ETH Zurich, Institute of Environmental Engineering, Chair of Ecological Systems Design, John-von-Neumann-Weg 9, CH-8093 Zurich, Switzerland.
Technische Hochschule Ingolstadt, Faculty of Mechanical Engineering, Geothermal Energy, Esplanade 10, P.O. Box 21 04 54, D-85049 Ingolstadt, Germany.
Sci Total Environ. 2018 Jul 15;630:913-921. doi: 10.1016/j.scitotenv.2018.02.222. Epub 2018 Mar 7.
Maintaining biotic capacity is of key importance with regard to global food and biomass provision. One reason for productivity loss is soil compaction. In this paper, we use a statistical empirical model to assess long-term yield losses through soil compaction in a regionalized manner, with global coverage and for different agricultural production systems. To facilitate the application of the model, we provide an extensive dataset including crop production data (with 81 crops and corresponding production systems), related machinery application, as well as regionalized soil texture and soil moisture data. Yield loss is modeled for different levels of soil depth (0-25cm, 25-40cm and >40cm depth). This is of particular relevance since compaction in topsoil is classified as reversible in the short term (approximately four years), while recovery of subsoil layers takes much longer. We derive characterization factors quantifying the future average annual yield loss as a fraction of the current yield for 100years and applicable in Life Cycle Assessment studies of agricultural production. The results show that crops requiring enhanced machinery inputs, such as potatoes, have a major influence on soil compaction and yield losses, while differences between mechanized production systems (organic and integrated production) are small. The spatial variations of soil moisture and clay content are reflected in the results showing global hotspot regions especially susceptible to soil compaction, e.g. the South of Brazil, the Caribbean Islands, Central Africa, and the Maharashtra district of India. The impacts of soil compaction can be substantial, with highest annual yield losses in the range of 0.5% (95% percentile) due to one year of potato production (cumulated over 100y this corresponds to a one-time loss of 50% of the present yield). These modeling results demonstrate the necessity for including soil compaction effects in Life Cycle Impact Assessment.
维持生物能力对于全球粮食和生物质供应至关重要。生产力下降的一个原因是土壤压实。在本文中，我们使用统计经验模型以区域化的方式评估长期土壤压实造成的产量损失，覆盖范围为全球，针对不同的农业生产系统。为了便于模型的应用，我们提供了一个包含作物生产数据（包括 81 种作物和相应的生产系统）、相关机械应用以及区域化土壤质地和土壤湿度数据的广泛数据集。我们针对不同的土壤深度水平（0-25cm、25-40cm 和>40cm 深度）对产量损失进行建模。这是特别重要的，因为表层土壤的压实在短期内被归类为可逆（大约四年），而底土层的恢复需要更长的时间。我们得出了特征化因子，这些因子将未来每年平均产量损失量化为当前产量的分数，适用于农业生产的生命周期评估研究。结果表明，需要增强机械投入的作物，如土豆，对土壤压实和产量损失有重大影响，而机械化生产系统（有机和综合生产）之间的差异较小。土壤湿度和粘粒含量的空间变化反映在结果中，显示出全球特别容易受到土壤压实影响的热点地区，例如巴西南部、加勒比岛屿、中非和印度马哈拉施特拉邦。土壤压实的影响可能很大，由于一年的土豆生产（100 年内累计），最高年产量损失在 0.5%（95%分位数）范围内，这相当于当前产量的 50%一次性损失。这些建模结果表明，在生命周期影响评估中必须包括土壤压实效应。
