Kaleda K. Denton, Marcus W. Feldman, and Jonathan F. Johannemann

PNAS 123 (25) e2530712123A continuous trait contains infinitely many variants on a spectrum, such as a spectrum of behaviors or ideologies. “Conformity” to such traits has been defined as the preference for the mean variant, even if this mean is not close to any individual variant (e.g., if half of the population falls on the far right and far left of a spectrum, respectively, the mean is in the center). Here, we define conformity as the preference for clusters of common variants, not average variants. Compared to trait-averaging models, this conformity model provides a better fit to empirical data on human decision-making under many conditions, and in simulations, it often produces different population-level outcomes such as faster shifts toward poles of a spectrum.

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Claus Metzner, Ali Ghebleh, Achim Schilling, Andreas Maier, Thomas Kinfe, Patrick Krauss

Complex adaptive systems often develop organized structures without centralized control. Yet the local mechanisms by which functional organization emerges and persists remain incompletely understood. Here we propose Surviving by Serving (SBS) as a general principle of self-organization: components persist as long as their outputs are utilized by other components, whereas prolonged non-utilization promotes adaptation and exploration. To investigate this idea, we introduce a minimal multi-agent model in which agents transform shared resources and receive only local feedback when their outputs are subsequently utilized elsewhere in the system. Despite the absence of global objectives, the system spontaneously self-organizes into functional interaction networks. We observe the emergence of stable transformation chains, core-periphery organization, and the generation of novel states that enable previously inaccessible target conditions to be reached. Remarkably, self-sustaining interaction networks can arise even without external selection pressures, creating a pre-adaptive search phase from which later functional solutions emerge. These findings suggest that functional utilization may provide a simple, substrate-independent mechanism for the emergence and stabilization of organized structure in complex adaptive systems.

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Klaus Jaffe

Infodynamics studies how energy and information interact and change over time. In social behaviour this interaction is especially visible: relationships involving asymmetric energy exchange, often take the form of parasitism or corruption. Corruption denotes behaviour that is unlawful, whereas social parasitism describes exploitative relationships that are socially damaging but legal. In contemporary societies a primary form of energy is money, and many instances of parasitic or corrupt behaviour revolve around its distribution and use. Social parasitic behaviour predate human society: primate studies document bribery-like exchanges for favours, status, food, shelter, transport, or priority in scarce resources, showing that moneyless systems are not immune to corruption. Corruption can cause incalculable harm to society as victims of earthquakes in Haiti, Tukey and Venezuela can attest. This essay reviews essential aspects of corruption and social parasitism among humans. Both phenomena are sustained when information is distorted and transparency is suppressed, preventing antagonistic or corrective forces from acting.

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Investigation of regional variations in CO2 growth rates : Integrating Emission Inventories and Atmospheric Observations
Yogesh Bali, Darja Cvetković, Juan Gancio, Adrián Gutiérrez-Arroyo, Sofia Vazquez Alferez, Xuan Tung Vu, Jin Yan, Pietro Zgaga, Fakhteh Ghanbarnejad, Nasrin Mostafavi Pak
Atmospheric carbon dioxide (CO2) growth rates reflects the combined influence of anthropogenic emissions, biospheric carbon exchange, and climate variability. While climate mitigation is primarily evaluated using bottom-up emission inventories within political boundaries, there is a need to validate these emission reductions using atmospheric measurements. Here, we present a global top-down analysis of atmospheric CO2 growth rates using CAMS atmospheric CO2 reanalysis, EDGAR anthropogenic emissions, GOSIF dataset and the Southern Oscillation Index (SOI) as a measures of biospheric activity, to quantify the relative influence of human and natural drivers. We find that atmospheric CO2 growth rate varies substantially across space and time but is dominated by natural carbon-cycle processes and global background trends. Anthropogenic emission signals are frequently masked by natural variability, making regional top-down detection of human emission changes difficult. The COVID-19 emission reductions in 2020, despite occurring during a neutral ENSO year, were not consistently reflected in regional atmospheric CO2 growth rates, highlighting the dominant roles of biospheric dynamics and atmospheric transport. Using unsupervised clustering and persistence analysis, we identify five characteristic carbon-cycle regimes. Spatial averaging removes much of the regional variability, leaving large-scale climate as the dominant control in most regimes. The active biosphere is the main exception, where strong biogenic signals persist, underscoring the critical role of tropical forests in shaping atmospheric CO2 variability.

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Subhendu Bhandary, Federico Carucci, Christos Charalambous, Francesca Dilisante, Ksenia Dvorkina, Anna Garbo, Jiaqi Liang, Riccardo Vasellini, Francesco Bertolotti

LLMs agents are increasingly used in multi-agent settings, yet their behaviour in sustainability games remains largely unexplored. This work investigates whether lying can emerge among LLM agents in a competitive sustainability game in which agents are informed that common resources can regenerate, although regeneration does not actually occur. We develop an agent-based model of a sustainability game in which agents manage industrial, military, and ecological resources, and interact through a network. LLM agents can observe neighbours’ status, declare future attacks, receive permission to lie, and access reputation information, while rule-based agents provide an interpretable behavioural baseline. The results show that neighbour information strongly changes system dynamics, increasing attacks while improving biosphere retention and coexistence. Also, the presence of future declarations reduce extinction risk without suppressing conflict. Behaviourally, deception emerges even when agents are not explicitly allowed to lie, and explicit permission mainly increases bluffing and diversion rather than direct backstabbing. Finally, the presence of reputation memory and information about the current biosphere level reduces system ecological depletion. These findings suggest that deception can arise as an emergent behaviour in LLM-agent systems and that communication between LLM-agents could support sustainability while dealing with risk.

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