Inter-Municipal Collaboration and Social-Ecological Scales Mismatches

Master´s Thesis, 60 credits Ecosystems, Governance and Globalization Master´s programme 2009/11, 120 credits

INTER-MUNICIPAL COLLABORATION AND SOCIAL-ECOLOGICAL SCALES MISMATCHES

A NETWORK ANALYSIS OF URBAN STOCKHOLM REGION

Diego Galafassi

INTER-MUNICIPAL COLLABORATION AND SOCIAL-ECOLOGICAL SCALES MISMATCHES: A NETWORK ANALYSIS OF URBAN STOCKHOLM REGION

Diego Galafassi

Stockholm Resilience Centre

Stockholm University

Submitted February 6th, 2012

A thesis submitted to Stockholm University in partial fulfillment of the requirements of the degree of Master of Science

Abstract- In the study of social-ecological systems, matching scales of social and ecological processes is regarded as a key factor for the effectiveness of institutions in governance of natural resources. Urban regions are heterogeneous systems often more prone to social-ecological scales mismatches. The landscape in Stockholm County presents high levels of ecological connectivity through large contiguous green areas extending from city core outwards – i.e. green wedges. These areas are commonly intersected by municipal boundaries. In this context, inter-municipal collaboration is deemed as a cornerstone to avoid fragmentation of regional green structure and to align management scales in the face of urban development and change. I use the network perspective to investigate how collaborative efforts between Stockholm County municipalities are used as a strategy to deal with scale mismatches. Inter-municipal collaborations vary in degree, from informal exchange of information to joint planning and may occur under a range of “management themes”. I investigate the general characteristics and relationship between collaboration networks of parks, forest and water management. I explore the role of different municipalities in these networks and assess patterns of collaborations among municipalities sharing green wedges and municipal borders. Informal collaborations, in the form of exchange of information, are a major component of these networks. Municipal borders are not the only determinant of collaborative efforts. Social-ecological mismatches with potential implication to the maintenance of regional ecological processes have been identified. I discuss these findings in the light of a theoretical model of network governance that combines ecological scales and social network structure at multiple scales.

Keywords- - Social-ecological mismatch, network, collaboration, regional planning, Stockholm

Acknowledgment-

Tack Örjan Bodin and Arvid Bergsten my supervisors for laughs and energy boosts! For being simultaneously close and distant and for the numerous pointers. Tim and Bea for endless openings, UEA time and beyond. Thank you Miriam Huitric, Lisa Deutsch and Matilda Baraibar, Henrik Ernstson for inspiration and for sharpening my sight towards network thinking. Always so very thankful to Fausto Tinti for energy, friendship and immense support and for getting me to Stockholm in the first place. Thanks to Stockholm Resilience Centre’s souls for creating a truly wonderful place to flourish. Many people unavoidably accompany you in such a long learning process. Since this is a network study I will mention them all so that each one of you can connect the dots and see how you are all linked to each other through this work. Thank you for being! Maria Inês Poloni, Johanna Källman, Quentin Dilasser, Kaitlyn Rathwell, Charlotta Järnmark, Daniel Galafassi, Itacir Galafassi, Jeremy Vachet, Douglas Tiago Galafassi, Chengyang Huang, Kit Hill, Garry Peterson, Emmanuele Cimana, Qianwen Cai, Bruno Moroni, Raffaela Irenze, Leandra Fatorelli, Frans Lenglet, Susanne Zetterblom, Juan Carlos Rocha, Eymundur Magnússon, Eygló Björk ólafsdóttir, Daniel Ospina Medina, Kate Brown, Dorice Agol, Natasha Grist, Fredrik Granath, Dale McDiarmid, Michael Wolff, Cinzia Giampieri, Laura Redaelli, Cristiane Polli, Rosaria Civitelli, Atito, Markus Källman, Johan Sundqvist, Mirko Dadich, Marilyn Mehlmann, Satyaprem, Andrew Merrie, Alexander Mehlmann, Antonella Perazza, Mumuksha Satchidananda, Alessandro Argnani, Andreas Zetterberg, Giorgio Leoni, Giuseppe Pesce, Andrew Merrie, Teatro delle Albe, Alessandra Cariani, Sara Borgström, Malin Borg, Alessio Tralli, Maria Schewenius, Matteo Torchiani, Inês Dossin, Nelson Dossin, Rolandz Sadauskis, Sara Turczyńska Tynnerson, Daniel Meyer, Christine Hammond, Erik Andersson, Maria de Lourdes Galafassi, Jardel Casagrande, Anna Emmelin, Emma Sundström, Emma Gabrielsson, Sara Börgstrom, Benoit Menard, Douglas Damião, Martin Scheffer, Valter Polli, Mariana Meerhoff, Carl Folke, Wolfgang Brunner, Zoi Farenzena, Steven Bacheler, Tony Parsons, Stefano Tardito, Shima, Rosella Urru, Mariano Calabrese, Tiago Eduardo Genehr, Monica Cibien, Marco Paglione, Sara Virgili, Miguel Polli, Amrita Keli, Andrea Contin, Diego Marazza, Lorenzo Benini, Manja Mentz, Ann-Christin Bolay, Luiz Carlos Galafassi, Laura Buscher, Holger Hoff, Jean Philippe Prodhomme, Johanna Mietala, Anna Normann, Francesco Reyes, Jeff Ranara, Camilla Zucchi, Thomas Elmqvist, Maria Tengö, Alberto Pessuto, Graciela Polli, Enrico Dinelli, Arthur Casagrande, Jardel Casagrande, Marcia Dossin, Nikhil Prem, Flavio Rodrigues, Geovana Polli, Eva Turicchia, Oscar Colato, Sturle Hauge Simonsen, Antonio Briones Dahlin, Per Olsson, Alan Akin, Debora Cristina da Silva, Johan Röckstrom, Ines Oueslati, Ana Karina Ramos, Emmeline Laszlo Ambjörnsson, Enrico Balugani, Victor Galaz, (…. put your name here ….). To Helena…

Table-of-Contents- Abstract-...... -3- Keywords-...... -3- Acknowledgment-...... -4- 1.-Introduction-...... -6- 1.1.( The(problem(of(fit(...... (7( 1.2.( Stockholm(and(scales(fit(...... (8( 1.3.( Defining(social(and(ecological(scales(...... (8( 1.4.( Theoretical(framework(...... (9( 1.5.( Research(Questions(...... (11( 2.-Methods-...... -13- 2.1.( The(area(of(study(...... (13( 2.2.( The(network(perspective(...... (14( 2.3.( Data(collection(...... (15( 2.4.( Data(analysis(...... (17( 3.-Results-...... -23- 4.-Discussion-...... -29- 5.-Conclusion-...... -34- 6.-References-...... -35- 7.-Appendices-...... -39- 7.1.( Figures(...... (39( 7.2.( Network(diagrams((Figures(S1]S4)(...... (40( 7.3.( Methods(...... (44( (

1. Introduction- Natural resource management problems often arise from a mismatch between scales of ecological and biophysical processes and scales at which social processes occur (Folke et al. 2007; Cash et al. 2006; Cumming and Redman 2006; Olsson, Bodin, and Folke 2010). Urban areas are typically more prone to scales mismatches due to fragmented and heterogeneous landscapes (Borgström et al. 2006). The presence of different administrative units and the multitude and often competing drivers of land use change exacerbates scale mismatches in urban context (Pickett et al. 2008). In Sweden, the County Administrative Board is expected to facilitate inter-municipal collaboration on a regional level. However, municipalities have the full autonomy to develop their land and exploit their resources. This administrative fragmentation has important implications for conservation planning, water resource management and all processes that depend on the regional ecological scale.

