Worldwide, cities face rapid changes in natural hazards, resident mobility, urban densification, sprawl or shrinkage, demographics, and lifestyles, all potentially affecting the access to the different services and resources necessary for good quality of life. Although there are many reasons for the ongoing global aggregation of people in cities, compact, built-up, and sealed spaces, high population densities, and intensive resource use pose a challenge to both health and well-being of city residents (Elmqvist et al. 2018a, 2021, McPhearson et al. 2021). Externalized support systems for satisfying many basic human needs of food and other environmental goods (Seto et al. 2012, Friis and Nielsen 2019) cannot solve all urban challenges in terms of environmental quality. For example, localized, and often locally caused environmental burdens (particles, noise, waste, soil and water contamination, heat island, flooding) threaten to seriously hamper the overall positive development of human health and well-being, as do more sedentary lifestyles (e.g., Tzoulas et al. 2007, van den Bosch and Sang 2017). Green and blue infrastructure (GBI), or the many different urban ecosystems and the ecosystem services (ES) they may provide for urban residents, is a core asset for improving, mitigating, or reducing many of these urban problems and vulnerabilities (e.g., Gómez-Baggethun et al. 2013, Haase et al. 2014, McPhearson et al. 2015). Although in theory greener cities have a broad general societal support, the reality of competing land uses, preferences for different urban amenities, diverging economic interests, and limitations to the mandate, resources, and policy instruments of local authorities have led to increasing pressures on GBI (e.g., Haase et al. 2017) rather than its expansion or improved quality. Moreover, even in city regions with extensive GBI, realizing well-being benefits can be challenging, at least for some social groups, because green spaces are subject to social conflicts and mental barriers (e.g., Seymour 2012, Rigolon 2016).
A fundamentally complex issue like sustained urban quality of life for all, through ever-changing interactions between urban residents and GBI requires a sophisticated understanding of the urban system. To be practically applicable, though, frameworks and approaches need to be simple and adaptable for working within existing governance structures and processes. Similar to other “wicked problems” (cf. Rittel and Webber 1973), there is an ongoing discussion about what the problem is about (physical green spaces or the actual benefits they may or may not provide for different beneficiaries), and how and by whom problems should be addressed (e.g., Lang et al. 2012, Turnhout et al. 2020). Thus, there are no straightforward, simple or universal solutions to ensuring urban quality of life. In response to the complex nature of the problem, theory and practice around urban resilience is receiving increasing interest and has become a major talking point within academia as well as outside (e.g., Pu and Qiu 2016, Elmqvist et al. 2019). However, the meaning and hence the usefulness of the concept is still intensively discussed and its application in policy remains inconsistent and potentially confusing (e.g., Meerow et al. 2016, Elmqvist et al. 2019, Edwards 2020). Plural meanings and sometimes a high level of abstraction makes it difficult to use resilience as an analytical tool or as an instrument for guiding the practice of sustainable development (Enfors-Kautsky et al. 2018, Romice et al. 2018, Sellberg et al. 2018). Although there is a value in plurality and not too narrowly defining resilience, we still see a need for more operational approaches for applying resilience and the theories behind the concept.
Portraying resilience as the capacity of a system to absorb disturbance, reorganize, and retain essentially the same functions over time (in line with Elmqvist et al. 2019), we show how a social-ecological-technological systems (SETS; sensu Grimm et al. 2016, McPhearson et al. 2016, 2021, Markolf et al. 2018) approach to resilience thinking in combination with transdisciplinary knowledge co-creation processes can be applied to investigate and build resilience around the generation and use of diverse GBI benefits (more details on our use of resilience can be found in Appendix 1). Our work provides, first, a brief description of our urban SETS conceptualization informed by resilience theory where generation and flow of GBI benefits are enabled or hindered by the composition and dynamics of the larger urban SETS. Second, we describe and discuss how we used the framework to guide three transdisciplinary case studies. We draw on the insights from these cases and multi-step processes to distil recommendations for future research as well as the practical application of the framework for building resilience around GBI benefits. Rather than converging on a more specific version of the conceptual framework, we use the cases to illustrate the need for flexibility and context-sensitive application, and how a conceptual framework evolves through case-specific deliberations.
