Analysis of fungal networks

Mycelial fungi grow as indeterminate adaptive networks that have to forage for scarce resources in a patchy and unpredictable environment under constant onslaught from mycophagous animals. Development of contrast-independent network extraction algorithms has dramatically improved our ability to characterise these dynamic macroscopic networks and promises to bridge the gap between experiments in realistic experimental microcosms and graph-theoretic network analysis, greatly facilitating quantitative description of their complex behaviour. Furthermore, using digitised networks as inputs, empirically-based minimal biophysical mass-flow models already provide a high degree of explanation for patterns of long-distance radiolabel movement, and hint at global control mechanisms emerging naturally as a consequence of the intrinsic hydraulic connectivity. Network resilience is also critical to survival and can be explored both in silico by removing links in the digitised networks according to particular rules, or in vivo by allowing different mycophagous invertebrates to graze on the networks. Survival depends on both the intrinsic architecture adopted by each species and the ability to reconnect following damage. It is hoped that a comparative approach may yield useful insights into not just fungal ecology, but also biologically inspired rules governing the combinatorial trade-off between cost, transport efficiency, resilience and control complexity for self-organised adaptive networks in other domains. ► Fungal mycelia form adaptive networks that forage for food in a patchy environment. ► The architecture is remodelled to balance transport efficiency, cost and resilience. ► Image enhancement allows rapid network extraction and graph-theoretic analysis. ► Nutrient transport can be explained by an advection, diffusion and delivery model. ► Fungal inspired rules may aid self-organised adaptive networks in other domains.