Browsing by Author "Chiyaka, TL"

Now showing 1 - 1 of 1
  • Thumbnail Image
    Item
    Biogeographical survey of soil microbiomes across sub-Saharan Africa: structure, drivers, and predicted climate-driven changes
    (2022) Cowan, DA; Lebre, PH; Amon, CER; Becker, RW; Boga, HI; Boulangé, A; Chiyaka, TL; Coetzee, T; de Jager, PC; Ramond, Jean-Baptiste; Eckardt, F; Greve, M; Harris, MA; Hopkins, DW; Houngnandan, HB; Houngnandan, P; Jordaan, K; Kaimoyo, E; Kambura, AK; Kamgan-Nkuekam, G; Makhalanyane, TP; Maggs-Kölling, G; Marais, E; Mondlane, H; Nghalipo, E; Olivier, BW; Ortiz, M; Pertierra, LR; Dikinya, O; Seely, M; Sithole-Niang, I; Valverde, A; Varliero, G; Vikram, S; Wall, DH; Zeze, A
    Background: Top-soil microbiomes make a vital contribution to the Earth’s ecology and harbor an extraordinarily high biodiversity. They are also key players in many ecosystem services, particularly in arid regions of the globe such as the African continent. While several recent studies have documented patterns in global soil microbial ecology, these are largely biased towards widely studied regions and rely on models to interpolate the microbial diversity of other regions where there is low data coverage. This is the case for sub-Saharan Africa, where the number of regional microbial studies is very low in comparison to other continents. Results: The aim of this study was to conduct an extensive biogeographical survey of sub-Saharan Africa’s top-soil microbiomes, with a specific focus on investigating the environmental drivers of microbial ecology across the region. In this study, we sampled 810 sample sites across 9 sub-Saharan African countries and used taxonomic barcoding to profile the microbial ecology of these regions. Our results showed that the sub-Saharan nations included in the study harbor qualitatively distinguishable soil microbiomes. In addition, using soil chemistry and climatic data extracted from the same sites, we demonstrated that the top-soil microbiome is shaped by a broad range of environmental factors, most notably pH, precipitation, and temperature. Through the use of structural equation modeling, we also developed a model to predict how soil microbial biodiversity in sub-Saharan Africa might be affected by future climate change scenarios. This model predicted that the soil microbial biodiversity of countries such as Kenya will be negatively affected by increased temperatures and decreased precipitation, while the fungal biodiversity of Benin will benefit from the increase in annual precipitation. Conclusion: This study represents the most extensive biogeographical survey of sub-Saharan top-soil microbiomes to date. Importantly, this study has allowed us to identify countries in sub-Saharan Africa that might be particularly vulnerable to losses in soil microbial ecology and productivity due to climate change. Considering the reliance of many economies in the region on rain-fed agriculture, this study provides crucial information to support conservation efforts in the countries that will be most heavily impacted by climate change.