Skip to main content

Advertisement

Log in

Soil Bacterial Community Changes in Sugarcane Fields Under Straw Removal in Brazil

  • Published:
BioEnergy Research Aims and scope Submit manuscript

Abstract

Global promotion of bioenergy for mitigating climate changes has arisen the interest of the Brazilian sugarcane industry to use crop residue (straw) as an important source of biomass for bioelectricity and cellulosic ethanol production. However, the sugarcane straw influences several soil properties, supporting soil quality and crop yields. Thus, defining an optimal removal rate would keep the benefits of the sugarcane straw in soil, and also maximize the bioenergy production. Shifts on soil bacterial structure have been used as a sensitive indicator of land management and could help to prescribe an optimal removal rate. We conducted a field study at two sites in São Paulo state to investigate how rates of sugarcane straw removal are associated with soil bacterial community changes over 1 year. Four sugarcane straw removal rates were evaluated: no removal (~ 14 Mg ha−1 of dry mass left) and 50% (~ 7.0 Mg ha−1), 75% (~ 3.5 Mg ha−1), and 100% of straw removal. The soil bacterial community structure was evaluated by the terminal restriction fragment length polymorphism (T-RFLP). Our results indicated that soil bacteria communities change over time, regardless of site conditions, and their changes are more strongly associated with changes on straw composition. A similar straw decomposition dynamics was observed under moderate (50%) and no removal treatments. Moderate straw removal induced the lowest modification of the bacterial niche occupancy and highest microbial interaction when compared with the no removal. Therefore, the identification of changes in soil bacterial structure community is useful to provide guidance for sugarcane straw removal.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

References

  1. CONAB, Companhia Nacional de Abastecimento (2018) Acompanhamento da safra brasileira: Cana-de-açúcar - V5 - safra 2018/19. Terceiro levantamento, dezembro 2018. https://www.conab.gov.br/info-agro/safras/cana/boletim-da-safra-de-cana-de-acucar. Accessed 11 March 2019

  2. Carvalho JLN, Nogueirol RC, Menandro LMS, Bordonal RO, Borges CD, Cantarella H, Franco HCJ (2017) Agronomic and environmental implications of sugarcane straw removal: a major review. GCB Bioenergy 9:1181–1195. https://doi.org/10.1111/gcbb.12410

    Article  CAS  Google Scholar 

  3. Menandro LMS, Cantarella H, Franco HCJ, Kolln OT, Pimenta MTB, Sanches GM, Rabelo SC, Carvalho JLN (2017) Comprehensive assessment of sugarcane straw: implications for biomass and bioenergy production. Biofuels Bioprod Biorefin 11:488–504. https://doi.org/10.1002/bbb.1760

    Article  CAS  Google Scholar 

  4. Cherubin MR, Oliveira DMS, Feigl BJ, Pimentel LG, Lisboa IP, Gmach MR, Varanda LL, Morais MC, Satiro LS, Popin GV, de Paiva SR, dos Santos AKB, de Vasconcelos ALS, de Melo PLA, Cerri CEP, Cerri CC (2018) Crop residue harvest for bioenergy production and its implications on soil functioning and plant growth: a review. Sci Agríc 75:255–272. https://doi.org/10.1590/1678-992x-2016-0459

    Article  CAS  Google Scholar 

  5. Sousa JG Jr, Cherubin MR, Cerri CEP, Cerri CC, Feigl BJ (2017) Sugar cane straw left in field during harvest: decomposition dynamics and composition changes. Soil Res 55:758–768. https://doi.org/10.1071/SR16310

    Article  CAS  Google Scholar 

  6. Pimentel LG, Cherubin MR, Oliveira DMS, Cerri CEP, Cerri CC (2019) Decomposition of sugarcane straw: basis for management decisions for bioenergy production. Biomass Bioenergy 122:133–144. https://doi.org/10.1016/j.biombioe.2019.01.027

    Article  CAS  Google Scholar 

  7. Oliveira DMS, Williams S, Cerri CEP, Paustian K (2017) Predicting soil C changes over sugarcane expansion in Brazil using the DayCent model. GCB Bioenergy 9:1436–1446. https://doi.org/10.1111/gcbb.12427

    Article  CAS  Google Scholar 

  8. Rachid C, Pires CA, Leite DCA, Coutinho HLC, Peixoto RS, Rosado AS, Salton J, Zanatta JA, Mercante FM, Angelini GAR, Balieiro FD (2016) Sugarcane trash levels in soil affects the fungi but not bacteria in a short-term field experiment. Braz J Microbiol 47:322–326. https://doi.org/10.1016/j.bjm.2016.01.010