Recent theoretical developments propose a governance system able to adjust the fitness of social and ecological scales (Ernstson, et al. 2010). The framework is founded on the understanding that actors interact with ecological processes in different ways at different scales. Local users for instance generate situated knowledge by devoting time and attention to local ecosystems through their social practice (Barthel, et al. 2010). Local actors might be articulated in users associations and other types of organizations. These are mesoscale actors that can harness a wider scale understanding of the landscapes by integrating and merging ecological knowledge from local users. At an even higher scale, municipalities articulated in inter-municipal collaborations and planning, can address regional ecological processes. The effectiveness of this urban ecosystems governance system depends on all three scales and inter-linkages between them (Ernstson, et al. 2010).

In this study I use the network perspective to provide an empirical analysis of collaboration among municipalities in Stockholm County. Long-term municipal planning may profoundly influence social-ecological dynamics at other scales. I investigate if and to what extent collaborative networks among municipalities could mitigate institutional fragmentation on a regional scale to protect ecological dynamics operating at that scale.

1.1 The-problem-of-fit- The problem of fit in scales emerge when important ecological processes occur at a scale that differs from the scale of management institutions (Folke et al. 2007). Scale is the spatial, temporal, quantitative or analytical dimension used to measure and study any phenomenon (Gibson, et al. 2000; Cash et al. 2006). Failure in taking account of scale and cross-scale dynamics in social-ecological systems is a common issue in policy and management (MA 2005). Because social–ecological systems are complex adaptive systems with nonlinear dynamics, even the most careful considerations may lead to institutional misfits (Galaz et al. 2008). Given that scales mismatches are a product of complex social and ecological factors, achieving a good fit between institutions and social-ecological dynamics is challenging and require restructuring multiple aspects of social organization (Cumming and Redman 2006) and attention to external drivers of change (Young 2002). However, in the course of recognizing and solving scale-mismatches opportunities emerge, for instance to develop new organizational forms and management (Ostrom 2002), and to innovate in social and environmental policy (Gunderson and Holling 2002).

Urban landscapes are susceptible to more pronounced scale mismatches (Borgström et al. 2006). The multitude of spatially oriented subdivisions among different administrative tasks makes it exceedingly hard to coordinate and match to ecological dynamics (Pickett et al. 1997). For instance, in urban landscapes, there is frequently limited space to allow ecosystem dynamics and disturbance cycles (Ernstson, et al. 2010b). Spatial administrative fragmentation is only one cause of exacerbated scale mismatches. The orchestration of many stakeholders’ perspectives in different administrative units of regional planning and implementation also posits great challenges.

Collaboration between government bodies to manage issues across jurisdictional boundaries is a strategy to deal with scale mismatches. They occur over a range of “management themes”. In Stockholm county landscape, collaborative processes are an expressed need for reaching regional goals of sustainable development (RUFS 2010; Elmqvist et al. 2004). In its more basic mode, collaboration is a source of information sharing and knowledge integration among the actors involved and harnesses the creation of common values. Ultimately a cross-border collaboration will

identify ecologically related cross-border issues and define common objectives to address them through joint planning and action.

1.2 Stockholm-and-scales-fit- Two studies have been instrumental in the study of scale mismatches in Stockholm region. Borgström et al. (2006) studied the mismatches between scales of ecological processes and associated management practices of five areas in Stockholm County. The study found that generally boundaries of management systems are not based on ecological restrictions but rather they are decided by socioeconomic factors such as ownership, administrative divisions, or former land use. Their results show that the regional context, even though often considered as important in official documents, is commonly neglected in practical management.

Ernstson, et al. (2010) has synthesized a set of seven case studies in 17 sites in the urban landscape of Stockholm. According to their analysis, the current governance of Stockholm’s green area ecosystems neglects cross-scale dynamics and actors involved in green area management currently lack dialogue. The study reveals that landscape ecological processes are not taken fully into account since managers (such as park and cemetery managers) tend to disregard relations to actors of adjacent green areas while relating more to actors of the same user classification. Consequently, there seems to be limited capacity to synchronize management across space for instance in providing complementary habitats for functional groups such as pollinators and seed dispersers (Colding 2007). This I exacerbated by the lack of actors operating at the mesoscale in the landscape.

1.3 Defining-social-and-ecological-scales- I investigate if and to what extent collaborative networks among municipalities could mitigate institutional fragmentation on a regional scale. The large undeveloped areas in Stockholm region – i.e. “green wedges” – that stretch from the rural parts of the county towards the central areas are multi-functional ecosystems. Their large continuous spatial dimension is key for biodiversity conservation (Pauleit et al. 2011). This green structure also control water flows, mitigate noise, promote access to open space, nature, culture and sport improving quality of life of urban citizens. I focus on the regional ability to maintain the functioning of the green structure and do not address the range of temporal and spatial ecological scales that compose them. 8

Two aspects are fundamental for upholding the green wedges. One of the main threats is loss of habitat to urban development and fragmentation that impairs ecological regional scale processes. In an un-coordinated situation, municipalities will delineate strategies of exploitation (or preservation) of the portions of green structure within their boundaries with little regard to cross-border processes. In the same ecosystem, what is is in one municipality planned for preservation could in the neighbor municipality be scheduled for housing projects. This is not a normative stance, it rather points to the need of cross-boundary articulation and learning about essential processes in order to avoid pushing fragmentation over thresholds beyond which biodiversity declines rapidly (Drinnan 2005).

A second important aspect is to prevent fragmentation in some critical areas of high importance for landscape connectivity (Urban and Keitt 2001). In Stockholm, cores of green structure are bonded by “green links” that are not necessarily fundamental for instance as major sources of recruitment, but rather for the long-term genetic flow through barriers such as built-up areas, infrastructure, or large water bodies (Zetterberg 2011, Zetterberg et al. 2010). Some of these green links fall across municipality boundaries suggesting that collaboration between these municipalities would increase the ability of maintaining processes of ecosystem regeneration such as seed dispersal and pollination that depend on the preservation of “green links” (RUFS 2010).

Together, maintenance of large and less disturbed areas and protection of weak ecological links pose important challenges to the fragmented municipal administrative scale of decision-making. Municipal collaboration is one way to address these challenges. Upholding the existence of continual and biodiversity-rich areas across municipality borders is however dependent not only on municipal collaborations. The range of ecosystem services generated by these areas also depends on actors’ activities at other scales. In the next paragraph I describe how this study is situated in a cross-scale perspective.

