Microbial Ecology

, Volume 64, Issue 2, pp 474–484 | Cite as

Tropical Soil Bacterial Communities in Malaysia: pH Dominates in the Equatorial Tropics Too

  • Binu M. Tripathi
  • Mincheol Kim
  • Dharmesh Singh
  • Larisa Lee-Cruz
  • Ang Lai-Hoe
  • A. N. Ainuddin
  • Rusea Go
  • Raha Abdul Rahim
  • M. H. A. Husni
  • Jongsik Chun
  • Jonathan M. Adams
Soil Microbiology


The dominant factors controlling soil bacterial community variation within the tropics are poorly known. We sampled soils across a range of land use types—primary (unlogged) and logged forests and crop and pasture lands in Malaysia. PCR-amplified soil DNA for the bacterial 16S rRNA gene targeting the V1–V3 region was pyrosequenced using the 454 Roche machine. We found that land use in itself has a weak but significant effect on the bacterial community composition. However, bacterial community composition and diversity was strongly correlated with soil properties, especially soil pH, total carbon, and C/N ratio. Soil pH was the best predictor of bacterial community composition and diversity across the various land use types, with the highest diversity close to neutral pH values. In addition, variation in phylogenetic structure of dominant lineages (Alphaproteobacteria, Beta/Gammaproteobacteria, Acidobacteria, and Actinobacteria) is also significantly correlated with soil pH. Together, these results confirm the importance of soil pH in structuring soil bacterial communities in Southeast Asia. Our results also suggest that unlike the general diversity pattern found for larger organisms, primary tropical forest is no richer in operational taxonomic units of soil bacteria than logged forest, and agricultural land (crop and pasture) is actually richer than primary forest, partly due to selection of more fertile soils that have higher pH for agriculture and the effects of soil liming raising pH.


Bacterial Community Actinobacteria Bacterial Diversity Terminal Restriction Fragment Length Polymorphism Alphaproteobacteria 
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.



This work was supported by a Brain Gain grant from the Government of Malaysia and by SNU new faculty research grant to JM Adams. BM Tripathi was supported by the Graduate Scholarship for Excellent Foreign Students Program, SNU, South Korea.

Supplementary material

248_2012_28_MOESM1_ESM.doc (388 kb)
ESM 1 (DOC 388 kb)


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Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Binu M. Tripathi
    • 1
  • Mincheol Kim
    • 1
  • Dharmesh Singh
    • 1
  • Larisa Lee-Cruz
    • 1
  • Ang Lai-Hoe
    • 2
  • A. N. Ainuddin
    • 3
  • Rusea Go
    • 3
  • Raha Abdul Rahim
    • 4
  • M. H. A. Husni
    • 5
  • Jongsik Chun
    • 1
  • Jonathan M. Adams
    • 1
    • 3
  1. 1.Department of Biological SciencesSeoul National UniversitySeoulRepublic of Korea
  2. 2.Division of Forest BiotechnologyForest Research Institute of Malaysia (FRIM)KepongMalaysia
  3. 3.INTROPUniversiti Putra MalaysiaSerdangMalaysia
  4. 4.Institute of Bioscience, Faculty of Biotechnology and Biomolecular SciencesUniversiti Putra MalaysiaSerdangMalaysia
  5. 5.Department of Land Management, Faculty of AgricultureUniversiti Putra MalaysiaSerdangMalaysia

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