Abstract
Lithuania is the only one of the Baltic States to run an ecological deficit (Global Footprint Network 2021). According to Lithuanian strategic documents (LAEI 2016), the agriculture sector remains one of the priority sectors and performs an important economic, environmental, and social role. However, the Lithuanian agricultural sector experiences numerous challenges in achieving environmental sustainability. This paper contributes to the practice by providing a tool for agri-environmental performance assessment at farm level using simple, sound, and transparent Agri-environmental Footprint Index (AFI) construction procedures, and the results of its application are presented through a case study in Lithuania for the years 2016 and 2017. The set of 12 indicators customized to Farm Accountancy Data Network (FADN) system data was devised to quantify the environmental pressures, which can assist in developing similar indicators or can be adopted in other studies. The findings for Lithuanian family farms indicate a good level of agri-environmental performance as over two-thirds of the sample farms were defined by medium AFI levels. Nevertheless, more than one-tenth of farms achieved a low level of AFI, and these farms require more stimulus and policy interventions for better environmental performance.
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References
Araro K, Legesse SA, Meshesha DT (2019) Climate change and variability impacts on rural livelihoods and adaptation strategies in Southern Ethiopia. Earth Syst Environ 4:15–26. https://doi.org/10.1007/s41748-019-00134-9
Areal FJ, Jones PJ, Mortimer SR, Wilson P (2018) Measuring sustainable intensification: combining composite indicators and efficiency analysis to account for positive externalities in cereal production. Land Use Policy 75:314–326. https://doi.org/10.1016/j.landusepol.2018.04.001
Bachev H (2017) Socio-economic and environmental sustainability of Bulgarian farms. Agric Resour Econ Int Scientif e-Js 3(2):5–21
Barnes AP, Thomson SG (2014) Measuring progress towards sustainable intensification: how far can secondary data go? Ecol Indic 36:213–220. https://doi.org/10.1016/j.ecolind.2013.07.001
Browne NA, Eckard RJ, Behrendt R, Kingwell RS (2011) A comparative analysis of on-farm greenhouse gas emissions from agricultural enterprises in south eastern Australia. Anim Feed Sci Technol 166:641–652. https://doi.org/10.1016/j.anifeedsci.2011.04.045
Czyżewski B, Matuszczak A, Muntean A (2019) Approaching environmental sustainability of agriculture: environmental burden, eco-efficiency or eco-effectiveness. Agric Econ 65(7):299–306. https://doi.org/10.17221/290/2018-AGRICECON
Dabkienė V (2018) The relative sustainability of the family farm assessment: methodology and application [monograph]. LAEI, Vilnius. https://www.laei.lt/?mt=leidiniai&straipsnis=1384&metai=2018. Accessed 1 Nov 2019 (in Lithuanian)
Dabkienė V, Baležentis T, Štreimikienė D (2020) Estimation of the carbon footprint for family farms using the Farm Accountancy Data Network: a case from Lithuania. J Clean Prod 121509. https://doi.org/10.1016/j.jclepro.2020.121509
Dantsis T, Douma C, Giourga C, Loumou A, Polychronaki EA (2010) A methodological approach to assess and compare the sustainability level of agricultural plant production systems. Ecol Indic 10(2):256–263. https://doi.org/10.1016/j.ecolind.2009.05.007
Diti I, Tassinari P, Torreggiani D (2015) The agri-environmental footprint: a method for the identification and classification of peri-urban areas. J Environ Manag 162:250–262. https://doi.org/10.1016/j.jenvman.2015.07.058
EC (2009) Directive 2009/128/EC of the European Parliament and of the Council of 21 October 2009 Establishing a Framework for Community Action to Achieve the Sustainable use of Pesticides. https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ:L:2009:309:0071:0086:en:PDF. Accessed 1 May 2020
EC (2019a) CAP context indicators – 2018. https://ec.europa.eu/agriculture/cap-indicators/context/2018_en. Accessed 8 May 2020
EC (2019b) The European Green Deal. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=COM%3A2019%3A640%3AFIN. Accessed Mar 2021
EC (2020a) EU 2030 biodiversity strategy. https://ec.europa.eu/commission/presscorner/detail/en/fs_20_906. Accessed 8 Oct 2020
EC (2020b) European Climate Law. https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:52020PC0080. Accessed Mar 2021
EC (2020c) Farm to fork strategy – for a fair, healthy and environmentally-friendly food system. https://ec.europa.eu/food/farm2fork_en. Accessed 8 Oct 2020
EC (2020d) The future of the common agricultural policy. https://ec.europa.eu/info/food-farming-fisheries/key-policies/common-agricultural-policy/future-cap_en#objectives. Accessed 8 July 2020
EC (2020e) Trends in harmonised risk indicators for member states. https://ec.europa.eu/food/plant/pesticides/sustainable_use_pesticides/harmonised-risk-indicators/trends-hri-ms_en. Accessed 8 Oct 2020
EC DG Agriculture and Rural Development (2020) RICC 1750 Standard results V SEP 2020. https://circabc.europa.eu/ui/group/880bbb5b-abc9-4c4c-9259-5c58867c27f5/library/17a3cb1f-8199-4df2-b857-161fefc4c857/details. Accessed 1 Mar 2021
Environmental Protection Agency (2020) 2018 m. Kuršių marių ir Baltijos jūros ekologinė ir cheminė būklė. http://vanduo.gamta.lt/cms/index?rubricId=0a48c125-a5cf-40e1-bb15-31fee9b2e45d. Accessed 1 July 2020 (in Lithuanian)
EU FADN (2020) FADN public database. [dataset]. https://ec.europa.eu/agriculture/rica/database/database_en.cfm. Accessed 8 July 2020
Eurostat (2011) Statistics explained. https://ec.europa.eu/eurostat/statistics-explained/index.php?title=File:Shannon_Diversity_Index_and_Shannon_Evenness_Index,_2009.PNG&oldid=62296. Accessed 1 July 2020
Eurostat (2020) Eurostat database. [dataset]. https://ec.europa.eu/eurostat/data/database. Accessed 1 July 2020
FADN (2018) Methodology. https://ec.europa.eu/agriculture/rica/pdf/site_en.pdf. Accessed 1 Nov 2019
FAOSTAT (2020) Pesticide indicators. [dataset]. http://www.fao.org/faostat/en/#data/EP/visualize. Accessed 1 May 2020
Field AP (2009) Discovering statistics using SPSS, 3rd edn. Sage
Frater P, Franks J (2013) Measuring agricultural sustainability at the farm-level: a pragmatic approach. Int J Agric Manag 2(4):207–225. https://doi.org/10.5836/ijam/2013-04-04
Galdeano-Gómez E, Aznar-Sánchez JA, Pérez-Mesa JC, Piedra-Muñoz L (2017) Exploring synergies among agricultural sustainability dimensions: an empirical study on farming system in Almería (southeast Spain). Ecol Econ 140:99–109. https://doi.org/10.1016/j.ecolecon.2017.05.001
Gan X, Fernandez IC, Guo J, Wilson M, Zhao Y, Zhou B, Wu J (2017) When to use what: methods for weighting and aggregating sustainability indicators. Ecol Indic 81:491–502. https://doi.org/10.1016/j.ecolind.2017.05.068
