Abstract
Land-use changes are critical for climate policy because native vegetation and soils store abundant carbon and their losses from agricultural expansion, together with emissions from agricultural production, contribute about 20 to 25 per cent of greenhouse gas emissions1,2. Most climate strategies require maintaining or increasing land-based carbon3 while meeting food demands, which are expected to grow by more than 50 per cent by 20501,2,3,,2,4. A finite global land area implies that fulfilling these strategies requires increasing global land-use efficiency of both storing carbon and producing food. Yet measuring the efficiency of land-use changes from the perspective of greenhouse gas emissions is challenging, particularly when land outputs change, for example, from one food to another or from food to carbon storage in forests. Intuitively, if a hectare of land produces maize well and forest poorly, maize should be the more efficient use of land, and vice versa. However, quantifying this difference and the yields at which the balance changes requires a common metric that factors in different outputs, emissions from different agricultural inputs (such as fertilizer) and the different productive potentials of land due to physical factors such as rainfall or soils. Here we propose a carbon benefits index that measures how changes in the output types, output quantities and production processes of a hectare of land contribute to the global capacity to store carbon and to reduce total greenhouse gas emissions. This index does not evaluate biodiversity or other ecosystem values, which must be analysed separately. We apply the index to a range of land-use and consumption choices relevant to climate policy, such as reforesting pastures, biofuel production and diet changes. We find that these choices can have much greater implications for the climate than previously understood because standard methods for evaluating the effects of land use4,5,6,7,8,9,10,11 on greenhouse gas emissions systematically underestimate the opportunity of land to store carbon if it is not used for agriculture.
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Data availability
LPJmL modelling results, in the form of global carbon and native net primary productivity maps, are available at https://doi.org/10.1594/PANGAEA.893761. The different datasets used to run LPJmL for this study are publicly available and described in Supplementary Information along with links. Any other materials generated for this study are available from the corresponding author on reasonable request.
Change history
References
Searchinger, T. et al. Creating a Sustainable Food Future. A Menu of Solutions to Sustainably Feed More Than 9 Billion People by 2050 (World Resources Institute, Washington, 2014).
Edenhofer, O. et al. in Climate Change 2014: Mitigation of Climate Change. Contribution of Working Group III to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Edenhofer, O. et al.) 1–30 (Cambridge Univ. Press, Cambridge, 2014).
Valin, H. et al. The future of food demand: understanding differences in global economic models. Agric. Econ. 45, 51–67 (2014).
Tilman, D. & Clark, M. Global diets link environmental sustainability and human health. Nature 515, 518–522 (2014).
Eshel, G., Shepon, A., Makov, T. & Milo, R. Land, irrigation water, greenhouse gas, and reactive nitrogen burdens of meat, eggs, and dairy production in the United States. Proc. Natl Acad. Sci. USA 111, 11996–12001 (2014).
Food and Agriculture Organization of the United Nations. EX-Ante Carbon-balance Tool (EX-ACT) http://www.fao.org/tc/exact/ex-act-home/en/ (2017).
Colomb, V. et al. Selection of appropriate calculators for landscape-scale greenhouse gas assessment for agriculture and forestry. Environ. Res. Lett. 8, 015029 (2013).
Gerber, P. et al. Tackling Climate Change Through Livestock: A Global Assessment of Emissions and Mitigation Opportunities (Food and Agriculture Organization of the United Nations, Rome, 2013).
Escobar, N., Ribal, J., Clemente, G. & Sanjuán, N. Consequential LCA of two alternative systems for biodiesel consumption in Spain, considering uncertainty. J. Clean. Prod. 79, 61–73 (2014).
Audsley, E. et al. How Low Can We Go? An Assessment of Greenhouse Gas Emissions from the UK Food System and the Scope Reduction by 2050 (WWF-UK, 2009).
Hertel, T. W. et al. Effects of US maize ethanol on global land use and greenhouse gas emissions: estimating market-mediated responses. Bioscience 60, 223–231 (2010).
Ranganathan, J. et al. Shifting Diets for a Sustainable Food Future (World Resources Institute, Washington, 2016).
Johnson, J. A., Runge, C. F., Senauer, B., Foley, J. & Polasky, S. Global agriculture and carbon trade-offs. Proc. Natl Acad. Sci. USA 111, 12342–12347 (2014).