We propose that actively working with system level filters (sensu Andersson et al. 2019) offers a way for building resilience around the flow of GBI benefits, which we identify as a core contribution to overall urban resilience. However, for successful real world application, SETS theory needs to connect to non-academic discourse and practice (McPhearson et al. 2021). Our SETS-grounded framework positions GBI as placed primarily in the ecological domain, although humans are actively part of the ecological dynamics through their use and management of GBI. Furthermore, we recognize the co-creation and distribution of diverse GBI benefits as a context-sensitive issue, embedded and enmeshed in social and technological facets of cities and urban life (Ernstson 2013, Andersson et al. 2015, Palomo et al. 2016, Juntti and Lundy 2017). To make SETS more operational, we follow a recommendation from resilience theory (cf. the recommended “3-5 key factors” for defining a state, Resilience Alliance 2010): Walker and colleagues (2012) point to the importance of controlling variables, the core features that over time shape and change the overall identity of the system. Given the focus of this study, the generation and flow of GBI benefits, we argue that three filters—physical infrastructure, societal institutions, and human perceptions and capacities—may serve as the controlling SETS variables in a sufficiently reductionist-while-embracing-complexity system framing. All three “are objects which are both plastic enough to adapt to local needs and the constraints of the several parties involving them, yet robust enough to maintain a common identity across sites. [...] They have different meanings in different social worlds [and across cultures] but their structure is common enough to more than one world to make them recognizable, a means of translation.” (Star and Griesemer 1989:393, see also Turnhout 2009; Box 1.). Hence, these three filters serve as our operational version of SETS.
The three filters are not only controlling variables, but are also, to a certain extent, controllable. Especially the first two are traditional targets for urban planning and governance. Infrastructure has been repeatedly demonstrated as highly relevant for connecting ES supply and demand, and it has multiple additional functional linkages to ES and GBI (hybrid grey-green infrastructure, land appropriation, environmental impacts, etc.; e.g., Grimm et al. 2016, Depietri and McPhearson 2017). Ostrom (e.g., 1999, 2009) showed how institutions frame the use of natural resources and not least the distribution of benefits, making them highly relevant for understanding use and its influence on the system (see also, e.g., Webster 2002, 2007, Colding and Barthel 2013). Finally, perceptions include both urban residents’ appraisal (including value attribution, agency in the sense of recognition of opportunities offered by the combined GBI, infrastructure, and institutions) of and capacity (based on multiple individual factors such as age, preferences, socioeconomic circumstances, etc.) to use the system. We hold perception to be the basis for final realization of benefits (e.g., Pierskalla and Lee 1998, Chemero 2003, Spangenberg et al. 2014, Chan et al. 2016, Raymond et al. 2018). Perception also provides a more individual, actor-based perspective to balance the focus on more systemic properties and processes in the other two filters. All three are thus analytically relevant and, importantly, they all come with intervention tools (e.g., policy instruments) for changing the system.
If the overall effect of a filter or combination of filters is that it reduces the flow of benefits, it constitutes a barrier, e.g., insufficient funds among certain groups of potential visitors for paying entrance fees to an urban park (Wolff, Mascarenhas, Haase, et al., unpublished manuscript). If instead the filter supports or strengthens the flow of benefits, it forms an enabling factor. For example, extensive infrastructure for cycling and walking connecting parks to residential areas and business districts enables more people to visit and make use of the parks. Benefits differ in their nature and any of the three variables can manifest as an enabling factor for one benefit, while creating a barrier to others, meaning that the overall effect of a filter can be mixed (e.g., a fenced off-leash dog park). Different beneficiaries may also experience the effects differently, depending for example on socioeconomic circumstances or age.
Working with the flow of GBI benefits through the filters may thus include (1) revising or repurposing the structure or function of the urban infrastructure (e.g., introducing more green in densely built up areas, providing alternative transportation options for reaching different green or blue spaces, reducing space for private transportation/parking); (2) making changes in property rights and use regulations (e.g., changing ownership, introducing spatial or temporal zonation, adjusting regulations around use and mobility/transportation), and (3) engaging with perceptions (e.g., new narratives or processes that broaden, reframe, and challenge how we read and understand the city, which areas that can be used for what, by whom, how, and when; see, e.g., Marcus and Colding 2014).