1.4 Theoretical-framework- This study is rooted in the understanding of urban landscapes as social-ecological systems (SES). This acknowledges that ecosystems and society are inextricably linked and interacting in a number of critical ways (Alfsen et al. 2011). Effectively, planning

and management are integral part of the complex social-ecological dynamics occurring in the urban space. By merging ecological scales and social network structure (Ernstson et al. 2010) proposes a framework (Figure 1) for ecosystem governance anchored in principles of adaptive co-management and adaptive governance (Gunderson and Holling 2002; Berkes and Colding 2003; Folke et al. 2005). In theory the model supports ecosystem services in the face of slow and fast change. It pays attention to ecosystem processes and their scales while having flexibility to switch between governance that prepares for change through decentralized social learning, and governance that responds to change through centralized collective action.

Their study defends that the ability in governance processes to recognize gradual changes in ecosystem dynamics depends on the engagement of a diversity of actors at different scales that through their practices generate experiences and situated knowledge. Three main scales are present in this framework. The local scale is defined by actors interacting directly with the landscape and capturing through their social practice place-specific social-ecological information and experience (Barthel et al. 2010). These clusters of local users might be articulated at the municipal scale through mesoscale managers. Different social networks act at the mesoscale such as user associations, NGOs. At the top scale, urban planners, municipal ecologists and architects municipal ecologists and urban planners interact with the landscape through GIS tools and reports. They are the ones involved with networks of municipalities that through collaboration and joint planning can deal with dynamics of larger spatial and temporal scales.

Each of these social scales correspond to different ecological scales. At the local level, ecosystems users such as allotment gardeners and park managers have an impact and interact with patch dynamics (Pickett 1986). At the city scale, the location of habitats assumes higher importance with aspects such as landscape supplementation and complementation and neighboring effect (Dunning et al. 1992). At the regional scale the main processes are landscape connectivity (Heller and Zavaleta 2009), sink-source dynamics (Pulliam and Danielson 1991) and dynamics of disturbance (Pickett et al. 2008).

The fully functioning governance system will pay attention to all these scales and inter-linkages between them. In this study I provide an empirical analysis of the regional scale since long-term municipal planning may influence greatly other scales. Particularly I investigate if and to what extent collaborative networks among municipalities could mitigate institutional fragmentation on a regional scale to protect ecological dynamics operating at that scale.

Local(scale((users)(

Figure 1. Network governance framework. Adapted from Ernstson et. al. 2010.

1.5 Research-Questions- The idealized network model for ecosystem governance above described provides a conceptual map to assess current governance. Here I use the network tools and approach to explore the component of this network governance that spans at greater spatial scales and long-term urban planning instruments. More specifically, I analyze networks of municipal collaborations related to forest management, parks and water resource management. Management and planning under these themes is likely to cover the main ecological processes in the region.

I conduct the research in two levels. First, I explore the general characteristics of collaborative efforts and contrasts in collaboration networks among the different management themes. The second level of analysis asks whether municipalities sharing green-wedges have more collaboration among themselves than they have with

municipalities elsewhere in the landscape. Also, as highlighted previously, green-wedges have “green links” across the landscape that are critical for the maintenance of dispersal flows and connectivity. I investigate whether these links fall across municipal borders and if so whether these municipalities are involved in some type of collaboration.

I address these aims by pursuing the following specific questions:

Q1. What are general characteristics of collaboration networks under different management themes?

Q1a. What are the general patterns of collaboration types – i.e. “strength” - under different themes?

Q1b. Is there a “spill-over effect” between management themes, in that collaboration under one theme co-occurs with collaboration in another theme?

Q2. Are municipalities that share green-wedges involved in a distinct pattern of collaboration?

Q2a. Are neighboring municipalities collaborating more than with others?

Q2b. Are there critical ecological links that fall across municipalities’ borders? How are these areas supported by collaboration between the municipalities sharing the area?

2. Methods-

2.1 The-area-of-study- The area of study is delimited by the County of Stockholm (Figure 2 – in Appendices). It extends over an area of 6,500 km2 (about 2% of total Swedish land area), is divided into 26 municipalities, with a population of about 2 million people. About 46% of the land area is forested, 18% is in agricultural use, 14% is settlement for human habitation, and 22% is in other land uses. Within a distance of 30 km from city’s center there are 48 nature reserves and one national park. Stockholm County landscape is marked by relatively large areas of contiguous forests – “green wedges” - that generate a diversity of natural, cultural, recreational values services a multiple scales. These areas, reflect long historical interactions between human and nature and have been shaped mainly by 20th century regional infrastructure development (Elmqvist et al. 2004). Green wedges harbor parks and natural reserves. They make up the backbone of green infrastructure responsible for regulating water flows, species dispersal, noise reduction and cultural activities.

The main drivers of change for Stockholm urban ecosystems is population growth and increase in urban development (Elmqvist et al. 2004). Population is projected to increase between 28-51% of 2010 figures until 2040 (RUFS 2010). Development is expected to occur primarily in areas with high regional accessibility. Municipalities are encouraged to increase urban density in these areas, which in cases may include green wedges and natural reserves (RUFS 2010).

In Sweden, municipalities have the sovereign right to exploit and develop their land without considering the impacts of such decisions on other municipalities. The Regional Planning Office is the one responsible to create overall objectives for regional development and to facilitate municipalities in taking a regional perspective in their planning processes. The approach and objectives are published on the Regional Development Plan (RUFS). RUFS provide guidance in regional development and seeks to form the basis of plans and initiatives at the municipal level. Yet, the municipalities are the main responsible for land use planning and development of initiatives.

2.2 The-network-perspective- This work assumes a network perspective to analyze existing inter-municipal collaborations in Stockholm County. The relational approach enables the structural analysis of patterns of formal and informal collaborations among municipalities as related to urban ecosystems. Due to its attention to systems interactions, the network perspective is appealing to a broad range of disciplines and is assuming increasingly interest in natural resource management research (Bodin and Prell 2011). Network analysis is a suite of tools especially powerful in the analysis of complex systems such as social-ecological systems (Janssen et al. 2006). Network analysis seeks to model the structure of relationships in a system and provides tools to tests hypotheses about the impact of this structure on the functioning of the system. The network approach has been successfully applied to generate insights on patterns of relationships among resource users and their implications for management (Bodin and Prell 2011). Network tools suite can be used to explore individual characteristics of specific components (actors, patches) and also how behavior of these components are constrained or facilitated by the overall pattern of interactions in the network as a whole (Wasserman and Faust 1994).

A network is composed of nodes and ties (links between nodes). Nodes in a social network can represent people and their social roles, countries, associations while in an ecological network it could be for instance a habitat patch. Ties represent a “flow” or some type of exchange between nodes. In a social network it could be friendship or information exchange while in an ecological network seed dispersal or pollination between patches is an usual type of flow studied.

