Community Ecology

, Volume 10, Issue 2, pp 173–181 | Cite as

Antibiotic resistance profiles of soil bacterial communities over a land degradation gradient

  • R. DoiEmail author
  • P. Sahunalu
  • C. Wachrinrat
  • S. Teejuntuk
  • K. Sakurai


This study profiled soils over a land degradation gradient to obtain formulae as integrative measures for describing the gradient as a result of deforestation in Thailand. We applied antibiotic resistance most-probable-number profiling to the soil bacterial communities, and then described the gradient. Soil samples were collected on the gradient represented by dry evergreen forest (the original vegetation), dry deciduous forest (moderately disturbed) and bare ground (the most degraded) in February (dry season), March (shortly after temporal precipitation) and June (rainy season) 2001. In the period of this study, the degradation was consistently shown as soil conditions like sandy texture, high bulk density, lower pH, high exchangeable acidity, poor mineral and organic nutrients and dryness. Soil fertility index and soil evaluation factor, as the integrative measures of the intensity of land degradation, were described by scores on the first or the second principal component derived from the soil bacterial community profiles for each sampling time (R>0.457, p<0.043) and by scores on the third and fourth principal components for the overall data set (R>0.501, p<0.001), suggesting great dry to moist seasonal effects. Further, the changes had significant relationships with gradients of soil moisture content, acidity and/or soil nitrogen content. The data sets on the soil bacterial community profiles had more complicated data structures than the physicochemical data sets, suggesting effects of the physicochemical changes on the soil bacterial community. The differences between the bacterial and the physicochemical aspects suggest that it is advantageous to observe multiple aspects of soil quality when describing a soil-related gradient of interest.


Deforestation Land degradation Multivariate profiling Soil bacterial community Tropics 



Principal Component.


