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首页> 外文期刊>Catena: An Interdisciplinary Journal of Soil Science Hydrology-Geomorphology Focusing on Geoecology and Landscape Evolution >Within-site drivers for soil nutrient variability in plantation forests: A case study from dry sub-humid New Zealand
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Within-site drivers for soil nutrient variability in plantation forests: A case study from dry sub-humid New Zealand

机译:土壤养分变异性的现场内驾驶员森林中的土壤养分变异性:干燥亚湿润新西兰的案例研究

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摘要

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.
机译:人工林土壤性质的精确空间信息是改善土壤养分管理和维持生产力所必需的。土壤氮、磷、钾、有机质、碳和硼是土壤肥力和质量的重要决定因素和指标。特别是在森林中,这些土壤性质在空间和时间上都是高度可变的。在这项研究中,土壤样本取自新西兰布伦海姆附近一个干旱半湿润地区的三个人工林地点。选择了30个采样点,从三个地点收集了一系列斜坡和坡向地层的样本。对土壤样品进行了总碳(totC)、总氮(totN)、总磷(totP)、可提取钾(exK)和热水可提取硼(exB)分析。所有检测的土壤性质在不同地点之间存在显著差异(p<0.05)。然后在地理信息系统软件中对一组可能解释这种变化的小比例尺(5米分辨率)地形表面进行插值或推导。地形表面包括高程、坡向、坡度、剖面和平面曲率、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建立预测模型。研究发现,所有土壤性质均与MPI呈正相关,与土壤湿度呈负相关。这表明土壤性质与周围地形和风的遮蔽有关。有趣的是,场内硼水平与剖面曲率(PrCurv)和地形湿度指数均相关,表明硼在地表随土壤水分的移动而移动。本研究中的建模方法有可能应用于利用土壤肥力的空间精确估计对人工林进行可持续管理。

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