Estes, L. D. et al. Reconciling agriculture, carbon and biodiversity in a savannah transformation frontier. Phil. Trans. R. Soc. Lond. B 371, 20150316 (2016).
Searchinger, T. D., Edwards, R., Mulligan, D., Heimlich, R. & Plevin, R. Do biofuel policies seek to cut emissions by cutting food? Science 347, 1420–1422 (2015).
Strassburg, B. B. N. et al. When enough should be enough: improving the use of current agricultural lands could meet production demands and spare natural habitats in Brazil. Glob. Environ. Change 28, 84–97 (2014).
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).
Luyssaert, S. et al. CO2 balance of boreal, temperate, and tropical forests derived from a global database. Glob. Change Biol. 13, 2509–2537 (2007).
Xu, B., Yang, Y., Li, P., Shen, H. & Fang, J. Global patterns of ecosystem carbon flux in forests: a biometric data-based synthesis. Glob. Biogeochem. Cycles 28, 962–973 (2014).
Hudiburg, T. W., Davis, S. C., Parton, W. & Delucia, E. H. Bioenergy crop greenhouse gas mitigation potential under a range of management practices. Glob. Change Biol. Bioenergy 7, 366–374 (2015).
Harris, Z. M., Spake, R. & Taylor, G. Land use change to bioenergy: a meta-analysis of soil carbon and GHG emissions. Biomass Bioenergy 82, 27–39 (2015).
Bryngelsson, D., Wirsenius, S., Hedenus, F. & Sonesson, U. How can the EU climate targets be met? A combined analysis of technological and demand-side changes in food and agriculture. Food Policy 59, 152–164 (2016).
Moll, S. & Remond-Tiedrez, I. CO 2 Emissions Induced by EU’s Final Use of Products are Estimated to Be 9 Tonnes per Capita (Eurostat, Luxembourg, 2011).
Neumann, C. G., Demment, M. W., Maretzki, A., Drorbaugh, N. & Galvin, K. A. in Livestock in a Changing Landscape, Volume 1: Drivers, Consequences, and Responses (eds Steinfeld, H. et al.) 221–248 (Island Press, Washington, 2010).
Regmi, A., Deepak, M. S., Seale, J. L. Jr & Bernstein, J. in Changing Structure of Global Food Consumption and Trade (ed. Regmi, A.) 14–22 (United States Department of Agriculture Economic Research Service, Washington, 2001).
Prestele, R. et al. Hotspots of uncertainty in land use and land cover change projections: a global scale model comparison. Glob. Change Biol. 22, 3967–3983 (2016).
Plevin, R., O’Hare, M., Jones, A., Torn, M. & Gibbs, H. Greenhouse gas emissions from biofuels’ indirect land use change are uncertain but may be much greater than previously estimated. Environ. Sci. Technol. 44, 8015–8021 (2010).
California Air Resources Board. Low Carbon Fuel Standard. Final Regulation Order Table 5, https://www.arb.ca.gov/regact/2015/lcfs2015/lcfsfinalregorder.pdf (2015).
Corley, R. H. V. How much palm oil do we need? Environ. Sci. Policy 12, 134–139 (2009).
Sitch, S. et al. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob. Change Biol. 9, 161–185 (2003).
Bondeau, A. et al. Modelling the role of agriculture for the 20th century global terrestrial carbon balance. Glob. Change Biol. 13, 679–706 (2007).
Eggleston, H. S., Buendia, L., Miwa, K., Ngara, T. & Tanabe, K. (eds) 2006 IPCC Guidelines for National Greenhouse Gas Inventories (IGES, Hayama, 2006).
Jobbágy, E. G. & Jackson, R. B. The vertical distribution of soil organic carbon and its relation to climate and vegetation. Ecol. Appl. 10, 423–436 (2000).
Malhi, Y., Baldocchi, D. D. & Jarvis, P. G. The carbon balance of tropical, temperate and boreal forests. Plant Cell Environ. 22, 715–740 (1999).
Roy, J., Saugier, B. & Mooney, H. A. (eds) Terrestrial Global Productivity (Academic Press, San Diego, 2001).
Trumper, K. et al. The Natural Fix? The role of Ecosystems in Climate Mitigation (UNEP-WCMC, Cambridge, 2009).
West, P. C. et al. Trading carbon for food: global comparison of carbon stocks vs. crop yields on agricultural land. Proc. Natl Acad. Sci. USA 107, 19645–19648 (2010).
