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The environmental costs and benefits of high-yield farming

An Author Correction to this article was published on 26 March 2019

Abstract

How we manage farming and food systems to meet rising demand is pivotal to the future of biodiversity. Extensive field data suggest that impacts on wild populations would be greatly reduced through boosting yields on existing farmland so as to spare remaining natural habitats. High-yield farming raises other concerns because expressed per unit area it can generate high levels of externalities such as greenhouse gas emissions and nutrient losses. However, such metrics underestimate the overall impacts of lower-yield systems. Here we develop a framework that instead compares externality and land costs per unit production. We apply this framework to diverse data sets that describe the externalities of four major farm sectors and reveal that, rather than involving trade-offs, the externality and land costs of alternative production systems can covary positively: per unit production, land-efficient systems often produce lower externalities. For greenhouse gas emissions, these associations become more strongly positive once forgone sequestration is included. Our conclusions are limited: remarkably few studies report externalities alongside yields; many important externalities and farming systems are inadequately measured; and realizing the environmental benefits of high-yield systems typically requires additional measures to limit farmland expansion. Nevertheless, our results suggest that trade-offs among key cost metrics are not as ubiquitous as sometimes perceived.

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Fig. 1: Framework for exploring how different environmental costs compare across alternative production systems.
Fig. 2: Externality costs of alternative production systems against land cost for five externalities in four agricultural sectors.
Fig. 3: Overall GHG cost against land cost of alternative systems in each sector, including the GHG opportunity costs of land under farming.

Data availability

The data that support the findings of this study are available from the corresponding author upon request.

Code availability

The R codes used for the analyses are available from the corresponding author upon request.

References

  1. 1.

    Poore, J. & Nemecek, T. Reducing food’s environmental impacts through producers and consumers. Science 360, 987–992 (2018).

    CAS  Google Scholar 

  2. 2.

    Green, R. E., Cornell, S. J., Scharlemann, J. P. W. & Balmford, A. Farming and the fate of wild nature. Science 307, 550–555 (2005).

    CAS  Google Scholar 

  3. 3.

    Tilman, D., Balzer, C., Hill, J. & Befort, B. L. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011).

    CAS  Google Scholar 

  4. 4.

    Hunter, M. C., Smith, R. G., Schipanski, M. E., Atwood, L. W. & Mortensen, D. A. Agriculture in 2050: recalibrating targets for sustainable intensification. Bioscience 67, 386–391 (2017).

    Google Scholar 

  5. 5.

    Godfray, H. C. J. et al. Food security: the challenge of feeding 9 billion people. Science 327, 812–818 (2010).

    CAS  Google Scholar 

  6. 6.

    Bajželj, B. et al. Importance of food-demand management for climate mitigation. Nat. Clim. Change 4, 924–929 (2014).

    Google Scholar 

  7. 7.

    Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).

    CAS  Google Scholar 

  8. 8.

    Ripple, W. J. et al. Ruminants, climate change and climate policy. Nat. Clim. Change 4, 2–5 (2014).

    CAS  Google Scholar 

  9. 9.

    Phalan, B., Onial, M., Balmford, A. & Green, R. E. Reconciling food production and biodiversity conservation: land sharing and land sparing compared. Science 333, 1289–1291 (2011).

    CAS  Google Scholar 

  10. 10.

    Balmford, A., Green, R. & Phalan, B. Land for food & land for nature? Daedalus 144, 57–75 (2015).

    Google Scholar 

  11. 11.

    Hulme, M. F. et al. Conserving the birds of Uganda’s banana-coffee arc: land sparing and land sharing compared. PLoS ONE 8, e54597 (2013).

    CAS  Google Scholar 

  12. 12.

    Kamp, J. et al. Agricultural development and the conservation of avian biodiversity on the Eurasian steppes: a comparison of land-sparing and land-sharing approaches. J. Appl. Ecol. 52, 1578–1587 (2015).

    Google Scholar 

  13. 13.

    Dotta, G., Phalan, B., Silva, T. W., Green, R. & Balmford, A. Assessing strategies to reconcile agriculture and bird conservation in the temperate grasslands of South America: grasslands conservation and agriculture. Conserv. Biol. 30, 618–627 (2016).

    CAS  Google Scholar 

  14. 14.

