García-Rodríguez A, Govezensky T, Naumis GG, Barrio RA

PLoS ONE 19(2): e0298791

Although friendship networks have been extensively studied, few models and studies are available to understand the reciprocity of friendship and foes. Here a model is presented to explain the directed friendship and foes network formation observed in experiments of Mexican and Hungarian schools. Within the presented model, each agent has a private opinion and a public one that shares to the group. There are two kinds of interactions between agents. The first kind represent interactions with the neighbors while the other represents the attitude of an agent to the overall public available information. Links between agents evolve as a combination of the public and private information available. Friendship is defined using a fitness function according to the strength of the agent’s bonds, clustering coefficient, betweenness centrality and degree. Enmity is defined as very negative links. The model allows us to reproduce the distribution of mentions for friends and foes observed in the experiments, as well as the topology of the directed networks.

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Tazzio Tissot, Mike Levin, View Chris Buckley, Richard Watson

How do multiple active components at one level of organisation create agential wholes at higher levels of organisation? For example, in organismic development, how does the multi-scale autonomy of the organism arise from the interactions of the molecules, cells and tissues that an organism contains? And, in the major evolutionary transitions, how does a multicellular organism, for example, arise as an evolutionary unit from the selective interests of its unicellular ancestors? We utilise computational models as a way to think about this general question. We take a deliberately minimalistic notion of an agent: a competency to take one of two possible actions to minimise stress. Helping ourselves to this behaviour at the microscale, we focus on conditions where this same type of agency appears spontaneously at a higher level of organisation. We find that a simple process of positive feedback on the timing of individual responses, loosely analogous to the natural phase synchronisation of weakly coupled oscillators, causes such a transition in behaviour. The emergent collectives that arise become, quite suddenly, able to respond to their external stresses in the same (minimal) sense as the original microscale units. This effects a dramatic rescaling of the system behaviour, and a quantifiable increase in problem-solving competency, serving as a model of how higher-level agency emerges from a pool of lower-level agents or active matter. We discuss how this dynamical ‘waking-up’ of higher-level collectives, through the alignment of their internal dynamics, might relate to reproductive/cell-cycle synchronisation in evolutionary transitions and development.

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Babak M. S. Arani, Stephen R. Carpenter, Egbert H. van Nes, Ingrid A. van de Leemput, Chi Xu, Pedro G. Lind, Marten Scheffer

Tipping points and alternative attractors have become an important focus of research and public discussions about the future of climate, ecosystems and societies. However, empirical evidence for the existence of alternative attractors remains scarce. For example, bimodal frequency distributions of state variables may suggest bistability, but can also be due to bimodality in external conditions. Here, we bring a new dimension to the classical arguments on alternative stable states and their resilience showing that the stochastic regime can distort the relationship between the probability distribution of states and the underlying attractors. Simple additive Gaussian white noise produces a one-to-one correspondence between the modes of frequency distributions and alternative stable states. However, for more realistic types of noise, the number and position of modes of the frequency distribution do not necessarily match the equilibria of the underlying deterministic system. We show that data must represent the stochastic regime as thoroughly as possible. When data are adequate then existing methods can be used to determine the nature of the underlying deterministic system and noise simultaneously. This may help resolve the question of whether there are tipping points, but also how realized states of a system are shaped by stochastic forcing vs internal stability properties.

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Daniel Hoyer, Samantha Holder, James S Bennett, Pieter François, Harvey Whitehouse, Alan Covey, Gary Feinman, Andrey Korotayev, Vadim Vustiuzhanin, Johannes Preiser-Kapeller, Kathryn Bard, Jill Levine, Jenny Reddish, Georg Orlandi, Rachel Ainsworth, and Peter Turchin

Societal ‘crises’ are periods of turmoil and destabilization in socio-cultural, political, economic, and other systems, often accompanied by varying amounts of violence and sometimes significant changes in social structure. The extensive literature analyzing societal crises has concentrated on relatively few historical examples (large-scale events such the fall of the Roman Empire or the French and Russian Revolutions) emphasizing different aspects of these events as potential causes or consistent effects. To investigate crises and prior approaches to explaining them, and to avoid a potential small-sample size bias present in several previous studies, we sought to uniformly characterize a substantial collection of historical crises, spanning millennia, from the prehistoric to post-industrial, and afflicting a wide range of polities in diverse global regions; the Crisis Database (CrisisDB). Here, we describe this dataset which comprises 168 crises suggested by historians and characterized by a number of significant ‘consequences’ (such as civil war, epidemics, or loss of population) including also institutional and cultural reforms (for example improved sufferance or constitutional changes) that might occur during and immediately following the crisis period. Our analyses show that the consequences experienced by each crisis is highly variable. The outcomes themselves are uncorrelated with one another and, overall, the set of consequences is largely unpredictable when compared to other large-scale properties of society suggested by previous scholars such as its territorial size, religion, administrative size, or historical recency. We conclude that there is no ‘typical’ societal crisis of the past, but crisis situations can take a variety of different directions. We offer some suggestions on the forces that might drive these varying consequences for exploration in future work.

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