You, L. et al. Spatial Production Allocation Model (SPAM) 2005 v3.2 http://MapSPAM.info (2017).
Gibbs, H. K. et al. Carbon payback times for crop-based biofuel expansion in the tropics: the effects of changing yield and technology. Environ. Res. Lett. 3, 034001 (2008).
Searchinger, T. D. et al. Use of U.S. croplands for biofuels increases greenhouse gases through emissions from land-use change. Science 319, 1238–1240 (2008).
Guo, L. B. & Gifford, R. M. Soil carbon stocks and land use change: a meta analysis. Glob. Change Biol. 8, 345–360 (2002).
Don, A., Schumacher, J. & Freibauer, A. Impact of tropical land-use change on soil organic carbon stocks – a meta-analysis. Glob. Change Biol. 17, 1658–1670 (2011).
Wei, X., Shao, M., Gale, W. & Li, L. Global pattern of soil carbon losses due to the conversion of forests to agricultural land. Sci. Rep. 4, 4062 (2014).
Sanderman, J., Hengl, T. & Fiske, G. J. Soil carbon debt of 12,000 years of human land use. Proc. Natl Acad. Sci. USA 114, 9575–9580 (2017); correction 115, E1700 (2018).
Nyawira, S. S., Nabel, J. E. M. S., Don, A., Brovkin, V. & Pongratz, J. Soil carbon response to land-use change: evaluation of a global vegetation model using observational meta-analyses. Biogeosciences 13, 5661–5675 (2016).
Food and Agriculture Organization of the United Nations. FAOSTAT Database http://www.fao.org/faostat/en/#home (2016).
Anderson-Teixeira, K. J. & DeLucia, E. H. The greenhouse gas value of ecosystems. Glob. Change Biol. 17, 425–438 (2011).
Poeplau, C. et al. Temporal dynamics of soil organic carbon after land-use change in the temperate zone – carbon response functions as a model approach. Glob. Change Biol. 17, 2415–2427 (2011).
Nordhaus, W. D. Revisiting the social cost of carbon. Proc. Natl Acad. Sci. USA 114, 1518–1523 (2017).
Yu, Z., Loisel, J., Brosseau, D. P., Beilman, D. W. & Hunt, S. J. Global peatland dynamics since the Last Glacial Maximum. Geophys. Res. Lett. 37, L13402 (2010).
Hiraishi, T. et al. (eds) 2013 Supplement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories: Wetlands (IPCC, Geneva, 2014).
Biancalani, R. & Avagyan, A. Towards Climate-Responsible Peatlands Management (Food and Agriculture Organization of the United Nations, Rome, 2014).
Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530, 211–214 (2016).
Anderson-Teixeira, K. J., Wang, M. M. H., McGarvey, J. C. & LeBauer, D. S. Carbon dynamics of mature and regrowth tropical forests derived from a pantropical database (TropForC-db). Glob. Change Biol. 22, 1690–1709 (2016).
Ramankutty, N., Evan, A. T., Monfreda, C. & Foley, J. A. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Glob. Biogeochem. Cycles 22, GB1003 (2008).
Wirsenius, S. Human Use of Land and Organic Materials. Modeling the Turnover of Biomass in the Global Food System. PhD Thesis, Chalmers Univ. of Technology and Göteborg Univ. (2000).
Bouwman, A. F., Van der Hoek, K. W., Eickhout, B. & Soenario, I. Exploring changes in world ruminant production systems. Agric. Syst. 84, 121–153 (2005).
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).
Zhang, X. et al. Managing nitrogen for sustainable development. Nature 528, 51–59 (2015).
Klein Goldewijk, K.K., Beusen, A., Doelman, J. & Stehfest, E. Anthropogenic land use estimates for the Holocene – HYDE 3.2. Earth Syst. Sci. Data 9, 927–953 (2017).
Stahl, C. et al. Soil carbon stocks after conversion of Amazonian tropical forest to grazed pasture: importance of deep soil layers. Reg. Environ. Change 16, 2059–2069 (2016).
Fujisaki, K. et al. From forest to cropland and pasture systems: a critical review of soil organic carbon stocks changes in Amazonia. Glob. Change Biol. 21, 2773–2786 (2015).
Zhou, G. et al. Grazing intensity significantly affects belowground carbon and nitrogen cycling in grassland ecosystems: a meta-analysis. Glob. Change Biol. 23, 1167–1179 (2017).