The choice of this method is motivated by recent advances in methods and techniques in the social-ecological systems literature that have employed network analysis to a variety of cases. The flexibility of describing both ecological and social aspects in the same form is of great advantage for analysts and can produce insights not available to other methodologies (Cumming et al. 2010). Moreover, the theoretical framework for network governance underpinning this study is drawing heavily on a network perspective.

I collected novel network data on how municipalities are linked to manage and plan different aspects of Stockholm County landscape.

2.3 Data-collection- One of the key questions in the study of social networks is the definition of network boundary. The criteria and problems that arise in defining who is alleged to be included in the network is a recurrent topic in the studies of networks. In this research, the choice was straightforward since the administrative limits of Stockholm County defined the spatial boundaries of the study. The departure point for the selection of individuals that were to represent their municipalities was a list of representatives from all 26 municipalities, who had been gathered under the auspices of another research project at the Stockholm Resilience Centre (see www.matrixgreen.org). This list included municipal ecologists, urban planners and planning architects. In their activities, these actors are likely to perform different tasks associated to urban ecosystems and the process of planning. Their position within municipal offices is likely to make them aware of inter-municipal collaborations of various issues related to ecological aspects of land use planning. In most municipalities they are the ones dealing directly with these types of inter-municipal collaborations. To a large extent these actors are either giving advice through meetings and reports to the process of planning and land use policy-making or directly involved in it.

I developed a web-survey tool for network data collection (see Appendix-Methods). Respondents were asked to answer the questionnaire on the behalf of the municipalities providing information about the collaborations they were involved. The advantage of this procedure is that the generated relational dataset refers to municipalities rather than individuals. Admittedly, data quality relies on factors such as how aware the respondent is to existing collaborative processes or even how well they can be recalled. In defense of the adopted strategy, in several municipalities, the survey respondent is the only person engaged in inter-municipal collaborations of the kind being investigated in this study.

The data collected captures only a subset of existing inter-municipal collaborations. Urban systems in a regional scale are highly connected in several domains such as infrastructure, public services, events, environmental assessment, etc. The social apparatus to manage for instance a regional water system, sewage systems or garbage collection, is almost always spreading over different municipal bodies, meaning that these systems are likely to generate inter-municipal networks. However, for the

purpose of this study, I distinguish these types of networks and only focus on relationships municipalities have under three themes of management and planning: Forest, Parks and Water. All of these networks are to a certain extent related to ecological processes associated to the resilience of green structure. Respondents were asked to report the relationship of their municipality to each one of the other 25 municipalities under each theme. To each relationship the respondent had to assign the ”strength” of the collaboration as reported in Table 1. These strengths represent fundamentally different types of relationships, ranging from informal collaborations – type 1 - through the exchange of reports to formalized joint planning. Exchange of ready-made reports might be the first step to resolve scale mismatches. This practice is likely to generate awareness to cross-boundary process that are not matched by appropriate institutional scales. Co-authorship of reports – type 2 - encourages collaborative reflection on integrative solutions able to address scales. Joint implementation and joint planning – type 3 - are the ideal level of collaboration, in which debates about institutional arrangements capable of effectively dealing with ecological processes depending on larger scales than the jurisdictional can take place. The strength of links can also be equated to the amount of resources used in each collaboration. In other words, the stronger the link the more resources are put into the collaboration and the higher the degree of consolidation of the network structure and formalization of the collaborative link.

Table 1. Four “strengths” that actors could associate to collaborations under each management theme - parks, forests, water.

Types-of-collaboration- 0(](No(relation( 1(](Exchange(of(ready]made(reports( 2(](Co]authorship(of(reports(and(articles( 3(](Joint(implementation(of(planning((or(shared(action)(

Each municipality received one questionnaire. Stockholm municipality had to be treated differently given the disproportional size of resources and personnel working with these issues. To ensure that the sampling was sufficient to capture the main interactions between Stockholm and other municipalities, three representatives from Stockholm participated in this study. The section Methods in the Appendices expands

on the methodology used to combine the different responses to ensure that most of Stockholm’s inter-municipal collaborations had been included.

The first interaction with respondents was through e-mail explaining the aim of the research and giving them access to the web-survey. Actors received three reminders over the period of eight weeks. Non-respondents received telephone reminder and finally a hard copy was sent to the remaining non-respondents to ensure maximum coverage of municipality. A drawback in using web-surveys is that they allow respondents to have different interpretations on the questions posed. Cases exhibiting evident signs of misinterpretation were contacted by phone and answers were verified. This process created the possibility of clarification about the nature of each category of interaction (from informal to joint-planning) and resulted in more accurate representation of linkages. However a bias remains in the sense that representatives might not be aware of all informal collaborations occurring, therefore this type of linkages has been considered sparingly during the analysis.

2.4 Data-analysis- The survey generated four types of networks between the municipalities (the fourth type were noted as “other” and was not included in the analysis). In these networks the basic social unit is a municipality and links are collaborations between municipalities. This data was translated in three adjacency tables and conformed to the Ucinet 6 format (Borgatti et al. 2002). Analysis was performed in Ucinet and network graphs drawn in Pajek (Batagelj and Mrvar 1998) and Adobe Illustrator.

Network analysis provides a collection of descriptive measures that can be linked to theories in each particular case. These measures have been progressively associated to features of social-ecological system and how they relate to particular aspects of adaptive management of ecosystems (Bodin et. al. 2006; Bodin and Prell 2011). There is a wide range of metrics developed for studying social networks. Here I focus on measures proposed in the literature of social network and NRM (Bodin et al. 2006).

Table 2 provides the definitions and explains how these measures can be informative in this particular research. In the next paragraphs I describe how these measures relate to the specific research questions.

Q1.-What-are-general-characteristics-of-collaboration-networks-under-different- management-themes?- Natural resource management occurs under different themes or management areas. In this study I focus on analyzing networks related to forest management, parks and water resource management. General characteristics of collaboration networks can help identifying different roles municipalities may play in this network. I analyze the number of people engaged with inter-municipal collaborations in each municipality and the average number of links for each network. I use Pearson correlation test to explore the strength of the relationship between the number of people responsible for collaborations and the number of links a particular municipality holds. I also describe the profile of these professionals, in particular, how close they are related to the decision making process. Centrality (Freeman 1979) was used to examine different network positions that certain municipalities or groups of municipalities may have in the overall pattern of collaboration networks (see Table 2 for further details).

Q1a.- What- are- the- general- patterns- of- collaboration- “strength”- under- different-themes?-

As described previously, collaborative ties have been defined under three types or strengths. Initially, municipalities may engage in informal collaborations through exchange of reports and information (type 1). Progressively, municipalities will start collaborating to generate reports (type 2), which enhances dialogue and the probability of learning from each other. In the strongest degree of collaboration municipalities will jointly plan their strategies to resource management (type 3). In this analysis I draw attention to the strength of ties under different themes by calculating network density in two instances. First considering all types of collaborative ties and then only types 2 and 3. The comparison between these density measures gives indication to the general patterns of collaborative ties in relation to the their strength. I also perform a simple count of how many links exist for each type in the different management networks.

