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Statistical Analysis Of Spatial Structure In Microbial Communities

Overview of methods and approaches
  • Rima B. Franklin
  • Aaron L. Mills

This chapter provides a review of the basic statistical techniques used to detect and quantify spatial structure in ecological data as they can be applied to the analysis of microbial communities. It also discusses the general implications of spatial structure in data analysis, including the inappropriate use of parametric statistical tests with spatially autocorrelated data, and suggests possible alternative procedures. Methods discussed include geostatistics and variogram analysis, kriging, correlograms, Mantel and partial Mantel tests, and time-series analysis. Keywords: spatial structure, microbial communities, statistical analysis, autocorrelation, geostatistics, kriging, scale, spatial autocorrelation

Keywords

Microbial Community Spatial Structure Spatial Autocorrelation Mantel Test Distance Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Becker, J. M., T. Parkin, C. H. Nakatsu, J. D. Wilbur, and A. Konopka, 2006, Bacterial activity, community structure, and centimeter-scale spatial heterogeneity in contaminated soil, Microb. Ecol. 51:220-231.CrossRefPubMedGoogle Scholar
  2. Beliaeff, B., and M. L. Cochard, 1995, Applying geostatistics to identification of spatial patterns of fecal contamination in a mussel farming area (Havre De La Vanlee, France), Water Res. 29:1541-1548.CrossRefGoogle Scholar
  3. Bonham, C. D., and R. M. Reich, 1999, Influence of spatial autocorrelation on a fixed-effect model used to evaluate treatment of oil spills, Appl. Math. Comput. 106:149-162.CrossRefGoogle Scholar
  4. Bradshaw, G. A., and T. A. Spies, 1992, Characterizing canopy gap structure in forests using wavelet analysis, J. Ecol. 80:205-215.CrossRefGoogle Scholar
  5. Brockman, F. J., and C. J. Murray, 1997, Microbiological heterogeneity in the terrestiral subsurface and approaches for its description, in: Microbiology of the Terrestrial Deep Subsurface, P. S. Amy and D. H. Haldeman, eds., CRC Press, Boca Raton, FL, pp. 72-102.Google Scholar
  6. Castrignanò, A., L. Giugliarini, R. Risaliti, and N. Martinelli, 2000, Study of spatial relation-ships among some soil physico-chemical properties of a field in central Italy using multi-variate geostatistics, Geoderma 97:39-60.CrossRefGoogle Scholar
  7. Cavigelli, M. A., G. P. Robertson, and M. J. Klug, 1995, Fatty-acid methyl-ester (FAME) profiles as measures of soil microbial community structure, Plant Soil. 170:99-113.CrossRefGoogle Scholar
  8. Clark, P. J., and F. C. Evans, 1954, Distance to nearest neighbor as a measurement of spatial relationships in populations, Ecology 35:445-453.CrossRefGoogle Scholar
  9. Cliff, A. D., and J. K. Ord, 1981, Spatial Processes: Models and Applications. Pion, London.Google Scholar
  10. Cressie, N. A. C., 1993, Statistics for Spatial Data. Wiley, New York.Google Scholar
  11. Dale, M. R. T., and M. J. Fortin, 2002, Spatial autocorrelation and statistical tests in ecology, Ecoscience 9:162-167.Google Scholar
  12. Dale, M. R. T., and M. Mah, 1998, The use of wavelets for spatial pattern analysis in ecology, J. Veg. Sci. 9:805-814.CrossRefGoogle Scholar
  13. Dandurand, L. M., G. R. Knudsen, and D. J. Schotzko, 1995, Quantification of Pythium-ultimum Var Sporangiiferum zoospore encystment patterns using geostatistics, Phytopathology 85:186-190.CrossRefGoogle Scholar
  14. Dandurand, L. M., D. J. Schotzko, and G. R. Knudsen, 1997, Spatial patterns of rhizoplane populations of Pseudomonas fluorescens, Appl. Environ. Microbiol. 63:3211-3217.PubMedGoogle Scholar
  15. Diggle, P. J., 1983, Statistical Analysis of Spatial Point Patterns. Academic Press, New York.Google Scholar
  16. Dobermann, A., P. Goovaerts, and T. George, 1995, Sources of soil variation in an acid Ultisol of the Philippines, Geoderma 68:173-191.CrossRefGoogle Scholar
