Image analysis of fractal geometry can be used to gain deeper insights into complex ecophysiological patterns and processes occurring within natural microbial biofilm landscapes, including the scale-dependent heterogeneities of their spatial architecture, biomass and cell-cell interactions of colonization behavior, all driven by the ecological theory of optimal spatial positioning of organisms to maximize their efficiency in utilization of allocated nutrient resources. For instance, at the core of the allometric scaling relationships between body size and metabolic rate in ecophysiology are the local variations in nutrient resource allocation within habitats being colonized. Acquiring enough food is the first key requirement for successful colonization of habitats in all of biology. Various ecological studies suggest that metabolic processes used for growth physiology rely on the hierarchical fractal-like nature of resource distribution networks, and that organisms have exploited a fourth spatial dimension by evolving hierarchical fractal-like structured spatial distributions designed to maximize nutrient resource acquisition and allocation [1-3]. Fractal descriptions of this self-similarity metric for biofilm communities provide quantitative insights about the spatial distribution of resources in situ and how organisms exploit and compete for those resources [3, 4]. This fractal partitioning of heterogeneous distributions and allocations of the same resource is an important trade‐off constraint that enables the coexistence of multiple species among community participants [3, 5].
We are pleased to introduce CMEIAS JFrad version 1.0, a new computing technology that analyzes the fractal geometry of complex biofilm architectures in digital landscape images. The software uniquely features a data-mining opportunity based on a comprehensive collection of 11 different mathematical methods to compute fractal dimension that are implemented into a wizard design to maximize ease-of-use for semi-automatic analysis of single images or fully automatic analysis of multiple images in a batch process. This improvement in computational image informatics will strengthen microscopy-based approaches to analyze the landscape ecology of microbial biofilm populations and communities in situ at spatial resolutions that range from single cells to microcolonies.
Our Ji et al. (6) publication formally introduces CMEIAS JFrad, describes its software logic, mathematical algorithms of its 11 methods to compute fractal dimension, experimental protocols to rank the importance of these different fractal analysis methods that discriminate biofilm architecture, how to optimize the variable settings of key image processing steps that must precede fractal analysis, and examples of its use to compare the spatial ecology and landscape architecture of microbial biofilms.
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- Ji Z, K Card & FB Dazzo (2015). CMEIAS JFrad: a digital computing tool to discriminate the fractal geometry of landscape architectures and spatial patterns of individual cells in microbial biofilms. Microbial Ecology 69:710-720. doi: 10.1007/s00248-014-0495-1.
Click here to download CMEIAS JFrad.