Modeling Fungal Decay Communities

From the foregoing it is evident that significant limitations exist in both field- and laboratory-based studies of wood-decay fungal communities. Moreover, much of the information reported is qualitative and at best semiquantitative. A complete understanding of the natural environment based on observation alone is probably unattainable due to its complexity, the appreciation of which may be approached in several ways. Conventional methods often involve an empirical or field based approach to investigate the activities of individual decay fungi and their temporal relationship with the abiotic and biotic environment. These may be analyzed statistically or further complemented with laboratory experiments. More rarely, fungal ecological investigation may involve the development of conceptual and experimental models based on general ecological theory (Carroll and Wicklow 1992). The use of conceptual representations or models has been instrumental in expanding the boundaries of our knowledge and understanding of the natural environment. A model in its broadest sense is a partial, simplified version of a real entity or system. The main value of models is that they allow us to first represent and then make measurements and predictions that would be otherwise awkward. Theoretical or mathematical models based on experimentally observed characteristics of fungi are increasingly being used, for e.g., in formulating hypothesis about their population dynamics and epidemiology (which will not be considered here and the reader is directed to Worrall 1999). A particular advantage of linked models is the interplay between quantitative experimental data and theoretical predictions. It is therefore possible to test and validate the theoretical model by predicting the result of, for e.g., changing an environmental factor in the experimental system and then observing whether the predicted result occurs.

The development of theoretical or mathematical models to describe any real ecological system will always be contentious, given the inevitable simplification or reduction of the system inherently required by such an approach. However, appropriate theoretical models should allow inferences to be made regarding the underlying mechanisms or processes driving ecological systems. Thus, the biological processes that regulate and generate patterns of organisation in fungal communities may be elucidated through the understanding of the interactive and feedback control steps involved within a working theoretical model. So, as Moorhead and Reynolds (1992) reasoned, "the process of developing a model tests our understanding of the system, identifies areas of uncertainty and, importantly, provides a means of examining alternative conceptual frameworks." Furthermore, mycology may offer important systems to study and test the suitability of general ecological theories and laws usually developed for determinate organisms, for application to indeterminate biological behavior. Rare examples of this approach include consideration of the ecological strategies of individual fungi (Andrews and Harris 1986; Boddy 1992), and testing the relevance of Island theory, and the Species-area curve, to certain fungal communities (Andrews et al. 1987; Newton and Haigh 1998; Wildman 1987).

The majority of natural environments display both spatial and temporal heterogeneity or patchiness in terms of both abiotic and biotic factors, which may profoundly effect the functioning and development of fungal communities (Ritz and Crawford 1999). So models that address environmental heterogeneity are the most likely to produce realistic theory. Certain distinctive biological attributes displayed by the fungal form should also be incorporated into any reasonable theoretical model. Features such as indeterminacy, inter-connectedness, variation, and versatility (genotypic and phenotypic plasticity), all contribute to varying degrees and at different scales, to the success of filamentous fungi within the natural heterogeneous environment. As indeterminate life-forms the growth of filamentous fungi is potentially unlimited, unlike that of determinate life forms such as unicells and animals, which possess genetically programmed limits in both space and time. However this statement may be an oversimplification of the fact, as the longevity of indeterminate individuals and species does vary. Ruderals, for e.g., may persist only briefly for a few weeks, whilst some such as Ganoderma and Armillaria are renowned to persist for years. Nevertheless, the indeterminacy displayed by eucarpic fungi facilitates success within a heterogeneous environment, as hyphae have the potential to temporally sustain or spatially extend great distances, often spanning inhospitable conditions in time or space to encounter new resource bases. Indeterminacy may generate versatile responses to environmental unpredictability in a way that determinate organisms can only engage with by way of evolutionary selection or social behavior.

Indeterminate and modular life forms show some analogies and have sometimes been treated as theoretically equivalent (Trinci 1978; Prosser 1994). However, modular organisms develop by repeated addition of the same organizational unit to a pre-existing one, whereas mycelia are nonadditive as they operate as dynamic flow systems with branching, anastomosing and radiating components communicating at different scales and to varying degrees (Rayner 1996). Therefore, the temptation to apply modular models, which incorporate iterative steps at a single reference scale, to indeterminate systems, should be considered with caution. The challenge will be to develop modeling frameworks that can link biological processes operating over multiple scales and with varying constancy, to large-scale or ecosystem behavior. Developing and therefore understanding this complexity would make a major contribution to both fungal and general ecoevolutionary theories.

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