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  • 1
    Language: English
    In: Ecological Modelling, 2008, Vol.216(3), pp.291-302
    Description: During the past 10 years, soil scientists have started to use 3D Computed Tomography in order to gain a clearer understanding of the geometry of soil structure and its relationships with soil properties. We propose a geometric model for the 3D representation of pore space and a practical method for its computation. Our basic idea consists in representing pore space using a minimal set of maximal balls (Delaunay spheres) recovering the shape skeleton. In this representation, each ball could be considered as a maximal local cavity corresponding to the “intuitive” notion of a pore as described in the literature. The space segmentation induced by the network of balls (pores) was then used to spatialize biological dynamics. Organic matter and microbial decomposers were distributed within the balls (pores). A valuated graph representing the pore network, organic matter and distribution of micro-organisms was then defined. Microbial soil organic matter decomposition was simulated by updating this valuated graph. The method was implemented and tested using real CT images. The model produced realistic simulated results when compared with data in the literature in terms of the water retention curve and carbon mineralization. A decrease in water pressure decreased carbon mineralization, which is also in accordance with findings in the literature. From our results we showed that the influence of water pressure on decomposition is a function of organic matter distribution in the pore space. As far as we know, this is the approach to have linked pore space geometry and biological dynamics in a formal way. Our next goal will be to compare the model with experimental data of decomposition using different soil structures, and to define geometric typologies of pore space shape that can be attached to specific biological and dynamic properties.
    Keywords: Computational Geometry ; Soil Science ; Pore Space Modelling ; Microbial Decomposition Simulation ; 3d Computer Vision ; Environmental Sciences ; Ecology
    ISSN: 0304-3800
    E-ISSN: 1872-7026
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