From social-ecological to social-ecological-technological systems (SETS)

Cities depend on technological and built infrastructure, such as electric power, water supply, and transportation networks, that sustain flows of resources over large distances. The emerging patterns of urbanization, including urban corridors and mega-regions, are driven by a complex mix of social and ecological-biophysical drivers along with the evolution of technology and infrastructure. Advancing the conceptual frameworks of urban ecology to understand complex dynamics of urbanization requires representing the built and technological infrastructure in urban systems more explicitly (Cadenasso et al. 2006; Ramaswami et al. 2012).

The built infrastructure is central to a city, and has been acknowledged previously in some urban ecological studies (Pickett et al. 2001; Alberti 2008; Cadenasso et al. 2006), but is often overlooked. More predominant in the field of urban ecology is the systems approach linking social and natural-ecological sciences (Grove et al. 2006; Collins et al. 2011). A key challenge to integrating the built, technological infrastructure into urban ecological science is expanding to include additional disciplinary perspectives, theories, methods, and data. To achieve this, urban ecology' must expand the conceptual framing to social—ecological—technological systems (SETS) and explicitly acknowledge the role of technology, engineering, and the urban built infrastructure (Figure 5.2; Redman and Miller 2015; Grimm et al. 2016; McPhearson et al. 2016a, 2016b). The SETS framing offers an inclusive urban science that accounts for interacting urban priorities of policy- and decision-makers from diverse sectors (McPhearson et al. 2016c; Acuto et al. 2018).

The integrated engineering and ecological solutions essential for urban planning and management may enhance future urban resilience to climate change and other global environmental changes. Ecological-based designs integrating green and gray infrastructure are often more flexible, diverse in features, and can be more ‘safe-to-faif. ‘Safe-to-fail’solutions are designed to allow for controlled failure (e.g. the planned flooding of a community greenspace rather than a residential neighborhood) that minimizes the consequences of failure. On the other hand, built, highly engineered infrastructure (e.g. a flood levee) is often the first line of defense for natural hazards

The SETS conceptual framework exemplified by the interacting social—behavioral, ecological-biophysical, and technological—infrastructural domains of urban systems

Figure 5.2 The SETS conceptual framework exemplified by the interacting social—behavioral, ecological-biophysical, and technological—infrastructural domains of urban systems

Source: Adapted from Depietri and McPhearson (2017) and designed to be ‘fail-safe’. Fail-safe infrastructure has a low probability of failure but significant consequences upon failure in extreme weather-related events. However, as urban infrastructure ages and the climate continues to change with more frequent and extreme weather-related events, the engineered fail-safe designs often require significant investment and increased capacity to keep up with demands of expanding populations. While growing cities have the opportunity to construct new infrastructure, it is often done with little consideration of ecologically based design or future needs (McHale et al. 2015). Ecologically-based hybrid gray-green infrastructure, with its capacity to provide multi-functional urban ecosystem services (Gomez-Baggethun and Barton 2013; Grimm et al. 2016; Kabisch et al. 2017), underscores the importance of integrating ecosystems and the SETS approach in urban management and planning.

Advancing urban systems science in urban ecology

As societies become more globalized, planning cities to be inclusive, safe, sustainable, and resilient is often an elusive United Nations Sustainable Development Goal. Urban systems science remains fragmented and disconnected from global and local policy (McPhearson et al. 2016c; Acuto et al. 2018). This disconnect further highlights the need for new tools and data to advance understanding of complex urban dynamics and to support decisionmaking for sustainability transformations. To capture the growing complexity of SETS interactions in cities, we must look to new data sources and innovative tools to capture transdisciplinary knowledge and decision-making needs to improve future urban sustainability and resilience.

The rise of ‘big data’

With ‘big data’, new information and communications technology' (ICT), and the Internet of Things (loT), there is seemingly endless potential for innovation and exploring data in complex urban systems (Ilieva and McPhearson 2018). Nearly real-time dynamic observations of the Earth’s systems, including people’s behaviors and what they value, can be examined with data across spatial scales — within a property, a city, a region, or globally (Figure 5.3). The use of new and massive data streams is a potential game changer in applying a SETS approach to urban ecology in, of, and for cities. This opportunity is perhaps especially relevant for evaluating progress and setting targets to achieve sustainability planning and policy toward the SDGs.

