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Soil climate and decomposer activity in Sub-Saharan Africa estimated from standard weather station data: a simple climate index for soil carbon balance calculations
Authors:Andrén Olof  Kihara Job  Bationo André  Vanlauwe Bernard  Kätterer Thomas
Institution:Department of Soil Science, Swedish University of Agricultural Sciences, Uppsala. Olle.Andren@mv.slu.se
Abstract:Soil biological activity was calculated on a daily basis, using standard meteorological data from African weather stations, a simple soil water model, and commonly used assumptions regarding the relations between temperature, soil water content, and biological activity. The activity factor r(e_clim) is calculated from daily soil moisture and temperature, thereby taking the daily interaction between temperature and moisture into account. Annual mean r(e_clim) was normalized to 1 in Central Sweden (clay loam soil, no crop), where the original calibration took place. Since soils vary in water storage capacity and plant cover will affect transpiration, we used this soil under no crop for all sites, thereby only including climate differences. The Swedish r(e_clim) value, 1, corresponds to ca. 50% annual mass loss of, e.g., cereal straw incorporated into the topsoil. African mean annual r(e_clim) values varied between 1.1 at a hot and dry site (Faya, Chad) and 4.7 at a warm and moist site (Brazzaville, Congo). Sites in Kenya ranged between r(e_clim) = 2.1 at high altitude (Matanya) and 4.1 in western Kenya (Ahero). This means that 4.1 times the Swedish C input to soil is necessary to maintain Swedish soil carbon levels in Ahero, if soil type and management are equal. Diagrams showing daily r(e_clim) dynamics are presented for all sites, and differences in within-year dynamics are discussed. A model experiment indicated that a Swedish soil in balance with respect to soil carbon would lose 41% of its soil carbon during 30 y, if moved to Ahero, Kenya. If the soil was in balance in Ahero with respect to soil carbon, and then moved to Sweden, soil carbon mass would increase by 64% in 30 y. The validity of the methodology and results is discussed, and r(e_clim) is compared with other climate indices. A simple method to produce a rough estimate of r(e_clim) is suggested.
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