The filters, like GBI itself, are exposed to external and internal drivers of change (e.g., Romice et al. 2018, Elmqvist et al. 2019), and a change in a filter is likely to have consequences for what benefits GBI can deliver and to whom these are accessible. Adapting to changes in the filters or actively changing them is essential for creating enabling contexts for realization of and distribution of GBI benefits (Fig. 1). We argue that the filters are fundamentally different in their dynamics and in which actors and processes can influence them in what ways. Hence, using the framework calls for flexible and adaptable mixed methods approaches that can tackle locally unique situations and decision making, differential access to information, and processes of deliberation (Andersson et al. 2021), as well as active involvement of multiple different actors that still allows for in-between case comparison (see Tables 1 and 2).
In line with the growing literature on resilience in practice (and in applied research) we recognize the need for frameworks and methodological approaches that support analyses of the roots of resilience and potential pathways for building or, when needed, reducing resilience (Sellberg et al. 2018; Fig. 2). Building on practice developed around participatory resilience assessments, we explored how the three filters framework can guide in-depth understanding of ES co-production and pathways for building resilience around flows of GBI benefits. Our approach follows a three-step knowledge process for assessing and building resilience around the flow of benefits from GBI: baseline systems understanding, understanding systemic change in relation to internal and external drivers, and building agency and formulating action strategies (Borgström et al. 2021).
Different theories and analytical approaches have been applied to describe, assess, and engage in transdisciplinary collaborations aimed at producing actionable knowledge. They include co-production or co-creation (e.g., Tengö et al. 2017, Norström et al. 2020, Turnhout et al. 2020, Cook et al. 2021), collaborative, inclusive, or participatory governance (e.g., Ansell and Gash 2008, Buijs et al. 2016), and collaborative planning (e.g., Healey 1998, Sirianni 2007). We primarily drew on the work on co-production to design our three cases, and took co-production to mean explicit involvement of individual citizens as well as organizational actors in the creation of (actionable) knowledge (more details on how we approached co-production can be found in Appendix 2). The application of the three filters framework was specific both to the case—three European cities, Halle, Barcelona, and Stockholm—and to each step in the process (Tables 1 and 2; see Andersson et al. 2021 for a more in-depth discussion of the flexible, multi-method designs) and presents an approach for context specific application in other cities.
In addition to the case specific objectives in terms of desired outcomes and which ES were in focus, guiding questions were (roughly in line with Resilience Alliance 2010, Enfors-Kautsky et al. 2018):
To capture these different aspects of filters and filtering, the three cases combined mixed methods designs weaving together deliberation with multiple other sources of information.
The higher the capacity to mobilize and synthesize knowledge and then apply it to find alternative pathways for realizing and maintaining flows of GBI benefits, the more resilient the system (Biggs et al. 2015). Thus, understanding the system in a way that helps you explore and test different answers to your questions is the first step in a resilience assessment. The filters framing in this first step helped identify and connect relevant system components and processes (Table 1), and thus provided a broad basis for understanding diversity and connectivity, two of the core components of resilience building (Biggs et al. 2015).
The Barcelona baseline assessment focused on greening policies, a central institutional instrument, complemented by consultation and literature studies. The assessment of the system descriptions and potential sources of ES resilience (loosely connected to a set of prioritized ES, see Table 1) in the policy documents built on Biggs et al.’s seven principles for building resilience (Biggs et al. 2012) in combination with the resilience definition in Elmqvist et al. (2019) and the three filters framework from Andersson et al. (2019). More explicitly, infrastructure was framed as urban morphology, physical connectivity, and mobility, institutions as planning approaches, governance arrangements, mandates, and normative context, and perceptions as recognition of human preferences and lifestyles. Perceptions were also analyzed in terms of how linkages between these (and other) aspects were made in the policy documents (see De Luca et al. 2021). The baseline assessment also identified demographic change, increased visitation (tourism), and global warming as the three most likely and imminent changes that would affect the use of GBI benefits.
Focusing on filters as barriers to access to and general recreational use of different green spaces, Halle took a spatially explicit approach to establishing the baseline system representation. The baseline was informed by existing ES model outcomes (Arnold et al. 2018, Gorn et al. 2018), interviews, and in-situ assessment of use and land use patterns. Most of the interviews were conducted through mental mapping survey (perceptions) about use or non-use of GBI (Haase et al. 2021), complemented by a wider literature-based exploration of reasons for not using GBI, including also infrastructural (physical) and institutional constraints to accessing GBI benefits. Based on this information a list and a geographical map of infrastructural (such as major roads or distance, fences), institutional (e.g., entrance fees or lack of sectoral collaboration and information exchange), and perceptual (e.g., negative images, user/beneficiary knowledge, and individual preferences) barriers were created (Barber et al. 2021, Wolff 2021; Wolff, Mascarenhas, Haase, et al., unpublished manuscript). Thus, in addition to the more direct barriers, the baseline study highlighted less recognized barriers like stigma and place identities or images (perceptions) as underlying drivers that shape GBI access and use.