As a growing, publicly available data source, social media data (SMD) has rapidly become a novel opportunity for city planners and engineers around the globe. Innovative uses of SMD from Twitter, Instagram, and Flickr have steadily grown in many fields. For example, SMD fills spatial and temporal data gaps affecting traditional social science data (e.g. the US Census) in urban ecological research (Ilieva and McPhearson 2018). However, use of SMD in urban ecological studies is still rare (but see Hamstead et al. 2018).

While SMD and other big data offer boundless opportunities, they will not solve all data needs for advancing urban sustainability. Big data has potential, however, to play a strong part in generating new hypotheses that can be assessed with temporally and spatially rich data streams. Geo-located SMD can complement other traditional forms of data collection to understand people’s activities, behavior, and perceptions about particular places or ecosystem services in nature (Wood et al. 2013) and in cities (Hamstead et al. 2018). With these advances in mind, SMD offers new opportunities for future research on the long-term ecology of and for cities.

Evolution of big-data sources and technologies and the rise of social-media data

Figure 5.3 Evolution of big-data sources and technologies and the rise of social-media data. The evolving data landscape over the past few decades demonstrates the increasing availability of location-based social, infrastructural, and biophysical data. Temporally and spatially explicit high resolution data availability is key to tracking global SDGs and local targets in urban-sustainability plans

Source: Adapted from Ilieva and McPhearson (2018)

New tools for urban complexity research

To advance sustainability and resilience solutions for and with cities, continued development of analytical methods and integration of transdisciplinary approaches in urban ecology will be required. Further research is needed to advance new analytical approaches that integrate SMD and similar novel data streams into wider use in research. New computing and modeling power linked to high resolution social—ecological data provides yet unknown opportunities for advancing our understanding of urban SETS. For example, machine learning provides powerful techniques for the analysis of big data. With the mainstreaming of data collection and data sharing, machine learning can exploit multi-dimensional, complex datasets, automate computation, find undetected synergies, and promote knowledge sharing to advance innovation and solutions across broad scales and scopes (Creutzig et al. 2019). Powerful machine learning techniques, such as neural networks, can be used to reduce complexity in order to understand the drivers of complex urban systems (Hinton and Salakhutdinov 2006). For example, convolutional neural networks can characterize and investigate land-use change, which is especially useful for urban development and urban landscape ecology (Krizhevsky et al. 2012; Castelluccio et al. 2015).

Ethics and governance of big data

Since much of the emerging big data is publicly available, it will be essential to ensure the responsible governance and use of these data. As smart technologies and modeling innovations advance, it is imperative: that data remain open access; that ethical concerns about data sourcing are addressed and acknowledged; and the politics of who generates versus who uses data are taken into account. For example, researchers must acknowledge the constraints, assumptions, and potential to perpetuate biases using data from communities with which they are not integrated. Moreover, ethical concerns about the privacy of social media users are becoming increasingly prominent. If the SMD is not used and shared carefully in collaborative projects, users’ private information may be unintentionally disclosed without their consent (Ilieva and McPhearson 2018; Creutzig et al. 2019). Effective guidelines, practices, and governance have to be established and agreed upon to prevent unethical use of social media and other publicly available big data in urban ecology research.

Participatory planning and urban futures

A stronger urban systems science requires the integration of research and policy not only across diverse academic disciplines including the humanities, but also through inclusive engagement, co-production of knowledge, and participatory planning with politicians, communities, and practitioners (Schwarz and Herrmann 2016; Acuto et al. 2018; Advisory Committee for Environmental Research and Education 2018). Co-production will be essential in implementing sustainability policies that are relevant to and reflect the values of those most impacted (Miller and Wyborn 2018).

To assess the barriers and goals for future urban sustainability and resilience, scenario codevelopment is one method and tool to integrate collective knowledge and collaboratively co-develop positive visions for the future. Scenarios are plausible narratives or visions about the future of a place or a situation that can richly describe social—ecological—technological systems from diverse perspectives (Iwaniec et al. 2014; Millennium Ecosystem Assessment 2005). Moreover, scenario co-development often engages with under-represented stakeholders (i.e.

marginalized and vulnerable citizens) in planning. Thus, the process creates opportunities to think beyond the current constraints and dominant ideas, and to envision innovative, equitable solutions to future challenges (McPhearson et al. 2017). Pluralism is imperative for advancing innovative, equitable solutions for the long-term future through actionable ecology for and with cities science.

 
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