  17. Dungan, J. L., J. N. Perry, M. R. T. Dale, P. Legendre, S. Citron-Pousty, M. J. Fortin, A. Jakomulska, M. Miriti, and M. S. Rosenberg, 2002, A balanced view of scale in spatial statistical analysis, Ecography 25:626-640.CrossRefGoogle Scholar
  18. Dutilleul, P., 1993, Spatial heterogeneity and the design of ecological field experiments, Ecology 74:1646-1658.CrossRefGoogle Scholar
  19. Dutilleul, P., 1998, Incorporating scale in ecological experiments: study design, in: Ecological Scale: Theory and Applications, D. L. Peterson and V. T. Parker, eds., Columbia University Press, New York, pp. 369-386.Google Scholar
  20. Englund, E., and A. Sparks, 1991, GEOEAS 1.2.1.: Geostatistical Environmental Assessment Software User’s Guide EPA 600/8-91/008, Environmental Monitoring Systems Laboratory, United States Environmental Protection Agency.Google Scholar
  21. Escudero, A., J. M. Iriondo, and M. E. Torres, 2003, Spatial analysis of genetic diversity as a tool for plant conservation, Biol. Conserv. 113:351-365.CrossRefGoogle Scholar
  22. Ettema, C. H., and D. A. Wardle, 2002, Spatial soil ecology, Trends Ecol. Evol. 17:177-183.Google Scholar
  23. Ford, E. D., and E. Renshaw, 1984, The interpretation of process from pattern using two-dimensional spectral-analysis - Modeling single species patterns in vegetation, Vegetatio 56:113-123.Google Scholar
  24. Fortin, M. J., P. Drapeau, and P. Legendre, 1989, Spatial auto-correlation and sampling design in plant ecology, Vegetatio 83:209-222.CrossRefGoogle Scholar
  25. Franklin, R. B., and A. L. Mills, 2003, Multi-scale variation in spatial heterogeneity for microbial community structure in an eastern Virginia agricultural field, FEMS Microbiol. Ecol. 44:335-346.CrossRefPubMedGoogle Scholar
  26. Franklin, R. B., L. K. Blum, A. C. McComb, and A. L. Mills, 2002, A geostatistical analysis of small-scale spatial variability in bacterial abundance and community structure in salt marsh creek bank sediments, FEMS Microbiol. Ecol. 42:71-80.CrossRefPubMedGoogle Scholar
  27. Franks, P. J. S., 2005, Plankton patchiness, turbulent transport and spatial spectra, Mar. Ecol. Prog. Ser. 294:295-309.CrossRefGoogle Scholar
  28. Geary, R. C., 1954, The contiguity ratio and statistical mapping, Incorp. Statist. 5:115-145.CrossRefGoogle Scholar
  29. Gilbert, R. O., 1987, Statistical Methods for Environmental Pollution Monitoring. Van Nostrand Reinhold, New York.Google Scholar
  30. Goovaerts, P., 1997, Geostatistics for Natural Resources Evaluation. Oxford University Press, New York.Google Scholar
  31. Goovaerts, P., 1998, Geostatistical tools for characterizing the spatial variability of micro-biological and physico-chemical soil properties, Biol. Fertil. Soils 27:315-334.CrossRefGoogle Scholar
  32. Goovaerts, P., 1999, Geostatistics in soil science: state-of-the-art and perspectives, Geoderma 89:1-45.CrossRefGoogle Scholar
  33. Griffith, D. A., 1978, A spatially adjusted ANOVA model, Geogr. Anal. 10:296-301.Google Scholar
  34. Grundmann, G. L., and D. Debouzie, 2000, Geostatistical analysis of the distribution of NH4+ and NO2−-oxidizing bacteria and serotypes at the millimeter scale along a soil transect, FEMS Microbiol. Ecol. 34:57-62.PubMedGoogle Scholar
  35. Haining, R., 1993, Spatial Data Analysis in the Social and Environmental Sciences. Cambridge University Press, Cambridge.Google Scholar
  36. Halvorson, J. J., H. Bolton, J. L. Smith, and R. E. Rossi, 1994, Geostatistical analysis of resource islands under Artemisia Tridentata in the shrub-steppe, Gt. Basin Nat. 54:313-328.Google Scholar
  37. Halvorson, J. J., J. L. Smith, H. Bolton, and R. E. Rossi, 1995, Evaulating shrub-associated spatial patterns of soil properites in a shrub-steppe ecosystem using multiple-variable geostatistics, Soil Sci. Soc. Am. J. 59:1476-1487.Google Scholar