Le Mouël, C. Agrimonde-Terra Foresight: Land Use and Food Security in 2050 (CIRAD/INRA, Paris, 2016).
Le Mouël, C. et al. Le Système Agricole et Alimentaire de la Région Afrique du Nord–Moyen-Orient à L’Horizon 2050 : Projections de Tendance et Analyse de Sensibilité (INRA, Paris/Rennes, 2015).
EPA. Life-Cycle Analysis of Greenhouse Gas Emissions from Renewable Fuels (2010).
Yan, X., Akiyama, H., Yagi, K. & Akimoto, H. Global estimations of the inventory and mitigation potential of methane emissions from rice cultivation conducted using the 2006 Intergovernmental Panel on Climate Change Guidelines. Glob. Biogeochem. Cycles 23, GB2002 (2009).
Adhya, T. K., Linquist, B., Searchinger, T. D., Wassmann, R. & Yan, X. Wetting and Drying: Reducing Greenhouse Gas Emissions and Saving Water from Rice Production (World Resources Institute, Washington DC, 2014).
Food and Agriculture Organization of the United Nations. FertiStat http://www.fao.org/tempref/agl/agll/docs/fertusebycrop.xls (2006; accessed 2016).
Myhre, G. et al. in Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (eds Stocker, T. F. et al.) 659–740 (Cambridge Univ. Press, Cambridge, 2013).
Opio, C. et al. Greenhouse Gas Emission from Ruminant Supply Chains: A Global Life Cycle Assessment (Food and Agriculture Organization of the United Nations, Rome, 2013).
MacLeod, M. et al. Greenhouse Gas Emissions from Pig and Chicken Supply Chains: A Global Life Cycle Assessment (Food and Agriculture Organization of the United Nations, Rome, 2013).
Edwards, R., Larivé, J. F., Rickeard, D. & Weindorf, W. Well-to-Tank Report Version 4.a: JEC Well-to-Wheels Analysis (European Commission, Joint Research Centre, Ispra, 2014).
Evans, S. G., Ramage, B. S., DiRocco, T. L. & Potts, M. D. Greenhouse gas mitigation on marginal land: a quantitative review of the relative benefits of forest recovery versus biofuel production. Environ. Sci. Technol. 49, 2503–2511 (2015).
Klasing, K. C. Displacement ratios for US corn DDGS (International Council on Clean Transportation, Washington, 2012).
Scharlemann, J. P., Tanner, E. V., Hiederer, R. & Kapos, V. Global soil carbon: understanding and managing the largest terrestrial carbon pool. Carbon Manag. 5, 81–91 (2014).
Estes, L. et al. A large-area, spatially continuous assessment of land cover map error and its impact on downstream analyses. Glob. Change Biol. 24, 322–337 (2017).
Fritz, S. et al. Highlighting continued uncertainty in global land cover maps for the user community. Environ. Res. Lett. 6, 044005 (2011).
Acknowledgements
We thank the David and Lucille Packard Foundation and the Norwegian Agency for Development Cooperation for financial support. We thank L. Germer for work on programming the Carbon Benefits Calculator, and J. Moretti and C. Klirs for help with graphics. We thank R. Boddey and A. Cardoso for additional data, advice and citations necessary for the Brazil examples. We thank R. Conant, K. Erb and H. Haberl for contributions to early thinking for this project, and C. Malins, S. Yeh and M. O’Hare for comments on early drafts.
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All authors contributed to all features of the paper. In addition, T.D.S. conceived the idea for the research and wrote the paper. S.W. programmed our spreadsheet model. T.B. performed global vegetation modelling and spatial analysis. P.D. estimated product-specific PEMs.
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Extended data figures and tables
Extended Data Fig. 1 Carbon benefits of different crop production systems based on the carbon benefits index.
Error bars reflect the range of literature estimates of vegetation and soil carbon stocks.
Extended Data Fig. 2 Carbon benefits of different potential Iowa cropland uses based on the carbon benefits index.
Error bars reflect the range of literature estimates of vegetation and soil carbon stocks.
Extended Data Fig. 3 Above- and below-ground carbon stocks of potential natural vegetation under current climate, used to derive COCs with the carbon loss method.
Data simulated with the LPJmL model and adjusted at the biome level according to reference values from the literature (see Supplementary Information).
