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A map of the topsoil organic carbon content of Europe generated by a generalized additive model

机译:广义添加剂模型生成的欧洲表土有机碳含量图

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There is an increasing demand for up-to-date soil organic carbon (OC) data for global environmental and climatic modelling. The aim of this study was to create a map of topsoil OC content at the European scale by applying digital soil mapping techniques to the first European harmonized geo-referenced topsoil (0-20 cm) database, which arises from the Land use/Cover Area frame statistical Survey (LUCAS). A map of the associated uncertainty was also produced to support careful use of the predicted OC contents. A generalized additive model (GAM) was fitted on 85% of the dataset (R-2 = 0.29), using OC content as dependent variable; a backward stepwise approach selected slope, land cover, temperature, net primary productivity, latitude and longitude as suitable covariates. The validation of the model (performed on 15% of the data-set) gave an overall R-2 of 0.27 and an R-2 of 0.21 for mineral soils and 0.06 for organic soils. Organic C content in most organic soils was under-predicted, probably because of the imposed unimodal distribution of our model, whose mean is tilted towards the prevalent mineral soils. This was also confirmed by the poor prediction in Scandinavia (where organic soils are more frequent), which gave an R-2 of 0.09, whilst the prediction performance (R-2) in non-Scandinavian countries was 0.28. The map of predicted OC content had the smallest values in Mediterranean countries and in croplands across Europe, whereas largest OC contents were predicted in wetlands, woodlands and mountainous areas. The map of the predictions' standard error had large uncertainty in northern latitudes, wetlands, moors and heathlands, whereas small uncertainty was mostly found in croplands. The map produced gives the most updated general picture of topsoil OC content at the European Union scale.
机译:对于用于全球环境和气候建模的最新土壤有机碳(OC)数据的需求日益增长。这项研究的目的是通过将数字土壤测绘技术应用到第一个欧洲统一的地理参考表土(0-20厘米)数据库中来创建欧洲规模的表层土壤OC含量地图,该数据库来自土地利用/覆盖面积框架统计调查(LUCAS)。还绘制了相关不确定性的图表,以支持谨慎使用预测的OC含量。使用OC含量作为因变量,将广义加性模型(GAM)拟合到数据集的85%(R-2 = 0.29);后退逐步方法选择坡度,土地覆盖率,温度,净初级生产力,纬度和经度作为适当的协变量。模型的验证(在数据集的15%上执行)得出矿物质土壤的总体R-2为0.27,R-2为0.21,有机土壤为0.06。大多数有机土壤中的有机碳含量被低估了,这可能是因为我们模型强加了单峰分布,其均值倾向于普遍的矿质土壤。斯堪的纳维亚半岛(有机土壤更为频繁)的预测不佳也证实了这一点,R-2值为0.09,而非斯堪的纳维亚国家的预测绩效(R-2)为0.28。在地中海国家和整个欧洲的农田中,预测的OC含量图值最小,而在湿地,林地和山区中预测的OC含量最大。预测的标准误差图在北部纬度,湿地,沼泽和荒地中具有较大的不确定性,而在农田中则存在较小的不确定性。绘制的地图提供了欧盟范围内表层土壤中OC含量的最新信息。

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