To understand the role of filters as conduits/drivers of change and/or evaluative tools for connecting change to ES and benefit flows we argue that you need to include two different perspectives: external drivers of change and how they affect the filters and thus indirectly the flow of GBI benefits, and how the filters interact and influence each other. Involving diverse stakeholders in different scenario and modeling exercises offers opportunities to explore both alternative options and possibilities within a given filter setting and potential interventions or actions for changing the context itself (e.g., Pereira et al. 2019, Sellberg et al. 2020). Focusing on awareness and understanding of filters as slow variables and boundary conditions (sensu Biggs et al. 2015) and their role for co-created GBI benefits, Stockholm and Barcelona used researcher-led, collaborative co-creation approaches to scenarios for thoroughly discussing the implications of different types of more systemic changes. Complementing these, the Halle computational modeling approach to scenarios was more spatially explicit and primarily expert driven, focusing on land use change and modeling the outcomes of different change scenarios on GBI benefits (expressed in ES performance).
In Barcelona, the scenario approach was co-designed by the researchers and city level strategic planners while the scenario workshop itself involved a wider group of expert stakeholders (local NGOs, private consultancies, small enterprises, different levels and departments of public administrations, and academia). Scenarios were first used to assess and envisage changes in GBI capacity (infrastructure) and demand (perceptions) in terms of a set of prioritized ES. Four different trajectories of change were explored in parallel, each focusing on one of the identified drivers of change: (1) aging and shrinking population (with a strong infrastructure/mobility component), (2) increased tourism (with institutional implications), (3) gender inequalities (emphasizing perceptions), and (4) global warming. For each future scenario, participants were asked to assess potential changes in ES based on combination of the following factors: (1) increase/decrease in the number of users and relative awareness of benefits leading to higher/lower pressure on urban GBI, shift in ecosystem service demand; (2) increase/decrease in availability of urban GBI leading to lower/higher ecosystem service capacity.
Halle used a land use state/trend-based forecast modeling approach for developing spatially explicit scenarios, based on existing previous knowledge (Nilsson et al. 2014) and core competence of the researcher’s team. The model included expected demand for residential space (infrastructure), use of GBI and a range of benefits derived from GBI (perceptions and to some extent institutions). Policy targets, plans, and strategies were treated as institutional drivers of change (e.g., policy changes), including to the extent of the participants’ knowledge potential changes in user rights (e.g., privatization). The model development was informed by consulting the Urban Planning department (interviews with experts regarding expected developments and uncertainties [infrastructure and institutions], used to create or modify rules for the land use model) and local neighborhood initiatives and perspectives (through the baseline mental mapping study exploring physical accessibility and how this might be perceived by different users, Haase et al. 2021). The model focused on infrastructural and land use change as predicted by land use configuration and external drivers. The scenarios generated by the model used filters as the medium connecting more generic drivers of change to their implications for the access to GBI benefits. However, the scenarios were at the city scale of Halle, and at this coarse scale there was not enough information to include in-depth dynamics based on individual (residents) perceptions.
Based on the baseline information, the Stockholm research team selected four key drivers acting directly or indirectly through the three filters: (1) urban development (changes in infrastructure), (2) environmental and climate change, (3) forms of housing tenure (institutions and indirectly perceptions), and (4) governance organization and decision making (institutions). These served as the foundation for a facilitated participatory workshop designed to explore and build a joint understanding of what was changing in landscape and how the drivers of change interact and potentially shape the future provision of recreational benefits (Borgström et al. 2021). Substantial time was invested in adjusting and modifying the filters framing the process and its targets to accommodate for varying familiarity with systems thinking as well as establishing a language for connecting perceptions. The scenarios were described and evaluated in terms of changes in preconditions (including elements from all three filters) and their implications for nature-based recreational activities.
