Jaakko Heikkinen, Joel Kostensalo, Riikka Keskinen, Helena Soinne, Visa Nuutinen
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引用次数: 0
摘要
芬兰农业土壤状况通过全国和欧盟(EU)范围内的 LUCAS 土壤采样进行定期监测。在本研究中,我们比较了 2009-2018 年两个数据集中有机碳含量(OC)、pH 值、磷(P)和钾(K)的时间趋势和变异性。国家监测计划包含更多的监测地块(620 个,2018 年为 134 个),而 LUCAS 的采样重复频率更高,除 2009 年和 2018 年的数据外,还包括 2015 年的数据。与国家监测数据相比,LUCAS 数据集中所有考察指标的时间变异性都要高得多。在矿质土壤中,2009 年和 2018 年测量的元素含量之间的斯皮尔曼等级相关系数在国家数据集中介于 0.82 和 0.94 之间,在 LUCAS 数据集中介于 0.52 和 0.67 之间。有机土壤的结果与矿质土壤的结果相同。LUCAS 数据集的变异性较高,这可能是由于取样地块的地理位置不够精确和/或取样方案不同,例如取样深度更大,以及使用铲子而不是岩心钻。LUCAS 数据集的时间变异性较大,加上取样地块数量较少,导致统计功率较低,从而使检测具有实际规模的趋势变得更具挑战性。此外,在 LUCAS 数据中,无论是否包含 2015 年的数据,趋势的置信区间大小相同。我们发现,全国数据集足以检测全国范围内的元素含量趋势。我们的研究结果表明,与增加采样点数量相比,完善采样方案和提高采样点位置的准确性是提高时间趋势估计精度的更具成本效益的方法。
Temporal trends in Finnish agricultural soils: A comparative analysis of national and LUCAS soil monitoring datasets
Finnish agricultural soil conditions are regularly monitored both through national and European Union (EU)-wide LUCAS Soil sampling. In this study, we compare temporal trends and variability in organic carbon content (OC), pH, phosphorus (P) and potassium (K) in 2009–2018 across the two datasets. The national monitoring programme encompasses more monitoring plots (620 vs. 134 in 2018), while LUCAS sampling is repeated more frequently and in addition to 2009 and 2018, it also includes data from 2015. The temporal variability in all examined indicators was substantially higher in the LUCAS dataset compared to the national monitoring data. In mineral soils, Spearman's rank correlation coefficient between element contents measured in 2009 and 2018 ranged between 0.82 and 0.94 in the national dataset, and between 0.52 and 0.67 in the LUCAS dataset. The results for organic soils mirrored those of mineral soils. The higher variability in the LUCAS dataset may be attributed to less precise geolocation of sampling plots and/or variations in the sampling protocol such as greater sampling depth and the use of a spade instead of a core auger. The greater temporal variability, coupled with a smaller number of sampling plots in the LUCAS dataset, resulted in lower statistical power making the detection of trends with a realistic magnitude more challenging. Further, in LUCAS data, the confidence intervals of trends were of the same magnitude, regardless of whether the data from the year 2015 was included or not. The national dataset was found to be sufficient for detecting nationwide trends in element contents. Our results indicate that refining sampling protocols and improving the location accuracy of sampling plots are more cost-effective approaches to enhance the precision of temporal trend estimation than increasing the number of sampling plots.
期刊介绍:
The EJSS is an international journal that publishes outstanding papers in soil science that advance the theoretical and mechanistic understanding of physical, chemical and biological processes and their interactions in soils acting from molecular to continental scales in natural and managed environments.