Modelling interactions in fungi

Abstract

Indeterminate organisms have received comparatively little attention in theoretical ecology and still there is much to be understood about the origins and consequences of community structure. The fungi comprise an entire kingdom of life and epitomize the indeterminate growth form. While interactions play a significant role in shaping the community structure of indeterminate organisms, to date most of our knowledge relating to fungi comes from observing interaction outcomes between two species in two-dimensional arena experiments. Interactions in the natural environment are more complex and further insight will benefit from a closer integration of theory and experiment. This requires a modelling framework capable of linking genotype and environment to community structure and function. Towards this, we present a theoretical model that replicates observed interaction outcomes between fungal colonies. The hypotheses underlying the model propose that interaction outcome is an emergent consequence of simple and highly localized processes governing rates of uptake and remobilization of resources, the metabolic cost of production of antagonistic compounds and non-localized transport of internal resources. The model may be used to study systems of many interacting colonies and so provides a platform upon which the links between individual-scale behaviour and community-scale function in complex environments can be built.

Observer-dependent variability of the thresholding step in the quantitative analysis of soil images and X-ray microtomography data

“…By repeating the whole process multiple times, following a traditional Monte Carlo approach, probability distributions are eventually obtained for fractal dimensions or LB modelling outputs. For calculation-intensive uses of soil images, for example LB modelling or fungal growth (Falconer et al, 2008), this type of Monte Carlo approach will require significantly more computer processing time than is currently the case with thresholded images. However, the fact that Monte Carlo codes are particularly easy to parallelize opens up many possibilities for large-scale computations involving multiple processors, including "grid" computing (Renard et al, 2009) or the fast-developing "cloud" computing (Buyya et al, 2009).…”

Understanding mechanisms of soil biota involvement in soil aggregation: A way forward with saprobic fungi?

“…mycorrhizal fungi). Addressing more complex research question could lead to the addition of data covering competition and even trophic interactions which would allow us to evaluate their impact on functional diversity of SF communities and their ability to affect soil aggregation (Falconer et al, 2008;Crowther et al, 2012).…”

Modelling and quantifying the effect of heterogeneity in soil physical conditions on fungal growth

“…As the objective of this study is to analyse the effect of pore geometry, we used parameters for one single fungal species only. In previous work the fungal trait set for effective invasion of heterogeneous environments was identified (Falconer et al, 2008). Simplified assumptions were made with respect to the nutritional heterogeneity of the soil environment: we assumed Carbon to be homogeneously distributed throughout the pore volume.…”