Q1b.- Is- there- a- “spill&over- effect”- between- management- themes,- in- that- collaboration- under- one- theme- co&occurs- with- other- collaboration- in- other- themes?-

Quadratic Assignment Procedure (QAP) (Simpson 2005) was used to assess the extent to which the analyzed management themes are related. QAP measures correlation between entries of two square matrices (networks), then it assesses the frequency of random measures as large as those observed. Significant correlations between the three networks can be interpreted as indicators of spillover effect in collaborations.

Q2.-Are-municipalities-that-share-green&wedges-involved-in-a-distinct-pattern-of- collaboration?- To address this question the three themed networks have been merged into a single network in which only the highest collaborative strength was kept (type 2 and 3). This reduces the resolution of analysis, enabling the account of collaborations as a single unit – independent of themes - and assumes that collaboration among themes is to a certain extent related. By disregarding informal collaborations I eliminate potential bias resulting from data collection and focus attention on significant collaborations in terms of learning and planning the shared ecosystems.

To test if green wedges have the capacity to generate more collaborative ties among the municipalities that share the particular wedge, I used Join-count analysis in Ucinet 6 (Borgatti et al. 2002). The routine splits the network into two groups and is based on counting the number of links within and outside the groups and comparing them with a randomized model. The test was performed for each individual green-wedge.

Q2a.-Are-neighboring-municipalities-collaborating-more-than-with-others?-

Testing the extent to which neighboring municipalities are collaborating to each other is a simple way to describe how cross-border ecosystems are being dealt with in a regional perspective. I constructed a network that models how municipalities are spatially linked through their administrative borders and used QAP again to test the correlation of physical borders to the merged collaboration network.

Q2b.- Are- there- critical- ecological- links- that- fall- across- municipalities’- borders?- Are- these- areas- supported- by- collaboration- between- the- municipalities-sharing-the-area?-

The latest RUFS (RUFS 2010) is an important instrument for guiding regional development and the ordination of land uses in the county. Among the various themes, it also indicates critical areas for maintaining green-wedges regional scale connectivity. RUFS maps out how green structure is linked across the landscape by these narrow stretches. These areas emerge also as important in studies of stepping-stone structures in ecological networks (Zetterberg et al. 2010). Stepping-stones patches are patches that lie on the way of the shortest path between other patches. They are critical to keep the network connected.

Uncontrolled exploitation of these critical links may result in fragmentation of green wedges impairing processes of regional dispersal and ecosystem regeneration. I used RUFS’s maps to identify particular sites of importance for regional connectivity. Next I plot the social network data on these maps and qualitatively assess the fitness between the scales of social and ecological processes.

Four municipalities did not respond to our persistent pleas (mine, and those of my two supervisors). Their absence in the dataset is treated explicitly as explained in Table 2. Despite the absence of some municipalities, with proper caution I am still able to study the complete County’s area based on the reported links from other municipalities to the missing ones.

Data on the linkages “strength” had to be treated carefully since the interpretation of what constitutes an informal collaboration revealed to be inconsistent across all respondents. This observation has also implications for further studies since, as results show, many of the collaboration happening today are in fact informal. More attention should be given to devise methods able to capture these informal processes to complement these results. Weak links are major components of bridging functions in social-ecological systems, which are critical for dealing with uncertainty and reorganization that follows abrupt change (Folke et al. 2005).

Table 2. Network measures and tests utilized to study micro-level and network-level of the observed networks. The term micro level measure indicates that the particular measure provides results to the specific municipality. Network level analysis in the other hand concentrates in overall patters and do not regard the specific municipality.

Measure/(analysis( Definition( What’s(used(for?( What(does(it(mean(in(this(study?( Micro(level( Degree%Centrality% The%number%of%links%incident%upon%a%node% Degree%centrality%is%a%fundamental%concept%in%social% Degree%centrality%in%this%work%is%used%to% (Freeman%1979)% network%analysis.%In%network%resource%management%it% compare%the%“role”%each%municipality%might% gives%indication%to%who%are%the%actor%with%higher% play%in%the%collaboration%networks.%By%role%I% number%of%connections%and%therefore%higher%access%to% mean%the%different%structural%position%a% resources%and%influence%in%decisionCmaking.%It%can%also% municipality%occupies%and%how%it%can%be% indicate%network%ability%of%coordination%in%times%of% translated%into%resources%access%and%level%of% change.% articulation%in%the%overall%network.% % Network(level( ( ( ( Density% Density%measures%the%extent%to%which%N% Density%gives%a%general%idea%of%the%cohesiveness%of%a% Density%is%used%to%study%the%composition%of% nodes%are%connected%among%themselves% particular%network.%It%indicates%the%proportion%of% the%overall%networks%in%terms%of%their%ties% (Carrington,%Scott,%and%Wasserman%2005).% potential%links%in%a%network%that%are%present.%It%is%a% strength.%

The%formula%is%as%follows% % versatile%measure%that%can%be%used%to%explain%several% 21 ! features%of%natural%resource%management% ! = ! !% 2!×!!! arrangements.% % Density%(D)%is%the%ratio%of%the%number%of% reported%links%(L)%among%nodes%divided%by% the%maximum%possible%links.%Missing%data% can%be%explicitly%accounted%for%by%using% % !! !! = % % ! !!!×! !!! ! Where%M%is%the%number%of%missing% municipalities% QAP%correlation%of% Computes%correlation%measures%between% Principally%used%to%test%the%association%between% Tests%the%correlation%between%networks.% networks% entries%of%two%square%matrices,%and% networks.%The%algorithm%proceeds%in%two%steps.%In%the% Also%used%to%test%whether%collaboration% assesses%the%frequency%of%random% first,%it%computes%the%correlation%coefficient%between% network%correlate%to%physical%borders.% measures%as%large%as%actually%observed% corresponding%cells%of%the%two%data%matrices.%In%the% (Borgatti%et%al.%2002)% second%step,%it%randomly%permutes%rows%and%columns%

(synchronously)%of%one%matrix%and%recomputes%the% correlation.%The%second%step%is%carried%out%thousands%of% times%in%order%to%compute%the%proportion%of%times%that% a%random%measure%is%larger%than%or%equal%to%the% observed%measure%calculated%in%step%one.%A%low% proportion%(<%0.05)%suggests%a%strong%relationship% between%the%matrices%that%is%unlikely%to%have%occurred% by%chance.% JoinCCount% Performs%randomization%test%of% The%routine%splits%the%network%into%two%groups%and% Used%to%test%whether%municipalities%sharing% Procedure% autocorrelation%for%a%adjacency%matrix% counts%the%number%of%links%within%and%between%the% green%wedges%have%more%collaboration%ties% which%is%partitioned%into%two%groups% groups.%Next,%random%permutations%of%the%network% than%expected%in%a%randomized%model.% % (Borgatti%2002).% executed.%Comparing%whether%the%ratio%of% observed/expected%links%among%the%municipalities% belonging%to%a%green%wedge%are%higher%then%the%links% among%other%municipalities%provides%a%way%to%assess% the%extent%to%which%the%presence%of%“green%wedges”%are%

related%to%the%network%observed.%

3. Results) The survey generated 26 responses. Four municipalities did not return the survey, thus the following results correspond to 85% of the municipalities. Besides non-repondents (Haninge, Lidingö, Norrtälje, Nynäshamn), only Upplands-Bro declared not having any collaboration in all network types. However, due to non-reciprocal links there are no isolates municipalities when all collaboration types are considered together.