    Williams, D. R. et al. Land‐use strategies to balance livestock production, biodiversity conservation and carbon storage in Yucatán, Mexico. Glob. Change Biol. 23, 5260–5272 (2017).

    Google Scholar 

  15. 15.

    Phalan, B. et al. How can higher-yield farming help to spare nature? Science 351, 450–451 (2016).

    CAS  Google Scholar 

  16. 16.

    Pretty, J. Agricultural sustainability: concepts, principles and evidence. Phil. Trans. R. Soc. B 363, 447–465 (2008).

    Google Scholar 

  17. 17.

    Matson, P. A., Parton, W. J., Power, A. G. & Swift, M. J. Agricultural intensification and ecosystem properties. Science 277, 504–509 (1997).

    CAS  Google Scholar 

  18. 18.

    Tilman, D., Cassman, K. G., Matson, P. A., Naylor, R. & Polasky, S. Agricultural sustainability and intensive production practices. Nature 418, 671–677 (2002).

    CAS  Google Scholar 

  19. 19.

    Didham, R. K. et al. Agricultural intensification exacerbates spillover effects on soil biogeochemistry in adjacent forest remnants. PLoS ONE 10, e0116474 (2015).

    Google Scholar 

  20. 20.

    Seufert, V. & Ramankutty, N. Many shades of gray – the context-dependent performance of organic agriculture. Sci. Adv. 3, e1602638 (2017).

    Google Scholar 

  21. 21.

    Kirchmann, H., Bergström, L., Kätterer, T., Andrén, O. & Andersson, R. in Organic Crop Production – Ambitions and Limitations (eds Kirchmann, H. & Bergström, L.) 39–72 (Springer, Dordrecht, 2008).

  22. 22.

    Madhusudan, M. D. The global village: linkages between international coffee markets and grazing by livestock in a South Indian wildlife reserve. Conserv. Biol. 19, 411–420 (2005).

    Google Scholar 

  23. 23.

    Nijdam, D., Rood, T. & Westhoek, H. The price of protein: review of land use and carbon footprints from life cycle assessments of animal food products and their substitutes. Food Policy 37, 760–770 (2012).

    Google Scholar 

  24. 24.

    Clark, M. & Tilman, D. Comparative analysis of environmental impacts of agricultural production systems, agricultural input efficiency, and food choice. Environ. Res. Lett. 12, 64016 (2017).

    Google Scholar 

  25. 25.

    Yan, X., Yagi, K., Akiyama, H. & Akimoto, H. Statistical analysis of the major variables controlling methane emission from rice fields. Glob. Change Biol. 11, 1131–1141 (2005).

    Google Scholar 

  26. 26.

    Pittelkow, C. M., Adviento-Borbe, M. A., van Kessel, C., Hill, J. E. & Linquist, B. A. Optimizing rice yields while minimizing yield-scaled global warming potential. Glob. Change Biol. 20, 1382–1393 (2014).

    Google Scholar 

  27. 27.

    Carrijo, D. R., Lundy, M. E. & Linquist, B. A. Rice yields and water use under alternate wetting and drying irrigation: a meta-analysis. Field Crop Res. 203, 173–180 (2017).

    Google Scholar 

  28. 28.

    Herrero, M. et al. Biomass use, production, feed efficiencies, and greenhouse gas emissions from global livestock systems. Proc. Natl Acad. Sci. USA 110, 20888–20893 (2013).

    CAS  Google Scholar 

  29. 29.

    Beauchemin, K., McAllister, T. A. & McGinn, S. M. Dietary mitigation of enteric methane from cattle. CAB Rev. Perspect. Agric. Vet. Sci. Nutr. Nat. Resour. 4, 1–18 (2009).

    Google Scholar 

  30. 30.

    Wilkinson, J. M. & Garnsworthy, P. C. Dietary options to reduce the environmental impact of milk production. J. Agric. Sci. 155, 334–347 (2017).

    CAS  Google Scholar 

  31. 31.

    IPCC 2006 IPCC Guidelines for National Greenhouse Gas Inventories (eds Eggleston, H. S. et al.) (IGES, 2006).

  32. 32.

    Gilroy, J. J. et al. Optimizing carbon storage and biodiversity protection in tropical agricultural landscapes. Glob. Change Biol. 20, 2162–2172 (2014).

    Google Scholar 

  33. 33.

    Lamb, A. et al. The potential for land sparing to offset greenhouse gas emissions from agriculture. Nat. Clim. Change 6, 488–492 (2016).