Sahunalu and Dhanmanonda (1995) abd Kanzaki et al. (1995) for tree species in the dry deciduous forest and the dry evergreen forest, respectively 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Beare, M.H., Coleman, D.C., Crossley, D.A., Hendrix, P.F. and Odum, E.P. 1995. A hierarchical approach to evaluating the significance of soil biodiversity to biogeochemical cycling. Plant Soil. 170: 5–22.Google Scholar
  2. Borneman, J. and Triplett, E.W. 1997. Molecular microbial diversity in soils from eastern Amazonia: evidence for unusual microorganisms and microbial population shifts associated with deforestation. Appl. Environ. Microbiol. 63: 2647–2653.PubMedPubMedCentralGoogle Scholar
  3. Böckelmann, U., Szewzyk, U. and Grohmann, E. 2003. A new enzymatic method for the detachment of particle associated soil bacteria. J. Microbiol. Meth. 55: 201–211.Google Scholar
  4. Brønstad, K., Drönen, K., Øvreas, L. and Torsvik, V. 1996. Phenotypic diversity and antibiotic resistance in soil bacterial communities. J. Ind. Microbiol. 17: 253–259.Google Scholar
  5. Cuenca, G. and Meneses, E. 1996. Diversity patterns of arbuscular mycorrhizal fungi associated with cacao in Venezuela. Plant Soil. 183: 315–322.Google Scholar
  6. de Boer, W., Folman, L.B., Summerbell, R.C. and Boddy, L. 2005. Living in a fungal world: impact of fungi on soil bacterial niche development. FEMS Microbiol. Rev. 29: 795–811.PubMedGoogle Scholar
  7. de Man, J.C. 1975. The probability of most probable numbers. Eur. J. Appl. Microbiol. 1: 67–78.Google Scholar
  8. Depee, J.L. and Rotenberry, J.T. 2008. Scale-dependent habitat use by fall migratory birds: vegetation structure, floristics, and geography. Ecol. Monogr. 78: 461–487.Google Scholar
  9. Doi, R. 2004. Soil bacterial community profiling with Biolog kinetic and antibiotic resistance most probable number approaches showed multidimensionality of land degradation. Int. J. Agric. Biol. 6: 284–288.Google Scholar
  10. Doi, R. 2005. Human-induced land degradation gradient shown by antibiotic susceptibility profiles of bacterial communities and physico-chemical soil quality characteristics. Nat. Hum. Act. 9: 33–45.Google Scholar
  11. Doi, R. and Puriyakorn, B. 2007. Physico-chemical and bacterial profiling of soils for describing a land degradation gradient. Curr. Sci. 92: 1050–1054.Google Scholar
  12. Doi, R. and Ranamukhaarachchi, S.L. 2007. Integrative evaluation of rehabilitative effects of Acacia auriculiformis on degraded soil. J. Trop. For. Sci. 19: 150–163.Google Scholar
  13. Doi, R. and Ranamukhaarachchi, S.L. 2009. Soil dehydrogenase in a land degradation-rehabilitation gradient: observations from a savanna site with a wet/dry seasonal cycle. Rev. Biol. Trop. 57: 223–234,PubMedGoogle Scholar
  14. Doi, R. and Sakurai, K. 2003. Soil environmental factors relating to diversity of culturable soil bacterial communities in the Sakaerat Environmental Research Station, Thailand. Tropics 12: 185–200.Google Scholar
  15. Doi, R. and Sakurai, K. 2004. Principal components derived from soil physico-chemical data explained a land degradation gradient, and suggested the applicability of new indexes for estimation of soil productivity in the Sakaerat Environmental Research Station, Thailand. Int. J. Sustain. Dev. World Ecol. 11: 298–311.Google Scholar
  16. Doi, R., Kaeoniam, P., Placksanoi, J., Sewakhonburi, S. and Jiraphong, J. 2008. Changes in antibiotic resistance profile of soil bacterial community in association with land degradation. In: Huang, Q. Huang, P.M. and Violante, A. (eds), Soil Mineral Microbe-Organic Interactions. Springer Berlin Heidelberg, Germany. pp. 317–344.Google Scholar
  17. Doyle, J.D. and Stotzky, G. 1993. Methods for the detection of changes in the microbial ecology of soil caused by the introduction of microorganisms. Microb. Releases 2: 63–72.Google Scholar
  18. Fenchel, T., King, G and Blackburn, H. 1998. Bacterial Biogeochemistry: The Ecophysiology of Mineral Cycling. Academic Pres, London, UK.Google Scholar
  19. Garland, J.L. 1996. Analytical approaches to the characterization of samples of microbial communities using patterns of potential C source utilization. Soil Biol. Biochem. 28: 213–221.Google Scholar
