The speed and uncertainty of environmental change in the Anthropocene challenge the capacity of coevolving social–ecological–technological systems (SETs) to adapt or transform to these changes. Formal government and legal structures further constrain the adaptive capacity of our SETs. However, new, self-organized forms of adaptive governance are emerging at multiple scales in natural resource-based SETs. Adaptive governance involves the private and public sectors as well as formal and informal institutions, self-organized to fill governance gaps in the traditional roles of states. While new governance forms are emerging, they are not yet doing so rapidly enough to match the pace of environmental change. Furthermore, they do not yet possess the legitimacy or capacity needed to address disparities between the winners and losers from change. These emergent forms of adaptive governance appear to be particularly effective in managing complexity. We explore governance and SETs as coevolving complex systems, focusing on legal systems to understand the potential pathways and obstacles to equitable adaptation. We explore how governments may facilitate the emergence of adaptive governance and promote legitimacy in both the process of governance despite the involvement of nonstate actors, and its adherence to democratic values of equity and justice. To manage the contextual nature of the results of change in complex systems, we propose the establishment of long-term study initiatives for the coproduction of knowledge, to accelerate learning and synergize interactions between science and governance and to foster public science and epistemic communities dedicated to navigating transitions to more just, sustainable, and resilient futures.

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Vicky Chuqiao Yang, Mirta Galesic, Harvey McGuinness, and Ani Harutyunyan
PNAS August 31, 2021 118 (35) e2106292118;

In collective decision-making systems, such as committees and governments, many individuals follow others instead of evaluating the options on their own. Can a group settle on the option with higher merit when social learners prevail? Previous research has reached mixed conclusions because collective decisions emerge from a complex interaction of cognitive and social factors, which are rarely studied together. This paper develops a simple yet general mathematical framework to study this interaction and predicts a critical threshold for the proportion of social learners, above which an option may prevail regardless of its merit. The results suggest predictable limits to the proportion of social learners in collective situations from teamwork to democratic elections, beyond which the collective performance is affected negatively.

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Surendra Hazarie, David Soriano-Paños, Alex Arenas, Jesús Gómez-Gardeñes & Gourab Ghoshal 
Communications Physics volume 4, Article number: 191 (2021)

The increasing agglomeration of people in dense urban areas coupled with the existence of efficient modes of transportation connecting such centers, make cities particularly vulnerable to the spread of epidemics. Here we develop a data-driven approach combines with a meta-population modeling to capture the interplay between population density, mobility and epidemic spreading. We study 163 cities, chosen from four different continents, and report a global trend where the epidemic risk induced by human mobility increases consistently in those cities where mobility flows are predominantly between high population density centers. We apply our framework to the spread of SARS-CoV-2 in the United States, providing a plausible explanation for the observed heterogeneity in the spreading process across cities. Based on this insight, we propose realistic mitigation strategies (less severe than lockdowns), based on modifying the mobility in cities. Our results suggest that an optimal control strategy involves an asymmetric policy that restricts flows entering the most vulnerable areas but allowing residents to continue their usual mobility patterns.

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Evo Busseniers,Tomas Veloz, and Francis Heylighen

Entropy 2021, 23(8), 1039

In this article, we attempt at developing a scenario for the self-organization of goal-directed systems out of networks of (chemical) reactions. Related scenarios have been proposed to explain the origin of life starting from autocatalytic sets, but these sets tend to be too unstable and dependent on their environment to maintain. We apply instead a framework called Chemical Organization Theory (COT), which shows mathematically under which conditions reaction networks are able to form self-maintaining, autopoietic organizations. We introduce the concepts of perturbation, action, and goal based on an operationalization of the notion of change developed within COT. Next, we incorporate the latter with notions native to the theory of cybernetics aimed to explain goal directedness: reference levels and negative feedback among others. To test and refine these theoretical results, we present some examples that illustrate our approach. We finally discuss how this could result in a realistic, step-by-step scenario for the evolution of goal directedness, thus providing a theoretical solution to the age-old question of the origins of purpose.

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