GRETA - GReen infrastructure: Enhancing biodiversity and ecosystem services for territorial development. Applied Research.

Transcription

1 GRETA - GReen infrastructure: Enhancing biodiversity and ecosystem services for territorial development Applied Research Inception Report Version 05/02/2018

2 This applied research activity is conducted within the framework of the ESPON 2020 Cooperation Programme, partly financed by the European Regional Development Fund. The ESPON EGTC is the Single Beneficiary of the ESPON 2020 Cooperation Programme. The Single Operation within the programme is implemented by the ESPON EGTC and co-financed by the European Regional Development Fund, the EU Member States and the Partner States, Iceland, Liechtenstein, Norway and Switzerland. This delivery does not necessarily reflect the opinion of the members of the ESPON 2020 Monitoring Committee. Authors Stefan Kleeschulte, Hugo Carrao, Mirko Gregor, Manuel Loehnertz, Yohannes Ayanu, Inge Kleeschulte, space4environment (Luxembourg) Jaume Fons, Raquel Ubach, Roger Milego UBA (Spain) Ryan Weber, Kjell Nilsson, Eeva Turunen,Elin Slatmo Nordregio (Sweden) Katherine Irvine, Jessica Maxwell, Laure Kuhfuss, Michela Faccioli, The James Hutton Institute (UK) Gemma-Garcia Blanco, Igone Garcia TECNALIA (Spain) Advisory Group Project Support Team: Blanka Bartol (Slovenia), Kristine Kedo (Latvia) and Josef Morkus (Czech Republic) ESPON EGTC: Michaela Gensheimer (Senior Project Expert), Laurent Frideres (Head of Unit Evidence and Outreach), Akos Szabo (Financial Expert). Information on ESPON and its projects can be found on The web site provides the possibility to download and examine the most recent documents produced by finalised and ongoing ESPON projects. This delivery exists only in an electronic version. ESPON, 2017 Printing, reproduction or quotation is authorised provided the source is acknowledged and a copy is forwarded to the ESPON EGTC in Luxembourg. Contact: info@espon.eu

3 a GRETA - GReen infrastructure: Enhancing biodiversity and ecosystem services for territorial development Disclaimer: This document is an inception report. The information contained herein is subject to change and does not commit the ESPON EGTC and the countries participating in the ESPON 2020 Cooperation Programme. The final version of the report will be published as soon as approved.

4 Table of contents 1 GRETA conceptual and methodological framework Working definition of Green Infrastructure for the GRETA project Inventory and analysis of definitions of GI Key principles of GI Working definition of GI First overview of geographical distribution of GI and ecosystem services in European cities and regions Data and data sources Data Management Main difficulties and backup solutions First overview map Methodological approach for mapping GI Analysis of the geographical distribution patterns of GI and ecosystem services Outlook Potential positive and negative effects of GI and ecosystem services on European territorial development Setting the scene key concepts Assesing interaction between ecosystem services Factors that can help in unlocking the GI and ecosystem services potential for further territorial development, First overview of existing policies, planning instruments and initiatives related to GI Snap-shot of GRETA Case applications Elaborated plan for development of guidelines for policy makers References List of Annexes... 1 ESPON 2020 i

5 List of Maps Map 3.1: Percentage cover of GI links per NUTS3 regions Map 3.2: Average of standardised ES composite index per NUTS Map 3.3: Percentage cover of urban green areas inside the FUA Map 3.4: Percentage cover of Natura 2000 area inside the FUA Map 7.1: Proposal GRETA case studies List of Tables Table 1 Glossary of elements used in GI working definition Table 3.1: Descriptive statistics of the four urban indicators Table 8.1: Draft example questions for soliciting input from Advisory Group on the main guidelines report ESPON 2020 ii

6 Abbreviations EC ES ESPON EU GI NUTS TEN European Commission Ecosystem Services European Territorial Observatory Network European Union Green Infrastructure Nomenclature of Territorial Units for Statistics Trans-European Network ESPON 2020 iii

7 Executive summary This Inception Report describes the conceptual and methodological frameworks (Chapter 1) that are used in GRETA and proposes a common working definition of GI (Chapter 2). A first overview of the geographical distribution of GI and ecosystem services in European cities and regions, with an assessment of data and data sources to be used in the project delivery, is also described (Chapter 3). The report highlights preliminary indications of potential positive and negative effects of GI and ecosystem services on European territorial development (Chapter 4), as well as first reflections on the enabling factors, including information on activities for introducing a TEN-G (Chapter 5). A first overview of existing policies and planning instruments supporting the implementation of GI is also included in this report (Chapter 6). The proposal for the twelve case studies is described in Chapter 7. The elaborated plan 1 for carrying out the case studies has been included as Annex 4. Chapter 8 is devoted to the plan for the development of guidelines and policy recommendations. The content of this report is expanded upon in the Annexes. 1 GRETA conceptual and methodological framework The GReen infrastructure: Enhancing biodiversity and ecosystem services for territorial development (hereafter referred to as GRETA) project aims to develop a comprehensive knowledge base for enhancing green infrastructure (hereafter referred to as GI) to benefit territorial development in different types of European regions and cities. More specifically, GRETA will: (i) explore the ecological, social, cultural and economic benefits of and demands for GI; (ii) analyse how these benefits are linked to territorial challenges, e.g. biodiversity protection and climate change adaptation; and (iii) examine how GI can be promoted through more integrated policies, landscape designs and other innovative multifunctional solutions. GI and ecosystem services (ES) have become hot topics in European policies over the past 10 to 15 years, starting with the definition of ES in the Millennium Ecosystem Assessment (MA, 2005). The decisive boost in importance was sparked by the EU Biodiversity Strategy to 2020 (EC, 2011) in which the vision to 2050 foresees that by 2050, European Union biodiversity and the ecosystem services it provides its natural capital are protected, valued and appropriately restored [ ]. In addition, Target 2 postulates that by 2020, ecosystems and their services are maintained and enhanced by establishing green infrastructure and restoring at least 15% of degraded ecosystems. Two years later, the EU s Green Infrastructure Strategy (EC, 2013) was very precise and defined GI as a strategically planned network of natural and semi-natural areas with other environmental features designed and managed to deliver a wide range of ecosystem services. This definition embraces three important aspects: the idea of a network of areas (i.e. connectivity), 1 Fully updated on ESPON

