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We must exploit socioeconomic tipping points and amplifiers Conventional approaches to mitigating climate change are not working. Despite the actions pledged under the 2015 Paris Agreement, actual progress is falling well short ( 1 ). Given limited time and resources, traditional efforts such as the climate stabilization wedge approach ( 2 ) are unlikely to be effective on their own. Physical science has shown how complex adaptive systems can cross critical thresholds (“tipping points”) ( 3 ), such that a relatively small change can trigger a larger change that becomes irreversible ( 4 ), where nonlinear feedback effects act as amplifiers ( 5 ). We propose to examine how to exploit similar sensitive intervention points (SIPs) and amplification mechanisms in socioeconomic, technological, and political systems to advance climate change mitigation. We focus on research and policies in which an intervention kicks or shifts the system so that the initial change is amplified by feedback effects that deliver outsized impact.

The level of antagonism between political groups has risen in the past years. Supporters of a given party increasingly dislike members of the opposing group and avoid intergroup interactions, leading to homophilic social networks. While new connections offline are driven largely by human decisions, new connections on online social platforms are intermediated by link recommendation algorithms, e.g., “People you may know” or “Whom to follow” suggestions. The long-term impacts of link recommendation in polarization are unclear, particularly as exposure to opposing viewpoints has a dual effect: Connections with out-group members can lead to opinion convergence and prevent group polarization or further separate opinions. Here, we provide a complex adaptive–systems perspective on the effects of link recommendation algorithms. While several models justify polarization through rewiring based on opinion similarity, here we explain it through rewiring grounded in structural similarity—defined as similarity based on network properties. We observe that preferentially establishing links with structurally similar nodes (i.e., sharing many neighbors) results in network topologies that are amenable to opinion polarization. Hence, polarization occurs not because of a desire to shield oneself from disagreeable attitudes but, instead, due to the creation of inadvertent echo chambers. When networks are composed of nodes that react differently to out-group contacts, either converging or polarizing, we find that connecting structurally dissimilar nodes moderates opinions. Overall, our study sheds light on the impacts of social-network algorithms and unveils avenues to steer dynamics of radicalization and polarization in online social networks.

Biological living materials, such as animal bones and plant stems, are able to self-heal, regenerate, adapt and make decisions under environmental pressures. Despite recent successful efforts to imbue synthetic materials with some of these remarkable functionalities, many emerging properties of complex adaptive systems found in biology remain unexplored in engineered living materials. Here, we describe a three-dimensional printing approach that harnesses the emerging properties of fungal mycelia to create living complex materials that self-repair, regenerate and adapt to the environment while fulfilling an engineering function. Hydrogels loaded with the fungus Ganoderma lucidum are three-dimensionally printed into lattice architectures to enable mycelial growth in a balanced exploration and exploitation pattern that simultaneously promotes colonization of the gel and bridging of air gaps. To illustrate the potential of such mycelium-based living complex materials, we three-dimensionally print a robotic skin that is mechanically robust, self-cleaning and able to autonomously regenerate after damage.Complex living structures with self-healing and regeneration capabilities are 3D printed using bioinks composed of fungal mycelium and an agar-based hydrogel.

The study of social-ecological systems (SES) has been significantly shaped by insights from research on complex adaptive systems (CAS). We offer a brief overview of the conceptual integration of CAS research and its implications for the advancement of SES studies and methods. We propose a conceptual typology of six organizing principles of CAS based on a comparison of leading scholars’ classifications of CAS features and properties. This typology clusters together similar underlying organizing principles of the features and attributes of CAS, and serves as a heuristic framework for identifying methods and approaches that account for the key features of SES. These principles can help identify appropriate methods and approaches for studying SES. We discuss three main implications of studying and engaging with SES as CAS. First, there needs to be a shift in focus when studying the dynamics and interactions in SES, to better capture the nature of the organizing principles that characterize SES behavior. Second, realizing that the nature of the intertwined social-ecological relations is complex has real consequences for how we choose methods and practical approaches for observing and studying SES interactions. Third, engagement with SES as CAS poses normative challenges for problem-oriented researchers and practitioners taking on real-world challenges.