    Google Scholar 

  34. 34.

    Cui, Z. et al. Pursuing sustainable productivity with millions of smallholder farmers. Nature 555, 363–366 (2018).

    CAS  Google Scholar 

  35. 35.

    Notarnicola, B. et al. The role of life cycle assessment in supporting sustainable agri-food systems: a review of the challenges. J. Clean. Prod. 140, 399–409 (2017).

    Google Scholar 

  36. 36.

    Bravo, V. et al. Monitoring pesticide use and associated health hazards in Central America. J. Int. J. Occup. Environ. Heal. 173, 1077–3525 (2011).

    Google Scholar 

  37. 37.

    Lambin, E. F. & Meyfroidt, P. Global land use change, economic globalization, and the looming land scarcity. Proc. Natl Acad. Sci. USA 108, 3465–3472 (2011).

    CAS  Google Scholar 

  38. 38.

    Ewers, R. M., Scharlemann, J. P. W., Balmford, A. & Green, R. E. Do increases in agricultural yield spare land for nature? Glob. Change Biol. 15, 1716–1726 (2009).

    Google Scholar 

  39. 39.

    Byerlee, D., Stevenson, J. & Villoria, N. Does intensification slow crop land expansion or encourage deforestation? Glob. Food Sec. 3, 92–98 (2014).

    Google Scholar 

  40. 40.

    Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).

    CAS  Google Scholar 

  41. 41.

    Yang, Q. et al. Added sugar intake and cardiovascular diseases mortality among US adults. JAMA Intern. Med. 174, 516 (2014).

    CAS  Google Scholar 

  42. 42.

    FAOSTAT: Food and Agriculture Data (Food and Agriculture Organization of the United Nations, 2017); http://fao.org/faostat

  43. 43.

    Bates, D., Mächler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–48 (2015).

    Google Scholar 

  44. 44.

    R: a Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2016); https://www.r-project.org

  45. 45.

    Guinée, J. B., Heijungs, R. & Huppes, G. Economic allocation: examples and derived decision tree. Int. J. Life Cycle Assess. 9, 23–33 (2004).

    Google Scholar 

  46. 46.

    Shang, Q. et al. Net annual global warming potential and greenhouse gas intensity in Chinese double rice-cropping systems: a 3-year field measurement in long-term fertilizer experiments. Glob. Change Biol. 17, 2196–2210 (2011).

    Google Scholar 

  47. 47.

    Liu, Y. et al. Net global warming potential and greenhouse gas intensity from the double rice system with integrated soil–crop system management: a three-year field study. Atmos. Environ. 116, 92–101 (2015).

    CAS  Google Scholar 

  48. 48.

    Chen, Z., Chen, F., Zhang, H. & Liu, S. Effects of nitrogen application rates on net annual global warming potential and greenhouse gas intensity in double-rice cropping systems of the Southern China. Environ. Sci. Pollut. Res. Int. 23, 24781–24795 (2016).

    CAS  Google Scholar 

  49. 49.

    Xue, J. F. et al. Assessment of carbon sustainability under different tillage systems in a double rice cropping system in Southern China. Int. J. Life Cycle Assess. 19, 1581–1592 (2014).

    CAS  Google Scholar 

  50. 50.

    Shen, J. et al. Contrasting effects of straw and straw-derived biochar amendments on greenhouse gas emissions within double rice cropping systems. Agric. Ecosyst. Environ. 188, 264–274 (2014).

    CAS  Google Scholar 

  51. 51.

    Ma, Y. C. et al. Net global warming potential and greenhouse gas intensity of annual rice–wheat rotations with integrated soil–crop system management. Agric. Ecosyst. Environ. 164, 209–219 (2013).

    Google Scholar 

  52. 52.

    Zhang, X., Xu, X., Liu, Y., Wang, J. & Xiong, Z. Global warming potential and greenhouse gas intensity in rice agriculture driven by high yields and nitrogen use efficiency. Biogeosciences 13, 2701–2714 (2016).

    CAS  Google Scholar 

  53. 53.

    Yang, B. et al. Mitigating net global warming potential and greenhouse gas intensities by substituting chemical nitrogen fertilizers with organic fertilization strategies in rice–wheat annual rotation systems in China: a 3-year field experiment. Ecol. Eng. 81, 289–297 (2015).