All three cases came to focus on slow changes and how to navigate long-term transitions, which may be a result of limited experiences with recent shocks or abrupt change (Borgström et al. 2021). The last step of the process focused on enabling factors that support current (or could support future) use of different ES afforded by GBI. To meet an overall increased demand for an uncertain supply of GBI benefits, the actions and measures discussed fall into two broad categories: (1) interventions aimed at increasing and sustaining current GBI infrastructures and measures that would improve access to GBI benefits for urban residents; and (2) alternative ways to make decision making and overall governance more resilient by involving stakeholders in different ways and better mobilize knowledge and resources.
Having the most specific objective and best fit between involved stakeholder mandates and the targeted decision making/policy formulation, Barcelona was the case that came closest to directly informing decisions. When asked to develop policy adaptations based on the identified shifts in provision and demand for different ES, workshop participants often proposed infrastructural and institutional measures connecting to policy sectors such as mobility, tourism, and health. Although the impact of ES on human health and well-being are at the center of many studies, identified measures in Barcelona also captured the need to better monitor long-term health benefits and the capacity of GBI to fulfil this need. The discussions triggered by the scenarios identified institutional connectors for integrating urban greening and planning with health, tourism, transport and mobility, education, and awareness. Although it is broadly recognized that urban planning decisions in sectors such as land use (e.g., Jennings et al. 2012, Hansen et al. 2015), transport and mobility (e.g., Cidell and Prytherch 2015), and tourism (e.g., Taff et al. 2019) have a strong impact on the GBI capacity to provide ES over time, the Barcelona case suggested that these changes also have an effect on ecosystem service demand, as they implicitly affect perceptions. However, workshop participants had few suggestions for how to engage with perceptions, possibly because this falls outside the usual ambit of strategic planning (De Luca et al. 2021).
In the Halle case, the outcomes of the study were twofold: First, the quantitative scenario outcomes provided input for a multifaceted discussion of how urban re-growth (primarily infrastructure) can be accomplished in a way that ensures the availability of GBI benefits at the district level. Second, the case highlighted how the identification of strategies for changing the current situation of GBI non-use at local scale, which is included in the city wide scenarios but not explicitly addressed, was hampered by perceived disempowerment and actors not seeing how they could make change happen. Here, scenario outcomes, while informative for science, appeared to be too coarse or general to support design or management decisions. Institutionally, there seems to be a gap between having power and mandate to influence infrastructure and formal institutions and the sensibility to recognize local perceptions and take specific action, a problem shared with the other two cases.
In the Stockholm case the final steps of the process concerned options for taking action based on a broadened understanding of the system, where the majority of the suggestions was about adaptations of present institutions, e.g., actors taking new roles, establishing collaborations and new rules, and securing capacity for continued dialogue across levels, sectors, and actors. The discussion lifted issues of how to use and connect existing, but fragmented knowledge, rather than monitoring or collecting additional information. Perceived lack of knowledge or agency (understood especially as limited access to decisions about infrastructure and institutions), possibly in combination with the Stockholm focus on capacity building rather than specific, bounded problems, kept discussions and strategies rather general. The discussions centered on governance and the different institutional processes and tools that could influence each, e.g., by urban planning as a decision-making process, institutions by new policies framing use or planning, or change in policy implementation, and peoples’ experienced benefits being the key target for the governance rather than specific actions or how these could be achieved.
One of the main challenges of complex systems and actively building or reducing specific resilience is to assess, catalogue, and connect diversity. The three filters framework can help actors identify and harness diversity, across SETS domains, by finding the linkages (thematic, policy, structures, actors, etc.) for connecting and aligning diversity relevant for different ES (as well as other “systemic” features). As the Barcelona and Stockholm cases show, a filter framed joint knowledge process for understanding the different preconditions and potential sources of GBI resilience can inform both potential solutions and clearly identify cases of, e.g., policy fragmentation or sectoral siloes. Our cases point to the need to understand connectivity also in less literal senses; beyond infrastructure there are institutional and perceptual linkages that are quite important for connecting different parts of a SETS, and taking action based on this understanding. A systems-based approach framed by the three filters offers both a foundation for developing and evaluating future scenarios and access to a broad suite of intervention options; especially infrastructure and institutions are two of the primary fields in policy and planning (Frantzeskaki et al. 2019, Pauleit et al. 2019). Understanding how the filters respond to internal and external stimuli and the implications of these often-interacting responses on ES generation and flows of benefits can help urban proactive planning and reflecting on long-term strategies; connecting different sources of diversity in new ways can open up opportunities to come up with alternative ways to do things (Buijs et al. 2016, Elmqvist et al. 2018b). Finally, the filters provide a language, or comparators (sensu Jacobs 2012), for joint learning, system exploration, and connecting visions and practices, within and between cases. Deliberations and joint exploration in Stockholm and Barcelona were especially helped by the filters as boundary or bridging concepts connected across interests, processes, and spheres. In Stockholm, recreational activities and their preconditions (e.g., user rights, facilities, knowledge, and capacities) served as a meaningful reference frame for the participants, whereas in Barcelona the use of broadly agreed on drivers of change helped connect the resilience thinking process to existing concepts and frameworks. Halle instead used infrastructure modeling as the starting point for comprehensively linking drivers of change with GBI-generated flows of benefits to beneficiaries to better be able to provide meaningful and accessible material for planned participatory processes integrated in the realization of the Master Plan of the town.