  38. Hoosbeek, M. R., A. Stein, H. van Reuler, and B. H. Janssen, 1998, Interpolation of agronomic data from plot to field scale: using a clustered versus a spatially randomized block design, Geoderma 81:265-280.CrossRefGoogle Scholar
  39. Isaaks, E. H., and R. M. Srivastava, 1989, An Introduction to Applied Geostatistics. Oxford University Press, New York.Google Scholar
  40. Journel, A. G., and C. J. Huijbregts, 1978, Mining Geostatistics. Academic Press, London.Google Scholar
  41. Keitt, T. H., and D. L. Urban, 2005, Scale-specific inference using wavelets, Ecology 86:2497-2504.CrossRefGoogle Scholar
  42. Legendre, P., 1993, Spatial autocorrelation - trouble or new paradigm, Ecology 74:1659-1673.CrossRefGoogle Scholar
  43. Legendre, P., and M. -J. Fortin, 1989, Spatial pattern and ecological analysis, Vegetatio 80:107-138.CrossRefGoogle Scholar
  44. Legendre, P., and L. Legendre, 1998, Numerical Ecology, 2nd Edition. Elsevier Scientific, Amsterdam.Google Scholar
  45. Legendre, P., N. L. Oden, R. R. Sokal, A. Vaudor, and J. Kim, 1990, Approximate analysis of variance of spatially autocorrelated regional data, J. Class. 7:53-75.CrossRefGoogle Scholar
  46. Legendre, P., M. R. T. Dale, M. J. Fortin, J. Gurevitch, M. Hohn, and D. Myers, 2002, The consequences of spatial structure for the design and analysis of ecological field surveys, Ecography 25:601-615.CrossRefGoogle Scholar
  47. Legendre, P., M. R. T. Dale, M. J. Fortin, P. Casgrain, and J. Gurevitch, 2004, Effects of spatial structures on the results of field experiments, Ecology 85:3202-3214.CrossRefGoogle Scholar
  48. Levin, S. A., 1992, The problem of pattern and scale in ecology, Ecology 73:1943-1967.CrossRefGoogle Scholar
  49. Lilleskov, E. A., T. D. Bruns, T. R. Horton, D. L. Taylor, and P. Grogan, 2004, Detection of forest stand-level spatial structure in ectomycorrhizal fungal communities, FEMS Microbiol. Ecol. 49:319-332.CrossRefPubMedGoogle Scholar
  50. Ludwig, J. A., and J. F. Reynolds, 1988, Statistical ecology: a primer on methods and computing. Wiley, New York.Google Scholar
  51. Mackas, D. L., 1984, Spatial autocorrelation of plankton community composition in a continental shelf ecosystem, Limnol. Oceanogr. 29:451-471.CrossRefGoogle Scholar
  52. Mantel, N., 1967, The detection of disease clustering and a generalized regression approach, Cancer Res. 27:209-220.PubMedGoogle Scholar
  53. Manz, W., G. Arp, G. Schumann-Kindel, U. Szewzyk, and J. Reitner, 2000, Widefield de-convolution epifluorescence microscopy combined with fluorescence in situ hybridiza-tion reveals the spatial arrangement of bacteria in sponge tissue, J. Microbiol. Methods 40:125-134.CrossRefPubMedGoogle Scholar
  54. Miller, J. R., M. G. Turner, E. A. H. Smithwick, C. L. Dent, and E. H. Stanley, 2004, Spatial extrapolation: The science of predicting ecological patterns and processes, Bioscience 54:310-320.CrossRefGoogle Scholar
  55. Moran, P. A., 1950, Notes on continuous stochastic phenomena, Biometrika. 37:17-23.PubMedGoogle Scholar
  56. Morris, S. J., 1999, Spatial distribution of fungal and bacterial biomass in southern Ohio hardwood forest soils: fine scale variability and microscale patterns, Soil Biol. Biochem. 31:1375-1386.CrossRefGoogle Scholar
  57. Mottonen, M., E. Jarvinen, T. J. Hokkanen, T. Kuuluvainen, and R. Ohtonen, 1999, Spatial distribution of soil ergosterol in the organic layer of a mature Scots pine (Pinus sylvestris L.) forest, Soil Biol. Biochem. 31:503-516.CrossRefGoogle Scholar
  58. Murray, C. J., 2001, Sampling and data analysis for environmental microbiology, in: Manual of Environmental Microbiology, C. J. Hurst, R. L. Crawford, G. R. Knudsen, M. J. McInerney, and L. D. Stetzenbach, eds., American Society for Microbiology Press, Washington, DC, pp. 166-177.Google Scholar
  59. Nunan, N., K. Ritz, D. Crabb, K. Harris, K. J. Wu, J. W. Crawford, and I. M. Young, 2001, Quantification of the in situ distribution of soil bacteria by large-scale imaging of thin sections of undisturbed soil, FEMS Microbiol. Ecol. 37:67-77.CrossRefGoogle Scholar
