Assessing the spatial variability of soils in Uganda
Uganda's soils were once considered the most fertile in Africa, but soil erosion and soil nutrient mining have led to soil degradation and declining agricultural productivity. Lack of environmental awareness among farmers, traditional agricultural practices, minimal inorganic fertilizer use, and little to no use of improved crop varieties all contribute to continued soil degradation. The objectives of this study were: (1) to characterize the spatial distribution of selected physical and chemical soil properties in Uganda on a national scale utilizing the data collected by Nkonya et al. (2008), and (2) to identify the major factors and processes that are dominant in explaining the spatial variability of these physical and chemical soil properties in Uganda on a national scale. This study used a 2003 Uganda National Household Survey dataset that included analyses of 2,185 soil samples that covered western, southwestern and northwestern Uganda, representing ∼50% of the country. Variables included pH, organic matter, total N, available K, total K, total P, and soil texture (Nkonya et al., 2008, IFPRI Research Report 159). Ordinary kriging was used for spatial analysis, while a generalized linear model was used to identify the most dominant factors influencing soil variability. ANOVA results found significant variation among soil properties means, as one would expect. Strong spatial correlation (< 25% nugget to sill ratio) was observed in available K, pH, sand, total N, and silt, while moderate spatial correlation (25% to 75% nugget to sill ratio) was observed for total K, clay, total P, and organic matter. Distances where spatial correlation occurred ranged between 69 and 230 km. Interpolated soil quality maps identified the Mt. Elgon and the southwestern highlands regions as having soils above the critical soil chemical and physical thresholds, indicating that these are the most favorable agricultural areas in the country. The remaining areas of the country had numerous constraints such as acidity, very sandy soils, low N and/or low organic matter, making these areas less optimal for agricultural production. There was no dominant factor that solely explained the variability of all the soil properties. However, climate had the strongest effect on the variability of total N, with higher soil N found in the cooler, higher elevations of Mt. Elgon and the southwestern highlands. This study showed that geostatistical approaches can be used to evaluate spatial diversity of natural resources at larger scales. Policy makers can use this information to implement region-specific soil management approaches to address soil quality degradation. For example, programs to increase the soil pH of acid soils should be focused on the southwestern region where soils are generally more acid than other parts of the country.
Schulze, Purdue University.
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