Existing governance processes and arrangements may be inadequate for navigating transformative change, or when interactive effects of filters undergoing change start to affect the flow of GBI benefits (Borgström 2019). Thus, even when filter settings are enabling flows of GBI benefits one might be interested in alternatives that better fit multiple ambitions and targets (Table 3). In the Stockholm case, for example, using and slightly repurposing stronger institutional instruments (e.g., designating areas to different types of formal protection, mainstreaming ES) is an active strategy for safeguarding at least core elements of the GBI. Beyond these basic principles, the actual factors to include will need to be decided by the case (see De Luca et al. 2021). One of the advantages of applying the three filters framework in different deliberative joint learning processes dedicated to understanding how the system works and anticipating future change is that it actively engages with perceptions and understandings of the stakeholders involved. This engagement helps strengthen the capacity to understand and use the current system in different or alternative ways, and to build the agency needed to get involved with changing infrastructures and institutions (e.g., Colding and Barthel 2013, Sellberg et al. 2018). This approach also offers an entry point for in-depth engagement with equity and justice issues (Langemeyer and Connolly 2020). According to the participants’ evaluations (Stockholm), an added benefit (and important contribution to the capacity to engage in resilience building along with the systems understanding) was the opportunity to make new contacts, and the process was found to fill an experienced lack of platforms for such system wide exchanges. The conclusion from our cases is that the joint learning started through a resilience thinking process must move back and forth between specific aspects of the filters and the broader systems understanding of how the filters fit together and how they jointly influence the flows of GBI benefits.
Our study shows that perceptions, as inherent parts of the system as well as a key actor attribute, need to be more explicitly woven into urban resilience work. Our studies clearly show the transformative and potentially enabling power of perceptions. Perceptions of, for example, the attractiveness of GBI elements are often quite volatile—in Barcelona a few crime events shifted the accessibility/safety perceptions of one of the largest urban parks within weeks. On the other hand, overall understanding of the system and how you can engage with it both as a user and a decision maker/manager is a slower process, and one that needs to be continuously nurtured (in the sense of weaving types of knowledge, Tengö et al. 2017). Yet, the readiness to anticipate change in and engage with the filters follows the opposite pattern. For infrastructure and institutions, it is relatively clear what is required/should be done to implement changes, and who could implement the changes. For perceptions, this seems to be much more complex or at least fuzzy.
In all cases, especially Barcelona and Stockholm, the stakeholders found it difficult to imagine “business as (un)usual” futures and to think outside their boxes of everyday practice and imagine potential radical future changes. The perceptions of the respective cities were in many ways quite static, especially concerning the built components and the institutions. At a fundamental level, the cases point to the need to think more about preparing also for more unlikely futures and discuss the interactions of multiple drivers of change. Similar to what other studies have shown (e.g., Borgström et al. 2006, Cumming et al. 2015), our cases also demonstrated the combined challenge of cross scale interactions and sectoral fragmentation when interventions normally take the form of interdependent tasks (as described by, e.g., Bodin and Nohrstedt 2016). Objectives that may seem closely connected from a scientific perspective may require very different processes (and actors) to be implemented (for an in-depth discussion about the participatory co-creation processes see De Luca et al. 2021 and Borgström et al. 2021).