    Google Scholar 

  54. 54.

    Zhang, Z. S., Guo, L. J., Liu, T. Q., Li, C. F. & Cao, C. G. Effects of tillage practices and straw returning methods on greenhouse gas emissions and net ecosystem economic budget in rice–wheat cropping systems in central China. Atmos. Environ. 122, 636–644 (2015).

    CAS  Google Scholar 

  55. 55.

    Xiong, Z. et al. Differences in net global warming potential and greenhouse gas intensity between major rice-based cropping systems in China. Sci. Rep. 5, 17774 (2015).

    CAS  Google Scholar 

  56. 56.

    Xu, Y. et al. Improved water management to reduce greenhouse gas emissions in no-till rapeseed–rice rotations in Central China. Agric. Ecosyst. Environ. 221, 87–98 (2016).

    CAS  Google Scholar 

  57. 57.

    Xu, Y. et al. Effects of water-saving irrigation practices and drought resistant rice variety on greenhouse gas emissions from a no-till paddy in the central lowlands of China. Sci. Total Environ. 505, 1043–1052 (2015).

    CAS  Google Scholar 

  58. 58.

    Yao, Z. et al. Nitrous oxide and methane fluxes from a rice–wheat crop rotation under wheat residue incorporation and no-tillage practices. Atmos. Environ. 79, 641–649 (2013).

    CAS  Google Scholar 

  59. 59.

    Xia, L., Wang, S. & Yan, X. Effects of long-term straw incorporation on the net global warming potential and the net economic benefit in a rice–wheat cropping system in China. Agric. Ecosyst. Environ. 197, 118–127 (2014).

    Google Scholar 

  60. 60.

    Zhang, A. et al. Change in net global warming potential of a rice–wheat cropping system with biochar soil amendment in a rice paddy from China. Agric. Ecosyst. Environ. 173, 37–45 (2013).

    Google Scholar 

  61. 61.

    Zou, J., Huang, Y., Zong, L., Zheng, X. & Wang, Y. Carbon dioxide, methane, and nitrous oxide emissions from a rice–wheat rotation as affected by crop residue. Adv. Atmos. Sci. 21, 691–698 (2004).

    Google Scholar 

  62. 62.

    Zhou, M. et al. Nitrous oxide and methane emissions from a subtropical rice–rapeseed rotation system in China: a 3-year field case study. Agric. Ecosyst. Environ 212, 297–309 (2015).

    CAS  Google Scholar 

  63. 63.

    Yao, Z. et al. Improving rice production sustainability by reducing water demand and greenhouse gas emissions with biodegradable films. Sci. Rep. 7, 39855 (2017).

    CAS  Google Scholar 

  64. 64.

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. WorldClim – Global Climate Data: WorldClim Version 2 (2017); http://www.worldclim.org/version2

  65. 65.

    Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. WorldClim – Global Climate Data: Bioclimatic Variables (2017); http://www.worldclim.org/bioclim

  66. 66.

    Heuzé, V., Tran, G. & Hassoun, P. Feedipedia: Rough Rice (Paddy Rice) (Feedipedia, a programme by INRA, CIRAD, AFZ and FAO, 2015); https://www.feedipedia.org/node/226

  67. 67.

    Liang, K. et al. Grain yield, water productivity and CH4 emission of irrigated rice in response to water management in south China. Agric. Water Manag. 163, 319–331 (2016).

    Google Scholar 

  68. 68.

    Kreye, C. et al. Fluxes of methane and nitrous oxide in water-saving rice production in north China. Nutr. Cycl. Agroecosyst. 77, 293–304 (2007).

    CAS  Google Scholar 

  69. 69.

    Lu, W., Cheng, W., Zhang, Z., Xin, X. & Wang, X. Differences in rice water consumption and yield under four irrigation schedules in central Jilin Province, China. Paddy Water Environ. 14, 473–480 (2016).

    Google Scholar 

  70. 70.

    Jin, X. et al. Water consumption and water-saving characteristics of a ground cover rice production system. J. Hydrol. 540, 220–231 (2016).

    Google Scholar 

  71. 71.

    Sun, H. et al. CH4 emission in response to water-saving and drought-resistance rice (WDR) and common rice varieties under different irrigation managements. Water Air Soil Pollut. 227, 47 (2016).

    Google Scholar 

  72. 72.