Extended Data Fig. 4 Soil carbon stocks of potential natural vegetation under current climate used to derive COCs with carbon loss method.
Data simulated with LPJmL and adjusted at the biome level according to reference values from the literature (see Supplementary Information).
Extended Data Fig. 5 Annual net primary productivity of potential native vegetation under current climate used to derive COCs with carbon gain method.
Data simulated with LPJmL.
Supplementary information
Supplementary Information
This document explains the basic concepts behind the carbon benefits index and its components, and includes Supplementary Fig. 1 and Supplementary Tables 1–9. It provides sensitivity calculations and describes the sources for information presented in the examples in the main manuscript.
Supplementary Data
This file contains the Carbon Benefits Calculator, which allows users to calculate the carbon benefits of a farm or hectare of land under existing and proposed new uses or management. Users may use various default values or provide site-specific information.
Supplementary Data
Zipped file containing ESRI ASCII files in geographic coordinates (WGS-84) for the maps shown in Extended Data Fig. 3, which shows estimated carbon stocks of native vegetation under current climate simulated with LPJmL and adjusted at the biome level according to literature reference values.
Supplementary Data
Zipped file containing ESRI ASCII files in geographic coordinates (WGS-84) for the map shown in Extended Data Fig. 4, which shows soil carbon stocks of native vegetation under current climate simulated with LPJmL.
Supplementary Data
Source Data for Supplementary Fig. 1.
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Searchinger, T.D., Wirsenius, S., Beringer, T. et al. Assessing the efficiency of changes in land use for mitigating climate change. Nature 564, 249–253 (2018). https://doi.org/10.1038/s41586-018-0757-z
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DOI: https://doi.org/10.1038/s41586-018-0757-z
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Uwe Fritsche
The old story of "carbon opportunity cost" does not become any better when being repeated under different heading: As discussed since about 10 years now (see various publications from IEA Bioenergy Task 38, and 40, and 43), the claim that LCA ignores LUC-related emissions, and that the "right" counterfactual scenario should be a world without humans (or only ones in hunter-gatherer mode) has not been substantiated...and this article does not, either. Well, a more substantial response will have to wait until after Xmas...
Tim Searchinger Replied to Uwe Fritsche
There are two types of LCAs typically done for bioenergy when bioenergy is produced on existing agricultural land.
One entirely treats the loss of that land's food output as having no carbon cost. It does so by ignoring the emissions from burning (and refining) those plants as not contributing to carbon in the atmosphere on the theory that the carbon absorbed by growing the plants offsets this carbon emitted by burning them. The loss of the food production plays no role.
Since a a paper I wrote in 2008, many other LCAs now use economic models to factor in indirect land use change, which partially estimates a land carbon opportunity cost because it tries to estimate the lost carbon to replace the food. But as we discuss here, the analysis is like the SUV example. These models will sometimes claim limited land use change to replace food because (a) higher prices lead many consumers to eat less, and (b) those same higher prices cause other farms to increase yields on their own land.(see discussion here http://science.sciencemag.o... These are changes in the efficiency of consumption and production by others, on other lands and at others' expense. These effects would occur even if the land devoted to biofuels were actually left bare and therefore became supremely inefficient. For this reason, these changes on other lands and by other people have nothing to do with the efficiency of devoting land to biofuels. When economic models factor in predictions of these effects, they are not factoring in the true opportunity cost of land to store carbon because they are crediting biofuels with these carbon "benefits" by others. Please see the further explanation here:
https://wriorg.s3.amazonaws...
(If a problem linking, google World Resources Institute carbon benefits index and click on the explanation to the right at the bottom of the page.)
There is actually a simpler way to factor carbon storage opportunity costs of land into biofuels in some form. That is simply to compare the carbon reductions in tons/hectare/year from displaced fossil fuels when devoting land to biofuels with the carbon reduction that would occur from allowing these lands to reforest. See Evans et al., Environ. Sci. Technol. 2015, 49, 2503−2511; Righelato & Spracklen, Science 2007, 317, 902; Searchinger et al., 2017, Energy Policy 110:434-446. In nearly all possible scenarios, multiple authors and using very obvious calculations have found that the savings from forest regrowth would exceed those from bioenergy. In other words, if you subtract this opportunity cost of not allowing land to reforest or otherwise regenerate some kind of native vegetation from the bioenergy savings, the net effect of biofuels is to increase emissions. And even under extreme yield assumptions for bioenergy, the % savings compared to fossil fuels become too small to be part of a true low-carbon economy. Although this simple approach is illustrative, we believe the Carbon Benefits Index provides a better approach when bioenergy displaces food production because the better use of land may still be to produce food (rather than forest), creating more space to preserve forest elsewhere.