  60. Nunan, N., K. J. Wu, I. M. Young, J. W. Crawford, and K. Ritz, 2003, Spatial distribution of bacterial communities and their relationships with the micro-architecture of soil, FEMS Microbiol. Ecol. 44:203-215.CrossRefPubMedGoogle Scholar
  61. Oberrath, R., and K. Bohning-Gaese, 2001, The Signed Mantel test to cope with auto-correlation in comparative analyses, J. Appl. Stat. 28:725-736.CrossRefGoogle Scholar
  62. Oden, N. L., and R. R. Sokal, 1986, Directional autocorrelation: an extension of spatial correlograms in two directions, Syst. Zool. 35:608-617.CrossRefGoogle Scholar
  63. O’Neill, R. V., and A. W. King, 1998, Homage to St. Michael; or, why are there so many books on scale?, in: Ecological Scale: Theory and Applications, D. L. Peterson and V. T. Parker, eds., Columbia University Press, New York, pp. 3-15.Google Scholar
  64. Parkin, T. B., 1987, Soil Microsites as a source of denitrification variability, Soil Sci. Soc. Am. J. 51:1194-1199.CrossRefGoogle Scholar
  65. Pennanen, T., E. Liski, E. Baath, V. Kitunen, J. Uotila, C. J. Westman, and H. Fritze, 1999, Structure of the microbial communities in coniferous forest soils in relation to site fertility and stand development stage, Microb. Ecol. 38:168-179.CrossRefPubMedGoogle Scholar
  66. Pielou, E. C., 1977, An Introduction to Mathematical Ecology, 2nd Edition. Wiley-Interscience, New York.Google Scholar
  67. Piontkovski, S. A., R. Williams, W. T. Peterson, O. A. Yunev, N. I. Minkina, V. L. Vladimirov, and A. Blinkov, 1997, Spatial heterogeneity of the planktonic fields in the upper mixed layer of the open ocean, Mar. Ecol. Prog. Ser. 148:145-154.CrossRefGoogle Scholar
  68. Platt, T., and K. L. Denman, 1975, Spectral analysis in ecology, Annu. Rev. Ecol. Syst. 6:189-210.CrossRefGoogle Scholar
  69. Renshaw, E., and E. D. Ford, 1984, The description of spatial pattern using two-dimensional spectral-analysis, Vegetatio 56:75-85.Google Scholar
  70. Ripley, B. D., 1976, The second order analysis of stationary point processes, J. Appl. Probab. 13:255-266.CrossRefGoogle Scholar
  71. Ripley, B. D., 1981, Spatial Statistics. Wiley, New York.CrossRefGoogle Scholar
  72. Robertson, G. P., 1987, Geostatistics in ecology: interpolating with known variance, Ecology 68:744-748.CrossRefGoogle Scholar
  73. Robertson, G. P., and D. W. Freckman, 1995, The spatial-distribution of nematode trophic groups across a cultivated ecosystem, Ecology 76:1425-1432.CrossRefGoogle Scholar
  74. Robertson, G. P., K. M. Klingensmith, M. J. Klug, E. A. Paul, J. R. Crum, and B. G. Ellis, 1997, Soil resources, microbial activity, and primary production across an agricultural ecosystem, Ecol. Appl. 7:158-170.CrossRefGoogle Scholar
  75. Rossi, J. -P., 1996, Statistical tool for soil biology. XI. Autocorrelogram and Mantel test, Eur. J. Soil Biol. 32:195-203.Google Scholar
  76. Rossi, R. E., D. J. Mulla, A. G. Journel, and E. H. Franz, 1992, Geostatistical tools for modeling and interpreting ecological spatial dependence, Ecol. Monogr. 62:277-314.CrossRefGoogle Scholar
  77. Saetre, P., 1999, Spatial patterns of ground vegetation, soil microbial biomass and activity in a mixed spruce-birch stand, Ecography 22:183-192.CrossRefGoogle Scholar
  78. Saetre, P., and E. Baath, 2000, Spatial variation and patterns of soil microbial community structure in a mixed spruce-birch stand, Soil Biol. Biochem. 32:909-917.CrossRefGoogle Scholar
  79. Schlesinger, W. H., J. A. Raikes, A. E. Hartley, and A. E. Cross, 1996, On the spatial pattern of soil nutrients in desert ecosystems, Ecology 77:364-374.CrossRefGoogle Scholar
  80. Schneider, D. C., 1994, Quantitative Ecology - Spatial and Temporal Scaling. Academic Press, San Diego.Google Scholar
  81. Seuront, L., F. Schmitt, Y. Lagadeuc, D. Schertzer, and S. Lovejoy, 1999, Universal multi-fractal analysis as a tool to characterize multiscale intermittent patterns: example of phyto-plankton distribution in turbulent coastal waters, J. Plankton Res. 21:877-922.CrossRefGoogle Scholar
