Stevens Antoine, Nocita Marco, Tóth Gergely, Montanarella Luca, van Wesemael Bas
Georges Lemaître Centre for Earth and Climate Research, Earth and Life Institute, UCLouvain, Louvain-la-Neuve, Belgium.
PLoS One. 2013 Jun 19;8(6):e66409. doi: 10.1371/journal.pone.0066409. Print 2013.
Soil organic carbon is a key soil property related to soil fertility, aggregate stability and the exchange of CO2 with the atmosphere. Existing soil maps and inventories can rarely be used to monitor the state and evolution in soil organic carbon content due to their poor spatial resolution, lack of consistency and high updating costs. Visible and Near Infrared diffuse reflectance spectroscopy is an alternative method to provide cheap and high-density soil data. However, there are still some uncertainties on its capacity to produce reliable predictions for areas characterized by large soil diversity. Using a large-scale EU soil survey of about 20,000 samples and covering 23 countries, we assessed the performance of reflectance spectroscopy for the prediction of soil organic carbon content. The best calibrations achieved a root mean square error ranging from 4 to 15 g C kg(-1) for mineral soils and a root mean square error of 50 g C kg(-1) for organic soil materials. Model errors are shown to be related to the levels of soil organic carbon and variations in other soil properties such as sand and clay content. Although errors are ∼5 times larger than the reproducibility error of the laboratory method, reflectance spectroscopy provides unbiased predictions of the soil organic carbon content. Such estimates could be used for assessing the mean soil organic carbon content of large geographical entities or countries. This study is a first step towards providing uniform continental-scale spectroscopic estimations of soil organic carbon, meeting an increasing demand for information on the state of the soil that can be used in biogeochemical models and the monitoring of soil degradation.
土壤有机碳是一种与土壤肥力、团聚体稳定性以及与大气中二氧化碳交换相关的关键土壤属性。由于现有土壤图和清单的空间分辨率低、缺乏一致性且更新成本高,因此很少能用于监测土壤有机碳含量的状态和演变。可见和近红外漫反射光谱法是一种提供廉价且高密度土壤数据的替代方法。然而,对于具有高度土壤多样性的地区,其产生可靠预测的能力仍存在一些不确定性。我们利用一项对约20000个样本、覆盖23个国家的大规模欧盟土壤调查,评估了反射光谱法预测土壤有机碳含量的性能。对于矿质土壤,最佳校准的均方根误差范围为4至15克碳/千克,对于有机土壤物质,均方根误差为50克碳/千克。模型误差显示与土壤有机碳水平以及其他土壤属性(如砂和粘土含量)的变化有关。尽管误差比实验室方法的重现性误差大约5倍,但反射光谱法对土壤有机碳含量提供了无偏预测。此类估计可用于评估大型地理区域或国家的平均土壤有机碳含量。本研究是朝着提供统一的大陆尺度土壤有机碳光谱估计迈出的第一步,满足了对可用于生物地球化学模型和土壤退化监测的土壤状态信息日益增长的需求。