED in that: • a multi-scale spatial approach is essential for the assessment of a project's impacts, where the maximum spatial extent is set by the widest spatial extent of impacts; • indicators used in evaluation should be understandable to all stakeholders, • pairing down the number of indicators used in a tool increases its comprehension; • the use of interactive (GIS-)mapping tools may enhance policy assessment. 4. A conceptual sketch and illustration of an integrating GIS-based SEED 4.1. SEED description In this section we present a conceptual sketch of a Wadden SEED, which allows for the integrated economic–ecologic strategic evaluation of projects (see Fig. 9). 10 11

This has a theoretical logic close to MCA, with its focus on the decision maker. This logic is closely connected to CBA's a-spatial market stance.

Fig. 8. Euclidean lines connecting national attractive natural places to the residential locations of respondents.

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public and the private sector. The feedback given during these validation sessions, if scientifically reasonable and practically feasible, is used to improve the spatial database's specification and its data contents. Once again, these are modest aims; this process cannot prevent or solve every conflict, nor can it provide complete understanding to everyone: but it can give a basic and shared understanding to many people. 4.3. Accessibility

Fig. 9. Conceptual model of the SEED.

non-aggregated core indicators allows for quick insights into the current state and trends that shape the assessed area and its wider spatial surroundings. In instances when the competitive positioning of areas or firms cannot be derived from statistics, a stakeholder-generated data — e.g. data obtained through spatially explicit surveys in which entrepreneurs are asked where their competitors are located — based core indicator should be used. To allow for more in-depth thematic assessments, core indicators can also be complemented by other indicators that are relevant but not central to answering the central question. Data used to answer central questions should be of the highest spatial precision (both useful and available). Data of a high spatial precision provide flexibility in the spatial aggregation towards a higher regional level. A flexible extent of the data layers allows for multi-scale insights into the competitiveness of a region's sub-areas, or their competitive positions relative to external areas. The spatial extent of these layers is best defined by the extent of a project's impacts, or the scale of economic or ecologic relations relevant to the evaluation. The maximum scale level for the SEED is global, and each layer should fit the scale requirements of each evaluation. However, in the illustrations provided in this paper, the Dutch national scale is used as a maximum scale level for practical reasons. For example, the SEED may require data at the European or even global level — scales at which data may not be available or consistent for all subareas. These data issues of inconsistency and limited availability of geographical data are addressed by the European Commission's Inspire Directive, enforced in 2007.12 The SEED is a spatial database that supports experts and policymakers in understanding the Wadden area's economy and ecology. A data base by itself may not be adequate at yielding understandable spatial insights into variables relevant to comprehension of a specific subject. For this reason we think that the SEED should be presented in a user-friendly interface that combines a GIS-viewer with a so-called ‘dashboard’ of graphs of SEED variables from which to select specific samples to highlight for the viewer (see Fig. 10). Quick and easy insight into the competitiveness of specific areas, or the co-location of, or interaction between, economic and ecologic values, can be provided by presenting the SEED in this way. 4.2. Stakeholder validation Given the complexity of modeling rural economic development in relation to ecology and environmental capital at both strategic and project level, we argue that stakeholder validation of the spatial database and the choice of data is valuable. Do the data and relations visualized in the SEED fit their purposes? Are the SEED's specification and the database's layers easy to understand by stakeholders involved in the planning process? Is there consensus among experts that the appropriate data are used to answer a policy question? Such concerns are answered in validation sessions with experts and other stakeholders from the 12

Source: INSPIRE Directive 2007/2/EC of the European Parliament and the Council. Official Journal of the European Union, 2007.

Spatial economic–ecologic conflict in the Wadden area, the policy debates that attempt to tackle this conflict, and the spatial planning that aims to minimize conflict, involves many stakeholders. A Wadden SEED should serve as a common knowledge base for individuals involved in these issues. The notion of inclusivity leads us to address two main concerns. First, the wide scope of a Wadden SEED (integrating relevant economic and ecologic values for the Wadden area) demands a semi-open character. Other researchers should be invited to judge its contents (e.g. “are the right data used to address a central question?”) and add other central questions and data relevant to a basic understanding of the economy and ecology of the Wadden area. Second, we suggest that the key variables of a Wadden SEED should be publicly available. The most straightforward option to accommodate these two concerns seems to be the availability of an online SEED. A web-based structure offers the opportunity to present data on dashboards in interactive graph format that e.g. permit a simple analysis of the spatial distribution of the values of mapped variables. A Wadden SEED may facilitate public understanding of the Wadden area's economy and ecology and its interrelations, and thus support integrated spatial planning at both project and strategic level. 5. Discussion 5.1. Integration of the ecology and economy: concepts versus data In recent years the literature has witnessed impressive growth in attempts to integrate ecology and economy. Several important contributions are of a conceptual nature (Chapin et al., 2006; Collins et al., 2011; Holling, 2001, 2004) and present what might be called ‘grand conceptual schemes.’ Although filling SEED with data is, as we have shown, backed up by theoretical concepts from both economics and ecology–economy interaction literature, the SEED itself is quite low-profile on the notion of a ‘grand conceptual scheme’ integration. The integration is firstly ‘merely’ spatial. Spatially explicit data for the same areas are brought together into one database, and allowance is made for further interpretation of these data by also providing contextual data for wider spatial areas. No large conceptual issues are resolved by a SEED with regard to all possible relations between ecology and economy, although many data of course touch upon these issues, and several data will yield new insights into these relations. The lack of conceptual integration can certainly be seen as a weakness of the SEED approach; it is ‘merely’ data. However, SEED does add another less modest point to the goal of integration, as it gathers stakeholder-validated data on key issues, which is both economic and ecological: e.g. on fish stocks, on employment, on population dynamics, and on tourism flows. As such, it seems to literally provide a database: a consensus-based fund of data on which to participate in debate, conduct evaluations and carry out refined modeling. Furthermore, all grand conceptual schemes eventually need data to give them operational backing; perhaps the Wadden area SEED will one day be able nourish and sharpen the development of integrative conceptual schemes. 5.2. GIS and evaluation Fueled by the GIS revolution, the literature also shows several spatial assessments and assessment tools, where both ecological and economic aspects are somehow weighed (Arciniegas et al., 2011; Gorsevski et al.,