In simplest terms, bioenergy is one way of using the potential of land to grow plants to reduce fossil emissions -- the benefit -- but the cost is not using that land for another purpose. LCAs have either completely or mostly not counted this effect.
We look forward to Uwe's further explanation.
John Stewart Replied to Tim Searchinger
Why did you assert that organic farmers do not use fertilizer?
Tim Searchinger Replied to John Stewart
We don't discuss that in this paper, but the typical criteria for organic production are not to use synthetic fertilizer. Organic farmers do typically fertilize with manure or legumes.
John Stewart
This study may be valid in Sweden only, since every organic farmer I know uses organic fertilizers and gets equal or more often greater yields per unit of area than conventional farmers. Plus it seems to assume that farms can only be created by clearcutting forests. A flawed study with invalid conclusions.
Tim Searchinger Replied to John Stewart
Organic farms can achieve different yields, and an organic farm that achieved equal or greater yields than a conventional farm on the same land would generate greater carbon benefits. The numbers we used in the paper are the relative average yields in Sweden and are used as illustration.
There is nothing in our paper that assumes that farms can only be created by clearcutting forests. Instead, we calculate the time-discounted, average carbon loss from changes in all forms of native vegetation (and associated changes in soil carbon) that have occurred to produce each food. Depending on the food, those converted native lands include not merely forests but savannas of all kinds and grasslands, and in the case of ruminants, sometimes involve little carbon loss for some of the grasslands. The index assumes in effect that any food not produced on one hectare will be replaced elsewhere at this global average cost.
The index makes this assumption in part because the alternative -- of attempting to estimate offsetting changes in consumption or yields of other farms -- do not reflect changes in the efficiency of the land being analyzed (i.e, the cropland that changes what or how it produces) but changes by other people on other lands. The index also makes this assumption to provide a benchmark for actual predictions of responses because those predictions otherwise require use of economic models, most of whose parameters and functional forms must be and are assumed.
John Stewart Replied to Tim Searchinger
Who paid for this flawed study with the flawed assumption that organic ag uses no fertilizer and therefore requires more land? Please look up "French intensive agriculture" and you will find plenty of articles showing organic methods use much less land than conventional ag. Your flawed study is already being used as propaganda to undermine organic ag. Thanks a lot.
Natália Mello
I agree with the statement that the study presents misleading conclusions if it assumes that farming can only occur in newly deforested areas. Moreover, I believe that the assessment should also encompass a comparison between Nitrous Oxide (N2O) emissions from organic and non-organic farms.
N2O is a green house gas (GHG) whose global warming potential is 298 times higher than that of CO2. Hence, the thorough understanding of which land-use incurs in a greater climate impact relies on accounting this GHG as well.
Tim Searchinger Replied to Natália Mello
The study does not assume that farming can only occur in newly deforested areas. In fact, it assumes that farming can occur on existing agricultural land, which avoids the need to clear more land either from forest or any other kind of native vegetation. The study also factors nitrous oxide into all calculations. They are some of the PEMs, i.e., Production Emissions.
Tim Searchinger
For those interested in this paper, I encourage people to read a further explanation under the link "explanation of paper and method," that can be found on the web page https://www.wri.org/carbon-.... Using a little extra space and without the need to explain all the details, this explanation in some ways better conveys the reasoning and implications of this paper.
Nicholas L
More study is needed as carbon intensive oil is used to make pesticides and fertilizers.
R B Replied to Nicholas L
Agreed, the article makes no mention of the carbon footprint associated with the extraction, refining, shipping, and application of the massive amounts of synthetic fertilizers and pesticides used in conventional farming. Never mind the exponential bioaccumulation of said chemicals in the ecosystem/food chain
Tim Searchinger Replied to R B
That is not correct. The emissions associated with the production of inputs is included in our calculations. They are part of PEMs.
Marko Vegano
I know I don't have the technical expertise to debate this study. But I can see there are others here that do.
