ARTE DE ECHAR Y ADIVINAR POR MEDIO DE LAS CARTAS ( Cartomancia)

. The hypothesis put forward is that both approaches may be complementary since they look at cities from different angles, where economic and socio-institutional dynamics (from global to local individual level) inevitably play a central role. In order to address concerns as to the future sustainability of cities, socio- ecological change must embrace socio-technical change and vice versa in a context of global development. Consequently, integrated approaches which consider insights from both fields of research are required.

Cities and urban networks in this dissertation are seen as complex socio-ecological systems. It is therefore that complexity gains a relevant role in this work.

Complexity starts with the definition of the urban area itself. Satterthwaite (2011) asserts that there is no widely accepted definition for an urban area or for a city; that assertions attributing population or consumption data to cities are often incorrect due to definition divergences. Urban areas vary in size, domestic economy, urbanisation patterns, etc. These differences are frequently influenced by geo-political needs, history and cultural heritage among other factors. Together with lifestyle patterns, they determine to a large extent the energy and material consumption levels that can be credited to urban areas. Urban areas that are undergoing shrinkage or expansion face different challenges which affect the urban development strategies and the resources available to support them. Even when the huge divergences in cities’ social, ecological, economic and institutional resources and their stages of development are acknowledged, not all cities are equally complex. Given that the challenges and targets regarding sustainability and resilience in cities are context-dependant, this dissertation addresses the problem in ordinary medium-

7 _{See Chapter 2, p. 33} 8 _{See Chapter 3, p. 69}

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sized9

Cities and the systems of cities can be understood as bringing together human and natural complex nested systems (Liu et al. 2007a; Ernstson et al. 2010b). This view is required to encapsulate the dynamics of the following three dimensions: (i) natural biophysical processes and metabolic flows generated by the demands of urban users; (ii) the effects on human wellbeing of changes in the flow of ecosystem and human services; and (iii) the gradual reactive socio-technical and economic adjustment of cities to shifts in their contextual landscape such as those that may arise in the context of global economic and environmental change.

cities with less than 500,000 inhabitants. Such cities currently house 50 per cent of the world’s urban population (see Fig. 1.1), and are therefore crucial for future urban development. Capacity for intervention in these cities may often be limited due, for example, to rigid governance structures, resource dependency, lack of social cohesion, strong historically unsustainable patterns or geographic and spatial constraints. Changes in technological, social and economic patterns would therefore be needed to jointly face resource scarcity constraints, population dynamics (growth or shrinkage) and climate change challenges.

From this point of view it is important to discuss what it means to understand a city as a system. In the context of complexity thinking and systems theory, cities are often observed as complex adaptive systems (hereafter CAS) (see e.g. Alberti et al. 2003; Ernstson et al. 2010b), similar to ecosystems themselves.

The concept of CAS has a certain level of abstraction and is understood differently by mathematics and physicists and by biologists. The most important characteristics of CAS that arise from both understandings is that complexity may be hidden in a very simple system, and that complex global systems patterns may emerge from interactions at local

9 _{Depending on the context, cities can be classified as small, medium, large or extra-large. Cities of less}

than 500,000 people are defined as small according to the UN (2012a). In the context of Europe, the OECD (Dijkstra and Poelman 2012) defines cities of less than 500,000 inhabitants as ranging from small (between 50,000 and 100,000) to large (between 250,000 and 500,000). From now on, we use the term ‘medium- sized cities’ to define cities of less than 500,000 inhabitants.

1 . I n t r o d u c t i o n

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level (called emergence) (Lansing 2003). Also, the property of self-organization that characterises CAS is relevant for our discussion. In this context, CAS evolve through four phases of transformation: conservation (K), release or collapse phase (Ω), reorgani zation or renewal phase (α), and exploitation or consolidation phase (r) (Holling 1986). A new

conservation phase starts again forming what is understood as the adaptive cycle10

As CAS, cities are seen as microstructures that gather forming systems of cities that work better and adapt in better conditions as a macrostructure rather than individually. Therefore, when urban areas are understood as social and ecological complex and adaptive co-evolving systems, the scale of the social network becomes relevant, especially regarding its energy, material and information flows. Any city is part of a ‘system of cities’ which gives rise to particular cross-scale interactions between the technical and social networks that tie urban areas together and sustain those energy, material and information flows (Ernstson et al. 2010b).

.

For this reason, focusing on the local (administrative) scale has its pitfalls, as it fails to take account of cross-scaling feedbacks from urban areas, given the globalisation of resource provision. As argued above, urban areas are not self-sufficient, sustainable units (Rees and Wackernagel 1996; UNU/IAS 2003b), and the ES provision on which they depend is often on a scale that extends well beyond the urban administrative boundaries where local interventions take place. Likewise, the environmental impacts of urban activities cannot be considered as contained within those boundaries. This makes the analysis of cities challenging, especially since they operate as open systems from the viewpoint of metabolism (Grimm and Redman 2004). These system dynamics cause the complexity which characterise urban areas presenting multiple challenges to decision- makers and therefore to those that aim at studying urban change (see Grimm et al. 2000; Pickett et al. 2001).

In line with the above, and recognising the social and environmental challenges that cities need to deal with, Prasad (2009) asserts that the new operational tools need to be provided to support long-term urban decision-making if global environmental change is

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to be tackled. This is partly translated into analytical frameworks to help understand the complexity of the interdependencies in ecological, social and economical systems across scales and time which could help forecast and avoid unintended effects (Holling 2001; Kinzig et al. 2006). This dissertation attempts to fill this gap from a conceptual and empirical point of view, by the use of innovative approaches that recognise such interdependencies.