8 the component of planning and management, and the concept of multiple ES (i.e. multifunctionality) (Mubareka et al., 2013). To properly support the planning and management process, information on existing GI and the connection between GI elements is indispensable. Within GRETA, the identification of GI and ES patterns and typologies will be undertaken in a reproducible way based on a scientifically sound methodology. The integration of diverse information will help to connect different scales and different types of data. The spatial scales that are relevant to the GRETA project are the (i) EU level (including the four EFTA countries that also belong to the ESPON space), (ii) member states/country level, (iii) regional level (i.e. NUTS 2/3), and (iv) local level (e.g. cities). Effective approaches for mapping GI are increasingly necessary to support planning processes at multiple scales. Although the spatial delineation of GI elements has often been based on a simple re-classification of available land use data combined with information on natural values of each use class (e.g. Weber et al., 2006; Wickham et al., 2010), recent studies have shown the relevance of including sector-specific models and connectivity in the analysis of policy impacts over different GI networks (Mubareka et al., 2013). Other approaches have thus been proposed to map ES and GI, which include the compilation of local/regional primary data or statistics on specific sectors (e.g. Kandziora et al., 2013), or the application of dynamic ecosystem models to project service provision in a spatially explicit manner for different sectors (e.g. Maes et al., 2015). In any approach it is important to identify and map the precise proxy for the biophysical process satisfying each requested ES, (i.e. it should represent the natural capacity of ecosystems to deliver the correspondent service (service supply)). GRETA will take a multi-scale approach and will explore twelve cases studies representing different spatial, institutional and jurisdictional settings that affect GI, from urban cores to rural countryside, with specific attention to urban complexity and benefits for human urban populations. GRETA will apply the place-based policy perspective to GI strengthen the usually missing dimensions of governance and planning/policy decision processes. GRETA will apply comprehensive research methods (i.e. mapping and quantitative spatial analysis (Tasks 1 and 2), questionnaire survey (Task 3), targeted interviews and desk based research (Task 4 and 5), and economic valuation methods for assessing GI demand (Task 2 and 4). GRETA will adopt a participatory research methodology through the involvement of end-users in an Advisory Group. The experience of the GRETA partnership and their access to different networks of expertise ensures that: i) the most relevant and up to date data and references will be used; and ii) the work will be efficiently executed by taking advantage of and building upon this existing knowledge base. ESPON

9 2 Working definition of Green Infrastructure for the GRETA project 2.1 Inventory and analysis of definitions of GI In Annex 1 Section 1 we present an inventory of GI definitions proposed and applied in different theory and policy spheres throughout the past years. This inventory was developed to collect information on the evolution of the GI concept, its key principles, main targets and envisioned scales of analysis, in order to select a comprehensive, yet flexible GI working definition within the GRETA project that is applicable and compliant to EU terminology and can be used from the local to the regional scales. This meta-analysis included a review of scientific literature, EU policy regulations, and also included a review of recently completed or on-going research programmes, such as OpenNESS 2, URBES 3, OPERAs 4 and ESMERALDA 5. The table presented in Annex 1 Section 1 lists the original GI definitions and their main characteristics. This includes referencing the first publication source and does not include the reuse of the definitions in successive research and operational settings. The results of this inventory, i.e. GI definitions and main key principles, will be discussed in the next two subsections; however, it is important to highlight some high level outcomes, which might not be directly apparent when reviewing Annex 1 Section 1. One interesting result is that none of the most recent research programmes have provided a novel GI working definition, but have instead reused definitions already published in the literature. For example, considering the overall goals of the OpenNESS project and its variety of case studies, it was decided to use the working definition provided by the European Commission (EC) communication Green Infrastructure Enhancing Europe's Natural Capital, commonly known as EU s Green Infrastructure Strategy (EC, 2013). Similarly, in its factsheet number 6, the URBES project also defines GI using the concept presented by the EU s GI Strategy. On the other hand, the FP7 project GREEN SURGE 6 makes reference to the definition from Benedict and McMahon (2002) that GI is understood as a strategic approach to develop an interconnected network of green space that conserves natural ecosystem values and functions, and that provides associated benefits to human populations. 2.2 Key principles of GI The last 20-year evolution of the GI concept in the literature, and its acknowledgement in many EC Communications, have defined it as a spatial concept (Naumann et al., 2011), embracing two key underlying principles connectivity and multifunctionality (Mell, 2017). These ideas are interrelated in a hierarchical manner. Connectivity refers to the enhancement ESPON

10 of species ability to move between areas, and can be of a structural nature (i.e. habitat continuity) or functional nature (i.e. how landscapes allow various species to move and expand to new areas without necessarily being physically connected) (Baro et al. 2015). Generally, two main components are identified to promote connectivity: hubs and links. Hubs are areas of natural vegetation, or areas of known ecological value that act as anchor for a variety of ecosystem services, providing source and sink habitats for species dispersing through the landscape (Benedict and McMahon 2002; Wickham et al. 2010). Links are the corridors that connect the ecosystems together, facilitating the movement of species and the flow of ecological processes (Lafortezza et al. 2013). Links can embrace natural and seminatural areas, forests of all types, pasture lands, agriculture lands, wetlands, rivers and all space that is either low-intensity or free from human use, with or without vegetation cover, provided those areas are biodiversity rich and managed in a way that provides multiple ES. Multifunctionality, on the other hand, represents the ability of GI to simultaneously provide multiple ES and other benefits in the same spatial area (Mell, 2017). This could constitute, for example, a park with many trees within a densely populated urban area that offers aesthetic appeal, cools the microclimate, provides a recreational opportunity and serves to functionally connect habitats for certain species. 2.3 Working definition of GI There is no single, widely accepted and recognized definition of GI in the literature, but there is consensus in research, policy and practice that GI presents an opportunity for delivering environmental, social and economic benefits (Wright 2011). Along with the more recent promotion of ES, GI is considered one of the most engaging forms of landscape investment and management for planners (Mell 2017). Still, different studies, technical reports and ground applications present a variety of GI definitions (for a comprehensive review in this report please see Annex 1 Section 1). These definitions are broadly consistent and overlapping in a number of key underlying elements and principles (as depicted in subsection 2.2 and Annex 1 section 1), but may differ in their emphasis on the various components, features and characteristics of GI, as well as the functions and services that it provides. While the term GI has been in place since at least the early 1990s (EC, 2010), its use has gradually increased over the last decade, and it has only recently become widely adopted in the EU. The GI concept has evolved and developed from an interesting extension of a number of existing green space planning activities into a defined and flexible approach to spatial planning (Mell, 2017). Since many GI type projects frequently used other terms or labels in the past, previous GI initiatives did not at least initially refer to themselves as such. Due to its versatility, coupled with an integrated approach to policy-practice debates, GI thinking has set itself apart from other forms of planning (Mell, 2013). In the EU context, the GI concept was first introduced in the 2009 EC White Paper on Adapting to Climate Change (EC, 2009), and it was defined as the interconnected network of natural areas [ ] that naturally regulate storm flows, temperatures, flooding risk, and water, ESPON

