Precise spatial information on soil properties in plantation forests is needed to improve soil nutrient management and to sustain productivity. Soil nitrogen, phosphorus, potassium, organic matter, carbon and boron are important determinants and indicators of soil fertility and quality. Particularly in forests, these soil properties are highly variable in space and time. In this study, soils were sampled from three plantation forest sites in a dry sub-humid region near Blenheim, New Zealand. Thirty sampling points were selected, and samples were collected from the three sites across a range of slope and aspect strata. Soil samples were analysed for total carbon (totC), total nitrogen (totN), total phosphorus (totP), extractable potassium (exK) and hot-water extractable boron (exB). All examined soil properties varied significantly (p < 0.05) within sites. A set of fine-scale (5 m resolution) topographic surfaces, that might explain this variability, were then interpolated or derived in geographic information system software. Topographic surfaces included elevation, aspect, slope, profile and plan curvature, topographic position index (TPI), topographic wetness index (TWI), wind exposition index (WEI), and morphometric protection index (MPI). A generalised linear mixed-effect model was applied to develop predictive models. The study found all soil properties were positively correlated with MPI and negatively correlated with the WEI. This indicated that soil properties were correlated with shelter from surrounding relief and wind. Interestingly, within-site boron levels were correlated with both profile curvature (PrCurv) and topographic wetness index, indicating boron movement through the surface with the movement of soil moisture. The modelling approach in this study has potential for application to sustainable management of plantation forests using spatially-precise estimates of soil fertility.

需要有关人工林土壤特性的准确空间信息，以改善土壤养分管理并维持生产力。土壤氮，磷，钾，有机质，碳和硼是决定土壤肥力和质量的重要决定因素和指标。特别是在森林中，这些土壤特性在空间和时间上变化很大。在这项研究中，土壤是从新西兰布伦海姆附近一个干燥的半湿润地区的三个人工林站点取样的。选择了三十个采样点，并从一定范围的坡度和纵横比的三个地点采集了样本。分析土壤样品的总碳（totC），总氮（totN），总磷（totP），可提取钾（exK）和可热水提取硼（exB）。所有检查的土壤性质均存在显着差异（p <0 05）在网站内。然后在地理信息系统软件中内插或导出了一组可以解释这种变化性的精细比例（5 m分辨率）的地形表面。地形表面包括海拔，纵横比，坡度，轮廓和平面曲率，地形位置指数（TPI），地形湿度指数（TWI），风暴露指数（WEI）和形态保护指数（MPI）。应用广义线性混合效应模型来开发预测模型。研究发现，所有土壤特性均与MPI正相关，而与WEI负相关。这表明土壤性质与避难所和风的掩盖作用有关。有趣的是，现场硼含量与剖面曲率（PrCurv）和地形湿度指数相关，表示硼随着土壤水分的运动而通过地表。本研究中的建模方法具有使用土壤肥力的空间精确估计来应用于人工林可持续管理的潜力。