Gaviglio A, Bertocchi M, Demartini E (2017) A tool for the sustainability assessment of farms: selection, adaptation and use of indicators for an Italian case study. Resources 6(4):60. https://doi.org/10.3390/resources6040060
Gerrard CL, Padel S, Moakes S (2012) The use of Farm Business Survey data to compare the environmental performance of organic and conventional farms. Int J Agric Manag 2(1):5–16
Global Footprint Network (2021) https://www.footprintnetwork.org/our-work/countries/. Accessed 1 Mar 2021
Goewie E, da Silva J, Zabaleta JP, de Souza RM (2006) What is sustainable farming? Public Admin Public Policy (New York) 118:189
Gómez-Limón JA, Sanchez-Fernandez G (2010) Empirical evaluation of agricultural sustainability using composite indicators. Ecol Econ 69(5):1062–1075. https://doi.org/10.1016/j.ecolecon.2009.11.027
Goswami R, Saha S, Dasgupta P (2017) Sustainability assessment of smallholder farms in developing countries. Agroecol Sustain Food Syst 41(5):546–569. https://doi.org/10.1080/21683565.2017.1290730
Guiomar N, Godinho S, Pinto-Correia T, Almeida M, Bartolini F, Bezak P et al (2018) Typology and distribution of small farms in Europe: towards a better picture. Land Use Policy 75:784–798. https://doi.org/10.1016/j.landusepol.2018.04.012
Hani F, Braga FS, Stampfli A, Keller T, Fischer M, Porsche H (2003) RISE, a tool for holistic sustainability assessment at the farm level. Int Food Agribus Manag Rev 6(1030-2016-82562):78–90
Hřebíček J, Valtinyová S, Křen J, Hodinka M, Trenz O, Marada P (2013) Sustainability indicators: development and application for the agriculture sector. In: Sustainability appraisal: quantitative methods and mathematical techniques for environmental performance evaluation. Springer, Berlin, pp 63–102
Hudrlíková L, Kramulová J, Zeman J (2013) Measuring sustainable development at the lower regional level in the Czech Republic based on composite indicators: measuring sustainable development in Czech LAU 1 regions using composite indicators. regional statistics. J Hungarian Central Statist Office 3:117–140
IPCC (2006) IPCC guidelines for national greenhouse gas inventories. Prepared by the National Greenhouse Gas Inventories Programme. http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html. Accessed 1 Nov 2019
Kasztelan A, Nowak A (2021) Construction and empirical verification of the Agri-Environmental Index (AEI) as a tool for assessing the green performance of agriculture. Energies 14(1):45. https://doi.org/10.3390/en14010045
Kelly E, Latruffe L, Desjeux Y, Ryan M, Uthes S, Diazabakana A et al (2018) Sustainability indicators for improved assessment of the effects of agricultural policy across the EU: is FADN the answer? Ecol Indic 89:903–911. https://doi.org/10.1016/j.ecolind.2017.12.053
Koloszko-Chomentowska Z, Žukovskis J, Gargasas A (2015) Ecological and economic sustainability of Polish and Lithuanian agricultural holdings specializing in animal production. In International scientific conference rural development 2017. https://doi.org/10.15544/RD.2015.130
Krajnc D, Glavič P (2005) How to compare companies on relevant dimensions of sustainability. Ecol Econ 55(4):551–563. https://doi.org/10.1016/j.resconrec.2004.06.002
Kudsk P, Jørgensen LN, Ørum JE (2018) Pesticide load: a new Danish pesticide risk indicator with multiple applications. Land Use Policy 70:384–393. https://doi.org/10.1016/j.landusepol.2017.11.010
LAEI (2016) Pasiūlymai dėl Lietuvos žemės ūkio ir kaimo plėtros strateginių krypčių ir siekinių iki 2030 metų „Tvarus Lietuvos žemės ūkis – gyvybingam kaimui“ file:///C:/Users/reader/Downloads/Strategija.pdf. Accessed 1 July 2020 (in Lithuanian)
LAEI (2020) FADN survey results. https://www.laei.lt/?mt=vt_UADT_tyrimas. Accessed 1 Nov 2019
LNIR (2019) Lithuania’s National Inventory Report: greenhouse gas emissions 1990–2017. https://unfccc.int/documents/194960. Accessed 1 Mar 2020
LNIR (2020) Lithuania’s National Inventory Report: greenhouse gas emissions 1990–2018. https://unfccc.int/documents/226319. Accessed 1 Mar 2021
Lynch J, Skirvin D, Wilson P, Ramsden S (2018) Integrating the economic and environmental performance of agricultural systems: a demonstration using Farm Business Survey data and Farmscoper. Sci Total Environ 628:938–946. https://doi.org/10.1016/j.scitotenv.2018.01.256
Meul M, Van Passel S, Nevens F, Dessein J, Rogge E, Mulier A, Van Hauwermeiren A (2008) MOTIFS: a monitoring tool for integrated farm sustainability. Agron Sustain Dev 28(2):321–332. https://doi.org/10.1051/agro:2008001
Migliorini P, Galioto F, Chiorri M, Vazzana C (2018) An integrated sustainability score based on agro-ecological and socioeconomic indicators. A case study of stockless organic farming in Italy. Agroecol Sustain Food Syst 42(8):859–884. https://doi.org/10.1080/21683565.2018.1432516
OECD-JRC (2008) Handbook on constructing composite indicators. Methodology and user guide. http://www.oecd.org/std/42495745.pdf. Accessed 1 July 2020
Paracchini ML, Bulgheron C, Borreani G, Tabacco E, Banterle A, Bertoni D et al (2015) A diagnostic system to assess sustainability at a farm level: the SOSTARE model. Agric Syst 133:35–53. https://doi.org/10.1016/j.agsy.2014.10.004
Peano C, Tecco N, Dansero E, Girgenti V, Sottile F (2015) Evaluating the sustainability in complex agri-food systems: the SAEMETH framework. Sustainability 7(6):6721–6741. https://doi.org/10.3390/su7066721
Purvis G, Louwagie G, Northe G, Mortimer, Park J, Mauchline A et al (2009) Conceptual development of a harmonised method for tracking change and evaluating policy in the agri-environment: the Agri-environmental Footprint Index. Environ Sci Pol 12(3):321–337. https://doi.org/10.1016/j.envsci.2009.01.005
Riaño B, García-González MC (2015) Greenhouse gas emissions of an on-farm swine manure treatment plant–comparison with conventional storage in anaerobic tanks. J Clean Prod 103:542–548. https://doi.org/10.1016/j.jclepro.2014.07.007
Ryan M, Hennessy T, Buckley C, Dillon EJ, Donnellan T, Hanrahan K, Moran B (2016) Developing farm-level sustainability indicators for Ireland using the Teagasc National Farm Survey. Ir J Agric Food Res 55(2):112–125. https://doi.org/10.1515/ijafr-2016-0011
Sabiha NE, Salim R, Rahman S, Rola-Rubzen MF (2016) Measuring environmental sustainability in agriculture: a composite environmental impact index approach. J Environ Manag 166:84–93. https://doi.org/10.1016/j.jenvman.2015.10.003
Savickienė J (2016). Šeimos ūkių ekonominio gyvybingumo vertinimas. Doctoral dissertation, Aleksandras Stulginskis University (in Lithuanian)
Schueler M, Hansen S, Paulsen HM (2018) Discrimination of milk carbon footprints from different dairy farms when using IPCC Tier 1 methodology for calculation of GHG emissions from managed soils. J Clean Prod 177:899–907. https://doi.org/10.1016/j.jclepro.2017.12.227
Statistics Lithuania (2018) Results of the Farm Structure Survey 2016. Vilnius.
