The increasing demand for agricultural commodities for food and energy purposes has led to intensified agricultural land management, along with the homogenization of landscapes, adverse biodiversity effects and robustness of landscapes regarding the provision of ecosystem services. At the same time, subsidized organic agriculture and extensive grassland use supports the provision of ecosystem services. Yet little is understood about how to evaluate a landscape’s potential to contribute to protecting and enhancing biodiversity and ecosystem services. To address this gap, we use plot-level data from the Integrated Administration and Control System (IACS) for Germany’s federal state of Brandenburg, and based on a two-step cluster analysis, we identify six types of agricultural landscapes. These clusters differ in landscape structure, diversity and measures for agricultural land management intensity. Agricultural land in Brandenburg is dominated by high shares of cropland but fragmented differently. Lands under organic management and those with a high share of maize show strong spatial autocorrelation, pointing to local clusters. Identification of different types of landscapes permits locally- and region-adapted designs of environmental and agricultural policy measures improves outcome-oriented environmental policy impact evaluation and landscape planning. Our approach allows transferability to other EU regions.

用于粮食和能源目的对农业商品的需求不断增长，导致加强了农业土地管理，以及景观的均质化，不利的生物多样性影响和景观在提供生态系统服务方面的稳健性。同时，有补贴的有机农业和广泛的草地利用支持了生态系统服务的提供。对于如何评估景观对保护和增强生物多样性及生态系统服务的潜力知之甚少。为了解决这一差距，我们使用了来自德国联邦勃兰登堡州综合管理与控制系统（IACS）的地块级数据，并基于两步聚类分析，确定了六种类型的农业景观。这些集群的景观结构不同，农业土地管理强度的多样性和措施。勃兰登堡州的农业用地以高耕地为主，但分割程度不同。有机管理的土地和玉米所占比例较高的土地表现出很强的空间自相关性，指向本地集群。识别不同类型的景观可以进行适合当地和地区的环境和农业政策措施设计，从而改善以结果为导向的环境政策影响评估和景观规划。我们的方法允许向其他欧盟地区转移。指向本地集群。识别不同类型的景观可以进行适合当地和地区的环境和农业政策措施设计，从而改善以结果为导向的环境政策影响评估和景观规划。我们的方法允许向其他欧盟地区转移。指向本地集群。识别不同类型的景观可以进行适合当地和地区的环境和农业政策措施设计，从而改善以结果为导向的环境政策影响评估和景观规划。我们的方法允许向其他欧盟地区转移。