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  9. Mendes LW, Brossi MJD, Kuramae EE, Tsai SM (2015) Land-use system shapes soil bacterial communities in Southeastern Amazon region. Appl Soil Ecol 95:151–160. https://doi.org/10.1016/j.apsoil.2015.06.005

    Article  Google Scholar 

  10. Zhao SC, Li KJ, Zhou W, Qiu SJ, Huang SW, He P (2016) Changes in soil microbial community, enzyme activities and organic matter fractions under long-term straw return in north-central China. Agric Ecosyst Environ 216:82–88. https://doi.org/10.1016/j.agee.2015.09.028

    Article  CAS  Google Scholar 

  11. Xu M, Xia H, Wu J, Yang G, Zhang X, Peng H, Yu X, Li L, Xiao H, Qi H (2017) Shifts in the relative abundance of bacteria after wine-lees-derived biochar intervention in multi metal-contaminated paddy soil. Sci Total Environ 599:1297–1307. https://doi.org/10.1016/j.scitotenv.2017.05.086

    Article  PubMed  CAS  Google Scholar 

  12. Finn D, Kopittke PM, Dennis PG, Dalal RC (2017) Microbial energy and matter transformation in agricultural soils. Soil Biol Biochem 111:176–192. https://doi.org/10.1016/j.soilbio.2017.04.010

    Article  CAS  Google Scholar 

  13. Wang J, Ren C, Cheng H, Zou Y, Bughio MA, Li Q (2017) Conversion of rainforest into agroforestry andmonoculture plantation in China: consequences for soil phosphorus forms and microbial community. Sci Total Environ 595:769–778. https://doi.org/10.1016/j.scitotenv.2017.04.012

    Article  PubMed  CAS  Google Scholar 

  14. Lammel DR, Nusslein K, Tsai SM, Cerri CC (2015) Land use, soil and litter chemistry drive bacterial community structures in samples of the rainforest and Cerrado (Brazilian Savannah) biomes in Southern Amazonia. Eur J Soil Biol 66:32–39. https://doi.org/10.1016/j.ejsobi.2014.11.001

    Article  CAS  Google Scholar 

  15. Karimi B, Maron PA, Boure NC-P, Bernard N, Gilbert D, Ranjard L (2017) Microbial diversity and ecological networks as indicators of environmental quality. Environ Chem Lett 15:265–281. https://doi.org/10.1007/s10311-017-0614-6

    Article  CAS  Google Scholar 

  16. Gumiere T, Gumiere SJ, Matteau J-P, Constant P, Létourneau G, Rousseau AN (2019) Soil bacterial community associated with high potato production and minimal water use. Front Environ Sci 6:1–14. https://doi.org/10.3389/fenvs.2018.00161

    Article  Google Scholar 

  17. Liao J, Cao X, Zhao L, Wang J, Gao Z, Wang M, Huang Y (2016) The importance of neutral and niche processes for bacterial community assembly differs between habitat generalists and specialists. FEMS Microbiol Ecol 92:1–10. https://doi.org/10.1093/femsec/fiw174

    Article  CAS  Google Scholar 

  18. Atlas R, Horowitz A, Krichevsky M, Bej A (1991) Response of microbial populations to environmental disturbance. Microb Ecol 22:249–256. https://doi.org/10.1007/BF02540227

    Article  PubMed  CAS  Google Scholar 

  19. USDA, United States Department of Agriculture (2014) Keys to soil taxonomy. USDA - Natural Resources Conservation Service, Washington, DC

    Google Scholar 

  20. Van Soest PJ, Robertson JB, Lewis BA (1991) Methods for dietary fiber, neutral detergent fiber, and nonstarch polysaccharides in relation to animal nutrition. J Dairy Sci 74:3583–3597. https://doi.org/10.3168/jds.S0022-0302(91)78551-2

    Article  PubMed  Google Scholar 

  21. Schutte UME, Abdo Z, Bent SJ, Williams CJ, Schneider GM, Solheim B, Forney LJ (2009) Bacterial succession in a glacier foreland of the High Arctic. ISME J 3:1258–1268. https://doi.org/10.1111/j.1365-294X.2009.04479.x

    Article  PubMed  Google Scholar 

  22. Durrer A, Gumiere T, Taketani RG, da Costa DP, Silva M, Andreote FD (2017) The drivers underlying biogeographical patterns of bacterial communities in soils under sugarcane cultivation. Appl Soil Ecol 110:12–20. https://doi.org/10.1016/j.apsoil.2016.11.005