Statistics Lithuania (2020) Database of indicators. [dataset]. https://osp.stat.gov.lt/statistiniu-rodikliu-analize#/. Accessed 1 Nov 2019
Stylianou A, Sdrali D, Apostolopoulos CD (2020) Integrated sustainability assessment of divergent mediterranean farming systems: Cyprus as a case study. Sustainability 12(15):6105. https://doi.org/10.3390/su12156105
Sulewski P, Kłoczko-Gajewska A (2018) Development of the sustainability index of farms based on surveys and FADN sample. Probl Agric Econ 3(356). https://doi.org/10.30858/zer/94474
Sulewski P, Kłoczko-Gajewska A, Sroka W (2018) Relations between agri-environmental, economic and social dimensions of farms’ sustainability. Sustainability 10(12):4629. https://doi.org/10.3390/su10124629
Svanbäck A, McCrackin ML, Swaney DP, Linefur H, Gustafsson BG, Howarth RW, Humborg C (2019) Reducing agricultural nutrient surpluses in a large catchment: links to livestock density. Sci Total Environ 648:1549–1559. https://doi.org/10.1016/j.scitotenv.2018.08.194
Trivino-Tarradas P, Gomez-Ariza MR, Basch G, Gonzalez-Sanchez EJ (2019) Sustainability assessment of annual and permanent crops: the Inspia model. Sustainability 11(3):738. https://doi.org/10.3390/su11030738
Tzouramani I, Mantziaris S, Karanikolas P (2020) Assessing sustainability performance at the farm level: examples from Greek agricultural systems. Sustainability 12(7):2929. https://doi.org/10.3390/su12072929
ul Haq S, Boz I (2020) Measuring environmental, economic, and social sustainability index of tea farms in Rize Province, Turkey. Environ Dev Sustain 22(3):2545–2567. https://doi.org/10.1007/s10668-019-00310-x
Uthes S, Herrera B (2019) Farm-level input intensity, efficiency and sustainability: a case study based on FADN farms (No. 2240-2019-3061)
Van Cauwenbergh N, Biala K, Bielders C, Brouckaert V, Franchois L, Cidad VG et al (2007) SAFE: a hierarchical framework for assessing the sustainability of agricultural systems. Agric Ecosyst Environ 120(2–4):229–242. https://doi.org/10.1016/j.agee.2006.09.006
Vesterager JP, Teilmann K, Vejre H (2012) Assessing long-term sustainable environmental impacts of agri-environment schemes on land use. Eur J For Res 131(1):95–107. https://doi.org/10.1007/s10342-010-0469-x
Volkov A, Melnikienė R (2017) CAP direct payments system’s linkage with environmental sustainability indicators. Public Policy Admin 14(2):231–244. https://doi.org/10.13165/VPA-17-16-2-05
Westbury DB, Park JR, Mauchline AL, Crane RT, Mortimer SR (2011) Assessing the environmental performance of English arable and livestock holdings using data from the Farm Accountancy Data Network (FADN). J Environ Manag 92(3):902–909. https://doi.org/10.1016/j.jenvman.2010.10.051
Wieck C, Hausmann I (2019) Indicators everywhere: the new accountability of agricultural policy? (No. 2230-2019-1957)
Wu J, Wu T (2012) Sustainability indicators and indices: an overview. In: Madu CN, Kuei C (eds) Handbook of sustainability management. Imperial Press, London, pp 65–86
Yona L, Cashore B, Jackson RB, Ometto J, Bradford MA (2020) Refining national greenhouse gas inventories. Ambio 49(10):1581–1586. https://doi.org/10.1007/s13280-019-01312-9
Zahm F, Viaux P, Vilain L, Girardin P, Mouchet C (2008) Assessing farm sustainability with the IDEA method: from the concept of agriculture sustainability to case studies on farms. Sustain Dev 16(4):271–281. https://doi.org/10.1002/sd.380
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Annexes
Annexes
5.1.1 Annex 1: Normalized Values of AFI Indicators by Type of Farming
Variables | COP | Field crops | Horticulture | Permanent crops | Dairy | Grazing livestock | Specialist granivores | Field crops-grazing livestock combined | Various mixed farms | Total | Significance | CV, % |
---|---|---|---|---|---|---|---|---|---|---|---|---|