  20. Garland, J.L. and Mills, A.L. 1991. Classification and characterization of heterotrophic microbial communities on the basis of patterns of community-level sole-carbon-source utilization. Appl. Environ. Microbiol. 57: 2351–2359.PubMedPubMedCentralGoogle Scholar
  21. Hart, S.C., DeLuca, T.H., Newman, G.S., MacKenzie, M.D. and Boyle, S.I. 2005. Post-fire vegetative dynamics as drivers of microbial community and function in forest soils. For. Ecol. Manage. 220: 166–184.Google Scholar
  22. Hemerik, L. and Brussaard, L. 2002. Diversity of soil macro-invertebrates in grasslands under restoration succession. Eur. J. Soil Biol. 38: 145–150.Google Scholar
  23. Heritage, J., Evans, E.G.V. and Killington, R.A. 1999. Microbiology in Action. Cambridge University Press, Cambridge, UK.Google Scholar
  24. Jha, D.K., Sharma, G.D. and Mishra, R.R. 1992. Soil microbial population numbers and enzyme activities in relation to altitude and forest degradation. Soil Biol. Biochem. 24: 761–767.Google Scholar
  25. Kaiser, H.F. 1960. The application of electronic computers to factor analysis. Educ. Psychol. Meas. 20: 141–151.Google Scholar
  26. Kanzaki, M., Yoda, K. and Dhanmanonda, K. 1995. Mosaic structure and tree growth pattern in a monodominant tropical seasonal evergreen forest in Thailand. In: Box, E.O., Peet, R.K., Masuzawa, T., Yamada, I., Fujiwara, K. and Maycock, P.F. (eds.), Vegetation Science in Forestry. Kluwer Publishers, Netherlands. pp. 495–513.Google Scholar
  27. Kirk, J.L., Beaudette, L.A., Hart, M., Moutoglis, P., Khironomos, J.N., Lee, H. and Trevors, J.T. 2004. Methods of studying soil microbial diversity. J. Microbiol. Meth. 58: 169–188.Google Scholar
  28. Kourtev, P.S., Ehrenfeld, J.G. and Häggblom, M. 2003. Experimental analysis of the effect of exotic and native plant species on the structure and function of soil microbial communities. Soil Biol. Biochem. 35: 895–905.Google Scholar
  29. Lorian, V. 1996. Antibiotics in Laboratory Medicine, 4th edition. Williams and Wilkins, Baltimore.Google Scholar
  30. Lu, D., Moran, E. and Mausel, P. 2002. Linking Amazonian secondary succession forest growth to soil properties. Land Degrad. Dev. 13: 331–343.Google Scholar
  31. McCune, B., Grace, J.B. and Urban, J.B. 2002. Analysis of Ecological Communities. M and M Software Design, Glenden Beach, Oregon.Google Scholar
  32. McInroy, J.A., Musson, G., Wei, G. and Kloepper, J.W. 1996. Masking of antibiotic-resistance upon recovery of endophytic bacteria. Plant Soil 186: 213–218.Google Scholar
  33. Moran, E.F., Brondízio, E.S., Tucker, J.M., da Silva-Forsberg, M.C., McCracken, S. and Falesi, I. 2000. Effects of soil fertility and land use on forest succession in Amazônia. For. Ecol. Manage. 139, 93–108.Google Scholar
  34. Oline, D.K. and Grant, M.C. 2002. Scaling patterns of biomass and soil properties: an empirical analysis. Landscape Ecol. 17: 13–26.Google Scholar
  35. Pankhurst, C.E., Doube, B.M. and Gupta, V.V.S.R. 1997. Biological Indicators of Soil Health. CAB International. Wallingford, UK.Google Scholar
  36. Pankhurst, C.E., Yu, S., Hawke, B.G. and Harch, B.D. 2001. Capacity of fatty acid profiles and substrate utilization patterns to describe differences in soil microbial communities associated with increased salinity or alkalinity at three locations in South Australia. Biol. Fertil. Soil. 33: 201–217.Google Scholar
  37. Pérez-de-Mora, A., Burgos, P., Madejón, E., Cabrera, F., Jaeckel, P. and Schloter, M. 2006. Microbial community structure and function in a soil contaminated by heavy metals: effects of plant growth and different amendments. Soil Biol. Biochem. 38: 327–341.Google Scholar
  38. Pillai, S.D. and Pepper, I.L. 1991. Transposon Tn5 as an identifiable marker in rhizobia survival and genetic stability of Tn5 mutant bean rhizobia under temperature stressed conditions in desert soils. Microb. Ecol. 21: 21–33.PubMedGoogle Scholar
  39. Poonpilai, W. and Malee, S. 1973. Soil and root fungi in Sakaerat dry evergreen forest. Kasetsart J. 7: 109–116.Google Scholar
  40. Póte, J., Ceccherini, M.T., Van, V.T., Rosselli, W., Wildi, W., Simonet, P. and Vogel, T.M. 2003. Fate and transport of antibitoic resistance genes in saturated soil columns. Eur. J. Soil Biol. 39: 65–71.Google Scholar
