in

Differential responses of termite gut bacterial and fungal community to tropical forest conversion


Abstract

Land-use change significantly impacts biodiversity, but its effects on the gut microbiomes of soil invertebrates remain poorly understood. We investigated how forest conversion to rubber plantations alters bacterial and fungal diversity, composition, and function in termite guts within a biodiversity hotspot Xishuangbanna, China. Our results showed that termites from natural forests harbored higher gut bacterial diversity than those from plantations, with effects varying across host species. Fungal diversity was shaped primarily by host species identity, with Odontotermes yunnanensis exhibiting the highest diversity index. While termite species solely governed bacterial community composition, both termite species and forest type shaped fungal composition. Fungal community variation correlated with local soil properties, whereas bacterial variation only associated with soil pH. Termites shared 17% of core gut bacteria (e.g., Bacillus, Pseudomonas, Mycobacterium) but 100% of fungi with the environment. Co-occurrence networks exhibited species-specific responses to forest conversion. Host species (Ancistrotermes and Odontotermes) predicted bacterial functional potential, but both forest type and host species influenced fungal functional potential. These findings demonstrate that termite gut microbiome responses to land-use change are multifaceted and taxon-specific, highlighting their role in ecosystem functional resilience under anthropogenic disturbance.

Similar content being viewed by others

Tree species determine soil microbial diversity: variation in fungal and bacterial communities in temperate forests

Patterns in soil microbial diversity across Europe

Structural characteristics of gut microbiota in Pseudogastromyzon fasciatus and their ecological implications

Data availability

Data available from the Dryad Digital Repository with http://datadryad.org/share/fnKA1xj1Z9F2f3p1hMETJdP-fepZMKtPgnWnenZCKAU

The whole raw and processed data available from the https://doi.org/10.6084/m9.figshare.31602532. Amplicon sequences are available on the NCBI sequence read archive under the PRJNA1437508.

References

  1. Newbold, T. et al. Global effects of land use on local terrestrial biodiversity. Nature 520, 45–50 (2015).

    Google Scholar 

  2. Barelli, C. et al. Habitat fragmentation is associated to gut microbiota diversity of an endangered primate: implications for conservation. Sci. Rep. 5, 1–12 (2015).

    Google Scholar 

  3. San Juan, P. A., Hendershot, J. N., Daily, G. C. & Fukami, T. Land-use change has host-specific influences on avian gut microbiomes. ISME J. 14, 318–321 (2020).

    Google Scholar 

  4. Singh, J., Eisenhauer, N., Schädler, M. & Cesarz, S. Earthworm gut passage reinforces land-use effects on soil microbial communities across climate treatments. Appl. Soil Ecol. 164, 103919 (2021).

    Google Scholar 

  5. Griffiths, H. M., Ashton, L. A., Evans, T. A., Parr, C. L. & Eggleton, P. Termites can decompose more than half of deadwood in tropical rainforest. Curr. Biol. 29, R118–R119 (2019).

    Google Scholar 

  6. Zanne, A. E. et al. Termite sensitivity to temperature affects global wood decay rates. Science 377, 1440–1444 (2022).

    Google Scholar 

  7. Maurice, N. & Erdei, L. Termite Gut Microbiome. Termites and Sustainable Management https://doi.org/10.1007/978-3-319-72110-1_4 (2018).

  8. Trevelline, B. K., Fontaine, S. S., Hartup, B. K. & Kohl, K. D. Conservation biology needs a microbial renaissance: a call for the consideration of host-associated microbiota in wildlife management practices. P. Roy. Soc. B Biol. Sci. 286, 20182448 (2019).

    Google Scholar 

  9. Mikaelyan, A. et al. Diet is the primary determinant of bacterial community structure in the guts of higher termites. Mol. Ecol. 24, 5284–5295 (2015).

    Google Scholar 

  10. Arora, J. et al. The functional evolution of termite gut microbiota. Microbiome 10, 1–23 (2022).

    Google Scholar 

  11. Tanaka, H. et al. Influence of the diet components on the symbiotic microorganisms community in hindgut of Coptotermes formosanus Shiraki. Appl. Microbiol. Biotechnol. 71, 907–917 (2006).

    Google Scholar 

  12. Menezes, L. R. et al. Dietary resilience of termite gut microbiota and enzymatic function reflects feeding strategy. Front. Ecol. Evol. 13, 1625443 (2025).