11 air and ecosystem quality, thereby already highlighting the two key principles of connectivity and multifunctionality. This EC White Paper set out a framework to reduce the EU s vulnerability to the impact of climate change, and the concept of GI highlighted that nature s capacity to absorb or control climate change impacts in urban and rural areas can be a more efficient way than simply focusing on single-purpose and disconnected grey infrastructures. A similar definition was proposed by the US Environmental Protection Agency (EPA, 2008 and 2013); however, the early EC concept focused on the ecological functionality of GI, and stressed its importance in providing single regulating ES, whose role can be compared to man-made infrastructures, such as engineered drainage systems or flood defences. Therefore, while pushing for mitigation and adaptation strategies to climate change that are mainly focused on natural ecosystems, the 2009 GI definition from the EC was also addressing a precondition for ecosystem protection, connectivity and for the first time touching on the supply of services rather than simple functions. By 2011, a report to the Directorate General for Environment of the EC (Naumann et al., 2011) has promoted GI as a valuable network for addressing not only climate change mitigation and adaptation, but also to fulfil the requirements for biodiversity protection and preservation, as well as societal needs in a complementary fashion. By maintaining healthy ecosystems, reconnecting fragmented natural areas and restoring damaged habitats, the GI network can offer a socio-economically viable and sustainable infrastructure that provides goods and services to human populations, and by which multiple objectives can be addressed. Indeed, one of the key novel features of GI at that time was its multifunctionality, i.e. its ability to perform several functions and provide several benefits in the same spatial area. Apart from its original and singular focus on ES, the updated concept of GI was promoting social and economic services, such as, respectively, providing water drainage and supplying jobs. In this modernised view, GI was endorsed as the ecological framework needed to preserve natural ecosystem values and functions that enhance the built environment and provide a means for urban and rural recreation, thus supporting human health and improving quality of life to human populations (as previously sustained in the scientific literature by e.g. Benedict and McMahon (2002 and 2006)). Based on the GI definition provided by the EC Communication (EC, 2009) and endorsed by the subsequent report for European Commission DG ENV (Naumann et al., 2011), a more recent and comprehensive, but flexible definition of GI was proposed by the EC in the EU s GI Strategy (EC, 2013). It was put in place to support key steps towards the success of the EU 2020 Biodiversity Strategy (EC, 2011). The definition proposed by the EU s GI Strategy embraces three important aspects: (i) the idea of a network of geographic areas; (ii) the component of planning and management; and (iii) the concept of multiple ES. In this sense, GI integrates the notions of planned ecological connectivity, as well as conservation and multifunctionality of ecosystems (Mubareka et al., 2013). Apart from its most physical and functional sense, this definition is also based on the principle that conserving and enhancing nature and natural capital, as well as the many benefits human populations can get from ESPON

12 nature, should be consciously and strategically integrated into spatial planning and territorial development. In this context, GI has the role of a management tool that focuses on a strategic approach to land use planning and conservation, which provides ecological, economic and social benefits through natural solutions, as earlier proposed by Benedict and McMahon (2006) and Mell (2008). In addition to the thematic aspects, the EU s GI Strategy (EC, 2013) also clearly highlights that GI is present in both rural and urban settings. At the urban level, GI is considered as a planning approach aimed at creating interconnected networks of green and blue spaces, which together deliver ecosystem benefits to society and the human population (Mattijssen et al., 2017). The selection of relevant urban GI elements is less focussed on conservation and restoration, but takes into account all possible benefits (such as mitigation of heat waves, improving air quality, and providing recreational space). Hence, GI includes any natural elements in towns and cities that provide an ecological or ES function. This includes identifying urban elements such as green parks, green walls and green roofs that host biodiversity and allow ecosystems to function and deliver their services by connecting urban, peri-urban and rural areas (Davies et al., 2006; Mell, 2008). Since structural elements are provided a priori, urban GI networks have the ability to provide many objectives and simultaneously support multiple policy sectors. Considering the extensive review of GI definitions provided in this task (see Annex 1 Section 1) and the historical evolution of the concept in research, policy and practice, the GRETA project will adopt and reinforce the working definition by the EC in the EU s GI Strategy (EC, 2013 see Error! Reference source not found.). In order to clarify the meaning of the proposed GI working definition within GRETA project, a set of key elements and criteria presented in the definition are described in more detail in the glossary presented in Table 1 on the next page. This glossary is an accompanying element of the working definition. GI is defined as a strategically planned network of natural and semi-natural areas with other environmental features designed and managed to deliver a wide range of ecosystem services. It incorporates green spaces (or blue if aquatic ecosystems are concerned) and other physical features in terrestrial (including coastal) and marine areas. On land, GI is present in rural and urban settings. This definition was a product of Target 2 in the Biodiversity Strategy 2020 (EC, 2011), but the concept is also a dedicated policy instrument for promoting the development of GI across the EU towards delivering economic, social and ecological benefits and contributing to sustainable growth. The rationale behind the EC definition is to guide the implementation of GI at the EU, regional, national and local levels and promote its integration in various capacities into sectoral policies, e.g. ecosystem-based adaptation (EbA) into climate change policies, nature based solutions (NBS) into research and innovation policies, natural water ESPON

13 retention measures (NWRM) into water and risk management policies, and multifunctional (and biodiversity supportive) green and blue spaces into nature policies. Apart from the policy perspective, it is a comprehensive yet flexible GI working definition, which integrates the conceptual and operational evolution of the term, and it is compatible with the main working definitions used in recent research programmes being implemented in the EU. Table 1 Glossary of elements used in GI working definition. Element in the definition Description strategically planned GI planning aims to conserve, restore or create networks of green (and blue) areas in order to provide environmental, economic and/or social benefits for urban and rural societies (at several institutional levels). Simultaneous maximisation of all potential benefits from GI is however unlikely, thus trade-offs need to be strategically assessed. Therefore, GI networks are strategically planned in that decisions about conservation, protection, and restoration of ecosystems incorporate information on how potential geographical areas fit within a network to optimise its functioning and maximise its benefits, the links, complementarities and contributions to different sectors. Integrating GI considerations into governance and planning processes allows all the relevant issues to be assessed and a considered comprehensive decision to be taken in order to secure as many benefits as possible. GI planning can make a significant contribution in the sectors of regional development, climate change, disaster risk management, agriculture/forestry and the environment. network GI relates to the identification and mapping of ecological networks. Two primary components of ecological networks are hubs and links (see section 2.2). Hubs are areas of natural vegetation, other open space, or areas of known ecological value, and links are the corridors that connect the hubs to each other. A set of hubs connected by links constitutes a network that can be used to inform conservation-related land-use decisions. natural and semi-natural areas The types of physical features that contribute to GI are diverse, specific to each location or place and very scaledependent. Natural and semi-natural areas include elements ESPON