    Article  Google Scholar 

  23. Liu WT, Marsh TL, Cheng H, Forney LJ (1997) Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl Environ Microbiol 63:4516–4522

    PubMed  PubMed Central  CAS  Google Scholar 

  24. Culman SW, Gauch HG, Blackwood CB, Thies JE (2008) Analysis of T-RFLP data using analysis of variance and ordination methods: a comparative study. J Microbiol Methods 75:55–63. https://doi.org/10.1016/j.mimet.2008.04.011

    Article  PubMed  CAS  Google Scholar 

  25. R Development Core Team (2018) R: a language and environment for statistical computing, reference index version 3.5.2. R Foundation for Statistical Computing, Vienna ISBN 3-900051-07-0, http://www.R-project.org

    Google Scholar 

  26. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Henry M, Stevens H, Szoecs E, Wagner H (2018) vegan: Community Ecology Package. R package version 2.5-3

  27. Chazdon RL, Chao A, Colwell RK, Lin S-Y, Norden N, Letcher SG, Clark DB, Finegan B, Arroyo JP (2011) A novel statistical method for classifying habitat generalists and specialists. Ecology 92:1332–1343. https://doi.org/10.1890/10-1345.1

    Article  PubMed  Google Scholar 

  28. Kurtz Z, Mueller C, Miraldi E, Bonneau R (2019) SpiecEasi Package. R package version 2.5-3

  29. Batushansky A, Toubiana D, Fait A (2016) Correlation-based network generation, visualization, and analysis as a powerful tool in biological studies: a case study in cancer cell metabolism. Biomed Res Int 2016:1–9. https://doi.org/10.1155/2016/8313272

    Article  Google Scholar 

  30. Bastian M, Heymann S, Jacomy M (2009) Gephi: an open source software for exploring and manipulating networks. In: Third International AAAI Conference on Weblogs and Social Media. pp 361-362.

  31. Ma Z (2018) The P/N (positive-to-negative links) ratio in complex networks—a promising in silico biomarker for detecting changes occurring in the human microbiome. Microb Ecol 75:1063–1073. https://doi.org/10.1007/s00248-017-1079-7

    Article  PubMed  CAS  Google Scholar 

  32. Newman MEJ (2006) Modularity and community structure in networks. Proc Nat Acad Sci 103:8577–8582. https://doi.org/10.1073/pnas.0601602103

    Article  PubMed  CAS  PubMed Central  Google Scholar 

  33. Zhou GX, Zhang JB, Mao JD, Zhang CZ, Chen L, Xin XL, Zhao BZ (2015) Mass loss and chemical structures of wheat and maize straws in response to ultraviolet-B radiation and soil contact. Sci Rep 5:11. https://doi.org/10.1038/srep14851

    Article  CAS  Google Scholar 

  34. Baumann K, Marschner P, Smernik RJ, Baldock JA (2009) Residue chemistry and microbial community structure during decomposition of eucalypt, wheat and vetch residues. Soil Biol Biochem 41:1966–1975. https://doi.org/10.1016/j.soilbio.2009.06.022

    Article  CAS  Google Scholar 

  35. Barreiro A, Baath E, Diaz-Ravina M (2016) Bacterial and fungal growth in burnt acid soils amended with different high C/N mulch materials. Soil Biol Biochem 97:102–111. https://doi.org/10.1016/j.soilbio.2016.03.009

    Article  CAS  Google Scholar 

  36. Fanin N, Bertrand I (2016) Aboveground litter quality is a better predictor than belowground microbial communities when estimating carbon mineralization along a land-use gradient. Soil Biol Biochem 94:48–60. https://doi.org/10.1016/j.soilbio.2015.11.007

    Article  CAS  Google Scholar 

  37. Sauvadet M, Chauvat M, Fanina N, Coulibaly S, Bertrand I (2016) Comparing the effects of litter quantity and quality on soil biota structure and functioning: application to a cultivated soil in Northern France. Appl Soil Ecol 107:261–271. https://doi.org/10.1016/j.apsoil.2016.06.010

    Article  Google Scholar 

  38. Zhou GX, Zhang JB, Chen L, Zhang CZ, Yu ZH (2016) Temperature and straw quality regulate the microbial phospholipid fatty acid composition associated with straw decomposition. Pedosphere 26:386–398. https://doi.org/10.1016/S1002-0160(15)60051-0

    Article  Google Scholar 

  39. McGuire KL, Treseder KK (2010) Microbial communities and their relevance for ecosystem models: decomposition as a case study. Soil Biol Biochem 42:529–535. https://doi.org/10.1016/j.soilbio.2009.11.016