In 2016 | ||||||||||||
Use of fertilizers | 0.68 (0.32) | 0.81 (0.29) | 0.83 (0.34) | 0.95 (0.11) | 0.93 (0.12) | 0.96 (0.10) | 0.95 (0.17) | 0.89 (0.18) | 0.82 (0.14) | 0.84 (0.25) | * | 10.5 |
Use of crop protection | 0.74 (0.30) | 0.85 (0.24) | 0.82 (0.35) | 0.92 (0.23) | 0.95 (0.11) | 0.97 (0.07) | 0.98 (0.10) | 0.94 (0.13) | 0.92 (0.13) | 0.87 (0.22) | * | 8.9 |
GHG emissions | 0.92 (0.14) | 0.97 (0.08) | 0.99 (0.03) | 0.99 (0.02) | 0.93 (0.12) | 0.92 (0.10) | 0.97 (0.11) | 0.92 (0.13) | 0.99 (0.02) | 0.94 (0.12) | * | 3.4 |
Energy intensity | 0.56 (0.30) | 0.70 (0.31) | 0.86 (0.16) | 0.59 (0.35) | 0.63 (0.27) | 0.69 (0.25) | 0.81 (0.29) | 0.56 (0.24) | 0.69 (0.24) | 0.62 (0.28) | * | 15.6 |
Biodiversity | 0.79 (0.18) | 0.79 (0.21) | 0.96 (0.11) | 0.34 (0.42) | 0.62 (0.34) | 0.51 (0.38) | 0.85 (0.30) | 0.80 (0.17) | 0.69 (0.32) | 0.71 (0.29) | * | 26.9 |
Meadows and pastures | 0.04 (0.09) | 0.16 (0.21) | 0.29 (0.36) | 0.05 (0.14) | 0.51 (0.37) | 0.39 (0.35) | 0.09 (0.24) | 0.32 (0.28) | 0.25 (0.33) | 0.28 (0.34) | * | 69.3 |
Livestock density | 0.98 (0.05) | 0.94 (0.08) | 0.94 (0.10) | 1.00 (0.01) | 0.72 (0.18) | 0.71 (0.19) | 0.42 (0.23) | 0.83 (0.11) | 0.87 (0.13) | 0.84 (0.17) | * | 22.4 |
Wooded area | 0.14 (0.28) | 0.06 (0.15) | 0.04 (0.32) | 0.05 (0.28) | 0.09 (0.29) | 0.05 (0.37) | 0.00 (0.07) | 0.15 (0.24) | 0.12 (0.37) | 0.11 (0.30) | * | 64.9 |
Accessibility | 0.01 (0.10) | 0.10 (0.31) | 0.11 (0.31) | 0.04 (0.21) | 0.04 (0.19) | 0.00 (0.04) | 0.20 (0.40) | 0.06 (0.24) | 0.01 (0.08) | 0.03 (0.18) | * | 101.4 |
Environment-friendly farming | 0.09 (0.27) | 0.16 (0.35) | 0.34 (0.46) | 0.36 (0.43) | 0.06 (0.18) | 0.13 (0.28) | 0.01 (0.07) | 0.10 (0.26) | 0.13 (0.33) | 0.10 (0.27) | * | 78.1 |
Water use | 0.73 (0.31) | 0.64 (0.36) | 0.78 (0.33) | 0.85 (0.28) | 0.60 (0.33) | 0.62 (0.30) | 0.76 (0.13) | 0.69 (0.31) | 0.64 (0.29) | 0.66 (0.32) | * | 12.0 |
Education | 0.42 (0.41) | 0.33 (0.39) | 0.36 (0.34) | 0.42 (0.40) | 0.33 (0.39) | 0.35 (0.42) | 0.08 (0.21) | 0.31 (0.38) | 0.28 (0.34) | 0.35 (0.39) | * | 31.6 |
In 2017 | ||||||||||||
Use of fertilizers | 0.67 (0.32) | 0.83 (0.22) | 0.71 (0.38) | 0.81 (0.36) | 0.92 (0.12) | 0.94 (0.10) | 0.86 (0.20) | 0.91 (0.15) | 0.93 (0.15) | 0.84 (0.24) | * | 11.6 |
Use of crop protection | 0.72 (0.31) | 0.85 (0.29) | 0.73 (0.39) | 0.79 (0.37) | 0.94 (0.13) | 0.95 (0.11) | 0.90 (0.15) | 0.93 (0.11) | 0.95 (0.12) | 0.87 (0.24) | * | 10.9 |
GHG emissions | 0.92 (0.14) | 0.97 (0.08) | 0.98 (0.04) | 0.99 (0.01) | 0.93 (0.11) | 0.93 (0.08) | 0.91 (0.17) | 0.94 (0.11) | 0.98 (0.03) | 0.94 (0.11) | * | 3.2 |
Energy intensity | 0.61 (0.31) | 0.71 (0.30) | 0.81 (0.18) | 0.70 (0.31) | 0.70 (0.24) | 0.63 (0.26) | 0.86 (0.14) | 0.59 (0.27) | 0.67 (0.23) | 0.65 (0.27) | * | 12.8 |
Biodiversity | 0.76 (0.22) | 0.72 (0.27) | 0.90 (0.24) | 0.32 (0.40) | 0.67 (0.32) | 0.62 (0.33) | 0.44 (0.43) | 0.78 (0.22) | 0.78 (0.27) | 0.72 (0.28) | * | 27.4 |
Meadows and pastures | 0.03 (0.08) | 0.07 (0.23) | 0.00 (0.03) | 0.04 (0.13) | 0.20 (0.27) | 0.20 (0.12) | 0.18 (0.39) | 0.16 (0.17) | 0.12 (0.21) | 0.13 (0.22) | * | 70.2 |
Livestock density | 0.97 (0.08) | 0.93 (0.15) | 0.86 (0.25) | 1.00 (0.01) | 0.46 (0.26) | 0.49 (0.25) | 0.08 (0.21) | 0.73 (0.18) | 0.64 (0.30) | 0.70 (0.30) | * | 44.1 |
Wooded area | 0.12 (0.31) | 0.12 (0.32) | 0.09 (0.29) | 0.04 (0.18) | 0.11 (0.30) | 0.03 (0.15) | 0.10 (0.29) | 0.13 (0.34) | 0.07 (0.25) | 0.10 (0.30) | * | 40.1 |
Accessibility | 0.04 (0.19) | 0.05 (0.22) | 0.01 (0.07) | 0.06 (0.23) | 0.03 (0.18) | 0.10 (0.31) | 0.00 (0.00) | 0.10 (0.30) | 0.04 (0.21) | 0.05 (0.22) | * | 73.1 |
Environment-friendly farming | 0.10 (0.30) | 0.09 (0.26) | 0.10 (0.24) | 0.35 (0.42) | 0.08 (0.24) | 0.07 (0.21) | 0.01 (0.10) | 0.11 (0.27) | 0.14 (0.31) | 0.10 (0.27) | * | 80.9 |