Next I present results of measures and tests for each research question.

Q1. What are general characteristics of collaboration networks under different management themes?

The number of people that each municipality has allocated to deal with inter-municipal collaboration indicates how much resources are invested in these efforts. The median number of professionals engaged in inter-municipal collaboration is 2, while 7 municipalities have only one person. Stockholm stands out with an estimated number of 30 people. A positive correlation (R = 0.635, p <= 0.001) was found between the estimation of number of people working with inter-municipal collaborations in each individual municipality and the number of cross-boundary links established.

In most municipalities (13), actors involved with collaborations are somewhat related to the process of decision-making in their activities by providing advice to the process in regular meetings with policy makers. Another important share (10) is responsible for collecting information and evidence to support decision-making. Only a small part (3) of respondents is directly involved with decisions taken about ecological policy-making.

The different management themes have distinct patterns of collaborations across Stockholm region. Table 3 reports the average number of links for each network. Forest network has the highest average number of links when all types of collaborations are considered (3.57). If informal links of information exchange are discarded then water management collaboration has the highest mean number of links (2.0). When the three management themes are considered together (merged network) the average number of links is 5.23 and 3.61 respectively in considering and dis-considering informal links.

Table 3. Average number of links in each network. In the first value column all types of collaboration strengths are considered, from informal to joint-planning. In the second column, only co-authorship of reports and joint-planning are taken into account.

Network) All)links) Only)strong)links) Forest' ' 3.57'±'4.22' 1.50'±'2.22' Water' 3.11'±'3.34' 2.00'±'2.57' Park' 2.07'±'4.40' 0.61'±'1.90' Merged' 5.23'±'5.31' 3.61'±'5.40'

Network measure of centrality can be useful to investigate different structural positions or “roles” that municipalities may have. These results lay on a typical assumption in network studies, that network structure constrains or allows the actions an actor can perform. Figure 3 illustrates the 26 municipalities as nodes and centrality as node size. Links represent some type of collaboration, regardless the strength. The measure refers to a merged network of all themes. When all links are considered (Figure 3a), Nacka and Vallentuna have the highest centrality. Most of the lowest centrality scores in that instance are associated to municipalities that are geographically peripheral. That is the case for example of Nynäshamn, Värmdo, Södertälje, Norrtälje and Tyresö. In contrast, Lidingö, although geographically central to the county, has a low centrality score. When considering only strong links (Figure 3b), the group of municipalities with higher score changes. Sollentuna and Stockholm have the highest scores. Excluding Tyresö, the group that follows with moderate scores of centrality are all municipalities located in the north part of the county (Danderyd, Täby, Vallentuna, Sundbyberg, Österåker, Solna, Järfalla, Botkyrka).

a)' b)'

Figure 3. The 26 Stockholm county municipalities merged networks a) with informal links b) only stronger links. Centrality represented as node size.

Q1a. What are the general patterns of collaboration types - “strengths” - in different management themes?

Density was calculated by explicitly considering the fact that some municipalities have not answered. Forest network has the highest density and Park network the lowest. Table 4 reports two density measures. The first was calculated for the networks including all collaboration strengths. In the second, weak links that correspond to informal collaboration through exchange of information have been excluded. Results demonstrate that accounting for weak links increases significantly network density. About 50% of network density in these networks is constituted of weak links, especially in the park network. Park network of strong links is remarkably low, about 70% are weak links. Water network density is less dependent on weak links. More than 60% of its density refers to strong links of joint implementation and action.

Table 4. Network densities. First when informal linkages are taken into account and second only stronger relationships

Networks) All)link)types) Only)strongest)links)(type)2)and)3)) Forest' 0.1691' 0.0709' Water' 0.1473' 0.0945' Park' 0.0982' 0.0291'

Figure 4 reports the links count for each collaboration type. The forest collaboration network has the highest number of weak links (50). Water network has little variance in the number of links of different types. It presents the highest number of strong collaborations (21). Park network presents the highest variability between weak links (36) and strong links (6).

50! !

36! 1 - Exchange of ready-made reports! 27! 25! 21! 21! 2 - Co-authorship of reports and 14! articles! 10! Number of Links Number of 6! 3 - Joint implementation of planning !

Forest! Water! Park! Networks!

Figure 4. Number of links in each type of collaboration for each network 25

Q1b. Is there a “spill-over effect” between management themes, in that collaboration under one theme co-occurs with other collaboration in another themes?

QAP analysis was used to measure the correlation between management themes. Results (Table 5) indicate a good level of correlation among the networks meaning that if two municipalities are involved in a collaboration related to forest they have a good probability of being also involved in park and water related collaborations (Pearson=0.627 and 0.637 respectively). Water and park networks are those presenting the lowest level of correlation but still are considerably high (Pearson 0.536 p=0.002).

Table 5. QAP correlation analysis

Network) Pearson) Average) SD) P(Large)) correlations) Coefficient) Forest=Park' 0.627' =0.001' 0.057' 0.002' Forest=Water' 0.637' =0.001' 0.056' 0.000' Water=Park' 0.536' =0.002' 0.056' 0.002'

Q2. Are municipalities that share green-wedges involved in a distinct pattern of collaboration?

Join count analysis provides statistical testing about the significance of groups of ties between municipalities that share green wedges (Table 6). The test is based on the analysis of significance of the difference between number of observed links and expected number of links in a random model. Ëkerökilen has not been included since the whole wedge is within Ekerö municipal boundaries.

Only three wedges have statistically significant more links than those expected in random networks: Järvakilen, Rösjokilen and Angarkilen. These results are supported by other secondary data on the development status of each of these wedges. In Järvakilen, since 2006 the seven municipalities sharing the green wedge are involved in activities to increase use and values of the area. Rösjökilen municipalities together with other organizations like The Society For The Conservation Of Nature, during the period 2006 – 2009 worked together to create a “highly valued and well visited nature area, which contribute to make the regions around it more attractive”. The six municipalities have started a formal collaboration project that will last from 2011 – 2020. In Angarnkilen, the municipalities have established collaboration during the development of a study aimed to describe the value the green wedge.