14 such as: Core areas: e.g. local nature reserves, water protection areas, landscape protection areas, Natura 2000 sites; Natural and semi-natural connectivity features: pastures, woodland, forest (no intensive plantations), ponds, bogs, rivers and floodplains, wetlands, lagoons, beaches, hedgerows, stone walls, small woodlands, ponds, wildlife strips, riparian river vegetation. other environmental features Other environmental features include elements such as: Green urban and peri-urban areas: street trees and avenues, city forests/woodlands, high-quality green public spaces and business parks/premises, green roofs and vertical gardens, allotments and orchards, storm ponds and sustainable urban drainage systems, city reserves incl. Natura ecosystem services The direct and indirect contributions of ecosystems to human wellbeing. Contributions can be of economic, social, cultural and/or ecological value. For example, a forest ecosystem might provide wood for forestry and/or for renewable energy, provide a recreational service, be part of a cultural landscape, regulate the supply of air, water and minerals, support biodiversity in the form of landscape cohesion and maintain ecosystem processes. other physical features Other physical features include elements such as: Artificial connectivity features: Eco-ducts, green bridges; animal tunnels (e.g. for amphibians), fish passes, road verges, ecological powerline corridor management. 3 First overview of geographical distribution of GI and ecosystem services in European cities and regions 3.1 Data and data sources Annex 1.2 provides a list of the datasets that have been identified and collected for mapping GI elements and the related ES within this first overview, at both the regional and local levels. It also elaborates on datasets that can be used to further refine the full map at the interim delivery and overcome some data challenges. ESPON

15 In order to map GI at the landscape level, two groups of datasets are required: (i) data related to the mapping of hubs ; and (ii) data related to the mapping and assessment of links (see subsection 2.2). The core elements of a landscape GI network, i.e. the hubs, are the Natura 2000 sites defined in the framework of the Birds Directive (2009/147/EC) and the Habitat Directive (92/43/EEC), as previously proposed by the European Commission (EC, 2010). On the other hand, the links of the GI network can be approximated by land cover or land use (LU/LC) classes, including natural and semi natural unprotected areas, forests types, pasturelands, agriculture lands, wetlands, rivers and spaces free from human use, with or without vegetation cover, as previously proposed by Maes et al. (2015). At the landscape level, LU/LC classes can be identified by the Map of European Ecosystem types and the CORINE Land Cover (CLC), and refined using standardized datasets such as the Copernicus HRL Imperviousness, HNV farmland, and Open Street Maps (OSM). Still, the relevance and value of those LU/LC classes for a EU level GI network has to be accounted for according to the supply of ES services, as highlighted in the GI definition (see subsection 2.3). Maps and data that provide standard and harmonized information on ES have recently been produced by the JRC (Maes et al., 2011; Maes et al. 2015a), and will be used for the first overview. The data situation is different at the urban level. Natura 2000 sites usually do not enter into cities, but might stretch into the urban-rural transition zone (which can be part of the Functional Urban Area of a city (FUA)). Also, the MAES ES maps (Maes et al. 2015a) do not usually provide useful information in cities. Therefore, unlike in a rural setting the approach to mapping GI in cities has been set in a more pragmatic way: whatever is green (and blue in this case) will be part of the urban GI network. Rather than targeting ES for biodiversity conservation (and potential restoration) alone, urban GI should enhance ecological, but also social and economic benefits to the urban populations within the limits of city areas (Mattijssen et al., 2017). Since almost all green (and blue ) elements serve a certain function, it is important to map all of them. This will be done using the Copernicus Urban Atlas. 3.2 Data Management To support tailored cross-sectoral policy analysis within other tasks of the project (namely Tasks 2, 3 and 5), the work in Task 1 includes the conception, implementation and harmonization of a gridded geospatial database to store and analyse the available ES datasets, as well as ancillary data across regional and urban areas in the EU (Annex 1.2). Since the grid data model will be populated with information about ES that are spatially coexisting, this approach is particularly suited for deriving tailored GI networks that cross regions with possibly conflicting policy requirements, such as food provision and biodiversity conservation. Following the Landscape level model presented in subsection 3.4.1, ES and ancillary data stored in the grid database can be strategically combined to define optimised GI networks that contribute to reaching the targets of different regulatory frameworks, as proposed by EEA (2011) and Schleyer et al. (2015), who performed a preliminary review of ESPON

16 ES serving different policies. The database focuses on EU data, but the same strategy can be used with data from the local and national scales. Metadata specifications will follow the ones developed in ESPON database. 3.3 Main difficulties and backup solutions The GRETA team has assessed the data situation in the EU with regard to the project topic. From the list of datasets collected in Annex 1 section 2, it is notable that most available layers only cover the EU countries (EU-27 or EU-28 depending on the reference year). The datasets often exclude Croatia, Iceland, Liechtenstein, Norway and Switzerland, as well as EU Candidate Countries and other countries of the Balkans. Moreover, most geographic layers are related to a single date (around the year 2012) or multiple dates that do not comprise present time. The Natura 2000 network stems from the Habitats Directive and, accordingly, only the Member States (MS) have designated these areas. Therefore, the current date geographic cover is constrained to the EU-28 countries, excluding four countries of the ESPON 2020 Cooperation Programme, namely Iceland, Liechtenstein, Norway and Switzerland, as well as EU Candidate Countries and other countries of the Balkans. Natura 2000 data is updated and available on a yearly basis since 1994, but only for the countries participating to the EU in each specific year (e.g. before July 2013 Croatia was not EU member and only 27 countries were covered). ES maps from Maes et al. (2015a) act as a EU reference for measuring Target 2 in the Biodiversity Strategy 2020 (EC, 2011). Therefore, the geographical extent of the Maes et al. (2015a) assessment is the EU countries (EU-28 or EU-27 depending on the data set). Reference date for the maps is 2010 and no more recent dataset is available. This is in agreement with the reference dates and geographic coverage of the Natura 2000 network, thus providing a consistent and robust basis for the first GI overview at the landscape level. Based on the preliminary analysis of the Natura 2000 network, LU/LC datasets and ES maps, it is suggested to use 2010 as a reference date for landscape GI and limit its geographic coverage to the EU-27 countries. This provides consistency to the results and avoids mismatches with the outcomes from other EU level projects that base their analysis on the standard ES maps of Maes et al. (2015). Moreover, and looking at changes on the landscape GI patterns over time, it is suggested to perform an analysis based only on the hubs of the network, i.e. Natura 2000 sites, for which there is a consistent time series over the EU-27. For the Interim Report, the changes in the number and extent of Natura 2000 sites will be mapped and statistically analysed, namely by calculating the difference between 2000 and 2012 to be compliant with the basic European land cover information data CLC. At the urban level, the Urban Atlas is the main information source for the indicators informing about GI. The Urban Atlas is a EU product that in its first version in 2006 mapped cities in the EU-27 territory. However, in the newest Urban Atlas (reference year 2012) EU-28 and the ESPON

