Multi-scale measurements show limited soil greenhouse gas emissions in Kenyan smallholder coffee-dairy systems
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Ortiz-Gonzalo D, de Neergaard A, Vaast P, Suárez-Villanueva V, Oelofse M, Rosenstock TS. 2018. Multi-scale measurements show limited soil greenhouse gas emissions in Kenyan smallholder coffee-dairy systems. Science of The Total Environment 626:328–339.
Permanent link to cite or share this item: http://hdl.handle.net/10568/91198
Efforts have been made in recent years to improve knowledge about soil greenhouse gas (GHG) fluxes from sub-Saharan Africa. However, data on soil GHG emissions from smallholder coffee-dairy systems have not hitherto been measured experimentally. This study aimed to quantify soil GHG emissions at different spatial and temporal scales in smallholder coffee-dairy farms in Murang'a County, Central Kenya. GHG measurements were carried out for one year, comprising two cropping seasons, using vented static chambers and gas chromatography. Sixty rectangular frames were installed on two farms comprising the three main cropping systems found in the area: 1) coffee (Coffea arabica L.); 2) Napier grass (Pennisetum purpureum); and 3) maize intercropped with beans (Zea mays and Phaseolus vulgaris). Within these fields, chambers were allocated on fertilised and unfertilised locations to capture spatial variability. Cumulative annual fluxes in coffee plots ranged from 1 to 1.9 kg N2O-N ha− 1, 6.5 to 7.6 Mg CO2-C ha− 1 and − 3.4 to − 2.2 kg CH4 -C ha− 1, with 66% to 94% of annual GHG fluxes occurring during rainy seasons. Across the farm plots, coffee received most of the N inputs and had 56% to 89% higher emissions of N2O than Napier grass, maize and beans. Within farm plots, two to six times higher emissions were found in fertilised hotspots – around the perimeter of coffee trees or within planted maize rows – than in unfertilised locations between trees, rows and planting holes. Background and induced soil N2O emissions from fertiliser and manure applications in the three cropping systems were lower than hypothesized from previous studies and empirical models. This study supplements methods and underlying data for the quantification of GHG emissions at multiple spatial and temporal scales in tropical, smallholder farming systems. Advances towards overcoming the dearth of data will facilitate the understanding of synergies and tradeoffs of climate-smart approaches for low emissions development.
CGIAR Author ORCID iDs
Daniel Ortiz Gonzalohttps://orcid.org/0000-0002-5517-1785
Andreas de Neergaardhttps://orcid.org/0000-0001-9108-1122
SubjectsLOW EMISSIONS DEVELOPMENT;
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