But reading other comments makes me wonder why this would be published on a newsfeed. Newsflash, people's lives that depend on organic farming could be jeopardized if people think this is compromising their belief that organic farming and food is best.
Could this study be funded by nonorganic farmer? And maybe corporations, like Monsanto, that would love to see their profits increase? Something smell rotten. And as long as we are talking about climate effect, let's not forget the studies on animal agricultural. The amount of organic emissions is a drop in the bucket compared to animal agriculture.
Take the blinders off and see the big picture.
Ok I'm done. But one more thing. I like not having GMO food that stinks of chemicals that are causing cancers. Read that studies. They are out there.
Tim Searchinger Replied to Marko Vegano
I can assure you nothing about this study was funded by Monsanto.
Much of the attention here appears to be about the findings relative to organic production in Sweden. Remember that individual organic farms can achieve different yields. The carbon benefits index is designed to allow analysis of individual farms and in fact individual hectares.
Organic production also has important environmental benefits relevant to pesticides, and those benefits are likely to become increasingly important as the world learns more about the die-off of insects globally. I personally think one of the great contributions of organic farming is the innovation in production techniques that can adopted by non-organic farms, such as advanced forms of integrated pest management.
ADIOFlo Replied to Tim Searchinger
Yes, that’s all well and good to be “admitting” in a comments section as to your personal admirations of organic farming. But you do realize what will be done with this article, right? It will be used by every shock-media purveyor, clickbait blogger, and worse yet, big, dirty farming paid advocate to muddy the waters in what is no less than a fight for our future health. Formally supported by Monsanto or not, this will unfortunately be used for their benefit. It’s dissappointing, to say the least, when doing their bidding means an assault on the human microbiome and a continued rise in chronic inflammatory diseases.
Thanks.
GodoStoyke Replied to Tim Searchinger
Thanks for your comment, Tim. It would be interesting to include carbon sequestration capacity of organic vs. conventional crop methods, as organic farmers typically rely on composting, which tends to increase soil organic matter and sequestered carbon.
Bertus Buizer
What the study does not mention is that 25% of all agricultural land is strongly degraded, 8% moderately degraded and 36% slightly degraded (FAO, 2011). This is in a large part due to conventional agriculture. Organic farming, on the other hand, restores the soil and stores a lot of CO2 in the soil.
According to Dr. Harry Donkers, the study also does not take into account the fact that the yield of organically grown agricultural products per ha after a period of 10 to 15 years equals or even exceeds the yield of conventionally grown agricultural products. That period is not taken into account. In addition, after organic cultivation during this period healthy soils remain, whereas in conventional cultivation only contaminated soils are left with chemical fertilizers and chemical pesticides.
It should also not be forgotten that funds for research and innovation since WW II have almost completely gone to conventional agriculture and not to organic farming. In that area, organic farming is significantly behind the usual agriculture. Most (climate and environmental) profits can be achieved by using resources for research and innovation for organic agriculture, Dr. Harry Donkers says.
Organic farming has the best credentials for an adequate sustainable food supply: https://www.sustainablefood... https://uploads.disquscdn.c...
Maharsi QeD Replied to Bertus Buizer
This comment point in the right direction. Not assuming that "conventional farming" is what degraded the land at first place (talk to French farmers..), and that the "conventional farming" can't be sustained, is a bias, at best. More, "conventional farming" are starting to plant trees in between rows of crops to increase biodiversity and that make better yield, that technique was used by organic farmer... so more lands needed is NOT the majority of what the literature says on the subject. Future more, "conventional farming" use corn crops to feed animals, thanks to Monsanto, before that beast, farmers used "grass/hay" which provide better yield (milk) that corn, is WAY more cheap and green that corn, and what is normally eaten by cow... so animals are healthier( then less medicine used). Mostly, organic micro-farmers are yielding more crops that simulation model can estimate and are the way organic farmers tend to go along the years. This article does not mention the health benefit for humans and the biodiversity, and that "conventional farming", read "chemists farming", are on the front line of the cause of cancers, Alzheimer( from paraquat)...etc.. articles can be easily found on that. So there is only a "climate change" point of view, with a limited view in time. The point of this is? Monsanto, read Bayers, should be happy, but the conclusion seems far fetched. Not counting for the production of chemical as product, producing bigger machinery to go in bigger field as "conventional farming" do, are to take account for, since organic and micro-farmer do not use such big and gas consuming technology. Plus, very high tech machinery use satellite to be guided in the field, That satellite, the launch and production of, used for "conventional farming", is another thing to take into account (even if it's small). If it use internet, that to must be into the counting point of climate change impact. This might be true for Sweden but not for North and South America... I know this sound far fetched, but used of the server of internet, is not free. Power needed is growing as demand is, a farmer didn't need internet to drive... small/micro - farming don't use those tech most of the time, conventional farmer now seems to tend that way, which consume every year more energy.
