Biological Invasion in Soil

complex network analysis

F. Perez-Reche, S. N. Taraskin, F. M. Neri, C. A. Gilligan, L. da F. Costa, M. P. Viana, W. Otten, D. Grinev

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

A network model for soil pore space is developed and applied to the analysis of biological invasion of microorganisms in soil. The model was parameterized for two soil samples with different compaction (loosely and densely packed) from images derived from an X-ray micro-tomography system. The data were then processed using 3-D imaging techniques, to construct the networks of pore structures with in the soil samples. The network structure is characterized by the measurement of features that are relevant for biological colonization through soil. These include the distribution of channel lengths, node coordination numbers, location and size of channel bottlenecks, and the topology of the largest connected cluster. The pore-space networks are then used to investigate the spread of a microorganism through soil, in which the transmissibility between pores is defined as a function of the channel characteristics. The same spreading process is investigated in artificially constructed homogeneous networks with the same average properties as the original ones. The comparison shows that the extent of invasion is lower in the original networks than in the homogeneous ones: this proves that inherent heterogeneity and correlations contribute to the resilience of the system to biological invasion.

Original languageEnglish
Title of host publicationProceedings of the 16th international conference on Digital Signal Processing
Place of PublicationNew York
PublisherIEEE Press
Pages1006-1013
Number of pages8
Volume1 & 2
ISBN (Print)978-1-4244-3297-4
Publication statusPublished - 2009
Event16th International Conference on Digital Signal Processing - Santorini
Duration: 5 Jul 20097 Jul 2009

Conference

Conference16th International Conference on Digital Signal Processing
CitySantorini
Period5/07/097/07/09

Cite this

Perez-Reche, F., Taraskin, S. N., Neri, F. M., Gilligan, C. A., Costa, L. D. F., Viana, M. P., ... Grinev, D. (2009). Biological Invasion in Soil: complex network analysis. In Proceedings of the 16th international conference on Digital Signal Processing (Vol. 1 & 2, pp. 1006-1013). New York: IEEE Press.

Biological Invasion in Soil : complex network analysis. / Perez-Reche, F.; Taraskin, S. N.; Neri, F. M.; Gilligan, C. A.; Costa, L. da F.; Viana, M. P.; Otten, W.; Grinev, D.

Proceedings of the 16th international conference on Digital Signal Processing. Vol. 1 & 2 New York : IEEE Press, 2009. p. 1006-1013.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Perez-Reche, F, Taraskin, SN, Neri, FM, Gilligan, CA, Costa, LDF, Viana, MP, Otten, W & Grinev, D 2009, Biological Invasion in Soil: complex network analysis. in Proceedings of the 16th international conference on Digital Signal Processing. vol. 1 & 2, IEEE Press, New York, pp. 1006-1013, 16th International Conference on Digital Signal Processing, Santorini, 5/07/09.
Perez-Reche F, Taraskin SN, Neri FM, Gilligan CA, Costa LDF, Viana MP et al. Biological Invasion in Soil: complex network analysis. In Proceedings of the 16th international conference on Digital Signal Processing. Vol. 1 & 2. New York: IEEE Press. 2009. p. 1006-1013
Perez-Reche, F. ; Taraskin, S. N. ; Neri, F. M. ; Gilligan, C. A. ; Costa, L. da F. ; Viana, M. P. ; Otten, W. ; Grinev, D. / Biological Invasion in Soil : complex network analysis. Proceedings of the 16th international conference on Digital Signal Processing. Vol. 1 & 2 New York : IEEE Press, 2009. pp. 1006-1013
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abstract = "A network model for soil pore space is developed and applied to the analysis of biological invasion of microorganisms in soil. The model was parameterized for two soil samples with different compaction (loosely and densely packed) from images derived from an X-ray micro-tomography system. The data were then processed using 3-D imaging techniques, to construct the networks of pore structures with in the soil samples. The network structure is characterized by the measurement of features that are relevant for biological colonization through soil. These include the distribution of channel lengths, node coordination numbers, location and size of channel bottlenecks, and the topology of the largest connected cluster. The pore-space networks are then used to investigate the spread of a microorganism through soil, in which the transmissibility between pores is defined as a function of the channel characteristics. The same spreading process is investigated in artificially constructed homogeneous networks with the same average properties as the original ones. The comparison shows that the extent of invasion is lower in the original networks than in the homogeneous ones: this proves that inherent heterogeneity and correlations contribute to the resilience of the system to biological invasion.",
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AB - A network model for soil pore space is developed and applied to the analysis of biological invasion of microorganisms in soil. The model was parameterized for two soil samples with different compaction (loosely and densely packed) from images derived from an X-ray micro-tomography system. The data were then processed using 3-D imaging techniques, to construct the networks of pore structures with in the soil samples. The network structure is characterized by the measurement of features that are relevant for biological colonization through soil. These include the distribution of channel lengths, node coordination numbers, location and size of channel bottlenecks, and the topology of the largest connected cluster. The pore-space networks are then used to investigate the spread of a microorganism through soil, in which the transmissibility between pores is defined as a function of the channel characteristics. The same spreading process is investigated in artificially constructed homogeneous networks with the same average properties as the original ones. The comparison shows that the extent of invasion is lower in the original networks than in the homogeneous ones: this proves that inherent heterogeneity and correlations contribute to the resilience of the system to biological invasion.

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