Countries influence the trade-off between crop yields and nitrogen pollution.
Journal
Nature food
ISSN: 2662-1355
Titre abrégé: Nat Food
Pays: England
ID NLM: 101761102
Informations de publication
Date de publication:
Nov 2020
Nov 2020
Historique:
received:
13
02
2020
accepted:
13
10
2020
medline:
1
11
2020
pubmed:
1
11
2020
entrez:
2
5
2023
Statut:
ppublish
Résumé
National institutions and policies could provide powerful levers to steer the global food system towards higher agricultural production and lower environmental impact. However, causal evidence of countries' influence is scarce. Using global geospatial datasets and a regression discontinuity design, we provide causal quantifications of the way crop yield gaps, nitrogen pollution and nitrogen pollution per crop yield are influenced by country-level factors, such as institutions and policies. We find that countries influence nitrogen pollution much more than crop yields and there is only a small trade-off between reducing nitrogen pollution and increasing yields. Overall, countries that cause 35% less nitrogen pollution than their neighbours only show a 1% larger yield gap (the difference between attainable and attained yields). Explanations of which countries cause the most pollution relative to their crop yields include economic development, population size, institutional quality and foreign financial flows to land resources, as well as countries' overall agricultural intensity and share in the economy. Our findings suggest that many national governments have an impressive capacity to reduce global nitrogen pollution without having to sacrifice much agricultural production.
Identifiants
pubmed: 37128040
doi: 10.1038/s43016-020-00185-6
pii: 10.1038/s43016-020-00185-6
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
713-719Informations de copyright
© 2020. The Author(s), under exclusive licence to Springer Nature Limited.
Références
Rockström, J., Edenhofer, O., Gaertner, J. & DeClerck, F. Planet-proofing the global food system. Nat. Food 1, 3–5 (2020).
doi: 10.1038/s43016-019-0010-4
Foley, J. A. et al. Solutions for a cultivated planet. Nature 478, 337–342 (2011).
pubmed: 21993620
doi: 10.1038/nature10452
West, P. C. et al. Leverage points for improving global food security and the environment. Science 345, 325–328 (2014).
doi: 10.1126/science.1246067
pubmed: 25035492
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).
doi: 10.1093/biosci/bix010
Ray, D. K., Mueller, N. D., West, P. C. & Foley, J. A. Yield trends are insufficient to double global crop production by 2050. PLoS ONE 8, e66428 (2013).
pubmed: 23840465
pmcid: 3686737
doi: 10.1371/journal.pone.0066428
Tilman, D., Balzer, C., Hill, J. & Befort, B. Global food demand and the sustainable intensification of agriculture. Proc. Natl Acad. Sci. USA 108, 20260–20264 (2011).
pubmed: 22106295
pmcid: 3250154
doi: 10.1073/pnas.1116437108
Godfray, H. C. J. et al. Food security: the challenge of feeding 9 billion people. Science 327, 812–818 (2010).
pubmed: 20110467
doi: 10.1126/science.1185383
Mueller, N. D. et al. Closing yield gaps through nutrient and water management. Nature 490, 254–257 (2012).
doi: 10.1038/nature11420
pubmed: 22932270
Folberth, C. et al. The global cropland-sparing potential of high-yield farming. Nat. Sustain. 3, 281–289 (2020).
doi: 10.1038/s41893-020-0505-x
Steffen, W. et al. Planetary boundaries: Guiding human development on a changing planet. Science 347, 1259855 (2015).
pubmed: 25592418
doi: 10.1126/science.1259855
Stevens, C. J. Nitrogen in the environment. Science 363, 578–580 (2019).
pubmed: 30733401
doi: 10.1126/science.aav8215
Seitzinger, S. P. & Phillips, L. Nitrogen stewardship in the Anthropocene. Science 357, 350–351 (2017).
pubmed: 28751593
doi: 10.1126/science.aao0812
Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).