    Article  CAS  Google Scholar 

  40. Cleveland CC, Reed SC, Keller AB, Nemergut DR, O’Neill SP, Ostertag R, Vitousek PM (2014) Litter quality versus soil microbial community controls over decomposition: a quantitative analysis. Oecologia 174:283–294. https://doi.org/10.1007/s00442-013-2758-9

    Article  PubMed  Google Scholar 

  41. Lu P, Lin YH, Yang ZQ, Xu YP, Tan F, Jia XD, Wang M, Xu DR, Wang XZ (2015) Effects of application of corn straw on soil microbial community structure during the maize growing season. J Basic Microbiol 55:22–32. https://doi.org/10.1002/jobm.201300744

    Article  PubMed  CAS  Google Scholar 

  42. Navarro-Noya YE, Gomez-Acata S, Montoya-Ciriaco N, Rojas-Valdez A, Suarez-Arriaga MC, Valenzuela-Encinas C, Jimenez-Bueno N, Verhulst N, Govaerts B, Dendooven L (2013) Relative impacts of tillage, residue management and crop-rotation on soil bacterial communities in a semi-arid agroecosystem. Soil Biol Biochem 65:86–95. https://doi.org/10.1016/j.soilbio.2013.05.009

    Article  CAS  Google Scholar 

  43. Hu W, Zhang Q, Tian T, Li D, Cheng G, Mu J, Wu Q, Niu F, Stegen JC, An L, Feng H (2015) Relative roles of deterministic and stochastic processes in driving the vertical distribution of bacterial communities in a permafrost core from the Qinghai-Tibet Plateau, China. Plos One 10:1–19. https://doi.org/10.1371/journal.pone.0145747

    Article  Google Scholar 

  44. Morais MC (2016) Efeito da remoção de quantidades de palha de cana-de-açúcar na biomassa e na comunidade microbiana do solo. Dissertation, University of São Paulo

  45. Lupatini M, Suleiman AKA, Jacques RJS, Antoniolli ZI, Ferreira AS, Kuramae EE, Roesch LFW (2014) Network topology reveals high connectance levels and few key microbial genera within soils. Front Environ Sci 2:1–11. https://doi.org/10.3389/fenvs.2014.00010

    Article  Google Scholar 

  46. Bauer WD, Robinson JB (2002) Disruption of bacterial quorum sensing by other organisms. Curr Opin Biotechnol 13:234–237. https://doi.org/10.1016/S0958-1669(02)00310-5

    Article  PubMed  CAS  Google Scholar 

  47. Connell JH (1978) Diversity in tropical rain forests and coral reefs. Science 199:1302–1310. https://doi.org/10.1126/science.199.4335.1302

    Article  PubMed  CAS  Google Scholar 

  48. Sheil D, Burslem DFRP (2013) Defining and defending Connell’s intermediate disturbance hypothesis: a response to Fox. Trends Ecol Evol 28:571–572. https://doi.org/10.1016/j.tree.2013.07.006

    Article  PubMed  Google Scholar 

  49. MME, Ministério de Minas e Energia (2019) RenovaBio. http://www.mme.gov.br/web/guest/secretarias/petroleo-gas-natural-e-combustiveis-renovaveis/programas/renovabio/principal. Accessed 11 March 2019

Download references

Acknowledgments

Laisa G. Pimentel, Thiago Gumiere, and Dener M. S. Oliveira thank the São Paulo Research Foundation - FAPESP (processes #2015/00308-0, #2013/18529-8, and #2014/08632-9) for providing their PhD scholarships. Maurício R. Cherubin thanks the Fundação de Estudos Agrários Luiz de Queiroz (Project #67555) for providing his postdoctoral fellowship and FAPEPS (Process #2018/09845-7).

Funding

This research received funding from the Brazilian Development Bank - BNDES and the Raízen Energia S/A (Project #14.2.0773.1).

Author information

Authors and Affiliations

Author notes

  1. Carlos C. Cerri is deceased. This paper is dedicated to his memory.

    • Carlos C. Cerri
Authors

Corresponding author

Correspondence to Laisa G. Pimentel.

Additional information

Publisher’s Note

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

Electronic Supplementary Material

ESM 1

(DOCX 403 kb)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Pimentel, L.G., Gumiere, T., Oliveira, D.M.S. et al. Soil Bacterial Community Changes in Sugarcane Fields Under Straw Removal in Brazil. Bioenerg. Res. 12, 830–842 (2019). https://doi.org/10.1007/s12155-019-10010-z

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12155-019-10010-z

Keywords

Navigation