Water use | 0.74 (0.29) | 0.65 (0.35) | 0.70 (0.40) | 0.75 (0.35) | 0.56 (0.35) | 0.56 (0.38) | 0.85 (0.22) | 0.59 (0.36) | 0.39 (0.36) | 0.61 (0.36) | * | 21.1 |
Education | 0.42 (0.42) | 0.29 (0.41) | 0.36 (0.36) | 0.39 (0.46) | 0.23 (0.35) | 0.46 (0.41) | 0.26 (0.35) | 0.23 (0.39) | 0.24 (0.35) | 0.31 (0.40) | * | 27.8 |
5.1.2 Annex 2: Normalized Values of AFI Indicators by Economic Farm Size Classes
Variables | (I) 4 ≤ 8 | (II) 8 ≤ 15 | (III) 15 ≤ 25 | (IV) 25 ≤ 50 | (V) 50 ≤ 100 | (VI) 100 ≤ 250 | (VII) ≥250 | Total | Significance | CV, % |
---|---|---|---|---|---|---|---|---|---|---|
In 2016 | ||||||||||
Use of fertilizers | 0.90 (0.17) | 0.87 (0.23) | 0.90 (0.19) | 0.77 (0.28) | 0.66 (0.32) | 0.56 (0.32) | 0.43 (0.30) | 0.84 (0.25) | * | 25.3 |
Use of crop protection | 0.92 (0.16) | 0.90 (0.21) | 0.93 (0.16) | 0.84 (0.23) | 0.73 (0.30) | 0.62 (0.32) | 0.42 (0.34) | 0.87 (0.22) | * | 24.8 |
GHG emissions | 0.98 (0.01) | 0.97 (0.02) | 0.95 (0.03) | 0.91 (0.05) | 0.83 (0.09) | 0.65 (0.18) | 0.21 (0.25) | 0.94 (0.12) | * | 35.5 |
Energy intensity | 0.57 (0.30) | 0.60 (0.29) | 0.63 (0.25) | 0.69 (0.23) | 0.75 (0.18) | 0.78 (0.15) | 0.83 (0.09) | 0.62 (0.28) | * | 14.1 |
Biodiversity | 0.73 (0.32) | 0.65 (0.30) | 0.69 (0.29) | 0.75 (0.22) | 0.74 (0.20) | 0.78 (0.16) | 0.75 (0.16) | 0.71 (0.29) | * | 6.0 |
Meadows and pastures | 0.36 (0.37) | 0.25 (0.32) | 0.32 (0.35) | 0.23 (0.30) | 0.14 (0.25) | 0.10 (0.20) | 0.04 (0.11) | 0.28 (0.34) | * | 57.0 |
Livestock density | 0.82 (0.20) | 0.86 (0.14) | 0.85 (0.15) | 0.86 (0.16) | 0.87 (0.18) | 0.89 (0.18) | 0.89 (0.20) | 0.84 (0.17) | * | 2.8 |
Wooded area | 0.13 (0.32) | 0.10 (0.26) | 0.13 (0.27) | 0.11 (0.25) | 0.09 (0.20) | 0.06 (0.13) | 0.07 (0.13) | 0.11 (0.27) | * | 27.7 |
Accessibility | 0.05 (0.21) | 0.03 (0.16) | 0.02 (0.13) | 0.02 (0.15) | 0.01 (0.12) | 0.01 (0.11) | 0.02 (0.15) | 0.03 (0.18) | * | 60.4 |
Environment-friendly farming | 0.08 (0.25) | 0.10 (0.27) | 0.15 (0.31) | 0.13 (0.31) | 0.10 (0.27) | 0.06 (0.23) | 0.02 (0.13) | 0.10 (0.27) | * | 47.4 |
Water use | 0.56 (0.35) | 0.63 (0.32) | 0.75 (0.25) | 0.79 (0.23) | 0.86 (0.17) | 0.92 (0.10) | 0.94 (0.08) | 0.66 (0.32) | * | 18.4 |
Education | 0.30 (0.36) | 0.32 (0.38) | 0.32 (0.39) | 0.48 (0.43) | 0.43 (0.43) | 0.59 (0.43) | 0.76 (0.42) | 0.35 (0.39) | * | 37.1 |
In 2017 | ||||||||||
Use of fertilizers | 0.87 (0.20) | 0.91 (0.17) | 0.87 (0.25) | 0.81 (0.24) | 0.65 (0.32) | 0.54 (0.33) | 0.44 (0.31) | 0.84 (0.24) | * | 25.4 |
Use of crop protection | 0.89 (0.21) | 0.92 (0.16) | 0.91 (0.20) | 0.85 (0.23) | 0.70 (0.32) | 0.60 (0.33) | 0.43 (0.35) | 0.87 (0.24) | * | 24.8 |
GHG emissions | 0.98 (0.01) | 0.97 (0.02) | 0.95 (0.03) | 0.92 (0.05) | 0.84 (0.07) | 0.67 (0.16) | 0.26 (0.25) | 0.94 (0.11) | * | 32.7 |
Energy intensity | 0.61 (0.29) | 0.63 (0.29) | 0.67 (0.24) | 0.72 (0.21) | 0.75 (0.22) | 0.79 (0.19) | 0.83 (0.12) | 0.65 (0.27) | * | 11.5 |
Biodiversity | 0.73 (0.31) | 0.69 (0.29) | 0.74 (0.25) | 0.73 (0.25) | 0.75 (0.21) | 0.77 (0.16) | 0.74 (0.16) | 0.72 (0.30) | * | 3.3 |
Meadows and pastures | 0.12 (0.19) | 0.15 (0.27) | 0.13 (0.22) | 0.11 (0.19) | 0.10 (0.21) | 0.09 (0.18) | 0.07 (0.15) | 0.13 (0.22) | * | 24.1 |
Livestock density | 0.64 (0.33) | 0.76 (0.25) | 0.71 (0.27) | 0.73 (0.31) | 0.76 (0.30) | 0.79 (0.32) | 0.81 (0.32) | 0.70 (0.30) | * | 7.6 |
Wooded area | 0.10 (0.28) | 0.13 (0.28) | 0.10 (0.25) | 0.11 (0.24) | 0.09 (0.21) | 0.06 (0.14) | 0.09 (0.16) | 0.10 (0.26) | * | 22.0 |
Accessibility | 0.09 (0.28) | 0.03 (0.18) | 0.01 (0.17) | 0.01 (0.10) | 0.01 (0.10) | 0.01 (0.10) | 0.03 (0.16) | 0.05 (0.22) | * | 94.3 |
Environment-friendly farming | 0.09 (0.26) | 0.09 (0.26) | 0.15 (0.31) | 0.15 (0.33) | 0.09 (0.27) | 0.06 (0.23) | 0.02 (0.13) | 0.10 (0.27) | * | 50.0 |
Water use | 0.45 (0.39) | 0.63 (0.31) | 0.72 (0.26) | 0.75 (0.26) | 0.82 (0.20) | 0.90 (0.14) | 0.92 (0.11) | 0.61 (0.36) | * | 22.1 |
