The Swiss agri-environmental data network (SAEDN): Description and critical review of the dataset

Abstract

CONTEXTThe Swiss agri-environmental data network (SAEDN) encompasses farm management data, which are collected and processed annually to calculate indicators such as greenhouse gas emissions, potential biodiversity impact, or erosion risk. These indicators are yearly published in the framework of an agri-environmental monitoring programme and serve as decision support for policy makers and other stakeholders. Furthermore, the collected data are frequently used for research projects. OBJECTIVEThis paper compares the SAEDN farms with the whole of Switzerland. It addresses the question of how appropriate the data collected are for monitoring purposes as well as research projects. METHODSThe data collection procedure of the SAEDN is described in detail, including automated tests that improve the data quality. Furthermore, key figures of the SAEDN farms are analysed and compared with the whole of Switzerland in order to assess the significance of the farm network. RESULTS AND CONCLUSIONSThe time-consuming data collection has resulted in a relatively small, non-random sample of Swiss farms (approx. 300 farms per year). The farms participating in the SAEDN represent the dominant agroecosystems of Switzerland reasonably well, while certain crop specialisations (viticulture and field vegetable production) and small ruminant husbandry are only marginally represented. The latter can partially be explained by an underrepresentation of farms located in southern Switzerland and in the mountains. Another problem is the continuously changing composition of the farm network. Thus, robust time series cannot be produced for all desired farm classifications (e.g. special crops). SIGNIFICANCEThe collected data offer valuable insights into Swiss land use and farm management practices. To our knowledge, the presented dataset is the most comprehensive source of agronomic data in Switzerland covering many aspects such as complete crop rotations, field-specific fertilisation, and plant protection product use. The data thus provide an important basis for research projects, decisions in the political and legal context, and the development of a future monitoring system.