    Wang, X. et al. The positive impacts of irrigation schedules on rice yield and water consumption: synergies in Jilin Province, Northeast China. Int. J. Agric. Sustain. 14, 1–12 (2016).

    CAS  Google Scholar 

  73. 73.

    Xiong, Y., Peng, S., Luo, Y., Xu, J. & Yang, S. A paddy eco-ditch and wetland system to reduce non-point source pollution from rice-based production system while maintaining water use efficiency. Environ. Sci. Pollut. Res. 22, 4406–4417 (2015).

    CAS  Google Scholar 

  74. 74.

    Shao, G.-C. et al. Effects of controlled irrigation and drainage on growth, grain yield and water use in paddy rice. Eur. J. Agron. 53, 1–9 (2014).

    Google Scholar 

  75. 75.

    Liu, L. et al. Combination of site-specific nitrogen management and alternate wetting and drying irrigation increases grain yield and nitrogen and water use efficiency in super rice. Field Crop Res. 154, 226–235 (2013).

    Google Scholar 

  76. 76.

    Chen, Y., Zhang, G., Xu, Y. J. & Huang, Z. Influence of irrigation water discharge frequency on soil salt removal and rice yield in a semi-arid and saline-sodic area. Water 5, 578–592 (2013).

    Google Scholar 

  77. 77.

    Ye, Y. et al. Alternate wetting and drying irrigation and controlled-release nitrogen fertilizer in late-season rice. Effects on dry matter accumulation, yield, water and nitrogen use. Field Crop Res. 144, 212–224 (2013).

    Google Scholar 

  78. 78.

    Peng, S. et al. Integrated irrigation and drainage practices to enhance water productivity and reduce pollution in a rice production system. Irrig. Drain. 61, 285–293 (2012).

    Google Scholar 

  79. 79.

    Bell, M. J. et al. Nitrous oxide emissions from fertilised UK arable soils: fluxes, emission factors and mitigation. Agric Ecosyst Environ 212, 134–147 (2015).

    CAS  Google Scholar 

  80. 80.

    Bell, M. J. et al. Agricultural Greenhouse Gas Inventory Research Platform - InveN2Ory: Fertiliser Experimental Site in East Lothian, 2011 Version: 1 [data set] (Freshwater Biological Association, 2017); https://doi.org/10.17865/ghgno606

  81. 81.

    Cardenas, L. M., Webster, C. & Donovan, N. Agricultural Greenhouse Gas Inventory Research Platform - InveN2Ory: Fertiliser Experimental Site in Bedfordshire, 2011 Version: 1 [data set] (Freshwater Biological Association, 2017); https://doi.org/10.17865/ghgno613

  82. 82.

    Williams, J. R. et al. Agricultural Greenhouse Gas Inventory Research Inventory Research Platform - InveN2Ory: Fertiliser Experimental Site in Herefordshire, 2011 Version: 1 [data set] (Freshwater Biological Association, 2017); https://doi.org/10.17865/ghgno675

  83. 83.

    Goulding, K. W. T., Poulton, P. R., Webster, C. P. & Howe, M. T. Nitrate leaching from the Broadbalk Wheat Experiment, Rothamsted, UK, as influenced by fertilizer and manure inputs and the weather. Soil Use Manag. 16, 244–250 (2000).

    Google Scholar 

  84. 84.

    Cardoso, A. S. et al. Impact of the intensification of beef production in Brazil on greenhouse gas emissions and land use. Agric. Syst. 143, 86–96 (2016).

    Google Scholar 

  85. 85.

    de Figueiredo, E. B. et al. Greenhouse gas balance and carbon footprint of beef cattle in three contrasting pasture-management systems in Brazil. J. Clean. Prod. 142, 420–431 (2017).

    Google Scholar 

  86. 86.

    Dick, M., Abreu Da Silva, M. & Dewes, H. Life cycle assessment of beef cattle production in two typical grassland systems of southern Brazil. J. Clean. Prod. 96, 426–434 (2015).

    Google Scholar 

  87. 87.

    Florindo, T. J., de Medeiros Florindo, G. I. B., Talamini, E., da Costa, J. S. & Ruviaro, C. F. Carbon footprint and life cycle costing of beef cattle in the Brazilian midwest. J. Clean. Prod. 147, 119–129 (2017).

    Google Scholar 

  88. 88.