Water scarcity is dynamic and complex, emerging from the combined influences of climate change, basin-level water resources, and managed systems’ adaptive capacities. Beyond geophysical stressors and responses, it is critical to also consider how multi-sector, multi-scale economic teleconnections mitigate or exacerbate water shortages. Here, we contribute a global-to-basin-scale exploratory analysis of potential water scarcity impacts by linking a global human-Earth system model, a global hydrologic model, and a metric for the loss of economic surplus due to resource shortages. We find that, dependent on scenario assumptions, major hydrologic basins can experience strongly positive or strongly negative economic impacts due to global trade dynamics and market adaptations to regional scarcity. In many cases, market adaptation profoundly magnifies economic uncertainty relative to hydrologic uncertainty. Our analysis finds that impactful scenarios are often combinations of standard scenarios, showcasing that planners cannot presume drivers of uncertainty in complex adaptive systems. The impacts of water scarcity depend on physical basin characteristics and global economic dynamics. Here, the authors show scenario assumptions can yield either highly positive or negative economic impacts due to water scarcity, and the drivers of these impacts are basin-specific and cannot be determined a priori.

Purpose - The purpose of this paper is to advance supply chain network theory by applying theoretical and empirical developments in complex network literature to the context of supply chains as complex adaptive systems. The authors synthesize these advancements to gain an understanding of the network properties underlying efficient supply chains. To develop a suitable theory of supply chain networks, the authors look to mirror the properties of complex network models with real-world supply chains.Design methodology approach - The authors review complex network literature drawn from multiple disciplines in top scientific journals. From this interdisciplinary review a series of propositions are developed around supply chain complexity and adaptive phenomena.Findings - This paper proposes that the structure of efficient supply chains follows a \"scale-free\" network. This proposal emerges from arguments that the key properties of efficient supply chains are a short characteristic path length, a high clustering coefficient and a power law connectivity distribution.Research limitations implications - The authors' discussion centres on applying advances found in recent complex network literature. Hence, the need is noted to empirically validate the series of propositions developed in this paper in a supply chain context.Practical implications - If efficient supply chains resemble a scale-free network, then managers can derive a number of implications. For example, supply chain resilience is derived by the presence of hub firms. To reduce the vulnerability of supply chains to cascading failures, it is recognized that managers could build in redundancy, undertake a multi-sourcing strategy or intermediation between hub firms.Originality value - This paper advances supply chain network theory. It offers a novel understanding of supply chains as complex adaptive systems and, in particular, that efficient and resilient supply chain systems resemble a scale-free network. In addition, it provides a series of propositions that allow modelling and empirical research to proceed.

The authors encode pixel values of a short motion picture into the DNA of a population of Escherichia coli . Movie stored on microbes Among many applications, harnessing the CRISPR–Cas microbial immune system has been suggested to turn DNA into a promising medium for archiving data within living cells. Now Seth Shipman and colleagues report a quantitative leap in this direction. They have encoded a motion picture into the DNA of a population of Escherichia coli by storing pixel values as a nucleotide code inserted into the genomes of several living cells. Besides the technological feat, the work also reveals new principles in the natural functioning of the CRISPR–Cas system that are relevant for understanding the biology of bacterial adaptation as well as its practical applications. DNA is an excellent medium for archiving data. Recent efforts have illustrated the potential for information storage in DNA using synthesized oligonucleotides assembled in vitro 1 , 2 , 3 , 4 , 5 , 6 . A relatively unexplored avenue of information storage in DNA is the ability to write information into the genome of a living cell by the addition of nucleotides over time. Using the Cas1–Cas2 integrase, the CRISPR–Cas microbial immune system stores the nucleotide content of invading viruses to confer adaptive immunity 7 . When harnessed, this system has the potential to write arbitrary information into the genome 8 . Here we use the CRISPR–Cas system to encode the pixel values of black and white images and a short movie into the genomes of a population of living bacteria. In doing so, we push the technical limits of this information storage system and optimize strategies to minimize those limitations. We also uncover underlying principles of the CRISPR–Cas adaptation system, including sequence determinants of spacer acquisition that are relevant for understanding both the basic biology of bacterial adaptation and its technological applications. This work demonstrates that this system can capture and stably store practical amounts of real data within the genomes of populations of living cells.