17 four EFTA countries Iceland, Norway, Switzerland and Liechtenstein, i.e. the entire ESPON space, are covered as well. Consequently, 32 countries can be analysed for the reference year 2012 whereas cities from 27 (EU-27) countries can theoretically be assessed regarding changes. This, however, needs to consider that the number of FUAs and cities increased substantially between 2006 and 2012 because the population threshold for cities to be included was decreased from to inhabitants. Overall, this means that the EU candidate countries and the other countries in south-eastern Europe cannot be taken into consideration in the analysis. The second major data set for the urban and peri-urban analysis is the Natura 2000 layer whose limitations were already described before, i.e. its lack of coverage of the four ESPON cooperation countries Iceland, Liechtenstein, Norway and Switzerland. 3.4 First overview map Methodological approach for mapping GI Landscape level The GRETA project uses a novel approach to quantify the geographical distribution of GI network and assess its capacity do deliver ecosystem services at the landscape level, which integrates the bottom-up frameworks to GI envisaged by, e.g. Maes et al. (2015) and the EEA (2014), with the top-down approach proposed by EC (2010) and applied by Estreguil et al. (2014) see Annex 1 section 3 for a schematic workflow. The top-down approach uses the Natura 2000 sites as the hubs that need to be connected and all natural and semi-natural areas in the landscape as potential GI network links. The bottom-up approach measures the ES provided at each location to evaluate the overall quality of the GI network defined by all natural and semi-natural areas connected in the landscape (not discriminating between links and hubs). The integrated approach used for this overview takes the Natura 2000 sites as the hubs of the landscape GI network and measures the quality of the natural and semi-natural areas connecting them at each administrative region based on the supplied ES. The first overview makes use of the following basic spatial elements (presented in subsection 3.1): Hubs: Natura 2000 sites extent as the backbone for the GI network, as proposed by EC (2010); and Links: ES maps for the MAES (Maes et al. 2015a) as the basis for qualifying relevant natural and semi-natural connectors between the Natural 2000 hubs. Regarding the top-down approach, the choice of the links to be include in the network depends on the land use and land cover classes that fit to the working definition of GI (see definition on page 6): natural and semi-natural areas with other environmental features. Therefore, for this overview and as similar as for Maes et al. (2015), all impervious areas (namely those defined in CLC 2012, Ecosystem Type Map for 2006, HRL Imperviousness and OSM Motorways see Annex 1 section 2) were removed from the analysis, as well as all permanent crops and pastures (as mapped in CLC2012 and MEE 2006 see Annex 1 section 2) that are not High Natural Value Farmlands (Paracchini et al., 2008). The ESPON

18 remaining natural and semi-natural landscape features were kept and used to identify all possible contiguous spatial links between the Natura 2000 hubs. To assess the quality of network links, we followed a bottom-up approach based on the ES maps produced in the framework of MAES (Maes et al. 2015a). At this step, the work included the selection of ES that contribute to the implementation of, or are promoted by the targets of Action 5 of the Biodiversity Strategy (Maes et al., 2013). Therefore, we deliberately did not include provisioning and cultural ES in the process because they are mainly driven by human inputs like energy (e.g. labour, fertilisers) or capital (e.g. touristic infrastructures), and constitute important trade-offs for biodiversity and other ecosystem services (Nelson et al. 2009, Maes et al. 2012, EEA 2014) please see Annex 1 section 4 for a complete list of used ES. Available ES maps strongly differ in the units, range of output values and spatial resolution. Thus, to enable compositing at each location, the maps were made consistent by aggregation to a common spatial resolution and normalizing the ES indicator values to a common range and unit. Selected ES were converted to a spatial resolution of 1x1km, and outlier values were removed based on the method proposed by Rousseeuw and Hubert (2011). In the sequence, data sets were normalized by the max-min technique (as similar as Maes et al. (2015), Schulp et al. (2014) and EEA (2014)), and subsequently combined through an arithmetic sum, in which the highest values represent the highest combined capacity of the potential network link to deliver regulating and maintenance ES across EU- 28. Only natural and semi-natural areas providing 2 or more ES were kept in the analysis to account for GI multi-functionality. Finally, for providing a first overview of the status of landscape GI network in Europe, the following parameters and indicators were calculated and mapped at each NUTS3 region: Percentage area covered by GI network; Average capacity of GI network to provide ES. Urban level As mentioned in subsection 2.3, the assessment of urban GI includes all available green and blue areas. As previously mentioned, the most relevant land cover/land use data set for this analysis in cities and their immediate hinterland (peri-urban space) is the Urban Atlas layer. To reflect the green (and blue) urban areas, all Urban Atlas classes that represent green and blue urban areas are aggregated into one class green urban areas (GUA) 7 and their proportion in relation to the total area of the reference units calculated. In addition to the land cover/land use information, Natura 2000 sites are also included in the analysis as they can reach into the outskirts of cities (see explanations in chapter 3.1). 7 For ease of terminology we stick to the term green urban areas (GUA) ; however, this term encompasses blue areas as well. ESPON