Education | 0.25 (0.35) | 0.25 (0.38) | 0.34 (0.40) | 0.43 (0.43) | 0.49 (0.43) | 0.58 (0.44) | 0.71 (0.41) | 0.31 (0.40) | * | 39.4 |
5.1.3 Annex 3: AFIPCA and AFIEW Values Concerning Farming Types and Economic Farm Size Classes
AFIPCA | AFIEW | |||||||
---|---|---|---|---|---|---|---|---|
Mean | SD | Min | Max | Mean | SD | Min | Max | |
In 2016 | ||||||||
Type of farming | ||||||||
COP | 0.50 | 0.07 | 0.26 | 0.85 | 0.51 | 0.07 | 0.28 | 0.84 |
Field crops | 0.53 | 0.11 | 0.28 | 0.78 | 0.54 | 0.11 | 0.29 | 0.78 |
Horticulture | 0.57 | 0.10 | 0.34 | 0.73 | 0.57 | 0.10 | 0.31 | 0.71 |
Permanent crops | 0.55 | 0.07 | 0.36 | 0.71 | 0.53 | 0.07 | 0.33 | 0.74 |
Dairy | 0.53 | 0.07 | 0.28 | 0.74 | 0.53 | 0.07 | 0.33 | 0.77 |
Grazing livestock | 0.52 | 0.06 | 0.38 | 0.73 | 0.53 | 0.07 | 0.39 | 0.77 |
Specialist granivores | 0.49 | 0.08 | 0.30 | 0.62 | 0.51 | 0.07 | 0.35 | 0.64 |
Field crops-grazing livestock combined | 0.54 | 0.07 | 0.30 | 0.77 | 0.55 | 0.07 | 0.34 | 0.80 |
Various mixed farms | 0.53 | 0.06 | 0.35 | 0.67 | 0.53 | 0.07 | 0.37 | 0.65 |
Economic farm size class | ||||||||
4 ≤ 8 | 0.52 | 0.07 | 0.38 | 0.78 | 0.52 | 0.07 | 0.37 | 0.78 |
8 ≤ 15 | 0.52 | 0.07 | 0.34 | 0.77 | 0.52 | 0.08 | 0.31 | 0.80 |
15 ≤ 25 | 0.54 | 0.07 | 0.35 | 0.74 | 0.55 | 0.08 | 0.36 | 0.75 |
25 ≤ 50 | 0.53 | 0.08 | 0.37 | 0.85 | 0.55 | 0.08 | 0.40 | 0.84 |
50 ≤ 100 | 0.50 | 0.07 | 0.34 | 0.72 | 0.52 | 0.07 | 0.33 | 0.73 |
100 ≤ 250 | 0.47 | 0.07 | 0.28 | 0.70 | 0.50 | 0.07 | 0.29 | 0.73 |
≥250 | 0.41 | 0.06 | 0.26 | 0.61 | 0.45 | 0.06 | 0.28 | 0.66 |
Total | 0.52 | 0.07 | 0.26 | 0.85 | 0.53 | 0.08 | 0.28 | 0.84 |
In 2017 | ||||||||
Type of farming | ||||||||
COP | 0.47 | 0.07 | 0.30 | 0.72 | 0.51 | 0.08 | 0.30 | 0.80 |
Field crops | 0.49 | 0.07 | 0.31 | 0.83 | 0.53 | 0.08 | 0.32 | 0.80 |
Horticulture | 0.48 | 0.07 | 0.35 | 0.71 | 0.52 | 0.08 | 0.34 | 0.67 |
Permanent crops | 0.50 | 0.08 | 0.39 | 0.72 | 0.52 | 0.09 | 0.38 | 0.70 |
Dairy | 0.44 | 0.07 | 0.26 | 0.73 | 0.49 | 0.07 | 0.32 | 0.74 |
Grazing livestock | 0.45 | 0.08 | 0.31 | 0.65 | 0.50 | 0.07 | 0.34 | 0.75 |
Specialist granivores | 0.39 | 0.07 | 0.26 | 0.51 | 0.45 | 0.07 | 0.29 | 0.56 |
Field crops-grazing livestock combined | 0.48 | 0.10 | 0.28 | 0.82 | 0.52 | 0.10 | 0.30 | 0.78 |
Various mixed farms | 0.45 | 0.08 | 0.30 | 0.70 | 0.49 | 0.07 | 0.36 | 0.69 |
Economic farm size class | ||||||||
4 ≤ 8 | 0.45 | 0.09 | 0.30 | 0.82 | 0.48 | 0.08 | 0.35 | 0.78 |
8 ≤ 15 | 0.48 | 0.07 | 0.31 | 0.68 | 0.51 | 0.07 | 0.34 | 0.73 |
15 ≤ 25 | 0.48 | 0.07 | 0.33 | 0.70 | 0.53 | 0.08 | 0.39 | 0.73 |
25 ≤ 50 | 0.48 | 0.07 | 0.27 | 0.83 | 0.53 | 0.08 | 0.29 | 0.80 |
50 ≤ 100 | 0.46 | 0.06 | 0.26 | 0.71 | 0.51 | 0.07 | 0.31 | 0.75 |
100 ≤ 250 | 0.44 | 0.06 | 0.30 | 0.71 | 0.49 | 0.07 | 0.32 | 0.73 |
≥250 | 0.39 | 0.06 | 0.26 | 0.62 | 0.45 | 0.07 | 0.30 | 0.70 |
Total | 0.46 | 0.08 | 0.26 | 0.83 | 0.50 | 0.08 | 0.29 | 0.80 |
5.1.4 Annex 4: Normalized Values of AFI Indicators of Farms with a Low AFI Level by Type of Farming in 2017
Variables | COP | Field crops | Horticulture | Permanent crops | Dairy | Grazing livestock | Specialist granivores | Field crops-grazing livestock combined | Various mixed farms | Total | Significance | CV, % |
---|---|---|---|---|---|---|---|---|---|---|---|---|
In 2017 EW | ||||||||||||
Use of fertilizers | 0.37 (0.31) | 0.90 (0.28) | 0.24 (0.42) | 0.19 (0.35) | 0.87 (0.14) | 0.86 (0.14) | 0.72 (0.29) | 0.79 (0.20) | 0.91 (0.20) | 0.72 (0.32) | * | 45.7 |
Use of crop protection | 0.50 (0.38) | 0.89 (0.29) | 0.21 (0.36) | 0.08 (0.28) | 0.85 (0.13) | 0.90 (0.06) | 0.78 (0.16) | 0.90 (0.19) | 0.98 (0.04) | 0.77 (0.16) | * | 49.2 |
GHG emissions | 0.85 (0.23) | 0.95 (0.15) | 0.98 (0.06) | 0.99 (0.00) | 0.94 (0.16) | 0.96 (0.12) | 0.90 (0.24) | 0.92 (0.26) | 0.97 (0.03) | 0.92 (0.20) | * | 4.7 |