Table 6. Results from Join Count test for each green wedge. Ekerokilen is located only within Ekero's municipal borders

GreenDwedges) Internal) links) Expected) in) a) P>=)Diff) observed) randomized)model) Järvakilen' 9' 2.908' 0.006' Rösjökilen' 6' 2.077' 0.033' Angarkilen' 4' 0.831' 0.012' Bogensunkilen' 1' 0.415' 0.352' NackaVärmdö' 0' 0.138' P<='0.860' Tyrestakilen' 1' 0.415' 0.341' Handevenkilen' 1' 0.831' 0.547' Borjokilen' 0' 0.831' P<=0.457' Gorvalnkilen' 1' 0.831' 0.535' Ekerökilen' ' N/A'

Q2a. Are neighboring municipalities collaborating more than with others?

To measure the extent to which administrative borders correlate to network of collaborations I used again QAP and the random permutation method. Administrative borders are moderately correlated to the merged network of strong collaborations - type 2 -3 (Table 7).

Table 7. Correlation between administrative borders and collaboration networks

Network)correlations) Pearson)Coefficient) Average) SD) P(Large)) Borders'–'Strong'Collab.' 0.382' 0.069' 0.024' 0.000'

Q2b. Are there critical ecological links that fall across municipalities’ borders? How are these areas supported by collaboration between the municipalities sharing the area?

Qualitative linking between official planning maps (RUFS 2010) and the novel network data was performed to respond to this question. Figure 5 displays results from three distinctive sites in the landscape and illustrates three possible cases. In Figure5a, a green link exists between Upplands-Bro municipality and Järfalla but social network analysis reveals that these municipalities are not enrolled in any type of collaboration. Another case of cross-boundary green link is between Nacka and Tyresö (Figure5b). In the collaboration network both municipalities are currently involved in co-authorship of reports – type 2 collaboration. Figure 5c shows a cluster of strongly connected municipalities. In this part of the landscape Täby and Österåker have a critical green link crossing an area of high development. The municipalities are however in an ongoing process of joint-planning.

Figure 5. Qualitative association of social network and ecological connectivity. Three sites in Stockholm County (a-b-c from top left to bottom left respectively). Small green dashed arrows (within non-shaded circles) represent important sites for green infrastructure connectivity according to RUFS (2010). Yellow shades denote inhabited areas. Orange shades are areas likely to be developed over the next 40 years. Red shades are city cores already well developed. Underlying map adapted from RUFS (2010).

4. Discussion) Inter-municipal collaborations networks have been analyzed over a gradient of relationship. The strength of links can also be equated to the amount of resources used on collaborations. The assumption is that the stronger the link the more resources are invested and higher the likelihood that the municipalities start taking cross-boundary ecological processes into account in the planning processes. Informal collaborations through exchange of reports and information on green areas represent a large component of inter-municipal collaboration networks in Stockholm region. In a network where these informal ties are taken into account (see supplementary figures in Appendices for network diagrams - Figures S1-S4), there is no disconnected municipality meaning that knowledge is able to circulate throughout the entire county and reach a high level in the decision-making processes. This social connectivity allows municipal bodies to learn from each other’s experiences and projects related to the different areas of natural resource management - in this work represented as forests, parks and water management. Awareness to regional ecological processes is a first step towards creating better suited local institutions (Cumming and Redman 2006). Park collaboration network (Figure S3) seems to be the least developed of the three management themes. Over 70% of collaborations in the park network are of the weak type, meaning that seldom municipalities work together to plan parks.

Water is the most developed collaboration network with over 60% of its collaborations being either of joint learning through co-authorship of reports or joint planning – i.e. the strongest form of collaboration (Figure S2). This might be due to advanced projects of watershed collaborations. In the network that considers only the strongest types of collaborations municipalities are not fully connected (Figure S4). In this network Lidingö and Vaxholm are isolates. The lack of regional coordination with these municipalities might lead to fragmentation of wedges intersecting the east part of the county.

A medium correlation has been observed between administrative borders and collaboration ties. This might be explained by the apparent tendency of municipalities in the outskirts of the county to collaborate with municipalities that are more centrally located and less with neighboring municipalities. The implication is a reduction on the capacity to deal with local shocks and disturbances that require coordination across local areas.

Some of the critical sites for maintaining regional ecological networks are located across administrative borders and have to be cautiously considered in urban development plans. A

mismatch was highlighted in one particular site between the municipalities of Upplands-Bro and Järfälla. The lack of collaboration through joint planning between the municipalities that share that particular sites suggests a vulnerability in the face of future development. The effects of fragmentation in that particular area might be relevant mainly to the green wedge Järvakilen, which might have its processes of migration and dispersal affected. More in depth research investigating these two municipalities development plans and institutions is required to assert how this mismatch is actually being addressed. Other similarly critical areas exist in the region (Zetterberg et al. 2010). It lies out of the scope of this work to look at all these areas. However the example discussed above demonstrates one way to hightlight existing social-ecological scale mismatches.

However, inter-municipal collaboration network is spatially heterogeneous meaning that in some key areas, joint planning exists and is potentially able to attend to ecological dynamics. The joint collaboration of planning between Täby and Osteråker creates a better fitting of scales since the important green link between the municipalities is likely to be incorporated in planning. Again, a closer look into the nature of these collaborations can clarify to what extent the ecological processes are taken into account. Also further investigation could highlight the underlying drivers of these collaborations.

The results provide evidence that collaboration under the three management themes analyzed – forests, park or water management – are likely to occur simultaneously. That is not to say that activities in these management themes are coordinated amongst each other. Yet it suggests that green-wedges can function as arenas of collaborations among municipalities. Conversely, six out of nine green wedges are not currently aligned by inter-municipal collaborations that either create knowledge about ecological dynamics or jointly plan future of developments in the area (Table 6). Without cross-boundary coordination, individual municipalities are less likely to initiate projects and regulations sensitive to ecological processes that depend on regional landscape. Thus this seems like a significant social-ecological mismatch. In three green wedges the municipalities sharing each particular wedge present a stronger pattern of linkages. In nurturing these linkages by pooling resources, the municipal network creates the institutional framework necessary for maintenance of multiple services flowing from the shared ecosystems.

In several of the 26 municipalities a single person is responsible for coordinating all activities related to inter-municipal collaboration. Those working with inter-municipal collaborations

are somewhat related to the process of decision-making and have an important role in the consolidation of ecological knowledge to support these decisions. In average municipalities have about five collaborations, including informal collaborations. When considering only strong collaborations, the average number of links is three. These numbers could be interpreted as an indicator of how many collaborative links can be established given the resources available. In fact a positive relationship has been found between the number of people working in inter-municipal collaborations and the number of links observed. This result does not have strong reliability given that only one person has been surveyed in most of the municipalities. Nonetheless the implications are that the number of people allocated to deal with trans-boundary issues seems to be a limiting factor to the number of collaborations that a municipality can maintain.

Slightly contrasting to this hypothesis is the fact that Stockholm’s centrality is equivalent to Sollentuna’s in a network of strong collaborative ties. Surely Stockholm’s central role in the networks is underpinned by the amount of resources dedicated to articulation with other municipalities. However, Sollentuna with much lower levels of resources allocated to inter-municipal articulation has been found in a similar structural position. Both municipalities have an important role in regional joint learning and planning. Their central role implies they have liaised with several other municipalities and built relationships around common values and interests. In times of rapid change these are important assets to coordinate action. In contrast, during slow processes of land planning and development exceedingly centralized positions may undermine emergence of diversification in collaborative approaches.