19 Hence, for providing a first overview of the status of urban GI, the following parameters and indicators will be calculated and mapped: Share of GUA within (i) the entire FUA (representing the entire reference unit), (ii) the core city (representing the city level) and (iii) the FUA without the core city 8 (representing the peri-urban space; all values in [%]); Share of Natura 2000 sites within the FUA (representing hubs within the urban and peri-urban space, in [%]) Analysis of the geographical distribution patterns of GI and ecosystem services Map 3.1 and Map 3.2 are the core analysis tools to evaluate the spatial patterns of GI and ES at the EU landscape level. Whereas Map 3.1 depicts the amount of natural and semi-natural areas connecting Natura 2000 sites within NUTS3 regions, Map 3.2 shows the average capacity of the GI connectors to provide ES. For complementary information on the distribution of Natura 2000 sites (i.e. GI hubs ) within EU please see Annex 1 section 5. Please note also that we only present the combined distribution of ES, as the individual ES patterns are fully depicted in Maes et al. (2015a). Looking at Map 3.1, one perceives that the percentage of natural and semi-natural areas connecting Natura 2000 sites within NUTS 3 regions is larger in central Iberian Peninsula, the Alps across France, Italy and Austria, Northwest UK, the Carpathian Mountains, and Scandinavian countries, namely Sweden and Finland. In some cases it happens that the natural and semi-natural areas within NUTS 3 regions are too fragmented to allow for the Natura 2000 sites to be connected. This is notable for regions where land is predominantly covered by urban fabric (e.g. Paris, London, Flanders, the Ruhr area, and Berlin) and/or used agricultural production (including managed pastures) northwest France, southeast England, and South Ireland, to cite but a few. Regarding Map 3.2, and as similar as for Map 3.1, we notice that regions with lower cumulative ES values coincide with areas predominantly covered by urban fabric and dedicated to intensive agricultural production. Additionally, dryer areas, where natural grasslands or shrubs are dominant in the landscape, but where also important agricultural activities take place, are characterized by lower ES values. This is particularly evident for agro-forestry areas in the centre of Iberian Peninsula, which are known to be affected by water stress and show less capacity to provide regulating and maintenance ES. Regions with a high proportion of forests and wetlands usually result in cumulative ES values that are higher than average (e.g. 8 For some cities the FUA is identical with the core city. Consequently, in those cases the GUA value will be identical to the core city value and hence be removed from the database. ESPON

20 Sweden and Finland, the Alps region, and northeastern France). Overall, these results are in line with the results from Maes et al. (2015) and EEA (2014), although the aggregation at NUTS 2 level performed by Maes et al. (2015) and the 1x1km analysis perform by the EEA (2014) makes difficult to compare with some of the hot and coldspots found in our data at NUTS 3 level. Map 3.1: Percentage cover of GI links per NUTS3 regions. Map 3.2: Average of standardised ES composite index per NUTS3. Map 3.3 shows the share of green urban (and blue) areas for all FUAs in Europe. It becomes clear that many European cities (including their commuting zones) are relatively green, many possessing more than 80 % green areas (mean equals 84.8 %, median even 88.3 %; see ESPON

21 descriptive statistics of all indicators in Table 3.1). The only clusters of regions in which values below 70 % are visible are located in the United Kingdom (the large majority of the cities at the end of the value ranking are located in the UK), a stretch from western Germany into the Netherlands, and the Baltic countries. Comparing this picture to the share of GUA in the core cities alone (i.e. the inner city without the oftentimes greener peri-urban areas, (see Annex 1 section 5) immediately shows lower values in many regions across Europe. The majority of cities has between 60 and 80 % green and blue areas within their boundaries (mean 64.1 %, median 66.9 %). Again, the UK and a zone from northwestern Germany over the Netherlands and Belgium towards the north-east of France possess clusters of cities with values below 60 % (down to the minimum value of 1.6 % in the City of London). In addition, other clusters of cities with low values can be found in Poland, the Baltic countries, Romania, northern Italy and parts of the Iberian Peninsula. On the other hand, looking at the share of GUA in the peri-urban space only, i.e. in the FUA without considering the core city (see Annex1 section 5), both the mean and median values increase to over 90 % with almost 550 cities having a share of GUA above 80 %. It needs to be taken into account, though, that for more than 100 cities the FUA is identical with the core city, so this map contains less cities than the previous two maps. Map 3.3: Percentage cover of urban green areas inside the FUA Lastly, to create the link to the hubs on the landscape level we have also calculated and mapped the share of Natura 2000 sites within the FUA, this to assess which cities do have a good potential for conserving or restoring a green infrastructure network in their immediate ESPON

22 surroundings. Map 3.4 shows that there are clusters of cities with high values (larger than 20 %) in the south of Spain and Portugal, along the Mediterranean coast in France, in a stretch from Greece over Bulgaria into Romania and in south-western and north-eastern Germany. Clusters of cities with values below 5 % only are located in a zone from the UK to northern France, Belgium, the Netherlands and north-western Germany, then in Sweden and Finland, northern Italy, northern Spain and Portugal as well as central Romania. Table 3.1: Descriptive statistics of the four urban indicators Indicator Max [%] Min [%] Mean [%] Median[%] Share of GUA (FUA) Share of GUA (core city) Share of GUA (FUA without core city) Share of Natura 2000 areas (FUA) 99.3 (Tromsø, NO) 98.9 (Tromsø, NO) 99.4 (Reykjavík, IS; Tromsø, NO) 70.3 (Algeciras, ES) 19.1 (Luton, UK) 1.6 (City of London, UK) 41.8 (Dordrecht, NL) 0.0 (46 cities, most of which from the UK) Map 3.4: Percentage cover of Natura 2000 area inside the FUA Outlook To complement the analysis at the regional level, other landscape metrics will be computed for the Interim Report. On the landscape level, these include, amongst others, the percentage area covered by GI hubs, the proportion of connected and isolated hubs, the proportion of ESPON

23 existing GI links to the total of natural and semi-natural areas providing multiple ES, as well as configuration metrics related to the distribution and spatial organization of links and hubs within NUTS regions. On the urban level, we plan to calculate the added share of GUA and Natural 2000 sites in the cities, and composite indices such as the relation of GUA inside the core city to the share of GUA in the peri-urban areas (FUA without core city). In addition, we will continue to explore the possibilities to assess changes of GI and ES. The HNVF map used for this overview was from 2006 and no data was available for Greece. We have decided to remove croplands and irrigated areas from the analysis for that country, based on CLC2012 classes, but the remaining agricultural areas might have weighted negatively the quality of the network there. In opposition, the inclusion of some HNVF areas in the network seem to have affected negatively the quality of GI in those NUTS 3 regions. Therefore, the use of HNVF map will be reviewed for the Interim Report. Similarly, the chosen ES will be further refined for the next phase, as well as the possibility of including a factor of value dispersion in composite ES index. The included ES will be tailored in close collaboration with Task 2, according to the regional demands that are going to be evaluated in that task. This will allow the GRETA project to map a full GI network that is more specific to the requirements of particular users and/or policies, as discussed in subsection Potential positive and negative effects of GI and ecosystem services on European territorial development Humans are taking advantage of the goods and services that nature is freely delivering such as food resources, clean water, regulated climate, and much more (Daily, 1997; Millennium Ecosystem Assessment, 2005), but the sustainable provision of these benefits depends on the land management and policy decisions we apply on the territory (Rounsevell et al., 2012). Nonetheless, increasing demands on natural resources suggest a likely global intensification of pressures on ecosystem services (ES) (Rodríguez et al., 2006). Despite extensive research on the concept of ES in recent years, progress in applying this knowledge for sustainable resource use remains unsufficient (Bennett et al., 2015). There is still a need to better integrate ES in land planning and management, also to have a real impact in policymaking and territorial development (Logsdon and Chaubey, 2013). 4.1 Setting the scene key concepts ES have become a mainstream concept, still the use of different terminologies for ES associations in research are a continued source of misunderstanding (Cord et al., 2017). Therefore, it is important to first identify those key concepts that are used in literature before starting any focused search and also to share a common understanding of them. In the Millennium Ecosystem Assessment (2005), Ecosystem services (ES) are defined as the benefits people obtain from ecosystems. Though there exist several other definitions of the ES concept, common to them all is the framing of ecosystem services as benefits only (Lyytimäki and Sipilä, 2009). In order to obtain a more balanced view, one should also ESPON

