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Validating the regional estimates of changes in soil organic carbon by using the data from paired-sites: the case study of Mediterranean arable lands
Carbon Balance and Management ( IF 3.9 ) Pub Date : 2021-06-07 , DOI: 10.1186/s13021-021-00182-7
Calogero Schillaci 1 , Sergio Saia 2 , Aldo Lipani 3 , Alessia Perego 1 , Claudio Zaccone 4 , Marco Acutis 1
Affiliation  

Legacy data are unique occasions for estimating soil organic carbon (SOC) concentration changes and spatial variability, but their use showed limitations due to the sampling schemes adopted and improvements may be needed in the analysis methodologies. When SOC changes is estimated with legacy data, the use of soil samples collected in different plots (i.e., non-paired data) may lead to biased results. In the present work, N = 302 georeferenced soil samples were selected from a regional (Sicily, south of Italy) soil database. An operational sampling approach was developed to spot SOC concentration changes from 1994 to 2017 in the same plots at the 0–30 cm soil depth and tested. The measurements were conducted after computing the minimum number of samples needed to have a reliable estimate of SOC variation after 23 years. By applying an effect size based methodology, 30 out of 302 sites were resampled in 2017 to achieve a power of 80%, and an α = 0.05. A Wilcoxon test applied to the variation of SOC from 1994 to 2017 suggested that there was not a statistical difference in SOC concentration after 23 years (Z = − 0.556; 2-tailed asymptotic significance = 0.578). In particular, only 40% of resampled sites showed a higher SOC concentration than in 2017. This finding contrasts with a previous SOC concentration increase that was found in 2008 (75.8% increase when estimated as differences of 2 models built with non-paired data), when compared to 1994 observed data (Z = − 9.119; 2-tailed asymptotic significance < 0.001). This suggests that the use of legacy data to estimate SOC concentration dynamics requires soil resampling in the same locations to overcome the stochastic model errors. Further experiment is needed to identify the percentage of the sites to resample in order to align two legacy datasets in the same area.

中文翻译:


使用配对地点的数据验证土壤有机碳变化的区域估计:地中海耕地的案例研究



遗留数据是估算土壤有机碳(SOC)浓度变化和空间变异性的独特场合,但由于采用的采样方案,它们的使用显示出局限性,并且分析方法可能需要改进。当使用遗留数据估计 SOC 变化时,使用在不同地块收集的土壤样本(即非配对数据)可能会导致有偏差的结果。在目前的工作中,N = 302 个地理参考土壤样本选自区域(西西里岛、意大利南部)土壤数据库。开发了一种可操作的采样方法,用于发现 1994 年至 2017 年同一地块 0-30 厘米土壤深度的 SOC 浓度变化并进行测试。测量是在计算出 23 年后可靠估计 SOC 变化所需的最小样本数量后进行的。通过应用基于效应大小的方法,2017 年对 302 个站点中的 30 个进行了重新采样,以达到 80% 的功效,且 α = 0.05。对 1994 年至 2017 年 SOC 变化进行的 Wilcoxon 检验表明,23 年后 SOC 浓度没有统计学差异(Z = − 0.556;2 尾渐近显着性 = 0.578)。特别是,只有 40% 的重采样点显示出比 2017 年更高的 SOC 浓度。这一发现与 2008 年发现的先前 SOC 浓度增加形成鲜明对比(当估计为使用非配对数据构建的 2 个模型的差异时,增加了 75.8%) ,与 1994 年观测数据相比(Z = − 9.119;2 尾渐近显着性< 0.001)。这表明,使用遗留数据来估计 SOC 浓度动态需要在相同位置进行土壤重采样,以克服随机模型误差。 需要进一步的实验来确定要重新采样的站点的百分比,以便对齐同一区域中的两个遗留数据集。
更新日期:2021-06-08
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