Abstract
The emphasis put on environmental issues of the European Union (EU) agricultural sector in the strategies like the European Green Deal, Biodiversity and Farm to fork strategy give new directions to the Common Agricultural Policy (CAP) changing the EU agricultural practice into a more environment-and climate-friendly manner. The modified support rules and obligations for farmers will necessitate adopting new farm management practices on farms. This paper proposes the Agri-environmental Footprint Index (AFI) as a tool to identify the current state of the environmental situation and to track the changes and achievements on farms. The proposed approach is applied for the case study in Lithuania for 2017. The farm-level data from the Lithuanian Farm Accountancy data Network (FADN) are exploited. The paper relies on the multivariate statistical techniques (Shannon Entropy and Principal Component Analysis) and multi-criteria approach (Simple Additive Weighting) to construct the composite indicators. The results are analyzed across farming types and farm size classes. The most environmentally beneficial farms are characterized as medium-sized (in economic terms) and specialized in field crops-grazing livestock. The highest share of farms with a low value of AFI was found for the largest farm size class and for farms specialized in horticulture (using Shannon entropy weighting) and orchards (using Principal Component Analysis (PCA) weighting). The results of AFIs using Shannon entropy and PCA weighting across farming types tended to differ. Therefore, in order to apply the proposed tool in practice, testing different weighting schemes is preferable.
Dabkienė, V.; Baležentis, T.; Štreimikienė, D. 2021. Development of agri-environmental footprint indicator using the FADN data: Tracking development of sustainable agricultural development in Eastern Europe. Sustainable Production and Consumption: Elsevier. ISSN 2352-5509. 27, July, p. 2121– 2133; DOI: 10.1016/j.spc.2021.05.017; [Citation Index Expanded (Web of Science)].