    Mazzetto, A. M., Feigl, B. J., Schils, R. L. M., Cerri, C. E. P. & Cerri, C. C. Improved pasture and herd management to reduce greenhouse gas emissions from a Brazilian beef production system. Livest. Sci. 175, 101–112 (2015).

    Google Scholar 

  89. 89.

    Pashaei Kamali, F. et al. Environmental and economic performance of beef farming systems with different feeding strategies in southern Brazil. Agric. Syst. 146, 70–79 (2016).

    Google Scholar 

  90. 90.

    Ruviaro, C. F., De Léis, C. M., Lampert, V. D. N., Barcellos, J. O. J. & Dewes, H. Carbon footprint in different beef production systems on a southern Brazilian farm: a case study. J. Clean. Prod. 96, 435–443 (2015).

    CAS  Google Scholar 

  91. 91.

    Ruviaro, C. F. et al. Economic and environmental feasibility of beef production in different feed management systems in the Pampa biome, southern Brazil. Ecol. Indic. 60, 930–939 (2016).

    Google Scholar 

  92. 92.

    Dick, M., Da Silva, M. A. & Dewes, H. Mitigation of environmental impacts of beef cattle production in southern Brazil - evaluation using farm-based life cycle assessment. J. Clean. Prod. 87, 58–67 (2015).

    Google Scholar 

  93. 93.

    Lesnoff, M. DynMod: a Tool for Demographic Projections of Tropical Livestock Populations Under Microsoft Excel, User’s Manual - Version 1 (CIRAD, Montpelier, Cedex; ILRI, Nairobi, Kenya, 2008).

    Google Scholar 

  94. 94.

    Broom, D. M., Galindo, F. A. & Murgueitio, E. Sustainable, efficient livestock production with high biodiversity and good welfare for animals. Proc. R. Soc. B 280, 20132025 (2013).

    CAS  Google Scholar 

  95. 95.

    Junior, C. C. et al. Brazilian beef cattle feedlot manure management: a country survey. J. Anim. Sci. 91, 1811–1818 (2013).

    Google Scholar 

  96. 96.

    Garnsworthy, P. C. The environmental impact of fertility in dairy cows: a modelling approach to predict methane and ammonia emissions. Anim. Feed Sci. Technol. 112, 211–223 (2004).

    CAS  Google Scholar 

  97. 97.

    Collins, A. L. & Zhang, Y. Exceedance of modern ‘background’ fine-grained sediment delivery to rivers due to current agricultural land use and uptake of water pollution mitigation options across England and Wales. Environ. Sci. Policy 61, 61–73 (2016).

    Google Scholar 

  98. 98.

    Chadwick, D. et al. Manure management: implications for greenhouse gas emissions. Anim. Feed Sci. Technol. 166–167, 514–531 (2011).

    Google Scholar 

  99. 99.

    Organic Dairy Cows: Milk Yield and Lactation Characteristics in Thirteen Established Herds and Development of a Herd Simulation Model for Organic Milk Production Project Report OF0170 (DEFRA, 2000); https://randd.defra.gov.uk/Default.aspx?Menu=Menu&Module=More&Location=None&Completed=0&ProjectID=8431

  100. 100.

    Wilkinson, J. M. Re-defining efficiency of feed use by livestock. Animal 5, 1014–1022 (2011).

    CAS  Google Scholar 

  101. 101.

    Webb, J., Audsley, E., Williams, A., Pearn, K. & Chatterton, J. Can UK livestock production be configured to maintain production while meeting targets to reduce emissions of greenhouse gases and ammonia? J. Clean. Prod. 83, 204–211 (2014).

    CAS  Google Scholar 

  102. 102.

    de Ponti, T., Rijk, B. & van Ittersum, M. K. The crop yield gap between organic and conventional agriculture. Agric. Syst. 108, 1–9 (2012).

    Google Scholar 

  103. 103.

    Gerber, P, Vellinga, T, Opio, C, Henderson, B. & Steinfeld, H. Greenhouse Gas Emissions from the Dairy Sector: A Life Cycle Assessment (Food and Agriculture Organization of the United Nations: 2010); http://www.fao.org/docrep/012/k7930e/k7930e00.pdf

  104. 104.

    Brown, K. et al. UK Greenhouse Gas Inventory, 1990 to 2010: Annual Report for Submission under the Framework Convention on Climate Change (DEFRA, 2012); https://uk-air.defra.gov.uk/assets/documents/reports/cat07/1204251149_ukghgi-90-10_main_chapters_issue2_print_v1.pdf

  105. 105.