  82. Smith, J. L., J. J. Halvorson, and H. J. Bolton, 1994, Spatial relationships of soil microbial biomass and C and N mineralization in a semi-arid shrub-steppe ecosystem, Soil Biol. Biochem. 26:1151-1159.CrossRefGoogle Scholar
  83. Smouse, P. E., J. C. Long, and R. R. Sokal, 1986, Multiple regression and correlation extensions of the Mantel test of matrix correspondence, Syst. Zool. 35:627-632.CrossRefGoogle Scholar
  84. Sokal, R., 1979, Testing statistical significance of geographic variation patterns, Syst. Zool. 28:227-232.CrossRefGoogle Scholar
  85. Sokal, R. R., 1986, Spatial data analysis and historical processes, in: Data Analysis and Informatics, IV, E. Diday, Y. Escoufier, L. Lebart, J. Pages, Y. Schertman, and R. Tomassone, eds., North Holland, Amsterdam, pp. 29-43.Google Scholar
  86. Sokal, R. R., and N. L. Oden, 1978, Spatial autocorrelation in biology. 2. Some biological implications and four applications of evolutionary and ecological interest, Biol. J. Linn. Soc. 10:229-249.CrossRefGoogle Scholar
  87. Sokal, R. R., J. Bird, and B. Riska, 1980, Geographic variation in Pemphigus populicaulis (Insecta: Aphididae) in eastern North America, Biol. J. Linn. Soc. 14:163-200.CrossRefGoogle Scholar
  88. Sokal, R. R., N. L. Oden, B. A. Thomson, and J. H. Kim, 1993, Testing for regional differences in means - distinguishing inherent from spurious spatial autocorrelation by restricted randomization, Geogr. Anal. 25:199-210.Google Scholar
  89. Star, J. L., and M. M. Mullin, 1981, Zooplankton assemblages in three areas of the North Pacific as revealed by continuous horizontal transects, Deep Sea Res. 28:1303-1322.CrossRefGoogle Scholar
  90. Steele, J. H., and E. W. Henderson, 1992, A simple-model for plankton patchiness, J. Plankton Res. 14:1397-1403.CrossRefGoogle Scholar
  91. Stein, A., J. Riley, and N. Halberg, 2001, Issues of scale for environmental indicators, Agric. Ecosyst. Environ. 87:215-232.CrossRefGoogle Scholar
  92. Thompson, S. K., 2002, Sampling. Wiley-Interscience, New York.Google Scholar
  93. Troussellier, M., P. Lebaron, B. Baleux, and P. Got, 1993, Spatial-distribution patterns of heterotrophic bacterial populations in a coastal ecosystem (Thau Basin, France), Estuar. Coast. Shelf Sci. 36:281-293.CrossRefGoogle Scholar
  94. Turner, M. G., 1989, Landscape ecology - the effect of pattern on process, Ann. Rev. Ecol. Syst. 20:171-197.CrossRefGoogle Scholar
  95. Turner, M. G., and S. R. Carpenter, 1999, Spatial variability in ecosystem function-Introduction, Ecosystems 2:383-383.CrossRefGoogle Scholar
  96. Upton, G., and B. Fingleton, 1985, Spatial Data Analysis by Example. Volume 1: Point Pattern and Quantitative Data. Wiley, Chichester, England.Google Scholar
  97. van Es, H. M., and C. L. van Es, 1993, Spatial nature of randomization and its effect on the outcome of field experiments, Agron. J. 85:420-428.CrossRefGoogle Scholar
  98. Walter, C., A. B. McBratney, R. A. V. Rossel, and J. A. Markus, 2005, Spatial point-process statistics: concepts and application to the analysis of lead contamination in urban soil, Environmetrics 16:339-355.CrossRefGoogle Scholar
  99. Wiegand, T., and K. A. Moloney, 2004, Rings, circles, and null-models for point pattern analysis in ecology, Oikos 104:209-229.CrossRefGoogle Scholar
  100. Wu, J. G., and S. A. Levin, 1994, A spatial patch dynamic modeling approach to pattern and process in an annual grassland, Ecol. Monogr. 64:447-464.CrossRefGoogle Scholar

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© Springer 2007

Authors and Affiliations

  • Rima B. Franklin
    • 1
  • Aaron L. Mills
    • 2
  1. 1.Department of BiologyVirginia Commonwealth UniversityRichmondUSA
  2. 2.Laboratory of Microbial EcologyUniversity of VirginiaCharlottesvilleUSA

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