pubmed: 26595273
doi: 10.1038/nature15743
Mekonnen, M. M. & Hoekstra, A. Y. Global gray water footprint and water pollution levels related to anthropogenic nitrogen loads to fresh water. Environ. Sci. Technol. 49, 12860–12868 (2015).
pubmed: 26440220
doi: 10.1021/acs.est.5b03191
Townsend, A. R. et al. Human health effects of a changing global nitrogen cycle. Front. Ecol. Environ. 1, 240–246 (2003).
doi: 10.1890/1540-9295(2003)001[0240:HHEOAC]2.0.CO;2
Kanter, D. R. et al. Nitrogen pollution policy beyond the farm. Nat. Food https://doi.org/10.1038/s43016-019-0001-5 (2019).
Wuepper, D., Borrelli, P. & Finger, R. Countries and the global rate of soil erosion. Nat. Sustain. 3, 51–55 (2020).
doi: 10.1038/s41893-019-0438-4
Yu, C. et al. Managing nitrogen to restore water quality in China. Nature 567, 516–520 (2019).
pubmed: 30818324
doi: 10.1038/s41586-019-1001-1
Searchinger, T. D. et al. Revising Public Agricultural Support to Mitigate Climate Change (World Bank, 2020).
Cui, Z. et al. Pursuing sustainable productivity with millions of smallholder farmers. Nature 555, 363–366 (2018).
pubmed: 29513654
doi: 10.1038/nature25785
Ju, X., Gu, B., Wu, Y. & Galloway, J. N. Reducing China’s fertilizer use by increasing farm size. Glob. Environ. Change 41, 26–32 (2016).
doi: 10.1016/j.gloenvcha.2016.08.005
Wu, Y. et al. Policy distortions, farm size, and the overuse of agricultural chemicals in China. Proc. Natl Acad. Sci. USA 115, 7010–7015 (2018).
pubmed: 29915067
pmcid: 6142251
doi: 10.1073/pnas.1806645115
Alesina, A., Tabellini, G. & Trebbi, F. Is Europe An Optimal Political Area? (National Bureau of Economic Research, 2017).
Alesina, A. & Giuliano, P. Culture and institutions. J. Econ. Lit. 53, 898–944 (2015).
doi: 10.1257/jel.53.4.898
Wuepper, D. Does culture affect soil erosion? Empirical evidence from Europe. Eur. Rev. Agric. Econ. 47, 619–653 (2020).
Pinkovskiy, M. Growth discontinuities at borders. J. Econ. Growth 22, 145–192 (2017).
doi: 10.1007/s10887-016-9139-2
Keele, L. & Titiunik, R. Natural experiments based on geography. Polit. Sci. Res. Methods 4, 65–95 (2016).
doi: 10.1017/psrm.2015.4
Cattaneo, M. & Escanciano, J. Regression Discontinuity Designs: Theory and Applications (Emerald Group, 2017).
Lee, D. S. & Lemieux, T. Regression discontinuity designs in economics. J. Econ. Lit. 48, 281–355 (2010).
doi: 10.1257/jel.48.2.281
Fiebig, D. G. in A Companion to Theoretical Econometrics (ed. Baltagi, B. H.) Ch. 5, 101–121 (Blackwell, 2001).
Smith, M. & Kohn, R. Nonparametric seemingly unrelated regression. J. Economet. 98, 257–281 (2000).
doi: 10.1016/S0304-4076(00)00018-X
Bastin, J.-F. et al. The global tree restoration potential. Science 365, 76–79 (2019).
pubmed: 31273120
doi: 10.1126/science.aax0848
Gu, B. et al. Cleaning up nitrogen pollution may reduce future carbon sinks. Glob. Environ. Change 48, 56–66 (2018).
doi: 10.1016/j.gloenvcha.2017.10.007
Kunčič, A. Institutional quality dataset. J. Inst. Econ. 10, 135–161 (2014).