  41. Rahal, J.J., Urban, C., Horn, D., Freeman, K., Segal-Maurer, S., Maurer, J., Mariano, N., Marks, S., Burns, J.M., Dominick, D. and Lim, M. 1998. Glass restriction of cephalosporin use to control total cephalosporin resistance in nosocomial Klebsiella. J. Amer. Med. Assoc. 280: 1233–1237.Google Scholar
  42. Ramos, M.L.G., Magalhaes, N.F.M. and Boddey, R.M. 1987. Native and inoculated rhizobia isolated from field grown Phaseolus vulgaris: effects of liming an acid soil on antibiotic resistance. Soil Biol. Biochem. 19: 179–185.Google Scholar
  43. Sahunalu, P. and Dhanmanonda, P. 1995. Structure and dynamics of dry dipterocarp forest, Sakaerat, northeastern Thailand. In: Box, E.O., Peet, R.K., Masuzawa, T., Yamada, I., Fujiwara, K. and Maycock, P.F. (eds.), Vegetation Science in Forestry. Kluwer Publishers, Netherlands. pp. 465–494.Google Scholar
  44. Sakurai, K., Tanaka, S., Ishizuka, S. and Kanzaki, M. 1998. Differences in soil properties of dry evergreen and dry deciduous forests in the Sakaerat Environmental Research Station. Tropics 8: 61–80.Google Scholar
  45. Sena, M.M., Poppi, R.J., Frighetto, R.T.S. and Valarini, P.J. 2000. Avaliação do uso de métodos quimiométricos em análise de solos. Quim. Nova 23: 547–556.Google Scholar
  46. Singleton, P. 1999. Bacteria in Biology, Biotechnology, and Medicine. 5th edition. John Wiley & Sons, West Sussex, UK.Google Scholar
  47. Smalla, K., Heuer, H., Gotz, A., Niemeyer, D., Krogerrecklenfort, E. and Tietze, E. 2000. Exogenous isolation of antibiotic resistance plasmids from piggery manure slurries reveals a high prevalence and diversity of IncQ-like plasmids. Appl. Environ. Microbiol. 66: 4854–4862.PubMedPubMedCentralGoogle Scholar
  48. Sollod, C.C., Jenns, A.E. and Daub, M.E. 1992. Mechanism of defense against photosensitizers in fungi. Appl. Environ. Microbiol. 58: 444–449.PubMedPubMedCentralGoogle Scholar
  49. ter Braak, C.J.F. and Šmilauer, P. 1998. Canoco Reference Manual and Users’ Guide to Canoco for Windows: Software for Canonical Community Ordination (vesion 4). Microcomputer Power, Ithaca, NY.Google Scholar
  50. Vessey, J.K. 2003. Plant growth promoting rhizobacteria as biofertilizers. Plant Soil 255: 571–586.Google Scholar
  51. Waldrop, M.P., Balser, T.C. and Firestone, M.K. 2000. Linking microbial community composition to function in a tropical soil. Soil Biol. Biochem. 32: 1837–1846.Google Scholar
  52. Wali, M. K. 1999. Ecological succession and the rehabilitation of disturbed terrestrial ecosystem. Plant Soil 213: 195–220.Google Scholar
  53. Westover, K.M., Kennedy, A.C. and Kelley, S.E. 1997. Patterns of rhizosphere microbial community structure associated with co-occurring plant species. J. Ecol. 85: 863–873.Google Scholar
  54. Widmer, F., Flieâbach, A., Laczkó, E., Shulze-Aurich, J. and Zeyer, J. 2001. Assessing soil biological characteristics: a comparison of bulk soil community DNA-, PLFA, and BiologTM -analyses. Soil Biol. Biochem. 33: 1029–1036.Google Scholar
  55. Wrenn, B.A. and Venosa, A.D. 1996. Selective enumeration of aromatic and aliphatic hydrocarbon degrading bacteria by a most-probable-number procedure. Can. J. Microbiol. 42: 252–258.PubMedGoogle Scholar
  56. Yanai, J., Sawamoto, T., Oe, T., Kusa, K., Yamakawa, K., Sakamoto, K., Naganawa, T., Inubushi, K, Hatano, R. and Kosaki, T. 2003. Spatial variability of nitrous oxide emissions and their soil-related determining factors in an agricultural field. J. Environ. Qual. 32: 1965–1977.PubMedGoogle Scholar
  57. Yemefack, M., Rossiter, D.G. and Njomgang, R. 2006. Developing a minimum data set for characterizing soil dynamics in shifting cultivation systems. Soil Till. Res. 86: 84–98.Google Scholar
  58. Zar, J.H. 1999. Biostatistical Analysis. Prentice-Hall, New Jersey.Google Scholar

Copyright information

© Akadémiai Kiadó, Budapest 2009

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Authors and Affiliations

  • R. Doi
    • 1
    • 4
    Email author
  • P. Sahunalu
    • 2
  • C. Wachrinrat
    • 2
  • S. Teejuntuk
    • 2
  • K. Sakurai
    • 3
  1. 1.Graduate School of Agricultural ScienceEhime UniversityMatsuyamaJapan
  2. 2.Department of Silviculture, Faculty of ForestryKasetsart UniversityChatuchak, BangkokThailand
  3. 3.Faculty of AgricultureKochi UniversityKochiJapan
  4. 4.AFE Building, School of Environment, Resources and DevelopmentAsian Institute of TechnologyKlong LuangThailand

Personalised recommendations