The community dynamics of two‐ and three‐fungal species interactions derived for a tessellated agar model system are described. The microcosm allows for the varied prescription of: (1) the number of fungal species interacting; (2) the spatial configuration (patchiness) of the distribution of individuals; (3) the magnitude of scale of spatial occupation by different fungal individuals; and (4) the operation of antagonistic mechanisms based on contact or longer range diffusible components. Stepwise logistic regressions for two‐species interactions are used to inform the design of the multi‐species interaction tessellations. The model prescribes and investigates complex parameters, such as spatiotemporal heterogeneity and microcosm scale (e.g. population patchiness and crossing times). Data are quantified as proportion, interface class and state transition class of viable fungal species. Spatiotemporal heterogeneity is represented using a novel application of principal component analysis which shows good intuitive agreement with visual assessment of the interaction outcome patterns, and allows effective comparison of the data as a whole. The model demonstrates the influence of the complex and coordinated behaviour of fungal mycelia on community development: interaction outcome of three‐species interactions cannot be directly extrapolated from the relevant binary component interactions; interaction outcomes of the multi‐species tessellations appears to be neither random nor fully deterministic; a degree of stochasticity is apparent in all tessellation arrangements; the smaller scale tessellations produce more consistent interaction outcome results, probably because experimental scale affects the duration of transient behaviour; and different initial spatial configurations of inoculum (irrespective of inoculum quantity or proportion) influence community development and reproducibility.

A stochastic cellular automaton for modelling the dynamics of a two-species fungal microcosm is presented. The state of each cell in the automaton depends on the state of a prede¢ned neighbourhood via a set of conditional probabilities derived from experiments conducted on pairwise combinations of species. The model is tested by detailed comparison with larger-scale experimental microcosms. By employing di¡erent hypotheses which relate the pairwise data to the conditional probabilities in the model, the nature of the local and non-local interactions in the community is explored. The hypothesis that the large-scale dynamics are a consequence of independent interactions between species in a local neighbourhood can be excluded at the 5% signi¢cance level. The form of the interdependencies is determined and it is shown that the outcome of the interactions at the local neighbourhood-scale depends on the community-scale patterning of individuals. The dynamics of the microcosm are therefore an emergent property of the system of interacting mycelia that cannot be deduced from a study of the components in isolation.

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In industrialised countries water service providers (WSPs) must provide an appropriate level of service with an acceptable performance at an acceptable cost to customers. In the UK a move towards sustainable development is now also a major goal for WSPs. However, the imposition of institutional systems and regulatory targets still encourage the adoption of less sustainable technologies or solutions by the water industry. It is within this context, that the Sustainable Water industry Asset Resource Decisions (SWARD) project has developed a set of decision support processes that allow WSPs to assess the relative sustainability of water/wastewater system asset development decisions. A Guidebook has been produced that takes the WSP and its stakeholders through the processes essential to incorporating sustainability in asset investment decision‐making. Several case studies that demonstrate the SWARD principles in application are included within the Guidebook, the experience of which is described in this paper.

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