Eskander, S. M. S. U. & Fankhauser, S. Reduction in greenhouse gas emissions from national climate legislation. Nat. Clim. Change https://doi.org/10.1038/s41558-020-0831-z (2020).
Lesiv, M. et al. Estimating the global distribution of field size using crowdsourcing. Glob. Change Biol. 25, 174–186 (2019).
doi: 10.1111/gcb.14492
Rockström, J. et al. A safe operating space for humanity. Nature 461, 472–475 (2009).
doi: 10.1038/461472a
pubmed: 19779433
Mueller, N. D. et al. Declining spatial efficiency of global cropland nitrogen allocation. Glob. Biogeochem. Cycles 31, 245–257 (2017).
Lassaletta, L. et al. Nitrogen use in the global food system: past trends and future trajectories of agronomic performance, pollution, trade, and dietary demand. Environ. Res. Lett. 11, 095007 (2016).
Pe’Er, G. et al. A greener path for the EU Common Agricultural Policy. Science 365, 449–451 (2019).
pubmed: 31371602
doi: 10.1126/science.aax3146
Finger, R. Nitrogen use and the effects of nitrogen taxation under consideration of production and price risks. Agric. Syst. 107, 13–20 (2012).
doi: 10.1016/j.agsy.2011.12.001
Pretty, J. Intensification for redesigned and sustainable agricultural systems. Science 362, eaav0294 (2018).
Holden, S. T. Fertilizer and sustainable intensification in Sub-Saharan Africa. Glob. Food Secur. 18, 20–26 (2018).
doi: 10.1016/j.gfs.2018.07.001
Finger, R., Swinton, S. M., Benni, N. E. & Walter, A. Precision farming at the nexus of agricultural production and the environment. Ann. Rev. Resour. Econ. 11, 1–23 (2019).
doi: 10.1146/annurev-resource-100518-093929
Walter, A., Finger, R., Huber, R. & Buchmann, N. Opinion: smart farming is key to developing sustainable agriculture. Proc. Natl Acad. Sci. USA 114, 6148–6150 (2017).
pubmed: 28611194
pmcid: 5474773
doi: 10.1073/pnas.1707462114
Wuepper, D. et al. Data: Countries influence the trade-off between crop yields and nitrogen pollution. https://doi.org/10.3929/ethz-b-000430354 (2020).
Keele, L. J. & Titiunik, R. Geographic boundaries as regression discontinuities. Polit. Anal. 23, 127–155 (2014).
doi: 10.1093/pan/mpu014
Cattaneo, M. D. & Vazquez-Bare, G. The choice of neighborhood in regression discontinuity designs. Observ. Stud. 2, A146 (2016).
Gridded Population of the World (GPW) v.4 (SEDAC, 2019); https://sedac.ciesin.columbia.edu/data/collection/gpw-v4
Gilbert, M. et al. Global distribution data for cattle, buffaloes, horses, sheep, goats, pigs, chickens and ducks in 2010. Sci. Data 5, 180227 (2018).
pubmed: 30375994
pmcid: 6207061
doi: 10.1038/sdata.2018.227
Wing, C. & Bello-Gomez, R. A. Regression discontinuity and beyond: options for studying external validity in an internally valid design. Am. J. Eval. 39, 91–108 (2018).
doi: 10.1177/1098214017736155
Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342, 850–853 (2013).
pubmed: 24233722
doi: 10.1126/science.1244693
Borrelli, P. et al. An assessment of the global impact of 21st century land use change on soil erosion. Nat. Commun. 8, 2013 (2017).
pubmed: 29222506
pmcid: 5722879
doi: 10.1038/s41467-017-02142-7
Carlson, K. et al. Greenhouse gas emissions intensity of global croplands. Nat. Clim. Change 7, 63–68 (2016).
doi: 10.1038/nclimate3158
Leach, A. M. et al. A nitrogen footprint model to help consumers understand their role in nitrogen losses to the environment. Environ. Dev. 1, 40–66 (2012).
doi: 10.1016/j.envdev.2011.12.005
Gu, B. et al. The role of industrial nitrogen in the global nitrogen biogeochemical cycle. Sci. Rep. 3, 2579 (2013).
pubmed: 23999540
pmcid: 3759834
doi: 10.1038/srep02579
Fertistat: On-Line Database on Fertilizer Use by Crop (FAO, 2012).