Energy intensity | 0.61 (0.38) | 0.29 (0.23) | 0.60 (0.16) | 0.89 (0.27) | 0.69 (0.26) | 0.52 (0.24) | 0.84 (0.19) | 0.28 (0.30) | 0.35 (0.19) | 0.56 (0.32) | * | 40.0 |
Biodiversity | 0.72 (0.17) | 0.37 (0.18) | 0.73 (0.44) | 0.81 (0.37) | 0.44 (0.44) | 0.55 (0.41) | 0.46 (0.45) | 0.66 (0.28) | 0.70 (0.25) | 0.58 (0.37) | * | 25.6 |
Meadows and pastures | 0.00 (0.01) | 0.00 (0.00) | 0.00 (0.00) | 0.01 (0.05) | 0.09 (0.14) | 0.21 (0.15) | 0.00 (0.00) | 0.02 (0.07) | 0.11 (0.15) | 0.07 (0.13) | * | 147.3 |
Livestock density | 0.95 (0.11) | 1.00 (0.01) | 1.00 (0.00) | 1.00 (0.00) | 0.31 (0.30) | 0.39 (0.15) | 0.00 (0.00) | 0.87 (0.10) | 0.23 (0.24) | 0.57 (0.38) | * | 62.6 |
Wooded area | 0.01 (0.04) | 0.00 (0.01) | 0.00 (0.02) | 0.00 (0.00) | 0.00 (0.02) | 0.00 (0.01) | 0.02 (0.01) | 0.01 (0.02) | 0.00 (0.00) | 0.00 (0.02) | * | 113.5 |
Accessibility | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.10) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | – | – |
Environment-friendly farming | 0.03 (0.16) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.01 (0.08) | 0.04 (0.16) | 0.00 (0.00) | 0.10 (0.24) | 0.03 (0.13) | * | 232.1 |
Water use | 0.55 (0.42) | 0.10 (0.28) | 0.06 (0.20) | 0.75 (0.24) | 0.25 (0.26) | 0.31 (0.45) | 0.75 (0.29) | 0.25 (0.26) | 0.06 (0.21) | 0.31 (0.37) | * | 81.1 |
Education | 0.14 (0.26) | 0.07 (0.19) | 0.80 (0.31) | 0.00 (0.00) | 0.12 (0.30) | 0.17 (0.15) | 0.03 (0.00) | 0.01 (0.10) | 0.00 (0.24) | 0.12 (0.38) | * | 169.1 |
In 2017 PCA | ||||||||||||
Use of fertilizers | 0.48 (0.35) | 0.89 (0.29) | 0.00 (0.00) | – | 0.86 (0.13) | 0.84 (0.14) | 0.75 (0.28) | 0.81 (0.17) | 0.84 (0.23) | 0.80 (0.25) | * | 44.6 |
Use of crop protection | 0.54 (0.44) | 0.88 (0.31) | 0.01 (0.03) | – | 0.82 (0.20) | 0.88 (0.11) | 0.80 (0.21) | 0.95 (0.15) | 0.92 (0.15) | 0.81 (0.27) | * | 43.6 |
GHG emissions | 0.70 (0.35) | 0.93 (0.21) | 0.99 (0.01) | – | 0.93 (0.16) | 0.92 (0.12) | 0.85 (0.24) | 0.88 (0.26) | 0.96 (0.03) | 0.91 (0.20) | * | 10.0 |
Energy intensity | 0.44 (0.41) | 0.28 (0.21) | 0.65 (0.10) | – | 0.70 (0.25) | 0.49 (0.24) | 0.83 (0.19) | 0.19 (0.29) | 0.45 (0.21) | 0.55 (0.31) | * | 43.0 |
Biodiversity | 0.73 (0.21) | 0.37 (0.18) | 0.99 (0.03) | – | 0.50 (0.44) | 0.75 (0.26) | 0.45 (0.45) | 0.62 (0.31) | 0.76 (0.19) | 0.62 (0.37) | * | 31.1 |
Meadows and pastures | 0.00 (0.01) | 0.00 (0.00) | 0.00 (0.00) | – | 0.08 (0.14) | 0.23 (0.11) | 0.02 (0.07) | 0.01 (0.05) | 0.09 (0.12) | 0.08 (0.13) | * | 147.4 |
Livestock density | 0.88 (0.14) | 1.00 (0.00) | 1.00 (0.00) | – | 0.29 (0.28) | 0.34 (0.18) | 0.00 (0.00) | 0.86 (0.12) | 0.27 (0.26) | 0.43 (0.35) | * | 68.3 |
Wooded area | 0.02 (0.05) | 0.00 (0.01) | 0.00 (0.00) | – | 0.00 (0.02) | 0.00 (0.01) | 0.02 (0.06) | 0.01 (0.03) | 0.00 (0.00) | 0.00 (0.02) | * | 131.5 |
Accessibility | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | – | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | – | – |
Environment-friendly farming | 0.07 (0.25) | 0.00 (0.00) | 0.00 (0.00) | – | 0.00 (0.00) | 0.01 (0.08) | 0.04 (0.16) | 0.00 (0.00) | 0.10 (0.20) | 0.03 (0.13) | * | 140.3 |
Water use | 0.48 (0.45) | 0.11 (0.30) | 0.02 (0.10) | – | 0.31 (0.27) | 0.18 (0.33) | 0.76 (0.28) | 0.26 (0.24) | 0.12 (0.23) | 0.26 (0.32) | * | 85.6 |
Education | 0.18 (0.36) | 0.05 (0.21) | 0.91 (0.27) | – | 0.18 (0.27) | 0.31 (0.31) | 0.06 (0.17) | 0.05 (0.19) | 0.28 (0.39) | 0.21 (0.33) | * | 113.1 |
5.1.5 Annex 5: Normalized Values of AFI Indicators of Farms with a Low AFI Level by Economic Farm Size Classes in 2017
Variables | (I) 4 ≤ 8 | (II) 8 ≤ 15 | (III) 15 ≤ 25 | (IV) 25 ≤ 50 | (V) 50 ≤ 100 | (VI) 100 ≤ 250 | (VII) ≥250 | Total | Significance | CV, % |
---|---|---|---|---|---|---|---|---|---|---|
In 2017 EW | ||||||||||
