SPATIAL VARIABILITY STATUS OF SELECTED SOIL PROPERTIES IN NORTH-EAST AKWA IBOM STATE, NIGERIA

Spatial variability status of selected soil properties in North-east Akwa Ibom State, Nigeria was assessed. The aim was to establish baseline information on the spatial variability status of selected soil properties in North-east Akwa Ibom State for site -specific and sustainable soil management. A terrain attribute (plan curvature) that is capable of capturing the short-scale spatial variability of soil properties in the field was used to guide field sampling. Plan curvature map was generated from digital elevation model (DEM) of the study area acquired from United State Geological Survey (USGS) at 30m resolution. The plan curvature map was classified into straight, convex and concave surfaces. Modified conditioned Latin hypercube sampling method was used in selecting observation points. Each observation point was purposefully selected to fall within the three classes of the plan curvature map to give a good coverage of both feature space (terrain attributes) and geographical space (study area). Soil samples were collected from each observation point at depths of 0-30 cm and 30-60 cm using soil auger. A total number of 152 soil samples were collected in the study area for laboratory analysis. Data generated were subjected to analysis of variance (ANOVA) and means were separated using least significant difference (LSD) at 5% level of significance. The depth interval of 0-30cm and 30-60 cm were integrated to form depth interval of 0-60 cm and data with skewed distribution were log transformed for semivariogram analysis. Soil properties were then subjected to semi-variogram analysis. The results showed that plan curvature was able to capture short scale spatial variation in some soil properties under study. Soil texture was sand in the surface and subsurface soils of both convex and concave slope while in straight slope, the soil texture was sand in the surface and loamy sand in the subsurface. Soil pH was strongly acidic in both straight and concave slope and slightly acidic in convex slope in both surface and subsurface soil. Organic carbon was high in concave and convex slope and very high in straight topography in both surface and subsurface soils. Total N was low in the convex and concave slope but moderately low in straight terrain. The available P of straight slope was higher than that of concave and convex slope.From the semi-variogram analysis, all the selected soil properties exhibited spatial dependence within some distances. The strength of the spatial dependence varied from moderate for sand, silt, soil pH, organic carbon, total N and available P to weak for clay and strong for exchangeable K. The best fitted models were Exponential for sand and silt; Gaussian for available P and Spherical for clay, pH, organic carbon, total N and exchangeable K.The range of autocorrelation was 136.2 m for sand, 76.4m for silt, 1.6 m for clay, 1.69 m for soil pH, 9.4 m for organic C, 7.1m for total N, 39.2 m for available P and 7.8 m for exchangeable K. This shows that beyond these ranges, the selected soil properties should be managed differently.

尼日利亚东北部Akwa Ibom州选定土壤特性的空间变异性状态已得到评估。本研究旨在建立该区域选定土壤特性空间变异性的基准信息，为精准且可持续的土壤管理提供支撑。采用一种可捕捉田间土壤特性短尺度空间变异性的地形属性（平面曲率，plan curvature）指导田间采样。平面曲率图由研究区的数字高程模型（DEM）生成，该DEM从美国地质调查局（USGS）获取，分辨率为30米。平面曲率图被分为平直、凸面和凹面三种表面。

采用改进的条件拉丁超立方抽样方法（Modified conditioned Latin hypercube sampling method）选择观测点。每个观测点均被精心选择，以覆盖平面曲率图的三类区域，从而实现特征空间（地形属性）与地理空间（研究区域）的良好覆盖。使用土壤钻（soil auger）在每个观测点采集0-30 cm和30-60 cm深度的土壤样本。研究区共采集152份土壤样本用于实验室分析。

生成的数据进行方差分析（ANOVA），并在5%显著性水平下采用最小显著差法（LSD）分离均值。将0-30 cm与30-60 cm深度区间合并为0-60 cm区间，对偏态分布的数据进行对数转换，以开展半变异函数分析（semivariogram analysis）。随后对土壤特性进行半变异函数分析。

结果表明，平面曲率可捕捉所研究部分土壤特性的短尺度空间变异。凸坡和凹坡的表层及亚表层土壤质地均为砂质；而平直坡表层为砂质，亚表层为壤质砂。平直坡与凹坡的表层及亚表层土壤pH值呈强酸性，凸坡则呈弱酸性。凹坡与凸坡的表层及亚表层土壤有机碳含量较高，平直地形则极高。凸坡与凹坡的全氮（Total N）含量较低，平直地形则为中等偏低。平直坡的有效磷（available P）含量高于凹坡与凸坡。

半变异函数分析显示，所有选定土壤特性在一定距离内均表现出空间依赖性。空间依赖性强度各异：砂粒、粉粒、土壤pH值、有机碳、全氮及有效磷为中等；黏粒为弱；交换性钾（exchangeable K）为强。最优拟合模型为：砂粒与粉粒采用指数模型（Exponential）；有效磷采用高斯模型（Gaussian）；黏粒、pH值、有机碳、全氮及交换性钾采用球状模型（Spherical）。自相关范围为：砂粒136.2米，粉粒76.4米，黏粒1.6米，土壤pH值1.69米，有机碳9.4米，全氮7.1米，有效磷39.2米，交换性钾7.8米。这表明，超出上述范围后，需对选定土壤特性采取差异化管理措施。