    Google Scholar 

  13. Liu, S. et al. Comparative responses of termite functional and taxonomic diversity to land-use change. Ecol. Entomol. 44, 762–770 (2019).

    Google Scholar 

  14. Nguyen, P. N. & Rehan, S. M. The effects of urban land use gradients on wild bee microbiomes. Front. Microbiol. 13, 1–15 (2022).

    Google Scholar 

  15. Liu, C. et al. A guide for comparing microbial co-occurrence networks. iMeta 2, e71 (2023).

  16. Yu, G., Chen, Y. & Guo, Y. Design of integrated system for heterogeneous network query terminal. J. Comput. Appl. 29, 2191–2193 (2009).

    Google Scholar 

  17. Fernandez De Landa, G. et al. The gut microbiome of solitary bees is mainly affected by pathogen assemblage and partially by land use. Environ. Microbiome 18, 38 (2023).

    Google Scholar 

  18. Youngblut, N. D. et al. Host diet and evolutionary history explain different aspects of gut microbiome diversity among vertebrate clades. Nat. Commun. 10, 1–15 (2019).

    Google Scholar 

  19. Mallott, E. K. & Amato, K. R. Host specificity of the gut microbiome. Nat. Rev. Microbiol. 19, 639–653 (2021).

    Google Scholar 

  20. Sadeghi, J., Chaganti, S. R., Johnson, T. B. & Heath, D. D. Host species and habitat shape fish-associated bacterial communities: phylosymbiosis between fish and their microbiome. Microbiome 11, 1–19 (2023).

    Google Scholar 

  21. Wang, Y. et al. High-resolution maps show that rubber causes substantial deforestation. Nature 623, 340–346 (2023).

    Google Scholar 

  22. Shi, B. et al. Seasonal and land-use impact on the stable isotopic signatures of termites. Appl. Soil Ecol. 215, 106439 (2025).

    Google Scholar 

  23. Abdul Rahman, N. et al. A molecular survey of Australian and North American termite genera indicates that vertical inheritance is the primary force shaping termite gut microbiomes. Microbiome 3, 1–16 (2015).

    Google Scholar 

  24. Marynowska, M. et al. Compositional and functional characterisation of biomass-degrading microbial communities in guts of plant fibre- and soil-feeding higher termites. Microbiome 8, 1–18 (2020).

    Google Scholar 

  25. Makonde, H. M. et al. Diversity of Termitomyces associated with fungus-farming termites assessed by cultural and culture-independent methods. PLoS ONE 8, e56464 (2013).

    Google Scholar 

  26. Tedersoo, L. et al. Shotgun metagenomes and multiple primer pair-barcode combinations of amplicons reveal biases in metabarcoding analyses of fungi. MycoKeys 10, 1–43 (2015).

    Google Scholar 

  27. Carter, M. R. & Gregorich, E. G. Soil Sampling and Methods of Analysis (CRC Press, 2007).

  28. Parada, A. E., Needham, D. M. & Fuhrman, J. A. Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples. Environ. Microbiol. 18, 1403–1414 (2016).

    Google Scholar 

  29. Toju, H., Guimarães, P. R., Olesen, J. M. & Thompson, J. N. Assembly of complex plant-fungus networks. Nat. Commun. 5, 1–7 (2014).

    Google Scholar 

  30. Callahan, B. J. et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Google Scholar 

  31. Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009).

    Google Scholar 

  32. Nilsson, R. H. et al. The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res. 47, D259–D264 (2019).

    Google Scholar 

  33. Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2-approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).

    Google Scholar 

  34. Bolyen, E. et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat. Biotechnol. 37, 852–857 (2019).

    Google Scholar 

  35. Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

    Google Scholar 

  36. Wang, Y., Naumann, U., Wright, S. T. & Warton, D. I. mvabund-an R package for model-based analysis of multivariate abundance data. Methods Ecol. Evol. 3, 471–474 (2012).

    Google Scholar 

  37. Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).

    Google Scholar 

  38. Csárdi, G. & Nepusz, T. The igraph software package for complex network research. (2006). InterJournal, Complex Systems, 1695. https://igraph.org.

  39. Michaud, C. et al. Efficient but occasionally imperfect vertical transmission of gut mutualistic protists in a wood-feeding termite. Mol. Ecol. 29, 308–324 (2020).