Strong path dependency or resilience of enabling factors for flows of GBI benefits would, from the perspective of this study, be something positive. However, because the filters may also function as barriers, filter resilience can be an undesirable feature. Undesirable resilience, often called lock-in or a trap, can be understood as cases when filters, acting as barriers, resist desired change or constrain the range of alternative configurations (e.g., Walker 2000, Boonstra and De Boer 2014, Tidball et al. 2016). In Stockholm, for example, formal institutions, especially around urban planning, were perceived as quite limiting (and hard to change) in what they allow and what kind of involvement in planning processes they support (Borgström et al. 2021). In an extended discussion about system inertia, Stedman (2016) contended that constructs such as system identity, stability and changes, are subjectively perceived, and acted upon by the social actors that occupy these systems, but that the lack of recognition of this subjectivity has itself become a “rigidity trap.” In Halle, persistent negative perceptions and the existence of other, more attractive options for accessing GBI benefits at larger but still manageable scales, were identified as one of the main barriers to why local GBI potential was not realized within residents’ own neighborhoods. This negative impression, or sometimes just unrecognized opportunity, we believe is partly connected to a feeling of marginalization and not being part of decision making. The experience from Halle was that lacking capacity and trust, together with very specific and therefore limited interest, across scales and sectors, obstructed both the development of a shared problem understanding and the identification of actionable strategies for addressing the problems.
Perceived or real, the literature on institutional traps describes them as created and reinforced by mechanisms of optimization, set identities and communities of practice and learning, and cultural inertia (e.g., Azariadis and Stachurski 2005). In terms of the learning process itself, rather than its outcomes, our three cases demonstrated institutional (and perhaps perceptual) constraints to what could be accepted as a legitimate process design. Our interpretation is that this was based on an institutional memory of (1) how decision making and deliberate processes are usually organized and how targets (relevant to our processes) are framed (governance traditions in each city), and (2) participant experiences of earlier co-creation or collaborative processes. As a consequence, we experienced some restrictions as to how we could discuss resilience, which strategies and solutions they were interested in exploring, and which of these that might actually be feasible without larger transformations of the system.
Cities, with their deep embodiment of human ideas and activities, highlight some of the fundamental aspects of the Anthropocene where human impacts are felt in every corner of the world. The three filters framework describing cities in terms of physical infrastructure, societal institutions, and human perceptions and capacities is a powerful tool for understanding and engaging with urban SETS. It is also a starting point for directly engaging with perceptions. However, although universally applicable in general terms, the three filters framework needs to be adapted and fitted to local contexts and case specific needs. The three step learning process described in this article (Fig. 2)—system mapping, system dynamics, alternative futures and finding resilient strategies for change—offer a pathway for tackling urban complexity and operationalizing resilience thinking for building capacity and agency needed to take action. It is a process that enables stakeholders to widen their perspective of the GBI including more different activities, being part of a changing landscape, and also reflecting on their present and potential role as individual and collective stakeholders in that landscape.
To achieve this, approaches that employ resilience thinking need to keep adjusting to both local normative goals, as well as the broader dynamics of the SETS that constrains or enables progress to achieve them. Our cases show how the filters framework can guide joint learning processes, and how specific meanings and interpretations of the filters and their effects evolve with the learning process. The three cases show, first, how the filters framework can be used to assess current flows of different GBI benefits and map out different SETS characteristics and context-sensitive configurations that may offer alternative ways of enabling benefit flows. Second, with their central role in mediating flows of benefits from GBI, the filters provide a key component for scenario or model building. Finally, focusing on the filters and their interactions serves as an entry point for discussing how different actors can contribute to making flows of benefits more resilient. To make the action strategies realistic a deep understanding of the filters themselves, their dynamics, resilience, and potential levers, is essential, and that all actors with influence over the three filters share this understanding. Although the primary focus of this paper was the resilience of flows of GBI benefits, our results point to the need for future studies to position this specific resilience as embedded in the resilience or changeability of the three filters.
This research was funded through the 2015-2016 BiodivERsA COFUND call for research proposals, with the national funders the Swedish Research Council for Environment, Agricultural Sciences, and Spatial Planning; the Swedish Environmental Protection Agency; the German Aerospace Center; the National Science Centre (Poland; grant no. 2016/22/Z/NZ8/00003); the Research Council of Norway; and the Spanish Ministry of Economy and Competitiveness. EA’s and SB’s participation was additionally supported by Formas project number 2015-00734. SB’s participation was additionally supported by the School of Architecture and Built Environment at the Royal Institute of Technology, in Stockholm, Sweden. JL acknowledges support from the ERC Consolidator Grant 818002-URBAG. TM’s participation was additionally supported by the U.S. National Science Foundation through grants #1444755, #1927167, and #1934933.
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