24 consider potential Ecosystem disservices (EDS) that are those functions or properties of ecosystems that cause effects that are perceived as harmful, unpleasant or unwanted (Lyytimäki and Sipilä, 2009; Lyytimäki, 2015). One of the key challenges in the sustainable, efficient and equitable management of ES is that they are not independent of each other (Bennett et al., 2009). Knowledge on the nature and character of the relationships between ES is crucial to foresee the impact of different environmental management choices (Mouchet et al., 2014) and, based on that, for making sound decisions about limited natural resources (Rodríguez et al., 2006). Some mechanisms may favour the simultaneous provision of a range of ES, that is promoting multifunctionality; for instance, wetlands acting at the same time as a buffer against climate variation, providing flood control and shoreline stability (Mouchet et al., 2014). ES interactions occur when multiple services respond to the same driver of change or ecological process, or when interactions among the services themselves cause changes in one service to alter the provision of another (Bennett et al., 2009). These interactions are defined as ES synergies when multiple services respond simultaneously, or ES trade-offs when the provision of one service is enhanced at the cost of reducing the provision of another service. Synergies imply win-win situations when there is a positive interaction and both services are increased. While trade-offs describe antagonistic circumstances that require choices or management decisions to be made between alternatives (Cord et al., 2017). Another important concept to consider when searching for general rules that determine ES associations is ES bundles as coherent sets of ES found repeatedly together across space and time (Raudsepp-Hearne et al., 2010). 4.2 Assesing interaction between ecosystem services A careful selection of ES indicators is critical for interpretation; the number and types of ES considered, the way they are quantified and the data used to measure them will influence the number of bundles, the types of interactions and distribution of resulting ES associations (Mouchet et al., 2017). It is necessary to distinguish which aspects of individual ES are quantified by selected indicators, specially when analysing the relation between several services. Most previous analyses have used a range of indicators mixing supply and demand (Spake et al., 2017). ES supply refers to the capacity of the structures and processes of a particular ecosystem to provide ES within a given time period (Burkhard et al., 2012), while ES demand considers the amount of a service required or desired by society (Villamagna et al., 2013). Bundles of supply and bundles of demand are likely to present different dynamics as well as respond to different drivers. Two key components are important in determining relationships between ES and governing issues of scale: the resolution, that is the spatial unit of analysis, and the extent, the size of the study area. Changing the spatial resolution, different processes take place showing or hiding synergies and trade-offs. ES interactions are usually analysed using administrative units at the local level, often driven by data availability. Although municipal boundaries may be meaningful for some ES, they may well be arbitrary for other ecological units, e.g. ESPON

25 whatersheds (Spake et al., 2017). Analysis of ES relations at this coarse resolution relies on spatial coincidence of ES, masking causal relationships between ES and socio-ecological aspects. At coarser resolutions spatial units are highly heterogeneous, so ES interactions are most likely to be driven by the fractional land cover and mainly reflect land use distribution. At finer resolutions, spatial units are less heterogeneous and normally represented by one single land cover type. Here, the main driver of ES variation is related to land use activities, allowing a more useful understanding of the governing processes. The spatial extent at which ES are analysed may also influence their interactions. At present, most research has considered ES relationships at regional level (Spake et al., 2017) where potential complementarities and trade-offs among municipalities may appear. Once individual ES are measured, values can be compared to identify spatial or temporal patterns in order to detect significant associations among ES. Mouchet and colleagues (2014) compiled the first guidelines for assessing trade-offs among ES, a comprehensive compilation of available methods to analyse ES interactions from the simplest graphic methods (i.e. map comparison, trade-off curves, or star diagrams) to a variety of statistical and computational methods. Pair-wise correlation and statistical tests are commonly used to identify the direction and strength of relation among ES, while ES bundles are often detected by clustering methods (e.g. K-means, and Principal Components Analysis). 5 Factors that can help in unlocking the GI and ecosystem services potential for further territorial development, The EU Green Infrastructure Strategy (2013) foresees a number of actions that include, for example, integrating green infrastructure (GI) into key policy areas, specific funding (European Regional Development Fund, Cohesion Fund, LIFE+ among others) or improving the knowledge base and encouraging innovation in relation to GI. However, its adoption and implementation are still quite heterogenous (EC, 2016). Therefore, it is key to identify barriers and the elements that facilitate (unlock) its development. From a preliminary literature search we have identified the following factors that influence the adoption of green infrastructure, sorted by relevance: Financial incentives. This is one the most referred factors. Financial incentives includes both direct, such as grants and subsidies, and indirect, such as energy cost savings. Existing regulations (laws and policies). Laws and policies play a significant role in the adoption of green infrastructure because they mandate the inclusion of green infrastructure in planning and design. At European level, for example, the Biodiversity Strategy already indicated the target to restore at least 15% of degraded ecosystems by At national or local level policies related to regulation on green roofs or ecological compensation for new buildings are being developed. Planning recommendations are used to encourage, rather than mandate, the use of green infrastructure. ESPON

