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Site climate more than soil properties and topography shape the natural arbuscular mycorrhizal symbiosis in maize and spore density within rainfed maize (Zea mays L.) cropland in the eastern DR Congo

Author

Listed:
  • Adrien Byamungu Ndeko
  • Abdala Gamby Diedhiou
  • Hassna Founoune-Mboup
  • Géant Basimine Chuma
  • Yannick Mugumaarhahama
  • Diegane Diouf
  • Saliou Fall
  • Gustave Nachigera Mushagalusa
  • Aboubacry Kane

Abstract

Rhizosphere microorganisms, particularly arbuscular mycorrhizal fungi (AMF), play a vital role in enhancing sustainable maize production. However, uncertainty persist regarding the influence of climate variables and soil properties on mycorrhizal colonization (MC) of maize and the abundance of AM fungal spores in the field. This study aimed to explore the environmental factors such as site climate variables, soil physicochemical properties and topography and vegetation variable, affecting the natural MC of maize and the density of AMF spores. The study hypothesizes that natural maize mycorrhizal colonization and AMF spore density vary significantly across different sites and agroecological zones. It further posits that climatic and edaphic variables predominantly explain the observed variation in mycorrhizal parameters. To assess the impact of these factors, a field study was conducted in 32 sites across three territories in the province of South Kivu, namely Kabare, Walungu, and Uvira. Rhizospheric soil and maize roots were collected from different sites. Maize MC varied significantly among sites, with Kabare and Walungu showing high colonization rates (52.1% and 44.7%, respectively) compared to Uvira (26.40%). Meanwhile, spore density was significantly higher in Uvira (1331.7 spores g-1 soil) than in Kabare (518.9 spores g-1 soil) and Walungu (468.58 spores g-1 soil). Correlation analysis indicated that maize MC was influenced by site climate and soil properties. The PLS-SEM model demonstrated that 76.5% (R2) of the total variance in maize root MC was explained by climatic variables and soil chemical properties. Compared to soil chemical properties, climate characteristics had a more pronounced impact on maize MC. Maize MC was inversely correlated with temperature, C and available P content, while being directly and positively correlated with altitude, rainfall, and base saturation rate. Furthermore, 68.5% (R2) of the spore density variability of AMF was explained by climatic variables and soil physical properties. Spore density was inversely correlated with sand and clay content, field capacity, rainfall, and altitude, while being positively correlated with temperature. The results of this study indicate that climatic conditions exert a more pronounced influence on the mycorrhizal colonization of maize and the density of AMF spores than soil characteristics.

Suggested Citation

  • Adrien Byamungu Ndeko & Abdala Gamby Diedhiou & Hassna Founoune-Mboup & Géant Basimine Chuma & Yannick Mugumaarhahama & Diegane Diouf & Saliou Fall & Gustave Nachigera Mushagalusa & Aboubacry Kane, 2024. "Site climate more than soil properties and topography shape the natural arbuscular mycorrhizal symbiosis in maize and spore density within rainfed maize (Zea mays L.) cropland in the eastern DR Congo," PLOS ONE, Public Library of Science, vol. 19(12), pages 1-29, December.
    • Handle: RePEc:plo:pone00:0312581
    DOI: 10.1371/journal.pone.0312581
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    References listed on IDEAS

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    1. Espoir M. Bagula & Jackson Gilbert M. Majaliwa & Gustave N. Mushagalusa & Twaha A. Basamba & John-Baptist Tumuhairwe & Jean-Gomez M. Mondo & Patrick Musinguzi & Cephas B. Mwimangire & Géant B. Chuma &, 2022. "Climate Change Effect on Water Use Efficiency under Selected Soil and Water Conservation Practices in the Ruzizi Catchment, Eastern D.R. Congo," Land, MDPI, vol. 11(9), pages 1-22, August.
    2. Abdoulaye Fofana Fall & Grace Nakabonge & Joseph Ssekandi & Hassna Founoune-Mboup & Arfang Badji & Abibatou Ndiaye & Malick Ndiaye & Paul Kyakuwa & Otim Godfrey Anyoni & Clovis Kabaseke & Amos Kipkemo, 2023. "Combined Effects of Indigenous Arbuscular Mycorrhizal Fungi (AMF) and NPK Fertilizer on Growth and Yields of Maize and Soil Nutrient Availability," Sustainability, MDPI, vol. 15(3), pages 1-12, January.
    3. Liu, Jiaguo & Li, Sujuan & Ji, Qiang, 2021. "Regional differences and driving factors analysis of carbon emission intensity from transport sector in China," Energy, Elsevier, vol. 224(C).
    4. Peres-Neto, Pedro R. & Jackson, Donald A. & Somers, Keith M., 2005. "How many principal components? stopping rules for determining the number of non-trivial axes revisited," Computational Statistics & Data Analysis, Elsevier, vol. 49(4), pages 974-997, June.
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