Food System Sustainability Metrics: Policies, Quantification, and the Role of Complexity Sciences

The rise of global attention toward sustainability and sustainable development (SD) has provided increased incentives for research development and investment in these areas. Food systems are at the center of human needs and global population growth sustainability concerns. These drives and the need to provide quantified support for related investment projects led to the proliferation of sustainability metrics and frameworks. While questions about sustainability definition and measurement still abound, SD policy design and control increasingly need adequate quantified support instruments. This paper aims to address this need, contributing to a more consistent and integrated application of food system sustainability metrics and quantified management of the implemented solutions. After presenting the relationships between sustainability, resilience, and robustness and summarizing food system sustainability quantification developments so far, we expose complexity sciences’ potential contributions toward SD quantified evaluation, addressing prediction, intangibles, and uncertainty issues. Finding a paramount need to make sense and bring existing sustainability metrics in context for operational use, we conclude that the articulated application of multiple and independent modeling approaches at the micro, meso, and macro levels can better help the development of food SD policies and implemented solution quantified management, with due regard to confidence levels of the results obtained.

Complexity Sciences

Social scientists have proposed several concepts to give account of the way scientific life organizes. By studying “complexity sciences” – established in the mid-1980s by the “Santa Fe Institute” in New Mexico (USA) –, the present article addresses to interdisciplinary studies and emergent domains literature by proposing a new concept to describe this domain. Drawing from Bourdieusian sociology of science and STS, a “scientific platform” is defined as a meeting point between different specialties, which, on the basis of a flexible common ground, pursue together shared or parallel socio-epistemic objectives. Most of the specialties inscribed in complexity suffer from a relative marginality in their disciplinary field. The term “platform” refers to what the heterogeneous members of the collective mutualize, both in cognitive and social terms, in order to exist and expand.

Regimes of Evidence in Complexity Sciences

Since their inception in the 1980s, complexity sciences have been described as a revolutionary new domain of research. By describing some of the practices and assumptions of its representatives, the present article shows that this field is an association of subdisciplines laying on existing disciplinary footholds. The general question guiding us here is: On what basis do complexity scientists consider their inquiry methods and results as valuable? To answer it, I describe five “epistemic argumentative regimes,” namely the ways in which complexity scientists argue the credibility of their research, and five “ontological views,” that is the ways in which they interpret the material and formal causes of their study objects and models. Finally, the article proposes the term of “regime of evidence” to designate the specific combination of one ontological view with one or more epistemic argumentative regimes.

Extremism, violence, and mind: Apprehending the super-complex

In this concluding chapter we review the key concepts and emergent research and practice domains for future investigation. We consider the shift from simple to complicated, complex, and super-complexity sciences as the foundation for future interdisciplinary research and practice, and synthesize the contributions in this chapter towards a future agenda.

The failed institutionalization of “complexity science”: A focus on the Santa Fe Institute’s legitimization strategy

“Complexity sciences” are an interdisciplinary and transnational domain of study that aims at modeling natural and social “complex systems.” They appeared in the 1970s in Europe and the United States, but were boosted in the mid-1980s by the Santa Fe Institute (SFI) under the formula of “science of complexity.” This small but famous institution is the object of the present article. According to their promissory ambitions and to the enthusiastic claims of some scientific journalists, complexity sciences were going to revolutionize all of knowledge and even private and public actors who had learned to master them. In the light of this, one would expect to observe a well-established and autonomous research and educational field, capable of reproducing itself through professional institutions. Yet this is not the case. To explain the paradox, I propose to combine different models of history and sociology of emergent and declining domains, in order to give account of the rise and failure of complexity sciences.

Complejidad en clave docente

There are different perspectives of the complexity sciences (CC) and the complex. A large part of the academic community of the social sciences is the same synonymous with uncertainty (Wallerstein, 2005), for other thinkers related to a literary perspective the matter a form of thought (Morin, 2005). Other views take into account the CC as an area that causes problems related to the study of the social with an innumerable range of impacts (Reynoso, 2016). This writing part of the reflection was carried out during the development of a social science research (Luján, 2016). Epistemological debt in the sense of explaining the task of understanding the aspects of covering complexity beyond the usual jargon in the concepts of non-linearity, self-organization, fractals and complex networks, among others.

Addressing Urban Sprawl from the Complexity Sciences

Urban sprawl is nowadays a pervasive topic that is subject of a contentious debate among planners and researchers, who still fail to reach consensual solutions. This paper reviews controversies of the sprawl debate and argues that they owe to a failure of the employed methods to appraise its complexity, especially the notion that urban form emerges from multiple overlapping interactions between households, firms and governmental bodies. To address such issues, this review focuses on recent approaches to study urban spatial dynamics from the perspective of the complexity sciences. Firstly, spatial metrics from landscape ecology provide means of quantifying urban sprawl in terms of increasing fragmentation and diversity of land use patches. Secondly, cellular automata and agent-based models suggest that the prevalence of urban sprawl and fragmentation at the urban fringe emerge from negative spatial interaction between residential agents, which seem accentuated as the agent’s preferences become more heterogeneous. Then, the review turns to practical applications that employ such models to spatially inform urban planning and assess future scenarios. A concluding discussion summarizes potential contributions to the debate on urban sprawl as well as some epistemological implications.