    Misselbrook, T. H., Sutton, M. A. & Scholefield, D. A simple process-based model for estimating ammonia emissions from agricultural land after fertilizer applications. Soil Use Manag. 20, 365–372 (2006).

    Google Scholar 

  106. 106.

    Misselbrook, T. H., Gilhespy, S. L., Cardenas, L. M., Williams, J. & Dragosits, U. Inventory of Ammonia Emissions from UK Agriculture2015: DEFRA Contract Report (SCF0102) (DEFRA, 2016); https://uk-air.defra.gov.uk/library/reports?report_id=928

  107. 107.

    Vellinga, T. V et al. Methodology Used in FeedPrint: a Tool Quantifying Greenhouse Gas Emissions of Feed Production and Utilization Report 674 (Wageningen UR Livestock Research, 2013).

  108. 108.

    Anthony, S., Quinn, P. & Lord, E. Catchment scale modelling of nitrate leaching. Asp. Appl. Biol. 46, 23–32 (1996).

    Google Scholar 

  109. 109.

    Wang, L. et al. The changing trend in nitrate concentrations in major aquifers due to historical nitrate loading from agricultural land across England and Wales from 1925 to 2150. Sci. Total Environ. 542, 694–705 (2016).

    CAS  Google Scholar 

  110. 110.

    Davison, P. S., Lord, E. I., Betson, M. J. & Strömqvist, J. PSYCHIC – A process-based model of phosphorus and sediment mobilisation and delivery within agricultural catchments. Part 1: Model description and parameterisation. J. Hydrol. 350, 290–302 (2008).

    CAS  Google Scholar 

  111. 111.

    Koponen, K. & Soimakallio, S. Foregone carbon sequestration due to land occupation - the case of agro-bioenergy in Finland. Int. J. Life Cycle Assess. 20, 1544–1556 (2015).

    CAS  Google Scholar 

  112. 112.

    Guo, L. B. & Gifford, R. M. Soil carbon stocks and land use change: a meta analysis. Glob. Change Biol. 8, 345–360 (2002).

    Google Scholar 

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Acknowledgements

We are grateful for funding from the Cambridge Conservation Initiative Collaborative Fund and Arcadia, the Grantham Foundation for the Protection of the Environment, the Kenneth Miller Trust, the UK-China Virtual Joint Centre for Agricultural Nitrogen (CINAg, BB/N013468/1, financed by the Newton Fund via BBSRC and NERC), BBSRC (BBS/E/C/000I0330), DEVIL (NE/M021327/1), U-GRASS (NE/M016900/1), Soils-R-GRREAT (NE/P019455/1), N-Circle (BB/N013484/1), BBSRC Soil to Nutrition (S2N) strategic programme (BBS/E/C/000I0330), UNAM-PAPIIT (IV200715), the Belmont Forum/FACEE-JPI (NE/M021327/1 ‘DEVIL’) and the Cambridge Earth System Science NERC DTP (NE/L002507/1); A.B. is supported by a Royal Society Wolfson Research Merit award. We thank F. Brendrup, E. Caton, A. Dobermann, T. J. Florindo, E. Fonte, O. Leyser, A. Mazzetto, J. Murthwaite, F. P. Kamali, R. Olea-Perez, S. Ramsden, C. Ruviaro, J. Storkey, B. Strassburg, M. Topliff, J. N. V. da Silva, D. Williams, X. Yan and Y. Zhang for advice, data or analysis, and K. Willott for much practical support.

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A.B., T.A., H.B., D.C., D.E., R.F., P.G., R.G., P.S., H.W., A.W. and R.E. designed the study and performed the research; D.M.B., A.C., J.C., T.F., E.G., A.G.-H., J.H.-M., M.H., F.H., A.L., T.M., B.P., B.I.S., T.T., J.V. and E.z.E. contributed and analysed data and results; and all authors contributed substantially to the analysis and interpretation of results and writing of the manuscript.

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Correspondence to Andrew Balmford.

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Balmford, A., Amano, T., Bartlett, H. et al. The environmental costs and benefits of high-yield farming. Nat Sustain 1, 477–485 (2018). https://doi.org/10.1038/s41893-018-0138-5

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