Agri-environmental footprint index of family farms using FADN data: methodology and application
Lithuania is running an ecological deficit as its Ecological Footprint exceeds its biocapacity. Despite the fact that this deficit is small (0.4 gha), Lithuania is the only country with an ecological deficit among Baltic countries. Lithuania is losing the image of "green country" and there are the reasons behind this state. Agriculture's role is essential, both in adaptation to the climate change and contribution to the mitigation efforts. Strategic plan for the next long-term EU budget 2021–2027 will be drawn by Lithuania under the EU Common Agricultural Policy strategic plan (COM (2018) 392) towards the transition to a more sustainable farming. The environmental performance of farming is linked to three of nine main objectives: "Contribute to climate change mitigation and adaptation, as well as sustainable energy"; "Foster sustainable development and efficient management of natural resources such as water, soil and air" and "Contribute to the protection of biodiversity, enhance ecosystem services and preserve habitats and landscapes". The environmental performance of agriculture is manifold, therefore to capture important aspects of farm environmental performance a list of criteria and indicators have been proposed to reveal the situation in the country. Having many indicators, there is a problem to view the main picture of environmental performance and to track the environmental changes influenced by policy. Alongside to that, most indicators enable the analysis at sector level, which limits to disclose problems within farm groups in terms of specialization and size. Farmers adopt new technologies and practices to deal with climate change, protect and preserve the environment, therefore it is important to determine how and how well farmers mitigate and adapt to climate change. Developing the Agri-environmental Footprint Index (AFI) of family farm addresses the need to assess the farm-scale environmental performance. The AFI methodology is based on index construction steps in combination with the primary data of Lithuanian FADN, to reveal differences across farms in terms of their specialization and economic size and to test whether it could be used routinely for policy purposes. Lithuanian FADN of family farms data of the year 2017 were used covering 1300 farms. Furthermore, in this paper the AFI values are reported on the basis of the weighting used in the Lithuanian FADN sample for Lithuanian family farms so that the surveyed farms results represent a national farming population. The final set of indicators for agrienvironmental assessment of the farms was derived from extensive literature review on farms' environmental and sustainability studies. The min–max method was applied to transform values of indicators expressed in variety dimensions for their need to be put on a common basis, namely in interval from 0 to 1. The Principal Components Analysis (PCA) and equal weighting was applied to estimate weights for the indicators. The thresholds values of farms' AFI intervals indicating low, medium and high environmental performance were estimated based on descriptive statistics. The findings of assessment indicates very good level of Lithuanian family farms environmental performance as 74% and 70% of the 44 sample farms were defined by medium level of AFI, using PCA and equal weighting, respectively. With respect to applied methods of weighting, the results differed within farm groups in terms of their specialization: the highest level of AFI was found for grazing livestock and for field crop farms, using PCA and equal weighting, respectively. At the other end of spectrum, the lowest values of AFI were found for specialist granivores farms regardless of the weighing method being applied. The highest AFI values within farm groups regarding their economic size were found for medium sized farms despite the weighting method used. The index structure is flexible and can respond to diverse local policy needs. The results of the AFI provide a new knowledge about farms environmental performance, disclose problems across farm groups and can be the basis for political decisions that lead to sustainable development of agricultural sector in Lithuania.