    Google Scholar 

  40. Bourguignon, T. et al. Rampant host switching shaped the termite gut microbiome. Curr. Biol. 28, 649–654.e2 (2018).

    Google Scholar 

  41. Huang, X. F., Bakker, M. G., Judd, T. M., Reardon, K. F. & Vivanco, J. M. Variations in diversity and richness of gut bacterial communities of termites (Reticulitermes flavipes) fed with grassy and woody plant substrates. Microb. Ecol. 65, 531–536 (2013).

    Google Scholar 

  42. Kerfahi, D., Tripathi, B. M., Dong, K., Go, R. & Adams, J. M. Rainforest conversion to rubber plantation may not result in lower soil diversity of bacteria, fungi, and nematodes. Microb. Ecol. 72, 359–371 (2016).

    Google Scholar 

  43. Lan, G. et al. Change in soil microbial community compositions and diversity following the conversion of tropical forest to rubber plantations in Xishuangbanan, Southwest China. Trop. Conserv. Sci. 10, 1940082917733230 (2017).

    Google Scholar 

  44. Lan, G. et al. Network complexity of rubber plantations is lower than tropical forests for soil bacteria but not for fungi. Soil 8, 149–161 (2022).

    Google Scholar 

  45. Guo, C. et al. Seasonally changing interactions of species traits of termites and trees promote complementarity in coarse wood decomposition. Ecol. Lett. 27, e70002 (2024).

    Google Scholar 

  46. Viana-Junior, A. B., Côrtes, M. O., Cornelissen, T. G. & Neves, F. D. S. Interactions between wood-inhabiting fungi and termites: a meta-analytical review. Arthropod Plant Interact. 12, 229–235 (2018).

    Google Scholar 

  47. Qiao, Y. et al. Nutrient status changes bacterial interactions in a synthetic community. Appl. Environ. Microbiol. 90, 1–16 (2024).

    Google Scholar 

  48. Calusinska, M. et al. Integrative omics analysis of the termite gut system adaptation to miscanthus diet identifies lignocellulose degradation enzymes. Commun. Biol. 1–12, https://doi.org/10.1038/s42003-020-1004-3 (2020).

  49. Williamson, E. M., Hammer, T. J., Hogendoorn, K. & Eisenhofer, R. Blanking on blanks: few insect microbiota studies control for contaminants. mBio 16, e02658-24 (2025).

    Google Scholar 

  50. Douglas, G. M. et al. PICRUSt2 for prediction of metagenome functions. Nat. Biotechnol. 38, 685–688 (2020).

Download references

Acknowledgements

We thank Chen Defu, Chen Zhiling and Center for Gardening and Horticulture, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences for field and laboratory assistance. This work was supported by the National Natural Science Foundation of China (41977057, 32201421), the Fundamental and Interdisciplinary Disciplines Breakthrough Plan of the Ministry of Education of China (JYB2025XDXM902), NSFC-UNEP (42061144005), Shenzhen Science and Technology Program (JCYJ20240813151036047) and research grant of the Sun Yat-sen University Bairen Plan (77010-18841290).

Author information

Authors and Affiliations

Authors

Contributions

Z.J., Y.M., and S.L. conceived the idea of the study and designed the study; Z.J., Y.M., and S.L. conducted the data analysis and wrote the paper; Z.J., Y.M., and S.L. collected the data; W.W., J.B., F.C., S.M., S.X., and X.Y. contributed to the writing (review and editing). All authors revised the manuscript and approved the final version of the manuscript.

Corresponding authors

Correspondence to
Yuanyuan Meng or Shengjie Liu.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Communications Biology thanks Ajay Harit, Alberto Arab, and Amrita Chakraborty for their contribution to the peer review of this work. Primary handling editors: Rupinder Kaur and Tobias Goris. A peer review file is available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary Information (download PDF )

Supplementary Table S9 (download PDF )

Reporting Summary (download PDF )

Transparent Peer Review File (download PDF )

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions

About this article

Cite this article

Jia, Z., Meng, Y., Wang, W. et al. Differential responses of termite gut bacterial and fungal community to tropical forest conversion.
Commun Biol (2026). https://doi.org/10.1038/s42003-026-09939-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s42003-026-09939-7


Source: Ecology - nature.com

The influence of human activities on the microbial community structure and function of a karst cave in southwest China

Honey environmental DNA reveals entomological fingerprints through dual mitochondrial cytochrome c oxidase subunit 1 (COI) and cytochrome b (CYTB) metabarcoding

Back to Top