Dresden University of Technology, Institute for Soil Science and Site Ecology, Pienner Strasse 19, Tharandt, Germany.
J Environ Manage. 2013 Sep;127 Suppl:S37-47. doi: 10.1016/j.jenvman.2013.04.050. Epub 2013 Jun 7.
Regarding increasing pressures by global societal and climate change, the assessment of the impact of land use and land management practices on land degradation and the related decrease in sustainable provision of ecosystem services gains increasing interest. Existing approaches to assess agricultural practices focus on the assessment of single crops or statistical data because spatially explicit information on practically applied crop rotations is mostly not available. This provokes considerable uncertainties in crop production models as regional specifics have to be neglected or cannot be considered in an appropriate way. In a case study in Saxony, we developed an approach to (i) derive representative regional crop rotations by combining different data sources and expert knowledge. This includes the integration of innovative crop sequences related to bio-energy production or organic farming and different soil tillage, soil management and soil protection techniques. Furthermore, (ii) we developed a regionalization approach for transferring crop rotations and related soil management strategies on the basis of statistical data and spatially explicit data taken from so called field blocks. These field blocks are the smallest spatial entity for which agricultural practices must be reported to apply for agricultural funding within the frame of the European Agricultural Fund for Rural Development (EAFRD) program. The information was finally integrated into the spatial decision support tool GISCAME to assess and visualize in spatially explicit manner the impact of alternative agricultural land use strategies on soil erosion risk and ecosystem services provision. Objective of this paper is to present the approach how to create spatially explicit information on agricultural management practices for a study area around Dresden, the capital of the German Federal State Saxony.
关于全球社会和气候变化带来的压力不断增加,评估土地利用和土地管理实践对土地退化的影响以及相关的生态系统服务可持续提供减少的问题,引起了越来越多的关注。现有的农业实践评估方法侧重于单一作物或统计数据的评估,因为实际上应用的作物轮作的空间明确信息大多不可用。这在作物生产模型中引发了相当大的不确定性,因为必须忽略或不能以适当的方式考虑区域具体情况。在萨克森州的一个案例研究中,我们开发了一种方法(i)通过结合不同的数据源和专家知识来推导出具有代表性的区域作物轮作。这包括整合与生物能源生产或有机农业相关的创新作物序列以及不同的土壤耕作、土壤管理和土壤保护技术。此外,(ii)我们开发了一种基于统计数据和从所谓的田间区块中获取的空间明确数据的区域化方法,用于转移作物轮作和相关的土壤管理策略。这些田间区块是最小的空间实体,必须报告农业实践才能在欧洲农村发展农业基金(EAFRD)计划框架内申请农业资金。最后,这些信息被整合到空间决策支持工具 GISCAME 中,以评估和以空间明确的方式可视化替代农业土地利用策略对土壤侵蚀风险和生态系统服务提供的影响。本文的目的是介绍如何为德国萨克森州首府德累斯顿周围的研究区域创建农业管理实践的空间明确信息的方法。