Use of fertilizers | 0.75 (0.29) | 0.89 (0.13) | 0.76 (0.31) | 0.80 (0.29) | 0.35 (0.33) | 0.28 (0.30) | 0.28 (0.27) | 0.72 (0.32) | * | 46.3 |
Use of crop protection | 0.79 (0.30) | 0.93 (0.14) | 0.86 (0.14) | 0.89 (0.17) | 0.47 (0.35) | 0.31 (0.32) | 0.29 (0.34) | 0.77 (0.32) | * | 43.5 |
GHG emissions | 0.98 (0.01) | 0.96 (0.01) | 0.95 (0.03) | 0.90 (0.05) | 0.83 (0.06) | 0.63 (0.14) | 0.18 (0.23) | 0.92 (0.16) | * | 37.3 |
Energy intensity | 0.50 (0.34) | 0.60 (0.27) | 0.49 (0.29) | 0.65 (0.23) | 0.75 (0.29) | 0.81 (0.18) | 0.84 (0.12) | 0.56 (0.32) | * | 21.7 |
Biodiversity | 0.63 (0.36) | 0.34 (0.39) | 0.58 (0.33) | 0.41 (0.37) | 0.69 (0.24) | 0.72 (0.17) | 0.72 (0.17) | 0.58 (0.37) | * | 26.3 |
Meadows and pastures | 0.10 (0.15) | 0.01 (0.05) | 0.02 (0.05) | 0.07 (0.12) | 0.03 (0.09) | 0.02 (0.06) | 0.05 (0.11) | 0.07 (0.13) | * | 78.0 |
Livestock density | 0.52 (0.38) | 0.51 (0.31) | 0.65 (0.35) | 0.53 (0.37) | 0.86 (0.28) | 0.86 (0.29) | 0.81 (0.34) | 0.57 (0.38) | * | 24.2 |
Wooded area | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.03 (0.08) | 0.04 (0.07) | 0.00 (0.02) | * | 174.7 |
Accessibility | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | – | – |
Environment-friendly farming | 0.03 (0.12) | 0.00 (0.05) | 0.12 (0.33) | 0.01 (0.09) | 0.00 (0.00) | 0.01 (0.08) | 0.00 (0.00) | 0.03 (0.13) | * | 178.2 |
Water use | 0.15 (0.27) | 0.44 (0.37) | 0.35 (0.27) | 0.41 (0.37) | 0.77 (0.22) | 0.86 (0.16) | 0.92 (0.14) | 0.31 (0.37) | * | 52.2 |
Education | 0.15 (0.25) | 0.00 (0.05) | 0.08 (0.18) | 0.03 (0.13) | 0.02 (0.11) | 0.13 (0.25) | 0.48 (0.45) | 0.12 (0.24) | * | 128.8 |
In 2017 PCA | ||||||||||
Use of fertilizers | 0.83 (0.19) | 0.89 (0.13) | 0.84 (0.29) | 0.93 (0.10) | 0.66 (0.38) | 0.41 (0.37) | 0.34 (0.31) | 0.80 (0.28) | * | 34.3 |
Use of crop protection | 0.84 (0.23) | 0.91 (0.12) | 0.95 (0.06) | 0.96 (0.08) | 0.74 (0.38) | 0.44 (0.41) | 0.35 (0.35) | 0.81 (0.27) | * | 33.4 |
GHG emissions | 0.98 (0.01) | 0.96 (0.01) | 0.95 (0.03) | 0.87 (0.06) | 0.78 (0.07) | 0.55 (0.17) | 0.11 (0.18) | 0.91 (0.20) | * | 32.7 |
Energy intensity | 0.48 (0.31) | 0.69 (0.21) | 0.63 (0.31) | 0.70 (0.21) | 0.70 (0.21) | 0.77 (0.19) | 0.84 (0.12) | 0.55 (0.31) | * | 16.7 |
Biodiversity | 0.66 (0.36) | 0.32 (0.40) | 0.53 (0.41) | 0.46 (0.34) | 0.66 (0.30) | 0.70 (0.24) | 0.75 (0.14) | 0.62 (0.37) | * | 26.0 |
Meadows and pastures | 0.10 (0.14) | 0.01 (0.07) | 0.04 (0.05) | 0.07 (0.10) | 0.07 (0.14) | 0.07 (0.18) | 0.05 (0.11) | 0.08 (0.13) | * | 45.2 |
Livestock density | 0.43 (0.34) | 0.37 (0.26) | 0.20 (0.22) | 0.27 (0.29) | 0.41 (0.39) | 0.68 (0.40) | 0.75 (0.37) | 0.43 (0.35) | * | 46.1 |
Wooded area | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.02) | 0.02 (0.07) | 0.05 (0.07) | 0.00 (0.02) | * | 173.0 |
Accessibility | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | 0.00 (0.00) | * | – |
Environment-friendly farming | 0.03 (0.12) | 0.01 (0.07) | 0.17 (0.38) | 0.00 (0.01) | 0.00 (0.00) | 0.01 (0.08) | 0.00 (0.04) | 0.03 (0.13) | * | 197.2 |
Water use | 0.14 (0.19) | 0.30 (0.26) | 0.48 (0.25) | 0.41 (0.33) | 0.71 (0.28) | 0.85 (0.17) | 0.91 (0.14) | 0.26 (0.32) | * | 53.3 |
Education | 0.22 (0.31) | 0.01 (0.06) | 0.19 (0.39) | 0.07 (0.21) | 0.28 (0.40) | 0.22 (0.34) | 0.62 (0.44) | 0.21 (0.33) | * | 86.3 |
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Dabkienė, V. (2021). Footprint of Agriculture. In: Structural Change, Productivity, and Climate Nexus in Agriculture. Springer, Cham. https://doi.org/10.1007/978-3-030-76802-7_5
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DOI: https://doi.org/10.1007/978-3-030-76802-7_5
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Publisher Name: Springer, Cham
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Online ISBN: 978-3-030-76802-7
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