Heffer, P. Assessment of Fertilizer Use by Crop at the Global Level (International Fertilizer Industry Association, 2009).
Fertilizer Use by Crop (International Fertilizer Industry Association, 2002).
Monfreda, C., Ramankutty, N. & Foley, J. A. Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Glob. Biogeochem. Cycles 22, 1–19 (2008).
doi: 10.1029/2007GB002947
Hijmans, R., Cameron, S., Parra, J., Jones, P. & Jarvis, A. Very high resolution interpolated global terrestrial climate surfaces. Int. J. Climatol. 25, 1965–1978 (2005).
doi: 10.1002/joc.1276
Licker, R. et al. Mind the gap: how do climate and agricultural management explain the ‘yield gap’of croplands around the world? Glob. Ecol. Biogeogr. 19, 769–782 (2010).
doi: 10.1111/j.1466-8238.2010.00563.x
Global Livestock Densities (FAO, 2012); http://www.fao.org/livestock-systems/global-distributions/en
Dentener, F. et al. The global atmospheric environment for the next generation. Environ. Sci. Technol. 40, 3586–3594 (2006).
pubmed: 16786698
doi: 10.1021/es0523845
Lesschen, J., Stoorvogel, J., Smaling, E., Heuvelink, G. & Veldkamp, A. A spatially explicit methodology to quantify soil nutrient balances and their uncertainties at the national level. Nutr. Cycl. Agroecosyst. 78, 111–131 (2007).
doi: 10.1007/s10705-006-9078-y
Liu, J. et al. A high-resolution assessment on global nitrogen flows in cropland. Proc. Natl Acad. Sci. USA 107, 8035–8040 (2010).
pubmed: 20385803
pmcid: 2867927
doi: 10.1073/pnas.0913658107
Bouwman, A., Boumans, L. & Batjes, N. Estimation of global NH
Bouwman, A., Boumans, L. & Batjes, N. Modeling global annual N
Batjes, N. H. ISRIC-WISE Derived Soil Properties on a 5 by 5 Arc-Minutes Global Grid (ver. 1.2) (ISRIC-World Soil Information, 2012).
Allen, R. G., Pereira, L. S., Raes, D. & Smith, M. Crop Evapotranspiration—Guidelines for Computing Crop Water Requirements Irrigation and Drainage Paper No. 56 (FAO, 1998).
Mitchell, T. D. & Jones, P. D. An improved method of constructing a database of monthly climate observations and associated high‐resolution grids. Int. J. Climatol. 25, 693–712 (2005).
doi: 10.1002/joc.1181
Potter, P., Ramankutty, N., Bennett, E. M. & Donner, S. D. Characterizing the spatial patterns of global fertilizer application and manure production. Earth Interact. 14, 1–22 (2010).
doi: 10.1175/2009EI288.1
Smil, V. Nitrogen in crop production: an account of global flows. Glob. Biogeochem. Cycles 13, 647–662 (1999).
doi: 10.1029/1999GB900015
Dentener, F. et al. Nitrogen and sulfur deposition on regional and global scales: a multimodel evaluation. Glob. Biogeochem. Cycles 20, 1–21 (2006).
doi: 10.1029/2005GB002672
Agricultural Waste Management Field Handbook (USDA, 1999).
Breiman, L. Random forests. Mach. Learn. 45, 5–32 (2001).
doi: 10.1023/A:1010933404324
Gorelick, N. et al. Google Earth Engine: planetary-scale geospatial analysis for everyone. Remote Sens. Environ. 202, 18–27 (2017).