High altitude hunting, climate change, and pastoral resilience in eastern Eurasia.

The transition from hunting to herding transformed the cold, arid steppes of Mongolia and Eastern Eurasia into a key social and economic center of the ancient world, but a fragmentary archaeological record limits our understanding of the subsistence base for early pastoral societies in this key region. Organic material preserved in high mountain ice provides rare snapshots into the use of alpine and high altitude zones, which played a central role in the emergence of East Asian pastoralism. Here, we present the results of the first archaeological survey of melting ice margins in the Altai Mountains of western Mongolia, revealing a near-continuous record of more than 3500 years of human activity. Osteology, radiocarbon dating, and collagen fingerprinting analysis of wooden projectiles, animal bone, and other artifacts indicate that big-game hunting and exploitation of alpine ice played a significant role during the emergence of mobile pastoralism in the Altai, and remained a core element of pastoral adaptation into the modern era. Extensive ice melting and loss of wildlife in the study area over recent decades, driven by a warming climate, poaching, and poorly regulated hunting, presents an urgent threat to the future viability of herding lifeways and the archaeological record of hunting in montane zones.

Self-organisation of small-world networks by adaptive rewiring in response to graph diffusion.

Complex networks emerging in natural and human-made systems tend to assume small-world structure. Is there a common mechanism underlying their self-organisation? Our computational simulations show that network diffusion (traffic flow or information transfer) steers network evolution towards emergence of complex network structures. The emergence is effectuated through adaptive rewiring: progressive adaptation of structure to use, creating short-cuts where network diffusion is intensive while annihilating underused connections. With adaptive rewiring as the engine of universal small-worldness, overall diffusion rate tunes the systems' adaptation, biasing local or global connectivity patterns. Whereas the former leads to modularity, the latter provides a preferential attachment regime. As the latter sets in, the resulting small-world structures undergo a critical shift from modular (decentralised) to centralised ones. At the transition point, network structure is hierarchical, balancing modularity and centrality - a characteristic feature found in, for instance, the human brain.

Spatially constrained adaptive rewiring in cortical networks creates spatially modular small world architectures.

A modular small-world topology in functional and anatomical networks of the cortex is eminently suitable as an information processing architecture. This structure was shown in model studies to arise adaptively; it emerges through rewiring of network connections according to patterns of synchrony in ongoing oscillatory neural activity. However, in order to improve the applicability of such models to the cortex, spatial characteristics of cortical connectivity need to be respected, which were previously neglected. For this purpose we consider networks endowed with a metric by embedding them into a physical space. We provide an adaptive rewiring model with a spatial distance function and a corresponding spatially local rewiring bias. The spatially constrained adaptive rewiring principle is able to steer the evolving network topology to small world status, even more consistently so than without spatial constraints. Locally biased adaptive rewiring results in a spatial layout of the connectivity structure, in which topologically segregated modules correspond to spatially segregated regions, and these regions are linked by long-range connections. The principle of locally biased adaptive rewiring, thus, may explain both the topological connectivity structure and spatial distribution of connections between neuronal units in a large-scale cortical architecture.