If informal links are taken into account then a new set of municipalities emerge. These can be seen as central actors to information diffusion and mediation of collaborative planning. Municipalities from the north part of the county have more of a central role than those of the south. As described in the methods section, data related to informal links has to be interpreted cautiously. However it suggests a higher disposition of north municipalities in bridging to other areas of the county. Investigation of the drivers behind these efforts lies beyond the scope of this work but it illustrates the existence of different roles municipalities may have to regional collaboration.

Returning to the network of joint learning and planning, this research identified two types of mismatches as related to regional ecological processes. First not all green wedges are

supported by collaborative ties among the municipalities that share and harbor the green area. This might lead to a lower degree of inclusion of social-ecological dynamics that occur and depend on that ecosystem in policies and institutions. The second mismatch relates to processes that link the green wedges and ensure connectivity and regeneration. A lack of articulation between development plans of municipalities sharing these green links may result in undesirable fragmentation and loss of sustaining processes such as seed dispersal and species migration.

Municipal collaboration is though only one aspect of solving these mismatches. At this stage a return to the theoretical framework can help situating the results in a larger context. The network governance framework described in the introduction emphasizes the key role of “scale-crossing brokers” in linking actor groups from different scales (Ernstson et al. 2010). Scale-crossing brokers are actors or processes with a particular network positions that link otherwise disconnected actor groups from lower or higher scales. Under this perspective, missing links between municipalities can be bridged by scale-crossing brokers.

This paper explored how collaboration links between municipalities are capable to address scale mismatches. The focus on the municipal level limits the contemplation of municipal links to other organizations and actors from different scales. By taking this approach, cross-scale brokering processes and actors becomes invisible. The missing social links highlighted here raise attention to the role of scale-crossing brokers in bridging actors and knowledge even in situations where there is no coordination at the municipal level. These cross-scale interactions are an integral part of regional planning. In fact, several municipalities have mentioned their linkages to actors at other scales. Development of plans for co-management that allows for power sharing and multiscale governance is a way to respond to scale mismatches (Galaz et al. 2008).

The network approach used is flexible and able to accommodate subsequent studies that focus in revealing empirically the potential of scale-crossing brokers or mid-scale managers in the governance urban ecosystems. Interesting to notice that municipal ecologists and urban planners – the ones that participated in this study - are in fact good candidates to such structural position. In their practice they interact with landscapes through spatial tools and long-term urban planning instruments. As results show they are somewhat related to the process of decision-making and as empirically demonstrated here, they are linked across the landscape in a social network with other municipal actors. Their interactions within this

network is likely to generate trust and shared understanding, both essential elements of social capital (Pretty 2003). In sum they potentially have the capacity to create the necessary scales inter-linkages required for governance of urban landscapes.

An important remark from a methodological point of view is that the data collected corresponds to how the network structure appears at this moment. This structure is a result of interactions in continuous change and of resources invested in “creating” this network. Measuring how particular patterns of interaction emerge does not fall under the umbrella of this study. Subsequent studies could explore aspects of causality behind the observed network.

An overarching theme of future research is to uncover the multi-scale and multi-thematic nature of ecosystem uses and management in the green wedges. More specifically, there are signals that green wedges can be designed as collaborative areas with a range of actors, including NGOs, composing the different scales through their use and practices. An alternative route and similarly interesting is to explore the temporal dynamic of these cross-scale network interactions in the green wedges in combination with the elements and artifacts that get woven into the process of becoming a co-management area (Ernstson 2008).

5. Conclusion) The network approach is a promising tool to investigate social-ecological mismatches. The set of tools can model and describe social interactions and ecological processes in the same form. As demonstrated in this work, networks of different kinds can be mapped out to highlight points of overlap or missing links. The extension of this work holds promise from a methodological perspective as well from a practical understanding of the nature of this overlap, which is highly relevant for effective of management of social-ecological system (Cumming et al. 2010).

Within the context of inter-municipal collaboration, two social-ecological mismatches occur. The first within green wedges and the second in processes that link and connect the urban landscape. This work focused on collaborative efforts among municipalities by means of network analysis. This is a first step in understanding how collaboration networks relate to ecological networks and how existing scale-mismatches can be elicited. However, this analysis corresponds to only one of the scales of urban ecosystem governance. In fact, other networks operating at lower scales (spatial and hierarchical) can have an impact in the generation, distribution and maintenance of ecological processes (Barthel 2008, Ernstson 2008), in how knowledge is generated and distributed to other scales and in shaping planning decisions and deliberations (Ernstson 2008). Therefore cross-scale interactions are also necessary to fully understand social-ecological mismatches.

I argue in this work that collaborations between municipalities through joint learning and planning are a way to address scale mismatches. This is not to say that this type of collaboration is the only way to address scale mismatch. In fact, collaboration efforts should also focus on how emergent social networks of a variety of actors across spatial scales can be harnessed for management of ecosystem services throughout the landscape. These networks create the basis for learning and experimentation which are key governance factors under uncertainty and change (Folke et al. 2005). Achieving a good fit is difficult in all cases and requires the coevolution of institutional arrangements with changing dynamics of social-ecological systems.

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7. Appendix)

7.1 Figures)

7.1.1. ) Figure)2.)Stockholm)County)

7.2 Network)diagrams) )

7.1.2. Figure)S1.)Forest)network)))

Yellow= informal links. Red= co-authorship of reports. Black=Joint planning

7.1.3. Figure)S2.)Water)network)

Yellow= informal links. Red= co-authorship of reports. Black=Joint planning

7.1.4. Figure)S3.)Park)network)

Yellow= informal links. Red= co-authorship of reports. Black=Joint planning

7.1.5. Figure)S4.)Merged)network)

7.3 Methods)

7.1.1. Stockholm)municipality)case) The high degree of overlap between Stockholm respondents suggests that the most important collaborations have been captured.

Stockholm because of its size has been treated differently than the other municipalities. Stockholm respondents have estimated 30 people working in inter-municipal collaboration. To test whether Stockholm’s three respondents have reported a fairly completed picture of Stockholm’s inter-municipal links, I tested the level of overlap of the reported links. The assumption is that a low degree of overlapping would indicate that I should seek for other respondents to complement the overall picture. First the three matrices were “binarized” because the strength of the link reported was not important but rather to whom the linkages were being directed. Next, Simple Matching procedure in Ucinet was used to test the degree of overlap. The procedure tests for each link whether it exists or not in the other matrices. The score varies from 0-1, with 0 being a situation in which links are completely different and 1 when the matrices are identical.

The result value is 0.969 with a P(large)=0.006 which indicates a high level of overlapping between the networks.

Following this result, I merged all three networks to obtain the composite Stockholm’s ego network used in the rest of analysis.

7.1.2. Online)Questionnaire)

[… here the list of all municipalities like in the example]