Social-ecological systems (SES) are complex adaptive systems. Social-ecological system phenomena, such as regime shifts, transformations, or traps, emerge from interactions among and between human and nonhuman entities within and across scales. Analyses of SES phenomena thus require approaches that can account for (1) the intertwinedness of social and ecological processes and (2) the ways they jointly give rise to emergent social-ecological patterns, structures, and dynamics that feedback on the entities and processes that generated them. We have developed a framework of linked action situations (AS) as a tool to capture those interactions that are hypothesized to have jointly and dynamically generated a social-ecological phenomenon of interest. The framework extends the concept of an action situation to provide a conceptualization of SES that focusses on social-ecological interactions and their links across levels. The aim of our SE-AS (social-ecological action situations) framework is to support a process of developing hypotheses about configurations of ASs that may explain an emergent social-ecological phenomenon. We suggest six social-ecological ASs along with social and ecological action situations that can commonly be found in natural resource or ecosystem management contexts. We test the ability of the framework to structure an analysis of processes of emergence by applying it to different case studies of regime shifts, traps, and sustainable resource use. The framework goes beyond existing frameworks and approaches, such as the SES framework or causal loop diagrams, by establishing a way of analyzing SES that focuses on the interplay of social-ecological interactions with the emergent outcomes they produce. We conclude by discussing the added value of the framework and discussing the different purposes it can serve: from supporting the development of theories of the emergence of social-ecological phenomena, enhancing transparency of SES understandings to serving as a boundary object for interdisciplinary knowledge integration.

PurposeBlockchain is a distributed ledger technology that uses cryptography to ensure transmission and access security, which provides solutions to numerous challenges to complex supply networks. The purpose of this paper is to empirically test the impact of blockchain implementation on shareholder value varying from internal and external complexity from the complex adaptive systems (CASs) perspective. It further explores how business diversification, supply chain (SC) concentration and environmental complexity affect the relationship between blockchain implementation and shareholder value.Design/methodology/approachBased on 138 blockchain implementation announcements of listed companies on the Chinese A-share stock market, the authors use event study methodology to evaluate the impact of blockchain implementation on shareholder value.FindingsThe results show that blockchain implementation has a positive impact on shareholder value, and this impact will be moderated by business diversification, SC concentration and environmental complexity. In addition, environmental complexity exerts a moderating effect on SC concentration. In the post hoc analysis, the authors further explore the impact of blockchain implementation on long-term operational performance.Originality/valueThis is the first research empirically examining the effect of blockchain implementation on shareholder value varying from internal and external complexity from the CASs perspective. This paper provides evidence of the different effects of blockchain implementation on short- and long-term performance. It adds to the interdisciplinary research of information systems (IS) and operations management (OM).

Infectious disease outbreaks recapitulate biology: they emerge from the multi-level interaction of hosts, pathogens, and environment. Therefore, outbreak forecasting requires an integrative approach to modeling. While specific components of outbreaks are predictable, it remains unclear whether fundamental limits to outbreak prediction exist. Here, adopting permutation entropy as a model independent measure of predictability, we study the predictability of a diverse collection of outbreaks and identify a fundamental entropy barrier for disease time series forecasting. However, this barrier is often beyond the time scale of single outbreaks, implying prediction is likely to succeed. We show that forecast horizons vary by disease and that both shifting model structures and social network heterogeneity are likely mechanisms for differences in predictability. Our results highlight the importance of embracing dynamic modeling approaches, suggest challenges for performing model selection across long time series, and may relate more broadly to the predictability of complex adaptive systems. Forecasting of infectious disease outbreaks can inform appropriate intervention measures, but whether fundamental limits to accurate prediction exist is unclear. Here, the authors use permutation entropy as a model independent measure of predictability to study limitations across a broad set of infectious diseases.