Modelling approaches, such as those described by Fricker et al. (Chapter 1) and Davidson (2006), are being developed to describe and predict mycelial behaviour under realistic parameters. These cover a range of scales. At cell scale, individual hyphae have been shown, by theoretical models parameterized from confocal imaging (using fluorescence recovery after photobleaching, 'FRAP', techniques), to be capable of supplying tip growth by vacuolar amino acid transport from cytoplasm several tens of micrometres behind the tip (Darrah et al., 2006), and by diffusion facilitated by movements of the dynamic pleiomorphic vacuolar system (Cole et al., 1998). Fungal vacuoles store N-rich amino acids including arginine (Klionsky et al., 1990), and there is evidence from arbuscular mycorrhizal fungi that spatially differentiated metabolism in hyphae underlies vacuolar amino acid transport between soil and root (Govindarajulu et al., 2005). Organism level network development is also being analysed with agent-based models that contribute the power of modern computing to explore and predict developmental responses (Meskauskas et al., 2004; Bebber et al., 2007; Chapter 1) over a wider parameter space than would ever be accessible by experimental approaches.

Mathematical analysis of networks in microcosms is revealing the way on which the conductivity conferred by cords is arranged within the network to maximise different adaptive attributes, including robustness to attack and the acquisition of distant resources (Chapter 1).

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