26 Education. It includes different aspects as awareness, knowledge, and understanding of the types and uses of green infrastructure, including the ecosystem services it provides, by the public, stakeholders, and policy -and decision-makers. Coordination among actors. The collaboration of public and private entities and individuals at a variety of scales, from the national to the local. All these factors interact in direct or indirect way. Therefore, it is important, to advance in the direction to better understand these connection, which will be a key development in the Interim Report. For example, the use of green infrastructure in an area positively influences awareness among the public, stakeholders, and policy -and decision-makers. This awareness and a deeper knowledge and understanding of green infrastructure may indirectly influence adoption through the creation of Laws and Policies, Planning Recommendations, and/or Financial Incentives. Awareness, knowledge, and understanding of green infrastructure in different groups may facilitate Coordination Among Actors whereas formal undergraduate and graduate programs function to promote technological innovation in green infrastructure, which positively affects the Provision of Ecosystem Services. 6 First overview of existing policies, planning instruments and initiatives related to GI Task 3 will first develop a detailed understanding and assessment of GI policies and implementation actions that are carried out in different countries, by different levels of government. Through information provided by a national policy survey, GRETA national policy factsheets will describe to what extent national GI policies have been developed in Europe, the way GI is integrated in key sectors, and how national policies influence GI implementation actions carried out at any territorial scale, from the transnational to the local. The GRETA survey will also include questions supporting the identification of 25 good practice examples, which will show how national policies have influenced the implementation of GI actions. A first overview of existing national GI policies, as well as planning instruments and initiatives of cities and regions at different territorial levels has been completed. Ten national policy factsheets and seven sector-specific factsheets from the EC website 9 have been analysed, as well GI policy studies conducted within the GREEN SURGE project 10. This will serve as an inspiration for how the GRETA survey to national policy experts will complement existing the existing knowledge base, with coverage of the 32 ESPON countries. The EC s national factsheets target countries with relatively low GI related information and commitment and the thematic factsheet target the main sectors associated with GI policy Green Infrastructure and Urban Biodiversity for Sustainable Urban Development and the Green Economy ESPON

27 deployment 11. The policy factsheets describe the national policy setting and ongoing implementation, as well as case examples of effective implementation, while the thematic factsheets offer examples of national policy and implementation. Four tables provided in Annex 3 show the analysis of the factsheets. The policy and implementation and the good practices section for each factsheet is described by categorising the main interventions by sector/theme. The good practices are also then categorised by the territorial scale(s) which are important for conceiving policies and implementation actions, and the thematic reviews are also categorised by the territorial scale of intervention, with country specific examples. Working notes based on the review are also provided. The review of both the national and the sector factsheets provide many insights to help in preparing the survey. First, land use planning aspects associated with Natura2000 areas and development of ecological corridors is a fundamental mechanism for implementing GI policy nationally, however, this has been implemented to varying degrees between countries. Likewise, many of the factsheets discuss the common objective to protect biodiversity and habitat/ecological network through GI policy, and they mention the status of MAES Mapping and Assessment of the state of Ecosystems and their Services implementation, which seems to vary considerably between the countries. Two countries (IT and LV) note the development of a national GI strategy/strategic framework, while there has been no MAES assessment in Latvia yet. Both the policy and implementation and the good practice sections tended to have a sectorbased discussion - the national perspective is mainly taken up in the context of interventions within different policy fields and strategic areas. In addition to land use and biodiversity, the main sectors/themes mentioned included: water resource management (including wetland/watercourse restoration and disaster prevention from flooding), climate mitigation and adaptation, and in the rural context, agricultural areas were identified as an area of both challenge and opportunity for GI policy implementation. However, even though the good practice examples are categorized into separate sectors, many of them appear to be based on the criteria of emphasizing the multiple functions and benefits, including connections between nature and socio-economic benefits (e.g. Wetland conservation areas can function as flood prevention, water filtration, maintenance of the water table, recreational possibilities, carbon storage and interconnected wildlife refuges, etc.). Most of the good practice examples in the national factsheets describe initiatives taking place in urban or peri-urban areas. However, a number of main territorial scales are identified in the 11 Trinomics (2016) Supporting the Implementation of Green Infrastructure: Final Report. Available at: pdf. Accessed: ESPON

28 review, especially the city-regional scale. Transboundary initiatives are also emphasized, while examples of comprehensive national GI strategic implementation were not noted. The briefing of the existing national GI factsheets helps to concentrate the specific questions of the GRETA survey so that the most common sources of policy insight are carefully scrutinized. Among other aspects, the extent of spatial coherence of the Natura 2000 network and MAES assessment implementation must be clarified by the respondents, as well as tailoring questions that allow respondents to providing reflection on how policies and good practices emphasize multiple benefits the different territorial perspectives under investigation in GRETA. Financing is also identified as an important area for the survey, in terms of identifying additional funding sources, the application of funds from different EU funding sources, as well as the use of economic rationales to promote GI implementation both short term financial gains as well as long term cost savings (e.g. cost avoidance associated with climate change mitigation/adaptation). It was also noted that finance sector interventions tend to dominated by national level policies and programmes, which will make it a priority for the GRETA survey (See Annex 3, Table 4). Based on these reflections, as well as regional survey questions created for the GREEN SURGE project, Annex 3 includes a first draft of the survey questions for gaining national information on national policies and good practices. 7 Snap-shot of GRETA Case applications GRETA will carry out twelve in-depth analyses of different types of European regions and cities, as a crosscutting activity of the project, to identify their development opportunities and challenges in the implementation of Green Infrastructure. GRETA case studies represent different territorial settings at local, regional and national levels which focus on different aspects of GI development and implementation in order to: validate the analytical framework on GI typologies developed in Task 1 provide a more detailed insight into the benefits of GI and ES for smart, sustainable and inclusive territorial development (Task 2.1); gain evidence on the perception of GI and ES by policy makers in European regions and cities and their knowledge needs for making full use of GI potential for territorial development (Task 2.1) critically evaluate the governance practices, policy and planning instruments and analyse the mechanisms applied to implement GI and enhance ES (Task 3); obtain evidence on the degree to which GI is rewarding from an economic point of view, but also on possibilities for policy making to overcome the potential resistance of the private sector to GI investment (Task 2.3) forge links with case study stakeholders early in the project to better inform policy messages and recommendations in Task 5. ESPON

29 Investigation of GI experiences will be based on two types of cases: i) Pilot cases and innovative projects where a broad selection of GI and ES improvements is implemented and, conversely, ii) Areas with underdeveloped GI and scarce innovation. Each of the case studies will produce: Feedback on Task 1 categorisation of GI, its connectivity and its functions. A summary of benefits and demands specific to the investigated case Task 2 An overview and evaluation of case-specific policies established and innovative as well as failed. This feeds into Task 3; Conclusions on GI potential for territorial development, policy messages and the conditions under which GI infrastructure implementation have succeed or fail to feed into Task 5. Map 7.1: Proposal GRETA case studies GRETA takes a multi-scale approach by exploring the different spatial, institutional and jurisdictional settings that affect GI, from urban cores to rural countryside. They have been selected based on their representation of different geographical, climatic, political, governance, societal and financial conditions, and thereby to help ensure that the GRETA outcomes can be used to support GI implementation globally. They all have complex climate resilience, social, economic and environmental problems to address. The elaborated plan for carrying out case studies is included in the Annex 4 of this Inception Report. ESPON