162 M.N. Daams, F.J. Sijtsma / Journal of Sea Research 82 (2013) 153–164 Fig. 10. Illustrative example of a dashboard in which graphs allow for interactive assessment of economic or ecological values shown in the map. In this case the neighborhoods at the Wadden isles are selected in a map which shows mean assessed property values at the neighborhood level in 2010 (source: Statistics Netherlands). The position of key indicators' values for the selected neighborhoods within the distribution of values for all neighborhoods shown at the selected spatial scale can be observed in graphs.

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2012; Hilferink and Rietveld, 1999; Santé-Riveira et al., 2008; Van Berkel and Verburg, 2011). Moreover, numerous studies on the evaluation of (future) land use change scenarios examine biodiversity, recreation, other ecosystem services, and economic aspects (Gascoigne et al., 2011; Polasky et al., 2008; Troy and Wilson, 2006). Outcomes may be presented as exclusively monetary (Gascoigne et al., 2011; Jenkins et al., 2010; Sukhdev, 2010), non-monetary (Hermans et al., 2007; MEA, 2005; Mendoza and Martins, 2006; Oikonomou et al., 2011; Wolfslehner and Seidl, 2010), or by a mix of both (Nelson et al., 2009; Polasky et al., 2008). How does a SEED for the Wadden area compare? The SEED is quite modest in its aims when compared to these tools. However, similar to GIS evaluation tools, SEED requires spatial data and it is rather comprehensive because it can handle a substantial set of indicators and data. But this is a somewhat ‘operational’ issue and not one to elaborate on here. More important is the issue of weights and judgment. Any GIS system focused on spatial decisions and support for decision making requires the development of weights to specify the relative importance of different aspects. This is crucial to any evaluation, but for many complex societal decisions reaching consensus on weights is far from easy (Sijtsma, 2006). The SEED for the Wadden area does no such thing. In our view, any evaluative judgment-oriented module should be separated from the consensus ‘data base.’ Obviously an evaluative, judgment-oriented GIS module should relate to the SEED: in specifying its criteria or interpreting its outcomes. But since the amount of consensus of such an evaluative GIS module can never be as large as the consensus on the elements of a SEED, and because the substantial Wadden area related literature on conflict suggests that one should be very keen on identifying areas of consensus and shared observations (Hanssen et al. 2009; Pouwels et al. 2011), we strongly advocate that an evaluative GIS module needs to be separated from a SEED. 5.3. Integrative management and Wadden Sea controversies The Wadden area has in the past experienced severe conflict and controversy around for instance, cockle fisheries and gas extraction (Floor et al., 2013; Turnhout et al. 2008). In the present day new controversies continue to arise, for instance, concerning energy plants in the Eemshaven, and salt extraction and a waste burning plant in Harlingen. The role of scientific knowledge in such conflicts has been widely discussed (Floor et al., 2013; Swart and Van Andel, 2008; Swart and Van der Windt, 2005). Many conflicts over the years have led to deeper scientific understanding (e.g. Ens et al., 2004), but this knowledge has not automatically been used correctly. As Runhaar and van Nieuwaal have asserted, the use of science to inform and underpin policy debate is far from self-evident, “as stakeholders often use science in a selective and strategic way” (Runhaar and van Nieuwaal, 2010, p. 239). Swart and Van Andel (2008) argue that not only is there a need for sound science, but also for a sound way to interact and communicate within the social realm. On the level of key data this is precisely what the Wadden SEED aims to do. Pouwels et al. (2011) discuss new tools to enhance a better balance between recreation and biodiversity and one of the main characteristics they advocate for these new map-based ecological–economic tools is that they interactively encourage stakeholders to engage in a learning process. Turnhout et al. (2008) also stress the importance of open learning possibilities when they discuss the Wadden conflicts. The encourage us “to move beyond endless competition between knowledge claims in policy–science interaction.” The Wadden area SEED can support such an open learning process. It aims to increase consensus towards a basic understanding of the Wadden area: a complex rural area situated between the world of the city and the world of the sea. Acknowledgements We are grateful to the anonymous reviewers for their constructive comments. We also thank Susan Davis for the correction of our English.

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