The big picture, and the right conclusion, is left for another article I presume.
Tim Searchinger Replied to Bertus Buizer
This is not a paper that says don't do organic farming. Our only finding regarding organic farming is that under average yields in Sweden, where yields are lower, there are land use costs. Obviously, if an organic farm obtains equivalent yields, then you don't have these costs and could have other carbon benefits through soils in addition to pesticide and other benefits. The calculator responds to the yields and also to changes in soil carbon.
GodoStoyke Replied to Tim Searchinger
Could you provide the reference for wheat and pea crop yields conventional vs. organic in Sweden? The reference is not shown below the table. Thanks!
Tim Searchinger Replied to GodoStoyke
The statistics are from the Swedish Board of Agriculture, which is cited in reference 53 of the supplementary information.
GodoStoyke Replied to Tim Searchinger
Thanks!
GodoStoyke Replied to Tim Searchinger
Do you happen to know if there are also data on changes in soil carbon stock over time in Sweden resulting from organic vs. conventional farming methods?
Tim Searchinger Replied to GodoStoyke
We were not aware of any consistent data on this point.
Tim Searchinger
This comment addresses the statement of IFOAM that can be found here. https://www.ifoam.bio/en/ne.... This statement is absolutely correct that this paper is not in general about organic agriculture but offers solely as a single example the output of peas and wheat in Sweden. There can be many important advantages to organic production, including its pioneering of techniques for pest control that can also be used by producers that are not fully organic. Organic yields can vary, and the only real implication of this paper for organic production is that high yields matter, and that it is important that organic producers realize their potential to achieve equivalent or higher yields than conventional producers.
I do not agree with one part of the IFOAM Statement, which is the suggestion that our analysis assumes that demand cannot change. In fact, we analyze the effect of changes in demand for different foods and biofuels. What our analysis does do is segregate the efficiency of consumption from the efficiency of production. Inefficient production cannot become efficient because it increases prices and causes people to consume less, and vice versa.
The basic reason for segregating the efficiency of production and consumption is that altering the production of any one hectare of land is a very poor way of influencing consumption. For example, even though consuming beef is inefficient, removing a hectare of beef from production is unlikely to influence that consumption much as most of the beef will be reproduced elsewhere. In fact, some farmers will respond to the marginally higher beef prices and shift from more efficient crops to replace the beef. And the poorest consumers will be affected the most. In fact, if the farmer who removes a hectare of beef from production is an efficient producer of beef, the replacement will likely less efficient overall. Thus, trying to reduce consumption of beef by taking one hectare of beef out of production will be both ineffective and inequitable. The same principle applies just to reducing yields of beef on a hectare. If you want to reduce beef consumption effectively and equitably, you need to have consumption-oriented policies.
One of the major limitations of prior approaches is that they commingle questions of the efficiency of production with the efficiency of consumption. That can lead to misguided policies. The carbon benefits index allows separate analysis of the two.
It is also not the case that we can likely feed the world without producing more food. That is covered in depth in the attached report by the World Resources Institute the World Bank, UN Environment and the UN Development Programme. https://www.wri.org/our-wor.... Among other things, that would not be true even if the world redistributed all food equitably among everyone. A perfectly equitable redistribution of food is also no more likely to happen than a perfectly equitable redistribution of housing, energy or transportation. The world needs an "all of the above" strategy that includes both moderation of the growth in food demand and increasing food production on each existing hectare of agricultural land.
Martin Lambertz
Could the authors please clarify what data for the consumption patterns was used in Figure 3?
I understand that the data was taken from Table S1 in Bryngelsson et al. (2016). In this table, did you use the column "Current (2013)" as your "Baseline" and create the other diet scenarios as deviations from this baseline? Or, did you use the column "Baseline" in Table S1 as your baseline and did you use the values in the subsequent columns ("Less meat", "Dairy beef", etc.) for the other diet scenarios? Or did you do something else entirely?
Thank you!